Activities-specific Balance Confidence Scale (ABC Scale)

Evidence Reviewed as of before: 30-11-2020
Author(s)*: Annabel Wildschut
Editor(s): Annie Rochette
Expert Reviewer: Johanne Filiatrault, erg., Ph.D.
Content consistency: Gabriel Plumier

Purpose

The Activities-specific Balance Confidence Scale (ABC Scale) is a structured questionnaire that measures an individual’s confidence in performing activities without losing balance.

In-Depth Review

Purpose of the measure

The Activities-specific Balance Confidence Scale (ABC Scale) is a structured questionnaire that measures an individual’s confidence in performing activities without losing balance.

Available versions

The ABC Scale was developed in 1995 using a convenience sample of 15 clinicians (physical and occupational therapists) and 12 physical therapy patients aged over 65 years. Clinicians were asked to ‘name the 10 most important activities essential to independent living, that while requiring some position change or walking, would be safe and nonhazardous to most elderly persons’. Seniors were asked the same question, in addition to the question: ‘Are you afraid of falling during any normal daily activities, and if so, which ones?’ (Powell & Myers, 1995). Items were chosen to include a number of difficult activities that potentially posed some hazard. A 0-100% response continuum was chosen to assess self-efficacy.

A modified version of the ABC Scale (ABC-Simplified [ABC-S]) was developed to (a) improve user friendliness by simplifying the cue question and response format; and (b) improve the scale’s congruence with public health falls prevention strategies by removing the final question regarding walking in icy conditions (Filiatrault et al., 2007). The psychometric properties of the ABC-S Scale were tested among a sample of 197 community-dwelling seniors. The ABC-S Scale has demonstrated high internal consistency (reliability index 0.86) and good convergent validity (statistically significant associations with perceived balance; performances on the one-leg stance, tandem stance, tandem walking, functional reach, and lateral reach [on the right side] tests; fear of falling; and occurrence of falls in the previous 12 months). Analyses also showed differing degrees of difficulty across items, allowing for a determination of the scale’s item hierarchy. However, no testing of the ABC-S Scale has been conducted with a stroke population.

A 6-item version of the ABC Scale (ABC-6) was also developed for clinical and research use. It includes 6 activities from the original ABC Scale on which participants demonstrated least confidence (Peretz et al., 2006). In a study conducted among a sample of 35 community-dwelling seniors, it has been shown to be a valid and reliable measure of balance confidence among community-dwelling adults. The scale could also differentiate confidence levels between fallers and non-fallers (Schepens et al., Goldberg, & Wallace, 2010). To date, no psychometric testing of the 6-item version of the ABC Scale has been conducted with a stroke population.

Features of the measure

Original items:
The ABC Scale consists of 16 questions that require the patient to rate his/her confidence that he/she will not lose balance or become unsteady while performing the following activities:

  1. Walking around the house
  2. Walking up or down stairs
  3. Bending over to pick up a slipper from the front of a closet floor
  4. Reaching for a small can off a shelf at eye level
  5. Standing on tiptoes and reaching for something above his/her head
  6. Standing on a chair to reach for something
  7. Sweeping the floor
  8. Walking outside the house to a car parked in the driveway
  9. Getting into or out of a car
  10. Walking across a parking lot to the mall
  11. Walking up or down a ramp
  12. Walking in a crowded mall where people rapidly walk past
  13. Being bumped into people as they walk through the mall
  14. Stepping on to or off an escalator while holding onto a railing
  15. Stepping onto or off an escalator while holding onto parcels (so that they are not able to hold the railing)
  16. Walking outside on icy sidewalks

If the patient does not currently perform the activity, he/she is instructed to imagine how confident he/she might be if he/she had to do the activity. If the patient normally uses a mobility aid to do the activity, he/she is instructed to rate his/her confidence level as if he/she was using this aid during the activity.

Scoring:
The patient is asked to rate his/her confidence performing activities without losing his/her balance or becoming unsteady. The original scale is a 0% to 100% continuous response scale. However, in a more recent publication, Myers (1999), replaced the 0%-to-100% continuous response scale with an 11-point response scale that includes 10% anchor increments (0%, 10%, . . ., 100%).

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
No confidence Completely confident

The overall score is calculated by adding the item scores and dividing the total by 16 (i.e. the number of items). This total score ranges from 0% to 100%.

Myers et al. (1998) use the following cut-off scores to define level of functioning among active older adults:

  • Lower than 50 %: low level of physical functioning
  • 50-80 %: moderate level of physical functioning
  • Above 80 %: high level of physical functioning

What to consider before beginning:
The ABC Scale provides a subjective measure of balance confidence. Scores are not based on clinician observation of performance. Clinicians should also consider factors such as self-esteem and insight when using the ABC Scale.

Time:
The original ABC Scale takes approximately 10-20 minutes to administer.

Training requirements:
No training requirements have been specified for the ABC Scale.

Equipment:
The ABC Scale is a structured questionnaire that does not require specific equipment.

Alternative forms of the Activities-specific Balance Confidence Scale

None.

Client suitability

Can be used with:

  • Individuals with stroke and other neurological conditions (Moore et al., 2014)
  • Individuals with vestibular disorders (Jarlsater & Mattsson, 2003)
  • Individuals with lower-limb amputation (Miller, Deathe & Speechley, 2003)
  • Individuals with Parkinson’s Disease (Franchignoni et al., 2014)
  • Community-dwelling seniors (Myers et al., 1996 ; Myers et al., 1998; Filiatrault et al., 2007)

Should not be used with:

  • The ABC Scale is not suitable for individuals with limited insight into their balance impairments. It is not recommended for patients who do not have a rehabilitation goal of improving balance confidence (Moore et al., 2018).

In what languages is the measure available?

Canadian French (Salbach et al., 2006; Filiatrault et al., 2007)
Chinese (Hsu & Miller, 2006; Mak et al., 2007)
Dutch (van Heuvelen et al., 2005)
English (Powell & Myers, 2005)
German (Schott, 2008)
Hindi (Moiz et al., 2017)
Korean (Jang et al., 2003)
Portuguese (Marques et al., 2013)
Swedish (Nilsagard & Forsberg, 2012)
Turkish (Karapolat et al., 2010)

Summary

What does the tool measure? Self-perceived confidence with mobility.
What types of clients can the tool be used for? The ABC Scale can be used with, but is not limited to, patients with stroke.
Is this a screening or assessment tool? Screening tool.
Time to administer 10-20 minutes.
ICF Domain Activity
Versions ABC-CF (Salbach et al., 2006)
ABC-Simplified (Filiatrault et al., 2007)
ABC-6 (Peretz et al,2006)
Other Languages French Canadian, Chinese, Dutch, German, Hindi, Korean, Portuguese, Swedish, Turkish.
Measurement Properties
Reliability Internal consistency:
– Two studies have reported high internal consistency of the ABC Scale in a stroke population (Botner et al, 2005; Salbach et al, 2006).
– One study reported high internal consistency of the ABC-CF Scale in a stroke population (Salbach et al, 2006).
– One study reported high internal consistency of a Swedish translation of the ABC Scale in a stroke population (Nilsagard & Forsberg, 2012).
Test-retest:
One study examined test-retest reliability of the ABC Scale within a stroke population and reported excellent test-retest reliability of the overall score and adequate to excellent item level test-retest reliability (Botner et al, 2005).
Intra-rater:
Intra-rater reliability of the ABC Scale has not been examined.
Inter-rater:
Inter-rater reliability of the ABC Scale has not been examined.
Validity Content:
One study conducted factor analysis of the ABC Scale within a stroke population and results revealed two factors: perceived low-risk activities and perceived high-risk activities (Botner et al, 2005).
Criterion:
Concurrent:
Concurrent validity of the ABC Scale has not been examined within a stroke population.
Predictive:
Predictive validity of the ABC Scale has not been examined within a stroke population.
Construct:
Convergent/Discriminant:
– Three studies (Botner et al., 2005; Salbach et al., 2006; Nilsagard & Forsberg, 2012) have examined convergent validity of the ABC Scale within a stroke population and reported : an adequate correlation with the Berg Balance Scale (BBS), gait speed, 6 Minute Walk Test (6MWT), Barthel Index (BI), Functional Ambulation Categories (FAC) and modified Rivermead Mobility Index (RMI); and adequate negative correlations with the Timed Up and Go test (TUG) and 10-m timed walk test. Correlations with the Medical Outcomes Study 36-Item Short-Form Health Survey – Physical function subscale (SF-36 PF) ranged from excellent to poor among studies.
– Two studies (Salbach et al., 2006; Nilsagard & Forsberg, 2012) have examined divergent validity of the ABC Scale within a stroke population and reported: an adequate correlation with the EQ-5D visual analog scale (EQ VAS); an adequate negative correlation with the Geriatric Depression Scale (GDS); and a low correlation with the SF-36 Mental component score.
– One study (Salbach et al., 2006) examined convergent / divergent validity of the ABC-CF Scale and reported: an excellent correlation with the EQ VAS; an excellent negative correlation with the GDS; adequate correlations with the SF-36 PF, BBS, walking speed, 6MWT and BI; and an adequate negative correlation with the TUG.
Known Groups:
Known-group validity of the ABC Scale has not been examined within a stroke population.
Floor/Ceiling Effects One study (Salbach et al., 2006) reported no floor/ceiling effects for the total score of the ABC Scale or the ABC-CF Scale in a sample of patients with subacute/chronic stroke, but noted a floor effect for 3 items and a ceiling effect for 8 items of both scales.
Sensitivity / Specificity Not reported.
Does the tool detect change in patients? No studies have reported on the responsiveness of the ABC Scale within a stroke population.
Acceptability The ABC Scale is non-invasive and quick to administer. The items are considered reflective of real-life activities.
Feasibility The ABC Scale is free and is suitable for administration in various settings. The assessment requires minimal specialist equipment or training.
How to obtain the tool? The print version of the scale may be freely reproduced for student training, research and clinical practices in which therapists and assistants use the scale to assess fewer than 1000 patients per year. Contact primary developer and copyright holder, Dr.Anita Myers at amyers@uwaterloo.ca.

Psychometric Properties

Overview

A literature search was conducted to identify all relevant publications on the psychometric properties of the Activities-specific Balance Confidence (ABC Scale). While numerous studies have been conducted on the use of the ABC Scale with other client populations, this review specifically addresses the psychometric properties of the ABC Scale with individuals with stroke. Three studies were identified (Salbach, Mayo, Hanley, Richards, & Wood-Dauphinee, 2006; Botner, Miller, & Eng, 2005; Nilsagard & Forsberg, 2012). The original paper by Powell & Myers (1995) has also been included below, although please note that this study uses a mixed population of community-dwelling adults and patients receiving physical therapy services; the number of participants who had a stroke was not specified.

Floor/Ceiling Effects

Salbach et al. (2006) examined floor/ceiling effects of the ABC Scale and the ABC-CF Scale in a sample of 86 participants (n=51 and 35, respectively) with subacute/chronic stroke and residual walking deficits. The authors reported a floor effect (whereby more than 20% of participants reported ‘no confidence’ or 0%) for 3 items of both scales; and a ceiling effect (whereby more than 20% of participants reported ‘complete confidence’ or 100%) for 8 items of both scales. There were no floor/ceiling effects for the total score of either scale.

Botner et al. (2005) reported that more than 80% of their study sample (n=77 participants with chronic stroke) scored between 40% and 80%, suggesting minimal floor or ceiling effects in their sample.

Reliability

The ABC Scale was developed using a convenience sample of 15 clinicians (physical and occupational therapists) and 12 physical therapy patients aged over 65 years (Powell & Myers, 1995).

Internal consistency:
Powell & Myers (1995) examined internal consistency of the ABC Scale in a sample of 102 community-dwelling adults aged over 65 and a convenience sample of 18 high-mobility and 7 low-mobility physiotherapy outpatients, using Cronbach’s alpha. The authors reported high internal consistency (a = 0.96). Stepwise deletion of each item did not alter internal consistency.

Botner et al. (2005) examined internal consistency of the ABC Scale in a sample of 77 participants with chronic stroke, using Cronbach’s alpha. Results revealed high internal consistency (a=0.94). Stepwise deletion did not alter internal consistency (a=0.93 – 0.94).

Salbach et al. (2006) examined internal consistency of the ABC Scale and the ABC-CF Scale in a sample of 86 participants (n=51, 35 respectively) with subacute/chronic stroke and residual walking deficit. The authors reported high internal consistency for both scales (a= 0.94, 0.93 respectively), measured using Cronbach’s alpha. Stepwise deletion of each item did not improve internal consistency of either scale.

Nilsagard & Forsberg (2012) examined internal consistency of a Swedish translation of the ABC Scale in a sample of 37 patients with acute/subacute stroke, using Cronbach’s alpha. Participants were retested 3 months later (n=31). The authors reported high internal consistency at both time points (a= 0.97, 0.94 respectively).

Absolute reliability:
Salbach et al. (2006) examined absolute reliability of the ABC Scale and the ABC-CF Scale in a sample of 86 participants (n=51, 35 respectively) with subacute/chronic stroke and residual walking deficit. Standard error of measurement of the ABC Scale was 5.05, and standard error of measurement of the ABC-CF Scale was 5.13.

Scalability:
Powell & Myers (1995) examined scalability of the ABC Scale in a sample of 102 community-dwelling adults aged over 65 and a convenience sample of 18 high-mobility and 7 low-mobility physiotherapy outpatients. Scalability encompassed (a) absence of idiosyncratic items, (b) ability of items to discriminate between respondents, and (c) presence of a fixed relation between items. Hierarchicality was measured using Mokken’s Stochastic Cumulative Scaling program (MSP), which revealed a strong cumulative scale (H coefficient = 0.59), and excellent reliability (Rho coefficient = 0.95).

Test-retest:
Powell & Myers (1995) examined 2-week test-retest reliability of the ABC Scale with a sample of 21 community-dwelling seniors. Results revealed excellent overall test-retest reliability (r=0.92, p<0.001). Correlations between the test-retest scores was not significant for two items (car transfers, r=0.19; walking in the home, r=0.36).

Botner, Miller and Eng (2005) examined 4-week test-retest reliability of the ABC Scale with a sample of 24 participants with chronic stroke, using intra-class correlation coefficients. Results indicated excellent test-retest reliability of the overall score (ICC = 0.85; 95% CI 0.68-0.93), and adequate to excellent item level test-retest reliability (ICC ranged from 0.53 – 0.93).

Intra-rater:
No studies have reported on the intra-rater reliability of the ABC Scale. Administration of the ABC Scale does not rely on clinician-observation of patient performance.

Inter-rater:
No studies have reported on the inter-rater reliability of the ABC Scale. Administration of the ABC Scale does not rely on clinician-observation of patient performance.

Validity

Content:
Botner, Miller & Eng (2005) conducted factor analysis of the ABC Scale in a sample of 77 participants with chronic stroke, using principal component analysis with Varimax rotation. Results revealed two components:
Factor 1: perceived low-risk activities (9 items; 55.7% of the variance); and
Factor 2: perceived high-risk activities (6 items; 12.9% of the variance).
One item (sweeping the floor) loaded almost equally on both components.

Criterion:
Concurrent:
Powell & Myers (1995) examined concurrent validity of the ABC Scale by comparison with the Falls Efficacy Scale (FES) in a sample of 102 community-dwelling adults aged over 65 and a convenience sample of 18 high-mobility and 7 low-mobility physiotherapy outpatients. There was an adequate correlation between scales (r=0.84, p<0.001).

Predictive:
No studies have reported on the predictive validity of the ABC Scale.

Construct:
Convergent/Discriminant:
Powell & Myers (1995) examined convergent validity in a sample of 102 community-dwelling adults aged over 65 and a convenience sample of 18 high-mobility and 7 low-mobility physiotherapy outpatients. Convergent validity was measured by comparison with the Physical Self-Efficacy Scale (PSES). There was an adequate correlation (r=0.49, p<0.001) between the ABC Scale and the PSES score, and an excellent correlation between the ABC scale and the PSES physical abilities subscale (r=0.63, p<0.001). There was no significant correlation between the ABC Scale and the PSES general self-presentation subscale (r=0.03).

Powell & Myers (1995) examined discriminant validity in a sample of 102 community-dwelling adults aged over 65 and a convenience sample of 18 high-mobility and 7 low-mobility physiotherapy outpatients. Discriminant validity was measured using the Positive and Negative Affectivity Scale (PANAS). Results were non-significant between the ABC Scale and the PANAS overall score, positive affect score and negative affect score.

Botner, Miller and Eng (2005) examined convergent validity of the ABC Scale with a sample of 77 participants with chronic stroke, using Spearman’s correlation coefficient. Convergent validity was measured by comparison with the Berg Balance Scale (BBS) and gait speed. Results showed an adequate correlation with both measures (BBS: r=0.36, p<0.001; gait speed: r=0.48, p<0.001).

Salbach et al. (2006) examined convergent validity of the ABC Scale and the ABC-CF Scale in a sample of 86 participants (n=51, 35 respectively) with subacute/chronic stroke and residual walking deficit, using Spearman correlation coefficients and associated 95% confidence intervals. Convergent validity was measured by comparison with the BBS, 5-m walking test (comfortable/maximal gait speed), Timed Up and Go test (TUG), 6-Minute Walk Test (6MWT), Barthel Index (BI), Medical Outcomes Study 36-Item Short-Form Health Survey – Physical function subscale (SF-36 PF), Geriatric Depression Scale (GDS), and the EQ-5D visual analog scale (EQ VAS). The ABC Scale showed an excellent correlation with physical function (SF-36 PF: r=0.60), adequate correlations with perceived health status (EQ VAS: r=0.52), balance function (BBS: r=0.42), walking speed (maximum: r=0.43, comfortable: r=0.42), functional walking capacity (6MWT: r=0.40) and functional independence (BI: r=0.37), and adequate negative correlations with functional mobility (TUG: r=-0.34) and depressive symptoms (GDS: r=-0.30). The ABC-CF Scale showed an excellent correlation with perceived health status (EQ VAS: r=0.68), an excellent negative correlation with depressive symptoms (GDS: r=-0.61), adequate correlations with physical function (SF-36 PF: r=0.56), balance function (BBS: r=0.49), walking speed (maximal: r=0.53; comfortable: r=0.48), functional walking capacity (6MWT: r=0.48), functional independence (BI: r=0.45), and an adequate negative correlation with functional mobility (TUG: r=-0.52).

Nilsagard & Forsberg (2012) examined convergent and divergent validity of the ABC Scale in a sample of 37 participants with acute/subacute stroke, using Kendall’s coefficient. Participants were retested 3 months later (n=31). Convergent validity was measured by comparison with the Functional Ambulation Categories (FAC), modified Rivermead Mobility Index (m-RMI), TUG, 10-m timed walk test, SF-36 Physical component (SF-36 PS), and the 12-item walking scale. The ABC Scale showed significant adequate correlations at both time points with the FAC (r=0.40, 0.49) and the modified RMI (r=0.38, 0.46), and an adequate to low correlation with the SF-36 PF (r=-0.33, 0.28). The ABC Scale showed adequate negative correlations at both time points with the TUG (r=-0.46, -0.43), 10-m timed walk test (r=-0.41 at both time points) and 12-item walking scale (r=-0.55, -0.52). Divergent validity was measured using the SF-36 Mental component score (SF-36 MF), with which the ABC Scale showed a low correlation at both time points (r=0.22, 0.12).

Known Group:
Powell & Myers (1995) examined known group validity in a sample of 102 community-dwelling adults aged over 65 and a convenience sample of 18 high-mobility and 7 low-mobility physiotherapy outpatients. Participants were self-categorized according to the following categories: fallers (57%), injured fallers (38%), fear of falling (57%) and activity avoidance due to fear of falling (30%). There was no significant difference in mean ABC scores between participants who had fallen in the past year and those who had not experienced a fall. There was no significant difference in mean ABC scores between participants who had been injured during a fall and those who had not been injured during a fall. Activity avoidance due to fear of falling was significantly more common in low mobility participants compared to high mobility participants (p<0.001). There was a significant difference (p<0.001) in mean ABC scores between high mobility and low mobility participants (t=9.34, ES=1.5). All ABC Scale items excluding item 4 (reaching at eye level) showed a significant difference between high mobility and low mobility participants, indicating an ability to discriminate between the two groups. Score ranges within high and low mobility groups indicated an adequate range of responses (score range 5% – 84% confidence for low mobility participants, 36% – 95% confidence for high mobility participants).

Responsiveness

Powell & Myers (1995) examined responsiveness of the ABC Scale in a sample of 102 community-dwelling adults aged over 65 and a convenience sample of 18 high-mobility and 7 low-mobility physiotherapy outpatients. Mean scores ranged from 21% confidence (item 16: walking on an icy sidewalk) to 90% (item 4: reaching at eye level).

Sensitivity & Specificity:
Powell & Myers (1995) examined item specificity of the ABC Scale by comparison with the Falls Efficacy Scale (FES) in a sample of 102 community-dwelling adults aged over 65 and a convenience sample of 18 high-mobility and 7 low-mobility physiotherapy outpatients. ABC Scale items 3-6 correlated significantly with the FES item ‘reach into cabinets or closets’ (r = 0.53-0.67, p<0.001), and ABC Scale items 9-15 correlated with the FES item ‘simple shopping’ (r=0.42-0.75).

References

Activities-specific Balance Confidence Scale. (2013, March 22). Retrieved from URL https://www.sralab.org/rehabilitation-measures/activities-specific-balance-confidence-scale

Botner, E.M., Miller, W.C., & Eng, J. J. (2005). Measurement properties of the Activities-specific Balance Confidence scale among individuals with stroke. Disability and Rehabilitation, 27(4), 156-63.

Filiatrault, J., Gauvin, L., Fournier, M., Parisien, M., Robitaille, Y., Laforest, S., Corriveau, H., & Richard, L. (2007). Evidence of the psychometric qualities of a simplified version of the Activities-specific Balance Confidence scale for community-dwelling seniors. Archives of Physical Medicine and Rehabilitation, 88, 664-72.

Franchignoni, F., Giordano, A., Ronconi, G., Rabini, A., & Ferriero, G. (2014). Rasch validation of the Activities-specific Balance Confidence Scale and its short versions in patients with Parkinson’s Disease. Journal of Rehabilitation Medicine, 46, 532-9.

Hsu, P.C., & Miller, W.C. (2006). Reliability of the Chinese version of the Activities-specific Balance Confidence scale. Disability and Rehabilitation, 28(20), 1287-92.

Jang, S.N., Cho, S.I., Ou, S.W., Lee, E.S., & Baik, H.W. (2003). The validity and reliability of Korean Fall Efficacy Scale (FES) and Activities-specific Balance Confidence scale (ABC). Journal of the Korean Geriatrics Society, 7(4), 255-68.

Jarlsater, S. & Mattsson, E. (2003). Test of reliability of the Dizziness Handicap Inventory and the Activities-specific Balance Confidence scale for use in Sweden. Advances in Physiotherapy, 5, 137-44.

Karapolat, H., Eyigor, S., Kirazli, Y., Celebisoy, N., Bilgen, C., & Kirazli, T. (2010). Reliability, validity, and sensitivity to change of Turkish Activities Specific Balance Confidence Scale in patients with unilateral peripheral vestibular disease. International Journal of Rehabilitation Research, 33, 12-18.

Mak, M.K., Lau, A.L., Law, F.S., Cheung, C.C., & Wong, I.S. (2007). Validation of the Chinese translated Activities-specific Balance Confidence scale. Archives of Physical Medicine and Rehabilitation, 88, 496-503.

Marques, A.P., Mendes, Y.C., Taddei, U., Pereira, C.A.B., & Assumpcao, A. (2013). Brazilian-Portuguese translation and cross cultural adaptation of the activities-specific balance confidence (ABC) scale. Braz J Phys Ther. Mar-Apr; 17(2), 170-178.

Miller, W.C., Deathe, A.B., & Speechley, M. (2003). Psychometric properties of the Activities-specific Balance Confidence scale among individuals with a lower-limb amputation. Archives of Physical Medicine and Rehabilitation, 84, 656-61.

Moiz, J.A., Bansal, V., Noohu, M.M., Gaur, S.N., Hussain, M.E., Anwer, S., & Alghadir, A. (2017). Activities-specific balance confidence scale for predicting future falls in Indian older adults. Clinical Interventions in Aging, 12, 645-651.

Moore, J.L., Potter, K., Blankshain, K., Kaplan, S.L., O’Dwyer, L.C., & Sullivan, J.E. (2018). A core set of outcome measures for adults with neurological conditions undergoing rehabilitation: a clinical practice guideline. Journal of Neurological Physical Therapy, 42, 174-216.

Myers, A.M., Fletcher, P.C., Myers, A.H., & Sherk, W. (1998). Discriminative and evaluative properties of the Activities-specific Balance Confidence (ABC) scale. Journal of Gerontology: Medical Sciences, 53A(4), M287-94.

Myers, A.M., Powell, L.E., Maki, B.E., Holliday, P.J., Brawley, L.R., & Sherk, W. (1996). Psychological indicators of balance confidence: relationship to actual and perceived abilities. Journal of Gerontology: Medical Sciences, 51A(1), M37-43.

Myers, A.M. (1999). Program evaluation for exercise leaders. Waterloo: Human Kinetics.

Nilsagard, Y., & Forsberg, A. (2012). Psychometric properties of the Activities-Specific Balance Confidence Scale in persons 0-14 days and 3 months post stroke. Disability & Rehabilitation, 34(14), 1186-1191.

Peretz, C., Herman, T., Hausdorff, J.M., & Giladi, N. (2006). Assessing fear of falling: can a short version of the Activities-specific Balance Confidence scale be useful? Movement Disorders, 21(2), 2101-5.

Powell, L.E. & Myers, A.M. (1995). The Activities-specific Balance Confidence (ABC) scale. Journal of Gerontology: Medical Sciences, 50A (1), M28-34.

Salbach, N.M., Mayo, N.E., Hanley, J.A., Richards, C.L., & Wood-Dauphinee, S. (2006). Psychometric evaluation of the original and Canadian French version of the Activities-Specific Balance Confidence scale among people with stroke. Archives of Physical Medicine and Rehabilitation, 87, 1597-1604.

Schepens, S., Goldberg, A., & Wallace, M. (2010). The short version of the Activities-specific Balance Confidence (ABC) scale: Its validity, reliability, and relationship to balance impairment and falls in older adults. Archives of Gerontology and Geriatrics, 51, 9-12.

Schott, N. (2008). [German adaptation of the “Activities-Specific Balance Confidence (ABC) scale” for the assessment of falls-related self-efficacy]. Zeitschrift für Gerontologie und Geriatrie, 41, 475-85.

van Heuvelen, M.J., Hochstenbach, J., de Greef, M.H., Brouwer, W.H., Mulder, T., & Scherder, E. (2005). [Is the Activities-specific Balance Confidence Scale suitable for Dutch older persons living in the community?]. Tijdschrift Voor Gerontologie En Geriatrie, 36, 146-54.

See the measure

How to obtain the Activities-specific Balance Confidence Scale

The print version of the scale may be freely reproduced for student training, research and clinical practices in which therapists and assistants use the scale to assess fewer than 1000 patients per year. In all other cases, including: translation into other languages than English, other modifications to the scale itself and/or instructions, use in clinical trials, for commercial or marketing purposes, or in larger scale practices (1,000+ patients per year) and electronic record keeping, permission must be obtained by the researcher or institution. There may be an associated cost.

Dr. Anita Myers is the primary developer and copyright holder of the ABC scale. email: amyers@uwaterloo.ca.

Table of contents

Berg Balance Scale (BBS)

Evidence Reviewed as of before: 07-11-2010
Author(s)*: Lisa Zeltzer, MSc OT; Annabel McDermott, OT
Editor(s): Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc

Purpose

The Berg Balance Scale (BBS) quantitatively assesses balance in older adults.

In-Depth Review

Purpose of the measure

The Berg Balance Scale (BBS) quantitatively assesses balance in older adults.

Available versions

The BBS was published in 1989 by Berg, Wood-Dauphinee, Williams and Maki.

Features of the measure

Items:
In this 14-item scale, patients must maintain positions and complete moving tasks of varying difficulty. In most items, patients must maintain a given position for a specified time.

Scoring:
Patients receive a score from 0-4 on their ability to meet these balance dimensions. A global score can be calculated out of 56. A score of 0 represents an inability to complete the item, and a score of 56 represents the ability to independently complete the item.

  • 0-20 on the BBS represents balance impairment;
  • 21-40 on the BBS represents acceptable balance;
  • 41-56 on the BBS represents good balance.

Subscales:
None typically reported.

Equipment:
Only simple and easily accessible equipment is needed to complete the BBS. This includes a ruler, stopwatch, chair, and a step or stool. Also, the patients will require enough room to move 360 degrees.

Training:
No special training is required to administer the BBS. It has been deemed highly reliable when administered by individuals with no formal training on the administration of the scale.

However, it is important to note that in order to ensure the safety of the patient, the BBS should only be administered by individuals with knowledge on how to safely manage those with stroke. The BBS is a risky assessment where a patient could fall if not supervised by someone with stroke expertise.

Time:
The scale takes approximately 10-15 minutes to complete. The patient must be directly observed to assess whether the task was completed.

Alternative forms of the BBS

  • A short form of the BBS (BBS-3P), which is composed of 7 items, has been developed (Chou, Chien, Hsueh, Sheu, Wang, & Hsieh, 2006).
  • The BBS-3P was found to be psychometrically similar (including test reliability, validity, and responsiveness) to the original BBS for people with stroke.
  • The BBS-3P takes less than 10 minutes to complete and requires only a chair and an object that the patient can retrieve from the floor. The BBS-3P is scored based on 3 levels: unable to complete the task, partially completes task, and able to complete the task. The 7 items included in the BBS-3P are: reaching forward with outstretched arm, standing with eyes closed, standing with one foot in front, turning to look behind, retrieving object from floor, standing on one foot, and changing from a sitting to standing position.
  • Compared with the original BBS, the BBS-3P is a quick and simple measure to complete in either a clinical or a research setting.

Client suitability

Can be used with:

  • Patients with stroke who understand spoken or written language who will find the items challenging.

The BBS was originally designed as a quantitative measure of balance and risk for falls in community-dwelling elderly patients. It has been shown to be a reliable and valid measure of balance in the elderly client with stroke.

Should not be used in:

  • More active elderly post-stroke patients.
  • Post-stroke patients who are younger.
    There may be a ceiling effect with these patients, in that the items may not be sufficiently challenging to measure higher-level balance such as walking outdoors.
  • Severely affected patients such as patients who cannot leave a seated position.
    There may be a floor effect with these patients, as there is only one item assessing balance in the seated position.

Instead, you may wish to consider the Postural Assessment Scale for Stroke Patients (PASS), which was designed as a balance assessment for patients with stroke that is applicable for all patients, even those with the most severe postural performance (Benaim, Pérennou, Villy, Rousseaux, & Pelissier, 1999).

Mao, Hsueh, Tang, Sheu, and Hsieh (2002) compared the psychometrics of the BBS to those of the balance subscale of the Fugl-Meyer Assessment and the Postural Assessment Scale for Stroke Patients in 123 patients with stroke up to 180 days after stroke onset and found that the FM-B and BBS showed a significant floor or ceiling effect at some days after stroke points, whereas the PASS did not show these effects.

In what languages is the measure available?

  • Translated and validated in Portuguese (Miyamoto, Lombardi, Berg, Ramos, & Natour, 2004).
  • Translated and validated in French (Institut de réadaptation de Montréal).
  • Translated (not yet validated) in: Iceland, Norway, Sweden, Denmark, Finland, Italy, the Netherlands, Poland, Korea, Japan, Spain, and Hong Kong and Germany.

Summary

What does the tool measure? Balance in older adults
What types of clients can the tool be used for? The BBS was developed for use with community-dwelling elderly individuals. It can also be used in patients with stroke.
Is this a screening or assessment tool? Assessment.
Time to administer Approximately 10-15 minutes to complete by direct observation.
Versions Short form of the BBS (BBS-3P)
Other Languages Translated and validated in Portuguese, French. Translated (not yet validated) in the following countries: Iceland, Norway, Sweden, Denmark, Finland, Italy, the Netherlands, Poland, Korea, Japan, Spain, and Hong Kong and Germany.
Measurement Properties
Reliability Internal consistency:
One study has reported excellent internal consistency.

Test-retest:
One study has reported excellent test-retest reliability.

Intra-rater:
One study has reported excellent intra-rater reliability.

Inter-rater:
Two studies have reported excellent inter-rater reliability.

Validity Content:
The items were selected based on interviews with 12 geriatric clients and 10 professionals. The list of items was revised following a pretest of all preliminary items.

Criterion:
Concurrent:
Excellent correlations with the Fugl-Meyer balance subscale, Postural Assessment Scale for Stroke Patients, Functional Reach, Tinetti Balance Scale, Timed Up and Go test and Single-Leg Stance; adequate to excellent correlations with the Motor Assessment Scale sitting section and Rivermead Mobility Index (although poor correlations with the weight shift test and step-up tests); adequate correlations with the Barthel Index mobility subscale, dynamic Balance Master measures, and postural sway.

Predictive:
Predicted risk of falling over next 12 months, moderately predictive of length of stay in rehabilitation unit, predicted motor ability 180 days after stroke; not a significant predictor of mean steps per day.

Construct:
Convergent/Discriminant:
Excellent correlations with the Barthel Index, and Fugl-Meyer balance subscale; adequate to excellent correlations with the Functional Independence Measure.

Known Groups:
One study reported that the BBS is able to differentiate between patients according to level of functional ambulation.

Floor/Ceiling Effects Significant floor and ceiling effects have been detected in the BBS.
Sensitivity/ Specificity No studies have reported on the sensitivity/specificity of the BBS with patients with stroke.
Does the tool detect change in patients?

One study reports general sensitivity to change and two studies report large responsiveness to change. Two studies indicate moderate responsiveness to change 6 weeks to 3 months post-stroke, but poor responsiveness following these times. One study reported a minimum absolute change score of 6 points represents genuine change.

Acceptability This direct observation test is not suitable for severely affected patients as it assesses only one item related to balance while sitting. Active individuals will find it too simple. The scale is not suitable for use by proxy.
Feasibility The BBS requires no specialized training to administer, however, the BBS should only be administered by individuals with knowledge on how to safely manage those with stroke as the BBS is a risky assessment where a patient could fall if not supervised by someone with stroke expertise. Relatively little equipment or space is required.
How to obtain the tool?

Click here to find a copy of the BBS.

Psychometric Properties

Overview

Berg, Wood-Dauphinee, Williams, and Maki (1992), and Berg, Wood-Dauphinee, and Williams (1995) examined both the validity and reliability of the BBS. Following these psychometric studies, current research on the BBS has focused mainly on comparing the psychometrics of the BBS to other balance measures (eg. Mao, Hsueh, Tang, Sheu, & Hsieh, 2002) and on testing the psychometrics of the short form of the BBS, the BBS-3P (Chou et al., 2006).

Floor/Ceiling Effects

In a study by Mao et al. (2002), three common balance scales (BBS, the Balance subscale of the Fugl-Meyer Assessment, and the Postural Assessment Scale for Stroke Patients) were compared. A significant floor effect was detected in the BBS and the balance subscale of the Fugl- Meyer 14 days after stroke onset. One possible explanation for this effect is that the least demanding item in these two tests is to sit independently. As patients with severe impairments may be unable to do any of the other activities – for example, stand on one foot, step up on a stool etc. – even as they improve, the result is a floor effect (the score does not show change for those with severe impairments). Thus, in those with severe impairments, you may wish to consider using another scale such as the Postural Assessment Scale for Stroke Patients, which is applicable to all stroke patients. The BBS also had a significant ceiling effect at 90 and 180 days after stroke onset for those with higher-level function, suggesting that the BBS may not be able to discriminate balance function after 90 days, the point at which people typically reintegrate into leisure and community activities.

Reliability

Internal consistency :
Berg et al. (1995) conducted a study to assess the internal consistency of the BBS in both elderly long-term care residents and patients with stroke. The BBS was administered to elderly residents (n=113) at baseline, and at 3, 6 and 9 months, and to patients with stroke (n=70) at 2, 4, 6 and 12 weeks post-stroke onset. At each evaluation, Cronbach’s alphas were greater than 0.83 and 0.97 for the elderly residents and patients with stroke respectively, showing that the BBS has excellent internal consistency.

Intra-rater:
Flansbjer, Blom & Brogardh (2012) conducted an intra-rater test-retest reproducibility study whereby 50 patients with chronic stroke were assessed with the BBS on 2 occasions, 7 days apart, by one rater. Test-retest reliability was excellent (ICC=0.88). The mean difference of test scores, measured by the Bland and Altman technique, was high and positive (d=0.72), indicating a learning effect.
Note: When performing a Bland and Altman analysis, a mean difference close to zero indicates higher agreement between measurements.

Inter-rater and intra-rater:
Berg et al. (1995) also assessed inter-rater reliability . Therapists administered the BBS to 35 patients with stroke within 24 hours of the independent rater. Similarly, caregivers were asked to test the elderly residents within one week of the independent rater. To assess intra-rater reliability , 18 residents and 6 stroke patients were assessed one week apart by the same rater. There was agreement between the raters (ICC = 0.98) and the same rater was consistent at two points in time (ICC = 0.97).

Stevenson (2001) examined inter-rater reliability of the BBS among 48 patients with stroke assessed by two different raters at initial assessment (T1) and second assessment within 24 hours (T2). Agreement between T1 and T2 data was excellent (ICC = 0.92).

Validity

Content:
The items were selected based on interviews with 12 geriatric clients and 10 professionals. The list of items was revised following a pretest of all preliminary items.

Criterion:
Concurrent:
Flansbjer, Blom & Brogardh (2012) reported excellent relationships between the BBS and the Single-Leg Stance (SLS) in 50 patients with chronic stroke (r=0.65 – 0.79, p<0.001), using Pearson product moment correlation coefficients.

Liston and Brouwer (1996) showed that BBS scores related to dynamic Balance Master measures (r ? 0.48) in 20 ambulatory hemiparetic subjects.

Mao et al. (2002) reported excellent relationships between BBS scores and the balance subscale of the Fugl-Meyer (r = 0.90 to 0.92), and Postural Assessment Scale for Stroke Patients (r = 0.92 to 0.95) at 4 assessment times (14, 30, 90, and 180 days post-stroke).

Tyson and DeSouza (2004) tested the concurrent validities of the sitting section of the Motor Assessment Scale, the Berg Balance Scale and Rivermead Mobility Index using Spearman’s rho and found that BBS scores correlated with the the appropriate comparator tests (r = 0.32 to 0.74), except the weight shift test and step-up tests which did not form significant relationship with Berg Balance Scale (r = 0.26 and 0.19 respectively).

Smith, Hembree, and Thompson (2004) found that the BBS correlated with Functional Reach (r = 0.78). When the relationship between the two measures for subjects with similar motor impairments were examined (based on the four categories of stroke severity from the motor section of the Fugl-Meyer as suggested by Duncan et al. (1992)), correlations differed according to patient severity, with the lowest correlation being for those with moderately severe motor impairment (a score of 36-55 on the Fugl-Meyer; r = 0.24), and the highest correlation for those with moderate motor impairments (a score of 56-79 on the FM; r = 0.80).

Thirty-one elderly clients were measured on the BBS, and on lab measures of postural sway and clinical measures of balance and mobility including the Tinetti Balance Subscale, the Barthel mobility subscale, and the Timed Up and Go Test. Postural sway correlated adequately with the BBS (r = -0.55), and clinical measure correlations ranged from poor (r = -0.46) to excellent (r = -0.67) and were negatively correlated (note: low scores on postural sway and clinical measures indicate normal function, whereas a high score on the BBS indicates normal function, resulting in a negative correlation). Correlation with the Tinetti Balance Subscale was excellent (r = 0.91), and the BBS adequately correlated with the Barthel mobility subscale (r = 0.67). Correlation with the Timed Up and Go Test was excellent and negative (r = -0.76), meaning that a low score on the Timed Up and Go Test (a low score suggests normal functioning) corresponds to a high score on the BBS (a high score indicates balance is intact) (Berg et al., 1992).

In this same study, correlations between scores on the BBS and ratings of 113 residents of a home for the elderly and their caregivers ranged from poor to adequate (elderly: r=0.39 to r=0.41; caregivers: r=0.47 to r=0.61) (Berg et al., 1992).

Predictive:
One hundred thirteen elderly individuals were followed for 12 months, and were classified as having 0, 1, and > 2 falls during that time. The relative risk of falling over the next 12 months was 2.7 times more likely in patients who obtained a BBS score < 45 (Berg et al., 1992).

Admission BBS was adequately predictive of length of stay (LOS) in rehabilitation unit (r = -0.39) (this negative relationship suggests that a higher BBS score results in a shorter length of stay) (Juneja et al., 1998).

In Mao et al. (2002), the predictive validity of the BBS was assessed by comparing the results of the BBS at 14, 30, and 90 days after stroke with that of the Motor Assessment Scale at 180 days after stroke by use of Spearman’s correlation coefficient. The scores of the BBS at the earlier 3 days after stroke points were highly correlated with the MAS scores on evaluations on 180 days after stroke (r > 0.8), indicating excellent predictive validity.

Fulk, Reynolds, Mondal & Deutsch (2010) examined the predictive validity of the 6MWT and other widely used clinical measures (FMA LE, self-selected gait-speed, SIS and BBS) in 19 patients with stroke. The BBS was found to not be a significant predictor of mean steps per day (r = 0.54; P = 0.016). Although gait speed and balance were related to walking activity, only the 6MWT was found to be a predictor of community ambulation in patients with stroke.

Construct:
Convergent/Discriminant:
Seventy acute stroke clients were tested on the BBS, the Barthel Index, and the balance subscale of the Fugl-Meyer Assessment at 4, 6 and 12 weeks post-stroke. Correlations between the BBS and the Barthel Index were excellent (ranging from r = 0.80 to r=0.94, and correlations between the BBS and the balance subscale of the Fugl-Meyer ranged from adequate to excellent (ranging from r = 0.62 to r = 0.94) (Berg et al., 1992).

BBS scores were also reported to correlate with the Functional Independence Measure (r = 0.57 to 0.70) (Juneja, Czyrny, & Linn, 1998) and r = 0.76 (Wee, Bagg, & Palepu, 1999).

Known Groups:
Stevenson (2001) examined the known groups validity of the BBS among 48 patients with acute stroke, using Dunn’s method. Patients were grouped according to Functional Ambulation Category (FAC) scores: ASSIST (FAC score ? 2, requiring physical assistance, n=16), SBA (FAC score = 3, requiring stand-by assistance, n=17) or INDEP (FAC score ? 4, independently ambulant, n=15). There was a significant difference between the INDEP and ASSIST groups (Q = 4.47, p<0.05) and the INDEP and SBA groups (Q = 3.07, p<0.05), but not between the SBA and ASSIST groups.

Responsiveness

Flansbjer, Blom & Brogardh (2012) examined the responsiveness of the BBS among 50 patients with chronic stroke who were assessed on 2 occasions, 7 days apart. The standard error of measurement (SEM), i.e. the smallest change that indicates a real improvement for a group of individuals, was 3%. The smallest real difference (SRD) for a single individual was 8%.

Stevenson (2001) examined the responsiveness of the BBS among 48 patients with acute stroke assessed by different raters over three intervals – initial assessment (T1), second assessment within 24 hours (T2), and third assessment after approximately 1 to 2 weeks of intervention (T3). Patients were categorized into one of three groups according to Functional Ambulation Category (FAC) scores: ASSIST (FAC score ≤ 2, requiring physical assistance); SBA (FAC score = 3, requiring stand-by assistance); and INDEP (FAC score ≤ 4, independently ambulant). All groups demonstrated statistically significant increases in BBS performance from T1 to T3 (Wilcoxon Signed Rank Test, W = 77.4 – 106, p ≤ 0.002), but not from T1 to T2. Minimal Detectable Change (MDC) from T1 to T2 = 5.8 (90% CI) indicating that a minimum absolute change score of 6 points represents change in a patient’s BBS performance when assessed by two different raters within 24 hours (all patients ± 6; INDEP group ± 6; SBA group ± 5; ASSIST group ± 7).

Mao et al. (2002) assessed the responsiveness of the BBS, the Balance subscale of the Fugl-Meyer Test, and the Postural Assessment Scale for Stroke Patients by calculating effect size (ES) (dividing the mean change scores by the standard deviation of the change score in the same subjects). The ES showed that the BBS was moderately responsive in detecting changes before 90 days after stroke. The ES for the BBS were greatest in the interval between 14 and 30 days (0.80) and diminished the further one moved through time from the stroke event (30 to 90 days after stroke, ES = 0.69). The ES for the BBS was considered poor at 90-100 days after stroke (ES = 0.40). The changes in the BBS at each stage were significant.

To determine whether the responsiveness of the measures varied depending on the initial stroke-induced deficits, patients were stratified into 1 of the following 3 groups on the basis of their Balance subscale of the Fugl-Meyer Test scores: 0 to 35, severe; 36 to 79, moderate; and 80, mild. The responsiveness of the BBS at different stages for subjects with different levels of stroke severity (ES = 0.21) suggested that the BBS is generally sensitive to change over time after a stroke. However, the BBS was found to be less responsive than the Balance subscale of the Fugl-Meyer Test and Postural Assessment Scale for Stroke Patients for severe patients with stroke, at 14 to 30 days after stroke. The reason for this finding might be that the BBS was not originally designed for patients with stroke, and only one item of the scale assesses balance ability in the sitting position. Because sitting balance is one of the first postures to be restored after a stroke, it seems that the BBS is lacking items to detect change in patients who are unable to stand independently.

Wood-Dauphinee, Berg, Bravo, and Williams (1997) reported an ES of 0.66 for initial 6-week post-stroke evaluation period, ES = 0.25 for 6-12 weeks post-stroke, and an overall ES = 0.97.

Salbach et al. (2001) used standardized response mean (SRM = mean change/standard deviation of change) to estimate the responsiveness of the 5-metre walk test, the 10-metre walk test, the BBS, the Barthel Index , the Stroke Rehabilitation Assessment of Movement, and the Timed Up and Go in 50 subjects with residual gait deficits after a first-time stroke. The SRM from 8-38 days post-stroke for the BBS was 1.04. The BBS was rated as the second most responsive measure (the 5-metre walk test was the most responsive measure) and was recommended for use in patients who have suffered a severe stroke.

English, Hillier, Stiller, and Warden-Flood (2006) investigated the sensitivity of gait speed, the BBS and the Motor Assessment Scale in 78 subjects receiving inpatient rehabilitation following a first or recurrent stroke to detect change over time. Subjects were assessed within one week of admission and one week of discharge. The BBS was sensitive to change (only two patients showed no change) and demonstrated a large ES (d = 1.01).

References

  • Benaim, C., Pérennou, D. A., Villy, J., Rousseaux, M., Pelissier J. Y. (1999). Validation of a Standardized Assessment of Postural Control in Stroke Patients: The Postural Assessment Scale for Stroke Patients (PASS). Stroke, 30, 1862-1868.
  • Berg, K.O., Wood-Dauphinee, S., Williams, J. L., Maki, B. (1989). Measuring balance in the elderly: Validation of an instrument. Physiotherapy Canada, 41(6), 304-311.
  • Berg, K., Wood-Dauphinee, S. L., Williams, J. I., Maki, B. E. (1992). Measuring balance in the elderly: Validation of an instrument. Canadian Journal of Public Health, 83(S2), S7-S11.
  • Berg, K., Wood-Dauphinee, S. L., Williams, J. I. (1995). The Balance Scale: reliability assessment with elderly residents and patients with an acute stroke. Sc and J Rehabil Med, 27(1), 27-36.
  • Chou, C. Y., Chien, C. W., Hsueh, I. P., Sheu, C. F., Wang, C. H., Hsieh, C. L. (2006). Developing a Short Form of the Berg Balance Scale for People With Stroke. Physical Therapy, 86(2), 195-204.
  • Juneja, J., Czyrny, J. J., Linn, R. T. (1998). Admission balance and outcomes of patients admitted for acute inpatient rehabilitation. Am J Phys Med Rehabil, 77, 388-393.
  • Liston, R., Brouwer, B. J. (1996). Reliability and validity of measures obtained from stroke patients using the balance master. Arch Phys Med Rehabil, 77, 425-430.
  • English, C. K., Hillier, S. L., Stiller, K., Warden-Flood, A. (2006). The sensitivity of three commonly used outcome measures to detect change amongst patients receiving inpatient rehabilitation following stroke. Clin Rehabil, 20(1), 52-55.
  • Fulk, G. D., Reynolds, C., Mondal, S., & Deutsch, J. E. (2010). Predicting home and community walking activity in people with stroke. Arch Phys Med Rehabil, 91, 1582-1586.
  • Flansbjer, U-B., Blom, J., & Brogardh, C. (2012). The reproducibility of Berg Balance Scale and the Single-Leg Stance in chronic stroke and the relationship between the two tests. Physical Medicine & Rehabilitation, 4(3), 165-170.
  • Mao, H. F., Hsueh, I. P., Tang, P. F., Sheu, C. F., Hsieh, C. L. (2002). Analysis and comparison of the psychometric properties of three balance measures for stroke patients. Stroke, 33, 1022.
  • Miyamoto, S. T., Lombardi, I. J., Berg, K. O., Ramos, L. R., Natour, J. (2004). Brazilian version of the Berg balance scale. Braz J Med Biol Res, 37(9), 1411-1421.
  • Salbach, N. M., Mayo, N. E., Higgins, J., Ahmed, S., Finch, L. E., Richards, C. L. (2001). Responsiveness and predictability of gait speed and other disability measures in acute stroke. Arch Phys Med Rehabil, 82, 1204-1212.
  • Scherfer, E., Bohls, C., Freiberger, E., Heise, K. F., Hogan, D. (2006). Berg-Balance-Scale – German Version – Translation of a standardized instrument for the assessment of balance and risk of falling. Physioscience, 2, 59-66.
  • Smith, P. S., Hembree, J. A., Thompson, M. E. (2004). Berg Balance Scale and Functional Reach: Determining the best clinical tool for individuals post acute stroke. Clin Rehabil, 18, 811-818.
  • Stevenson, T.J. (2001). Detecting change in patients with stroke using the Berg Balance Scale. Australian Journal of Physiotherapy, 47, 29-38.
  • Tyson, S. F., De Souza, L. H. (2004). Reliability and validity of functional balance tests post stroke. Clin Rehabil, 18, 916-923.
  • Wee, J. Y. M., Bagg, S. D., Palepu, A. (1999). The Berg Balance Scale as a predictor of length of stay and discharge in an acute stroke rehabilitation setting. Arch Phys Med Rehabil, 80, 448-452.
  • Wood-Dauphinee, S., Berg, K. O., Bravo, G., Williams, J. L. (1997). The Balance Scale: responsiveness to clinically meaningful changes. Can J Rehab, 10, 35-50.

See the measure

Click here to find a copy of the full BBS

By clicking here, you can access a video showing how to administer the assessment.

Table of contents

Charlson Comorbidity Index (CCI)

Evidence Reviewed as of before: 03-02-2009
Author(s)*: Sabrina Figueiredo, BSc
Editor(s): Lisa Zeltzer, MSc OT; Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc

Purpose

The Charlson Comorbidity Index (CCI) assesses comorbidity level by taking into account both the number and severity of 19 pre-defined comorbid conditions. It provides a weighted score of a client’s comorbidities which can be used to predict short term and long-term outcomes such as function, hospital length of stay and mortality rates. The CCI is the most widely used scoring system for comorbities used by researchers and clinicians (Charlson, Pompei, Ales, & Mackenzie, 1987; Elixhauser, Steiner, Harris, & Coffey, 1998).

In-Depth Review

Purpose of the measure

The Charlson Comorbidity Index (CCI) assesses comorbidity level by taking into account both the number and severity of 19 pre-defined comorbid conditions. It provides a weighted score of a client’s comorbidities which can be used to predict short term and long-term outcomes such as function, hospital length of stay and mortality rates. The CCI is the most widely used scoring system for comorbities used by researchers and clinicians (Charlson, Pompei, Ales, & Mackenzie, 1987; Elixhauser, Steiner, Harris, & Coffey, 1998).

Available versions

The CCI was published by Charlson, Pompei, Ales, and Mackenzie in 1987.

Features of the measure

Items:
The CCI is comprised of 19 comorbid conditions: myocardial infarct, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, diabetes, hemiplegia, moderate or several renal disease, diabetes with end organ damage, any tumor, leukemia, lymphoma, moderate or severe liver disease, metastatic solid tumor, AIDS. Each disease is given a different weight based on the strength of its association with 1-year mortality as follows (Charlson et al., 1987):

Assigned weights for diseases Comorbid Conditions
1 Myocardial infarct, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, diabetes
2 Hemiplegia, moderate or several renal diseases, diabetes with end organ damage, any tumor, leukemia, lymphoma
3 Moderate or severe liver disease
6 Metastatic solid tumor, AIDS

The CCI can be completed from medical records, administrative databases, or interview-based questionnaires (Bravo, Dubois, Hebert, De Wals, & Messier, 2002).

Scoring:
The total score in the CCI is derived by summing the assigned weights of all comorbid conditions presented by the client. Higher scores indicate a more severe condition and consequently, a worse prognosis (Charlson, Szatrowski, Peterson, & Gold, 1994).

Time:
Not reported

Subscales:
None

Equipment:
Not applicable.

Training:
No specific training is available.

Alternative forms of the CCI

The CCI has a weighted age version, two adaptations to be used with ICD-9 databases, and one version to be used with clients with amputations (Charlson et al., 1994; Deyo, Cherkin, & Ciol, 1992; Melchiore, Findley, & Boda, 1996; Romano, Roos, & Jollis, 1993).

Client suitability

Can be used with:

  • Clients with stroke.
  • The CCI is a general scoring system allowing for its use with a variety of populations (Groot, Beckerman, Lankhorst, & Bouter, 2003).

Should not be used in:

  • To date, there is no information on restrictions for using the CCI.

In what languages is the measure available?

Not applicable

Summary

What does the tool measure? The CCI measures comorbidity level.
What types of clients can the tool be used for? The CCI can be used with, but is not limited to clients with stroke.
Is this a screening or assessment tool? Screening.
Time to administer Not reported.
Versions Age CCI; ICD-9-CM; CCI for clients with amputations.
Other Languages Not applicable
Measurement Properties
Reliability Internal consistency:
No studies have examined the internal consistency of the CCI.
Test-retest:
One study has examined the test-retest reliability of the CCI and reported excellent test-retest reliability using Intraclass Correlation Coefficient (ICC) and Spearman’s Rank Correlation.
Intra-rater:
No studies have examined the intra-rater reliability of the CCI.
Inter-rater:
One study examined the inter-rater reliability of the CCI and reported adequate inter-rater reliability using ICC.
Validity Content:
One study examined the content validity of the CCI by reporting the steps for generating the weighted comorbidity index.
Criterion:
Concurrent:
No studies have examined the concurrent validity of the CCI.
Predictive:
Four studies have examined the predictive validity of the CCI and reported that the CCI was able to predict function at 3 months post-stroke, poor outcomes on the modified Rankin Scale at discharge, and mortality after 1 year. In contrast, the CCI was not able to predict length of stay, Functional Independence Measure scores, and modified Rankin Scale scores at 4 months post-stroke.
Construct:
Convergent:
Three studies examined the convergent validity of the CCI and reported excellent correlations between the CCI and the Functional Comorbidity Index, poor to adequate correlations between the CCI and total numbers of medication consumed, numbers of hospitalization, length of stay, total costs, laboratory studies, therapeutic interventions, consultations and days of interruption of the rehabilitation program using Spearman rank correlation.
Known Groups:
No studies have examined the known groups validity of the CCI.
Floor/Ceiling Effects No studies have examined floor/ceiling effects of the CCI.
Sensitivity/ Specificity No studies have examined the sensitivity/specificity of the CCI.
Does the tool detect change in patients? No studies have examined the responsiveness of the CCI.
Acceptability The CCI is the most widely used index to assess comorbidity.
Feasibility The CCI can be completed from medical records, administrative databases, or interview-based questionnaires.
How to obtain the tool? The CCI can be obtained from its original publication: (Charlson, Pompei, Ales, & Mackenzie, 1987)

Psychometric Properties

Overview

We conducted a literature search to identify all relevant publications on the psychometric properties of the Charlson Comorbidity Index (CCI) in individuals with stroke. We identified 6 studies.

Reliability

Test-retest:
Katz, Chang, Sangha, Fossel, and Bates (1996) evaluated the test-retest reliability of the questionnaire format of the CCI in 25 inpatients with different diagnoses including stroke. Participants were evaluated by the same rater twice within 24 hours. Test-retest reliability was excellent as calculated using Intraclass Correlation Coefficient (ICC = 0.92) and Spearman’s Rank Correlation (rho = 0.94).

Inter-rater:
Liu, Domen and Chino (1997) assessed the inter-rater reliability of the CCI in 10 clients with stroke. The CCI was administered by two examiners blinded to each other’s scores. Inter-rater reliability, as calculated using Intraclass Correlation Coefficient, was adequate (ICC = 0.67).

Validity

Content:
Charlson et al. (1987) identified the comorbid conditions of 559 inpatients with breast cancer. They then calculated the relationship of potential prognostically important variables to survival using Cox’s regression analysis. Finally, the adjusted relative risk was estimated to each comorbid condition.

Criterion:
Concurrent:
No gold standard exists against which to compare the CCI.

Predictive:
Liu et al. (1997) estimated the ability of the CCI at hospital admission to predict length of stay and the Functional Independence Measure (FIM) score (Keith, Granger, Hamilton, & Sherwin, 1987) at discharge. Predictive validity was calculated in 106 clients with Spearman’s Rank Correlation. Correlation between the CCI and the FIM was poor(rho = -0.19) as was the correlation between the CCI and length of stay (rho = 0.16). These results suggest that the CCI measured at hospital admission may not be predictive of length of stay or the FIM at discharge.

Goldstein, Samsa, Matchar, and Horner (2004) examined in 960 clients with acute stroke whether the CCI measured at admission was able to predict the modified Rankin Scale (mRS) (Rankin, 1957) at hospital discharge, and, 1-year mortality rates. Predictive validity was analyzed using logistic regression. The CCI was dichotomized into low comorbidity (scores <2) and high comorbidity (scores <2) and the mRS into good outcomes (scores <2) and poor outcomes (scores ≥2). Higher CCI scores were associated with a 36% increased odds of having poor outcomes on the modified Rankin Scale and 72% greater odds of death at 1 year post-stroke.

Fischer, Arnold, Nedeltchev, Schoenenberger, Kappeler, Hollinger et al. (2006) verified in 259 clients the ability of the CCI, as measured at admission to a stroke unit, to predict poor outcomes on the modified Rankin Scale (mRS – Rankin, 1957) at 4 months after hospital discharge. The mRS was dichotomized into good outcomes (scores ≤ 2) and poor outcomes (scores >2). Logistic regression analyses revealed that the CCI was not able to predict poor outcomes on the mRS. In this study, the predictors of the mRS score at 4 months post-stroke were stroke severity, atrial fibrilation, coronary artery disease and diabetes.

Tessier, Finch, Daskalopoulou, and Mayo (2008) examined, in 672 participants, the ability of the CCI, the Functional Comorbidity Index (Groll, Bombardier, & Wright, 2005), and a stroke-specific comorbidity index (developed by the same authors) to predict function 3 months post-stroke. Predictive validity was calculated by use of c-statistics to calculate the area under the Receiver Operating Characteristic (ROC) curve. The ability of the CCI (AUC = 0.76), the Functional Comorbidity Index (AUC = 0.71) and the stroke-specific comorbidity index (AUC = 0.71) to predict function at 3 months post-stroke were all adequate. These results suggest that the percentage of patients correctly classified according to their function at 3 months post-stroke is slightly higher when using the CCI over these other comorbidity measures.

Construct:
Convergent/Discriminant:

Katz et al. (1996) tested the convergent validity of the CCI by comparing it to self-reported number of prescription medications consumed, number of hospitalizations, length of stay and total financial costs in 170 hospital inpatients, including those with stroke. Correlations, as calculated using Spearman’s Rank Correlation, were all poor between the CCI and self-reported number of prescription medications (rho = 0.06), number of hospitalizations (rho = 0.22), length of stay (rho = 0.20) and total costs (rho = 0.26).

Liu et al. (1997) measured the convergent validity of the CCI in 106 clients with stroke, by comparing it to the number of medication consumed, laboratory studies, therapeutic interventions, number of consultations during hospital’s stay, and days of interruption of participation in rehabilitation due to complications. Adequate correlations were found between the CCI and the total number of medications consumed (rho = 0.48) and poor correlations were found between the CCI and laboratory studies (rho = 0.28), therapeutic interventions (rho = 0.19), consultations (rho = 0.25), and days of interruption of rehabilitation participation (rho = 0.22).

Tessier et al. (2008) analyzed the convergent validity of the CCI by comparing it to the Functional Comorbidity Index (Groll et al., 2005) in 437 clients with Correlations were found to be excellent (rho = 0.62).

Known groups:
No studies have examined known groups validity of the CCI.

Responsiveness

No studies have examined the responsiveness of the CCI.

References

  • Bravo, G., Dubois, M.F., Hebert, R., De Wals, P., & Messier, L. (2002). A perspective evaluation of the Charlson Comorbidity Index for use in long-term care patients. JAGS, 50, 740-745.
  • Charlson, M., Pompei, P., Ales, M.L., & Mackenzie C.R. (1987). A new method of classifying comorbidity in longitudinal studies: Development and validation. J Chronic Dis, 40, 373-393.
  • Charlson, M., Szatrowski, T.P., Peterson, J., & Gold, J. (1994). Validationof a Combined Comorbidity Index. Journal of Clinical Epidemiology, 47(11), 1245-1251.
  • De Groot, V., Beckerman, H., Lankhorst, G.J., & Bouter, L.M. (2003). How to measure comorbidity: A critical review of available methods. Journal of Clinical Epidemiology, 56, 221-229.
  • Deyo, R.A., Cherkin, D.C., & Ciol, M.A. (1992). Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. Journal Clinical Epidemiology, 45, 613-619.
  • Elixhauser, A., Steiner, C., Harris, D.R., & Coffey, R.M. (1998).Comorbidity measures for use with administrative data. Medical Care, 36(1), 8-27.
  • Fischer, U., Nedeltchev, K., Schoenenberger, R.A., Kappeler, L., Hollinger, P.,Schroth, G. et al. (2006). Impact of comorbidity on ischemic stroke outcome. Acta Neurol Scand, 113, 108-113.
  • Goldstein, L.B., Samsa, G.P., Matchar, D.B., & Horner, R.D. (2004). Charlson Index Comorbidity Adjustment for Ischemic Stroke Outcome Studies. Stroke, 35, 1941-1945.
  • Groll, D., Bombardier, C., & Wright, J. (2005). The development of a comorbidity index with physical function as the outcome. Journal of Clinical Epidemiology, 58, 595-602.
  • Hall, W. H., Ramachandran, R., Narayan, S., Jani, A. B., & Vijayakumar, S. (2004). An electronic application for rapidly calculating Charlson comorbidity score. BMC Cancer, 4, 94.
  • Katz, J., Chang, L., Sangha, O., Fossel, A., & Bates, D. (1996). Can comorbidity be measured by questionnaire rather than medical record review? Medical Care, 34(1), 73-84.
  • Keith, R.A., Granger, C.V., Hamilton, B.B., & Sherwin, F.S. (1987). The functional independence measure: A new tool for rehabilitation. Adv Clin Rehabil, 1, 6-18.
  • Liu, M., Domen, K., & Chino, N. (1997). Comorbidity measures for stroke outcome research: A preliminary study. Arch Phys Rehabil, 78, 166-172.
  • Melchiore, P.J., Findley, T., Boda, W. (1996). Functional outcome and comorbidity indexes in the rehabilitation of the traumatic versus the vascular unilateral lower limb amputee. Am J Phys Med Rehabil, 75, 9-14.
  • Rankin, J. (1957). Cerebral vascular accidents in patients over the age of 60. Scott Med J, 2, 200-215.
  • Romano, P.S., Roos, L.L., & Jollis, J.G. (1993). Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. Journal of clinical epidemiology, 46 (10) 1075-1079.
  • Tessier, A., Finch. L., Daskalopoulou, S.S., Mayo, N.E. (2008). Validation of the Charlson Comorbidity Index for Predicting Functional Outcome of Stroke. Arch Phys Med Rehabil, 89, 1276-1283.

See the measure

How to obtain the CCI

An electronic application for rapidly calculating Charlson Comorbidity Index score

The following link will allow you to download an Excel Spread sheet calculator for Charlson Comorbidity Index: Excel calculator Charlson Index

Table of contents

Chedoke-McMaster Stroke Assessment

Evidence Reviewed as of before: 19-08-2008
Author(s)*: Sabrina Figueiredo, BSc; Katie Marvin, MSc, PT Candidate
Editor(s): Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc; Lisa Zeltzer, MSc OT

Purpose

The Chedoke-McMaster Stroke Assessment measures physical impairment and disability in clients with stroke and other neurological impairment. The measure consists of an Impairment Inventory and an Activity Inventory (Moreland, Gowland, Van Hullenaar, & Huijbregts, 1993). The first inventory aims to determine the presence and severity of common physical impairments, to classify or stratify patients when planning, selecting interventions and evaluating their effectiveness and to predict outcomes. The second inventory measures changes in physical function (Gowland, Stratford, Ward, Moreland, Torresin, Van Hullenar, Sanford, Barreca, Vanspall, & Plews, 1993). The Chedoke-McMaster Stroke Assessment is a discriminative, predictive and evaluative tool.

In-Depth Review

Purpose of the measure

The Chedoke-McMaster Stroke Assessment measures physical impairment and disability in clients with stroke and other neurological impairment. The measure consists of an Impairment Inventory and an Activity Inventory (Moreland, Gowland, Van Hullenaar, & Huijbregts, 1993). The first inventory aims to determine the presence and severity of common physical impairments, to classify or stratify patients when planning, selecting interventions and evaluating their effectiveness and to predict outcomes. The second inventory measures changes in physical function (Gowland, Stratford, Ward, Moreland, Torresin, Van Hullenar, Sanford, Barreca, Vanspall, & Plews, 1993). The Chedoke-McMaster Stroke Assessment is a discriminative, predictive and evaluative tool. It is recommended that measures of motor impairment, such as the Chedoke-McMaster Stroke Assessment, be accompanied by a measure of functional disability such as the Barthel Index (BI) or Functional Independence Measure (FIM) (Poole & Whitney, 2001).

Available versions

There is only one version of the Chedoke-McMaster Stroke Assessment, which was developed by Gowland, Van Hullenar, Moreland, Vanspall, Barreca, Ward, Huijbregts, Stratford and Barclay-Goddard from the original work by Brunnstrom.

A complimentary measure for the Chedoke-McMaster Stroke Assessment, the Chedoke Arm and Hand Inventory (CAHAI), was developed by Barreca, Gowland, Stratford, Huijbregts, Griffiths, Torresin, Dunkley, Miller and Masters, in 2004, to assess, exclusively, the recovery of the paretic upper limb. To date, there are three different versions of the CAHAI. The original version comprehends 13 items, which was then shortened to a version with 9 and 7 items. This CAHAI is summarized in its own module.

Features of the measure

Items:
The Chedoke-McMaster Stroke Assessment is a performance-based measure that consists of two inventories: the Impairment Inventory and the Activity Inventory.
The Impairment Inventory is used to determine the presence and severity of common physical impairments. It has six dimensions (recovery stage of the arm, hand, leg, foot, postural control, and shoulder pain). Each dimension is measured on a 7-point scale (Gowland et al., 1993). The 7-point scale corresponds to seven stages of motor recovery. The 7-point scale for shoulder pain is based on pain severity. The Impairment Inventory is considered to be a discriminative and predictive tool (Huijbregts, Gowland, & Gruber, 2000; Moreland et al., 1993).

The Activity Inventory was originally called the Disability Inventory. Its name changed in 1999, in accordance with the World Health Organization (WHO) terminology (Huijbregts et al., 2000). The aim of this inventory is to measure clinically important changes in the client’s functional ability. This Activity Inventory is made up of the gross motor function and walking indexes.

The gross motor function index consists of the 10 following items: 1 – supine to side lying on strong side; 2 – supine to side lying on weak side; 3 – side lying to long sitting through strong side; 4 – side lying to sitting on side of the bed through strong side; 5 – side lying to sitting on side of the bed through weak side; 6 – standing; 7 – transfer to and from bed toward strong side; 8 – transfer to and from bed toward weak side; 9 – transfer up and down from floor to chair; 10 – transfer up and down from floor and standing. The walking index consists of the 5 following items: 11 – walking indoors; 12 – walking outdoors, over rough ground, ramps, and curbs; 13 – walking outdoors several blocks; 14 – stairs; 15 – age and sex appropriate walking distance in meters for 2 minutes. (Finch et al., 2002; Gowland et al., 1993; Huijbregts at al., 2000). The Activity Inventory is considered an evaluative tool (Huijbregts at al., 2000; Moreland et al., 1993).

Scoring:
The Impairment Inventory is scored on a 7-point scale, where 1 – is flaccid paralysis; 2 – spasticity is present and felt as a resistance to passive movement; 3 – marked spasticity but voluntary movement present within synergistic patterns; 4 – spasticity decreases; 5 – spasticity wanes but is evident with rapid movement at the extremes of range; 6 – coordination and patterns of movement are near normal; and 7 – normal movement. The 7-point scale corresponds to seven stages of motor recovery. The 7-point scale for shoulder pain is based on pain severity. The minimum score for the Impairment Inventory is 6 and the maximum score is 42 (Gowland et al., 1993).

The Activity Inventory is also scored on a 7-point scale, based on the amount of assistance the individual with stroke requires. It is categorized by the need for assistance from another person, the need for equipment, or the need for extra time to accomplish a task (Huijbregts at al., 2000). For the Activity Inventory, the scoring key from the Functional Independence Measure (Keith, Granger, Hamilton & Sherwin, 1987) is used, where 1 – the client needs total assistance; 2 – maximal assistance; 3 – moderate assistance, 4 – minimal assistance, 5 – clients needs supervision; 6 – client is modified independent (needs assistance from devices); 7 – client is timely and safely independent (Gowland et al., 1993).

The maximum score is 100, where higher scores reflect normal function (Finch et al., 2002; Gowland et al., 1993). More specifically, the maximum score for the gross motor function index is 70 and for the walking index is 30 (Gowland et al., 1993). Additionally, a 2-point bonus should be assigned for those who walk, appropriate distances, in meters, accordingly to the norms for their age and sex, on item 15 (the 2-Minute Walk Test) (Huijbregts at al., 2000).

Detailed administration guidelines and scoring are in the development manual that can be obtained by emailing to the following address: djohnstn@mcmaster.ca at a cost of $50.00 CAD.

Time:
The time to administer the Chedoke-McMaster Stroke Assessment typically varies from 45 to 60 minutes depending on the client’s ability to complete the required task (Finch et al., 2002; Gowland et al., 1993; Poole & Whitney, 2001). Clients with severe stroke will typically take longer to accomplish all tasks when compared to clients with mild stroke.

Subscales:
The Chedoke-McMaster Stroke Assessment is divided into two inventories: Impairment and Activity. The Activity Inventory, initially called the Disability Inventory, subdivides into gross motor and walking indexes (Finch et al., 2002; Gowland et al., 1993; Huijbregts at al., 2000).

Equipment:

  • An adjustable table (Finch et al., 2002)
  • A chair with armrests (Finch et al., 2002)
  • A floor mat (Finch et al., 2002)
  • Pillows (Finch et al., 2002)
  • Pitcher with water (Finch et al., 2002)
  • Measuring cup (Finch et al., 2002)
  • A ball 2.5 inches in diameter (Finch et al., 2002)
  • A footstool (Finch et al., 2002)
  • 2m line marked on the floor (Finch et al., 2002)
  • A stopwatch (Finch et al., 2002)

Training:
Training is provided by the authors at McMaster University in Hamilton, Ontario. Further information about training can be obtained by emailing: pmiller@mcmaster.ca

Alternative forms of the Chedoke-McMaster Stroke Assessment

None.

Client suitability

Can be used with:

  • Clients with stroke.
  • Clients with other neurological impairment

Should not be used with:

  • Clients younger than 19 years old (Finch et al., 2002), as the measure was developed with adults and its psychometrics properties were tested only for this population.
  • It is not suited to proxy use.

In what languages is the measure available?

English, French and German

Summary

What does the tool measure? The Chedoke-McMaster Stroke Assessment measures specific changes in limb function among individuals who sustained cortical damage resulting in hemiplegia.
What types of clients can the tool be used for? The Chedoke-McMaster Stroke Assessment can be used with, but is not limited to clients with stroke.
Is this a screening or assessment tool? Screening and assessment.
Time to administer An average of 45 to 60 minutes.
Versions There are no alternative versions.
Other Languages French.
Measurement Properties
Reliability Internal consistency:
No studies have examined the internal consistency of the Chedoke-McMaster Stroke Assessment.
Test-retest:
One study has examined the test-retest reliability of the Chedoke-McMaster Stroke Assessment and reported excellent test-retest reliability using ICC.
Intra-rater:
One study has examined the intra-rater reliability of the Chedoke-McMaster Stroke Assessment and reported excellent intra-rater reliability using ICC.
Inter-rater:
Three studies have examined the inter-rater reliability of the Chedoke-McMaster Stroke Assessment and reported excellent inter-rater reliability using ICC.
Validity Content:
Two studies have examined the content validity of the Chedoke-McMaster Stroke Assessment.
Criterion:
Concurrent:
One study has examined the concurrent validity of the Chedoke-McMaster Stroke Assessment and reported excellent correlation between the Chedoke-McMaster Stroke Assessment total score and the Fugl-Meyer Assessment total score and the Functional Independence Measure (FIM) total score, using Pearson correlation.
Predictive:
One study has examined the predictive validity of the Chedoke-McMaster Stroke Assessment and reported it is a predictor of functional ability and sensorimotor recovery after stroke.
Construct:
Convergent:
Two studies examined convergent validity of the Chedoke-McMaster Stroke Assessment, 1 reported excellent correlations between similar impairments from the Impairment Inventory and the Fugl-Meyer Assessment and between similar activity limitations from the Activity Inventory and the Functional Independence Measure, using Pearson Correlation. The other reported excellent correlation between totals scores on the Activity Inventory (AI) of the Chedoke-McMaster Stroke Assessment and the Clinical Outcomes Variable Scale at admission, discharge and change from admission to discharge.
Known Groups:
One study examined known groups validity of the Chedoke-McMaster Stroke Assessment and reported that it is able to distinguish between subjects who changed little (<20 on FIM), and those who change more (>20 on FIM), using student t-test.
Floor/Ceiling Effects No studies have examined floor/ceiling effects of the Chedoke-McMaster Stroke Assessment.
Sensitivity/ Specificity No studies have examined the sensitivity/specificity of the Chedoke-McMaster Stroke Assessment.
Does the tool detect change in patients? Two studies have examined the responsiveness of the Chedoke-McMaster Stroke Assessment and reported that it has a large variance ratio and a minimal clinically-important change is expressed by a change of 8 units in the Activity Inventory.
Acceptability Administration of the entire Chedoke-McMaster Stroke Assessment is lengthy. The test is scored by direct observation.
Feasibility The Chedoke-McMaster Stroke Assessment must be administered by a trained physical or occupational therapist. It does not require any specialized equipment.
How to obtain the tool?

The Chedoke-McMaster can be ordered by email: djohnstn@mcmaster.ca

Psychometric Properties

Overview

We conducted a literature search to identify all relevant publications on the psychometric properties of the Chedoke-McMaster Stroke Assessment in individuals with stroke. We identified six studies. The Chedoke-McMaster Stroke Assessment appears to be responsive in clients with stroke.

Floor/Ceiling Effects

No studies have examined the floor/ceiling effects of the Chedoke-McMaster Stroke Assessment.

Reliability

Test-retest:
Gowland, Stratford, Ward, Moreland, Torresin, Van Hullenar, et al. (1993) examined the test-retest reliability of the Activity Inventory section of the Chedoke-McMaster Stroke Assessment in 32 clients with stroke, at a mean age of 64 years. Participants were re-assessed with a 5-day interval. The test-retest reliability for the Activity Inventory, as calculated using Intraclass Correlation Coefficient (ICC), was excellent (ICC = 0.98), as were the gross motor function (ICC = 0.96) and walking (ICC = 0.98) indexes.

Intra-rater:
Gowland et al. (1993) estimated the intra-rater reliability of the Impairment Inventory section of the Chedoke-McMaster Stroke Assessment in 32 clients with stroke, at a mean age of 64 years. Participants were assessed at admission to the rehabilitation center, and their performances were videotaped. Scoring on the second evaluation was based on the videotape recorded previously. The intra-rater reliability, as calculated using ICC was excellent for both Impairment Inventory evaluations (ICC = 0.98), as well as for the dimension’s shoulder pain (ICC = 0.96), postural control (ICC = 0.96), arm (ICC = 0.95), hand (ICC = 0.93), leg (ICC = 0.98) and foot (ICC = 0.94).

Inter-rater:
Gowland et al. (1993) estimated the inter-rater reliability of the Activity Inventory section of the Chedoke-McMaster Stroke Assessment in 32 clients with stroke, at a mean age of 64 years. Participants were assessed simultaneously by two raters. The ICC for the total score showed excellent agreement (ICC = 0.97), as well as for the dimension’s shoulder pain (ICC = 0.95), postural control (ICC = 0.92), arm (ICC = 0.88), hand (ICC = 0.93), leg (ICC = 0.85) and foot (ICC = 0.96).

Gowland et al. (1993) examined the inter-rater reliability of the Impairment Inventory section of the Chedoke-McMaster Stroke Assessment in 32 clients with stroke, at a mean age of 64 years. Participants were re-assessed within 5 days by a second rater. The inter-rater reliabilities as calculated using ICC were excellent for the Impairment Inventory (ICC = 0.99), as well as for the gross motor function (ICC = 0.98) and walking (ICC = 0.98) indexes.

Crowe, Harmer, and Sharp (1996) assessed the inter-rater reliability of the Impairment Inventory section of the Chedoke-McMaster Stroke Assessment in 28 participants with Acquired Brain Injury. Participants were assessed with a 2-week interval by two therapists. Agreement between raters for the Impairment Inventory, as calculated using ICC, was excellent (r = 0.99).
Note: The severity of the Acquired Brain Injury and the reason for the 2 weeks delay when measuring inter-rater reliability were not specified by the authors.

Validity

Content:
Moreland, Gowland, Van Hullenar, and Huijbregts (1993) performed a literature review to gather evidence for a theoretical basis of the Chedoke-McMaster Stroke Assessment. All items from both inventories had enough scientific evidence supporting its assumptions. Thus, the authors were able to establish a theoretical basis underlying the content of the Chedoke-McMaster Stroke Assessment.

Huijbregts, Gowland, and Gruber (2000) carried out a survey in 34 clients with stroke and 27 caregivers to verify whether the content in the Activity Inventory is representative of skills that are important to that population. On a scale where 1 is not at all important and 7 is extremely important, all items received a 7 from at least one person in each group. For most items, the mean level was above 5, except for the 2-Minute Walk Test, which had the lowest score from both clients (1.78) and caregivers (3.52). The two most important items according to clients’ and caregivers’ perspective was standing and transferring from and to bed towards the strong side.

Criterion:
Concurrent:
Gowland et al. (1993) compared the Chedoke-McMaster Stroke Assessment with the Fugl-Meyer Assessment –FMA (Fugl-Meyer, Jääskö, Leyman, Olsson, & Steglind, 1975) and the Functional Independence Measure (FIM) (Keith, Granger, Hamilton & Sherwin, 1987) in 32 participants with stroke. Using Pearson Correlation Coefficients, the correlation between the Chedoke-McMaster Stroke Assessment total score and the FMA total score (r = 0.95) and the FIM total score (r = 0.79) were excellent.

Predictive:
Gowland (1984) examined whether the Chedoke-McMaster Stroke Assessment was able to predict sensorimotor recovery at discharge from an active rehabilitation program. Predictive validity of the Chedoke-McMaster Stroke Assessment was examined in 335 active stroke rehabilitation inpatients. Assessments were performed at admission to and at discharge from the rehabilitation center. The length of stay varied from 1 to 49 weeks with an average of seven weeks. At discharge, the 23 independent variables selected were able to predict 11 out of 14 outcomes. Among these independent variables, stage of recovery of the leg was found to be the most important predictive variable, followed by weeks’ post-stroke and gross motor performance.

Valach, Singer, Hartmeier, Hofer & Cox Steck (2003) examined whether scores from the Chedoke-McMaster Stroke Assessment (CMSA) were predictive of scores on the Barthel Index (BI) and vice versa, in 127 patients with vascular brain-damage. Regression analysis revealed that as few as 3 items on the CMSA disability index were needed to predict BI scores, however 6 to 8 items on the BI were needed to predict CMSA scores. Although only a few items on the CMSA were required to predict BI scores, there was still a large portion of unexplained variance and thus, it is recommended that both the BI and CMSA be performed in situations where a comprehensive evaluation of patients is desired.

Construct:
Convergent/Discriminant:
Gowland et al. (1993) evaluated the convergent validity of the Chedoke-McMaster Stroke Assessment by comparing similar impairments between the Impairment Inventory and the Fugl-Meyer Assessment (FMA) (Fugl-Meyer et al., 1975). Correlations, as calculated using Pearson Correlation Coefficients, were excellent between postural control (Impairment Inventory) and balance (FMA) (r = 0.84); arm and hand (Impairment Inventory) and shoulder, elbow, forearm, wrist and hand (FMA) (r = 0.95); leg and foot (Impairment Inventory) and hip, knee, foot and ankle (FMA) (r = 0.93); shoulder pain (Impairment Inventory) and upper limb joint pain (FMA) (r = 0.76). Furthermore, the authors compared similar activity limitations between the Activity Inventory and the Functional Independence Measure (FIM) (Keith et al., 1987). Correlations, as calculated using Pearson Correlation Coefficients were excellent between the gross motor function index (Activity Inventory) and the Mobility subscale of the FIM (r = 0.90) and between the walking index (Activity Inventory) and the Locomotion subscale of the FIM (r = 0.85).

Sacks et al. (2010) evaluated the construct validity of the Chedoke-McMaster Stroke Assessment Activity Inventory (AI) and the Clinical Outcomes Variable Scale (COVS) (Seaby & Torrance, 1989) in 24 geriatric inpatients (mean age 83 years) receiving care in a rehabilitation unit. Correlations between AI and COVS total scores at admission and discharge, and change in total scores from admission to discharge, as calculated by Pearson Correlation Coefficients, were excellent (r=0.92, r=0.91 and r=0.84 respectively). All subscales of the AI and COVS demonstrated excellent correlation at admission, discharge and change from admission to discharge, except for the walking subscale, which was found to have adequate correlation for change from admission to discharge (r=0.59).

Known groups:
Crowe at al. (1996) analyzed whether the Activity Inventory was able to distinguish between subjects who changed little (<20) and those who change more (>20) on the Functional Independence Measure (FIM) (Keith et al., 1987) in 28 clients with Acquired Brain Injury. Known groups validity, as calculated using a student t-test, showed that the Activity Inventory is able to distinguish between clients with lower and higher scores on FIM.

Responsiveness

Gowland et al. (1993) estimated the responsiveness of the Activity Inventory and the Functional Independence Measure (FIM) (Keith et al., 1987) in 32 participants with stroke. Participants were assessed at two points in time: at admission and discharge from the rehabilitation centre. Variance ratios were calculated. Compared to the FIM, the Activity Inventory had a greater variance ratio (0.53 for Activity Inventory vs. 0.30 for FIM) suggesting that the Activity Inventory of Chedoke-McMaster Stroke Assessment is a more sensitive measure to detecting change.

Huijbregts et al. (2000) assessed clinically-important changes based on a global rating of change for the Activity Inventory, gross motor function index, and walking index in 34 clients. For the Activity Inventory, no change was represented by a mean change in score of 0, small changes by a mean change in score of 8, and moderate to large changes by a mean change in score of 20. For the gross motor function index, no change was represented by a mean change in score of 1, small changes by a mean change in score of 7, and moderate to large changes by a mean change in score of 7. For the walking index, no change was represented by a mean change in score of 1, small changes by a mean change in score of 5, and moderate to large changes by a mean change in score of 13. All this information suggests that for the client, a minimum change of 20 points in the Activity Inventory score is required for him to perceive a moderate to large change. Furthermore, important change as perceived by the client and the real change score of the measure have an excellent correlation (r = 0.74).

Sacks et al. (2010) evaluated the responsiveness of the Activity Inventory (AI) of the Chedoke-McMaster Stroke Assessment and the Clinical Outcomes Variable Scale (COVS) (Seaby & Torrance, 1989) in 24 geriatric inpatients (mean age 83 years) receiving care on a rehabilitation unit. Large effect sizes were found for both the AI and COVS (1.53 and 1.43); and a stronger standardized response mean (SRM) was found for the COVS compared to that of the AI (2.30 and 1.83). Results from this study suggest that both measures are responsive to change in geriatric patients but the COVS is more responsive than the AI in this population.

References

  • Crowe, J., Harmer, D., & Sharpe, D. (1996). Reliability of the Chedoke-McMaster Disability Inventory in acquired brain injury. Physiotherapy Canada, 48(1), 25.
  • Finch, E., Brooks, D., Stratford, P.W, & Mayo, N.E. (2002). Physical Outcome Measures: A guide to enhance physical outcome measures. Ontario, Canada: Lippincott, Williams & Wilkins.
  • Fugl-Meyer, A.R., Jääskö, L., Leyman, I., Olsson, S., & Steglind, S. (1975). The post-stroke hemiplegic patient 1. A method for evaluation of physical performance. Scandinavian Journal of Rehabilitation Medicine, 7, 13-31.
  • Gowland, C., Stratford, P., Ward, M., Moreland, J., Torresin, W., Van Hullenaar, S. et al. (1993). Measuring physical impairment and disability with the Chedoke-McMaster Stroke Assessment. Stroke, 24, 58-63.
  • Gowland, C., Van Hullenaar, S., Torresin, W., et al. (1995). Chedoke-McMaster Stroke Assessment: development, validation, and administration manual. Hamilton, ON, Canada: School of Rehabilitation Science, McMaster University.
  • Gowland, C. (1984). Predicting sensorimotor recovery following stroke rehabilitation. Physiotherapy Canada, 36, 313-320.
  • Gowland, C. (1982). Recovery of motor function following stroke: profile and predictors. Physiotherapy Canada, 34, 77-84.
  • Huijbregts, M.P., Gowland, C., Gruber, R. (2000). Measuring clinically important change with the Activity Inventory of the Chedoke-McMaster Stroke Assessment. Physiotherapy Canada, 52, 295-304.
  • Keith, R.A, Granger, C.V., Hamilton, B.B., & Sherwin, F.S. (1987). The Functional Independence Measure: a new tool for rehabilitation. In: Eisenberg, M.G. & Grzesiak, R.C. (Ed.), Advances in clinical rehabilitation (pp. 6-18). New York: Springer Publishing Company.
  • Moreland, J., Gowland, C., Van Hullenar, S., Huijbregts, M. (1993). Theoretical basis of the Chedoke-McMaster Stroke Assessment. Physiotherapy Canada, 45, 231-238.
  • Poole, J.L. & Whitney, S.L. (2001). Assessment of motor function post stroke: A review. Physical and Occupational Therapy in Geriatrics, 19, 1-22.
  • Sacks, L., Yee, K., Huijbregts, M., Miller, P.A., Aggett, T. & Salbach, N.M. (2010). Validation of the activity inventory of the Chedoke-McMaster Stroke Assessment and the Clinical Outcome Variables Scale to evaluate mobility in geriatric clients. Journal of Rehabilitation Medicine, 42, 90-92.
  • Valach, L., Signer, S., Hartmeier, A., Hofer, K. & Cox Steck, G. (2003). Chedoke-McMaster Stroke Assessment and modified Barthel Index self-assessment in patients with vascular brain damage. International Journal of Rehabilitation Research, 26, 93-99.

See the measure

How to obtain the Chedoke-McMaster Stroke Assessment

The Chedoke-McMaster can be ordered by email: djohnstn@mcmaster.ca

Table of contents

Comprehensive Coordination Scale (CCS)

Evidence Reviewed as of before: 11-11-2021
Author(s)*: Sandra R. Alouche; Marika Demers; Roni Molad ; Mindy F. Levin

Purpose

The Comprehensive Coordination Scale (CCS) is a measure of coordination of multiple body segments at both motor performance (endpoint movement) and quality of movement (joint rotations and interjoint coordination) levels based on observational kinematics.

In-Depth Review

Purpose of the measure

 The Comprehensive Coordination Scale (CCS) is a measure of coordination of multiple body segments at both motor performance (endpoint movement) and quality of movement (joint rotations and interjoint coordination) levels based on observational kinematics. Coordinated movements are defined as movements of one or more limbs or body segments that occur together in identifiable temporal (i.e., timing) and spatial (i.e., positional/angular) patterns, concerning the desired action. It can be measured at a specific point in time during the movement or over the whole movement time.

The CCS can be used by healthcare professionals to assess coordination in older adults and individuals with various neurological conditions. The CCS is composed of six different tests: the Finger-to-Nose Test, the Arm-Trunk Coordination Test, the Finger Opposition Test, the Interlimb Coordination (synchronous anti-phase forearm rotations) Test, the Lower Extremity MOtor COordination Test (LEMOCOT) and the Four-limb Coordination (Upper and lower limb movements) Test.

Available versions

The CCS was developed by Alouche et al. (2021) from valid and reliable tests used in clinical practice and research to assess complementary aspects of motor coordination of the trunk, upper limb (UL), lower limb (LL) and combinations of them. Behavioral elements used to perform each test were identified and rating scales were developed to guide observational kinematic analysis by expert consensus (Alouche et al., 2021).

Features of the measure

 Items:
The CCS consists of 6 different tests used in either clinical practice or research to assess complementary aspects of motor coordination of the trunk, upper limb (UL), lower limb (LL) and combinations of them.

  1. Finger-to-Nose Test (FTN)
  2. Arm-Trunk Coordination Test (ATC)
  3. Finger Opposition Test (FOT)
  4. Interlimb Coordination Test (ILC-2)
  5. Lower Extremity MOtor COordination Test (LEMOCOT)
  6. Four-limb Coordination Test (ILC-4)
Body parts tested Type of test Test Behavioral elements scored
Upper limb Unilateral Finger-to-Nose (FTN) Spatial: Stability, smoothness, accuracy
Temporal: Speed
Trunk and arm Unilateral Arm-Trunk Coordination test (ATC) Spatial: Accuracy, interjoint coordination
Upper limb (fine dexterity) Unilateral Finger Opposition (FOT) Spatial: Selectivity
Temporal: Timing
Interlimb coordination=both upper limbs Bilateral Alternate movements of two upper limbs (ILC-2) Spatial: Compensation
Temporal: Synchronicity/ timing
Lower limb Unilateral Lower Extremity MOtor COordination Test (LEMOCOT) Spatial: Smoothness, accuracy
Temporal: Speed
Four-limb coordination = upper limbs and lower limbs Bilateral Alternate movements of both hands and feet (ILC-4) Temporal: Timing/ complexity

Scoring:
Multiple behavioral elements of each test are scored on separate rating scales ranging from 3 (normal coordination) to 0 (impaired coordination) to assess different elements of motor behavior needed to perform the action.
The CCS includes a total of 13 rating scales for the 6 tests.
The CCS score ranges from 0 to 69 points, with higher scores indicating better motor coordination. The CCS total score represents a coordination score for the whole body.
The CCS scores can be broken into 4 subscores: UL, LL, Unilateral, Bilateral.
UL: 54 points (includes FTN-24 points, ATC-12 points, FOT-12 points, and ILC2-6 points).
LL: 12 points (includes LEMOCOT-12 points).
Unilateral: 30 points (includes FTN-12 points, ATC-6 points, FOT-6 points, and LEMOCOT-6 points).
Bilateral: 9 points (includes ILC2-6 points and ILC4-3 points).
The manual describes the initial position, the instructions, and the detailed scoring.

What to consider before beginning:
The CCS is scored based on observational kinematics.

Time:
The CCS takes approximately 10-15 minutes to administer (Molad et al., 2021).

Training requirements:
The healthcare professional should read the CCS manual available on Open Science Framework:  Marika Demers, Mindy F Levin, Roni Molad, and Sandra Alouche. 2021. “Comprehensive Coordination Scale.” OSF. July 12. osf.io/8h7nm.

 Equipment:

  • Chair with back support and without armrests (suggested seat height: 46 cm)
  • Footstool, if needed
  • Targets:
    • One 2.54 cm-diameter sticker (FNT)
    • One target (sphere of 2.54 cm-diameter or a cube of similar dimensions) on an adjustable height support (ATC)
    • Two 5 cm-diameter stickers placed 30 cm (centre-to-centre) apart and attached to a cardboard (LEMOCOT test)
  • Stopwatch / timer
  • Table (optional, suggested height: 72 cm)
  • Pillow (optional)

Client suitability

Can be used with:

  • Individuals with neurological disorders

Should not be used with:

  • No information availble

In what languages is the measure available?

English

Summary

What does the tool measure? Temporal and spatial aspects of coordination.
What types of clients can the tool be used for? The CCS can be used with patients with neurological disorders.
Is this a screening or assessment tool? Assessment tool.
Time to administer 10-15 minutes.
ICF Domain Body function.
Other Languages French Canadian, Portuguese (both not published)
Measurement Properties
Reliability Internal consistency:
One study has reported high internal consistency of the CCS in a stroke population (Molad et al., 2021).

Test-retest:
One study examined test-retest reliability of the CCS within a stroke population and reported excellent test-retest reliability (ICC = 0.97; 95% CI: 0.93-0.98; Molad et al., 2021).

Intra-rater:
One study examined intra-rater reliability of the CCS within a stroke population and reported excellent intra-rater reliability (ICC = 0.97; 95% CI: 0.93-0.98; Molad et al., 2021).

Inter-rater:
One study examined intra-rater reliability of the CCS within a stroke population and reported excellent intra-rater reliability (ICC = 0.98, 95% CI: 0.95-0.99; Molad et al., 2021).

Validity Content:
One study has examined the content validity of the CCS. Using a Delphi Study done by a panel of experts. The CCS was found to have strong content validity (Alouch et al., 2021).

Criterion:
Concurrent:
Concurrent validity of the CCS has not been examined within a stroke population.
Predictive:
Predictive validity of the CCS has not been examined within a stroke population.

Construct:
Convergent/Discriminant:
One study has examined convergent validity of the CCS within a stroke population and reported: Adequate convergent validity with Fugl-Meyer-Total Score (ρ=0.602; p=0.001) and Fugl-Meyer-Motor Score (ρ=0.585; p<0.001) (Molad et al, 2021).
Known Groups:
One study has examined the known-group validity of the upper-limb Interlimb Coordination Test (ICL2), a subscale of the CCS, within a stroke population and reported that the ICL2 is able to distinguish between aged-match healthy individiuals and chronic stroke survivors (Molad & Levin, 2021).

Floor/Ceiling Effects One study reported excellent floor and ceiling effects for the CCS (Molad et al., 2021).
Does the tool detect change in patients? No studies have reported on the responsiveness of the CCS within a stroke population.
Acceptability The CCS is non-invasive and quick to administer. The use of visual observation instead of complex and costly motion analysis equipment to analyze movement makes this scale clinically accessible and easy to use.
Feasibility The CCS is free and is suitable for administration in various settings. The assessment requires minimal specialist equipment or training. It takes 10-15 minutes to be completed.
How to obtain the tool? Alouche SR, Molad R, Demers M, Levin MF. Development of a Comprehensive Outcome Measure for Motor Coordination; Step 1: Three-Phase Content Validity Process. Neurorehabil Neural Repair. 2021 Feb;35(2):185-193. doi: 10.1177/1545968320981955. [Supplementary materials]
The CCS manual can be accessed on the Open Science Framework website: Marika Demers, Mindy F Levin, Roni Molad, and Sandra Alouche. 2021. “Comprehensive Coordination Scale.” OSF. July 12. osf.io/8h7nm.

Psychometric Properties

Overview

A literature search was conducted to identify all relevant publications on the psychometric properties of the Comprehensive Coordination Scale (CCS) in individuals with stroke. We identified two studies.

Floor/Ceiling Effects

Molad et al. (2021) examined floor/ceiling effects of the CCS in a sample of 30 participants with chronic stroke. There were no floor/ceiling effects for the total score of the CCS and CCS-Bilateral subscale. For the CCS-UL and CCS-LL subscales, 3.3% and 6.7% of participants reached the maximal score, respectively. Ten percent of participants scored 0 or 30 on the CCS-Unilateral subscale.

Reliability

Internal consistency:
Molad et al. (2021) assessed the internal consistency of the CCS in a sample of 30 chronic stroke survivors, using principal component analysis and confirmatory factor analysis. The authors reported excellent internal consistency (composite reliability = 0.938). Factor analysis of the entire CCS revealed two components explaining 99% of the variance: Factor 1: movement quality (8 items), Factor 2: endpoint performance (5 items).

Intra-rater:
Molad et al. (2021) assessed the intra-rater reliability of the CCS in 30 chronic stroke survivors. The intra-rater reliability was evaluated with intraclass correlation coefficients (ICC) with 95% confidence intervals (CI). The CCS has excellent intra-rater reliability (ICC = 0.97; 95%; CI: 0.93-0.98). All four subscales also have excellent intra-rater reliability: CCS-UL subscale (ICC = 0.96; 95%; CI: 0.92-0.98), CCS-LL subscale (ICC = 0.79; 95%; CI: 0.36-0.92), CCS-Unilateral (ICC = 0.98; 95%; CI: 0.96-0.99) and CCS-Bilateral scores (ICC = 0.95; 95%CI: 0.89-0.97).

Inter-rater:
Molad et al. (2021) assessed the inter-rater reliability of the CCS in 30 chronic stroke survivors. The inter-rater reliability was evaluated with intraclass correlation coefficients (ICC) with 95% confidence intervals (CI). The CCS has excellent inter-rater reliability (ICC = 0.98; 95%; CI: 0.95-0.99). All four subscales also have excellent inter-rater reliability: CCS-UL subscale (ICC = 0.96; 95%; CI: 0.91-0.98), CCS-LL subscale (ICC = 0.76; 95%; CI: 0.25-0.9), CCS-Unilateral scores (ICC = 0.99; 95%; CI: 0.97-0.99) and CCS-Bilateral (ICC = 0.95; 95%; CI: 0.89-0.98).

Validity

Content:
Alouche et al. (2021) conducted a 3-phase content validation supporting the importance, level of comprehension and feasibility of the CCS in identifying and quantifying coordination of movements made by individuals with neurological deficits in a clinical setting. First, a literature review was performed to generate unilateral and bilateral tests of UL, LL, and trunk coordination currently used in clinical practice or research studies for the CCS. From the 2761 studies reviewed, 5 tests were selected: FTN, ATC, LEMOCOT, ILC2, and ILC4. A Delphi study, using a structured questionnaire with open-ended questions, was done with 8 expert clinicians and researchers to identify the relative importance of each test, test element, and rating scales, the level of comprehension of the instructions, and the feasibility of each test. Then, a focus group meeting was held with 6 experts to refine the instructions and the rating scales. A consensus was reached to add the Finger Opposition Test (FOT) to the final version of the CCS to assess the selectivity and timing of finger movements.

Criterion:
Concurrent:
No studies have reported on the concurrent validity of the CCS.

Predictive:
No studies have reported on the predictive validity of the CCS.

Construct:
Convergent/Discriminant:
Molad et al. (2021) examined the convergent validity in a sample of 30 chronic stroke survivors. Convergent validity of the total CCS was measured with the Fugl-Meyer Assessment (total score and motor score). Adequate convergent validity of the CCS with FMA-Total Score (ρ=0.602; p=0.001) and FMA-Motor Score (ρ=0.585; p<0.001) was obtained. The convergent validity of the subcales was measured with the Fugl-Meyer Assessment, prehension and pinch strength, Box and Blocks and 10-meter walk test. CCS-UL and CCS-Unilateral scores were moderate to strongly correlated with the Fugl-Meyer Assessment (total score and motor score), prehension and pinch strength, Box and Blocks and 10-meter walk test. The CCS-LL subscale was moderately correlated with the Fugl-Meyer Assessment (total score and motor score) and the Box and Blocks. The CCS-Bilateral subscale was moderately correlated with the Fugl-Meyer Assessment (total score and UL motor score) and the Box and Blocks.

Known Group:
Molad & Levin (2021) examined the known group validity of the ILC2 subscale in a sample of 13 stroke survivors and 13 healthy participants. They compared ILC2 scores with trunk and upper limb kinematics during synchronous bilateral anti-phase forearm rotations in 4 conditions: self-paced internally-paced, fast internally-paced, slow externally-paced, and fast externally-paced. Healthy participants had near maximal ILC2 scores and high temporal and spatial coordination indices. However, participants with stroke had lower ILC2 scores and used trunk and shoulder compensations to perform the task. ILC2 scores distinguished between healthy participants and participants with chronic stroke.

Responsiveness

 The responsiveness for the CCS has not been established.

Measurement error:
Molad et al. (2021) examined the measurement error in a sample of 30 chronic stroke survivors. The standard error of the measurement (SEM) was calculated based on the standard deviation (SD) of the sample and the reliability of measurement.  The minimal detectable change (MDC) at the 95% confidence level was computed. The CCS SEM was 1.80 points and the MDC95 was 4.98 points. The SEM and MDC values for the CCS, the CCS-UL, CCS-Unilateral and CCS-bilateral were less than 17%. Only the CCS-LL had an MDC greater than 17%.  For the CCS and all subscales, the SEM was smaller than the MDC.

References

Alouche, S.R., Molad, R., Demers, M., Levin, M.F. (2021) Development of a Comprehensive Outcome Measure for Motor Coordination; Step 1: Three-Phase Content Validity Process. Neurorehabil Neural Repair. 35(2):185-193. doi: 10.1177/1545968320981955. PMID: 33349134.

Molad, R., Alouche, S.R., Demers, M., Levin, M.F. (2021) Development of a Comprehensive Outcome Measure for Motor Coordination, Step 2: Reliability and Construct Validity in Chronic Stroke Patients. Neurorehabil Neural Repair. 35(2):194-203. doi: 10.1177/1545968320981943. PMID: 33410389.

Molad, R., & Levin, M. F. (2021) Construct validity of the upper-limb Interlimb Coordination Test (ILC2) in stroke. Neurorehabil Neural Repair [epub ahead of print]. doi: 10.1177/1545968321105809. PMID: 34715755

See the measure

The tool is available as supplementary material in:
Alouche SR, Molad R, Demers M, Levin MF. Development of a Comprehensive Outcome Measure for Motor Coordination; Step 1: Three-Phase content validity Process. Neurorehabil Neural Repair. 2021 Feb;35(2):185-193. doi: 10.1177/1545968320981955. [Supplementary materials]

The CCS manual can be accessed on the Open Science Framework website:
Marika Demers, Mindy F Levin, Roni Molad, and Sandra Alouche. 2021. “Comprehensive Coordination Scale.” OSF. July 12. osf.io/8h7nm.

Table of contents

Cone Evasion Walk test (CEW)

Evidence Reviewed as of before: 24-01-2023
Author(s)*: Annabel McDermott, OT
Editor(s): Annie Rochette, PhD OT
Expert Reviewer: Hanna Sjöholm, PT

Purpose

The Cone Evasion Walk test (CEW) assesses fall risk in individuals in the acute phase of stroke recovery, by their ability to evade obstacles. The CEW test can be performed with or without a walking aid.

In-Depth Review

Purpose of the measure

Walking is recognized as an activity that demands attentional, perceptual, visual, neuromusculoskeletal and movement-related functions. The Cone Evasion Walk test was developed to assess fall risk by the ability to avoid obstacles.

Available versions

The Cone Evasion Walk test was developed from literature, clinical experience and in collaboration with patients and physiotherapists.

Features of the measure

Items:

The Cone Evasion Walk test is a single-item assessment. Cones are spaced over a length of 3m. The participant completes the 3m walk two times.

Scoring:

  1. Record the number of cones the patient touches while completing the task two times. A cone is judged as touched regardless of whether the base or the cone itself is touched.
  2. Summarise the number of cones touched on the left (possible outcomes 0-4), the right (possible outcomes 0-4) and total number of cones touched (possible outcomes 0-8).

Note: If there is any doubt regarding the participant’s performance, the cone should not be judged as touched.

For individuals using a walking aid: Record whether the cone is touched by the front wheel or the back wheel. If the participant touches a cone with both the front and the back wheel, only the front wheel is noted. If the walking device has a frame between the front and back wheels, everything behind the front wheel is judged as the back wheel.

What to consider before beginning:

Individuals who rely on a walking aid (walker, crutch, walking stick, other) should use this while performing the assessment.

If the individual requires the support of another person to walk, the individual must control the walk as much as possible.

Note whether the individual requires physical support or supervision to complete the task.

Time:

Allow approximately 5 minutes for initial set-up. The Cone Evasion Walk test takes less than 5 minutes to administer/complete.

Training requirements:

No training requirements have been specified for the Cone Evasion Walk test.

Equipment:

The Cone Evasion Walk test requires four cones, tape and a free space of 3m length.

Participants use their ordinary walking aid.

Client suitability

Can be used with:

Individuals with acute stroke

Should not be used with:

The Cone Evasion Walk test is not suitable for use with individuals who are not mobile nor able to mobilise safely.

The Cone Evasion Walk test has not been evaluated on individuals with subacute or chronic stroke.

Languages of the measure

Swedish
English

Summary

What does the tool measure? Fall risk
What types of clients can the tool be used for? The Cone Evasion Walk test can be used with individuals with acute stroke.
Is this a screening or assessment tool? Screening
Time to administer 5 minutes
ICF Domain Activity
Versions There is one version of the Cone Evasion Walk test.
Languages Swedish
English
Measurement Properties
Reliability Internal consistency:
No studies have reported on internal consistency of the CEW.
Test-retest:
No studies have reported on test-retest reliability of the CEW.
Intra-rater:
One study reported good to excellent intra-rater reliability of the CEW.
Inter-rater:
One study reported good to excellent inter-rater reliability of the CEW.
Validity Content:
Face validity of the CEW test was established through review and pilot-testing by clinical physiotherapists.
Criterion:
Concurrent:
No studies have reported on concurrent validity of the CEW.
Predictive:
One study reported significant weak correlations between number of cones touched and number of falls, and between number of cones touched and number of days from admission to first fall incident. A weak correlation was reported between number of cones touched and number of falls when the sample population was restricted to individuals who touched the cones during the assessment period.
Construct:
Convergent/Discriminant:
One study reported a weak correlation between the CEW and the Timed Up and Go test, and weak to moderate negative correlations between the CEW and the Functional Ambulation Categories, Montreal Cognitive Assessment Serial 7s attention task and Star Cancellation Test.
Known Groups:
One study reported individuals with a right hemisphere stroke were significantly more likely to hit cones on the left side than the right; individuals with a left hemisphere stroke were significantly more likely to hit cones on the right side than on the left.
Floor/Ceiling Effects A floor effect was detected among individuals with acute stroke with good mobility.
Does the tool detect change? No studies have reported on the responsiveness of the CEW.
Acceptability The CEW is non-invasive and quick to administer. The CEW measures activity relevant to real-life.
Feasibility The CEW is suitable for administration in various settings. The CEW is quick to administer and requires minimal specialist equipment or training.
How to obtain the tool? Le Cone Evasion Walk test (Swedish version)
Le Cone Evasion Walk test (English version)

Psychometric Properties

Overview

The Cone Evasion Walk test was developed in consultation with a convenience sample of 9 physiotherapists and occupational therapists (Sjoholm et al., 2019). A literature search was conducted to identify all relevant publications on the psychometric properties of the Cone Evasion Walk test pertinent to use with participants following stroke. Two studies were identified.

Floor/Ceiling Effects

Sjoholm et al. (2019) reported a floor effect on the Cone Evasion Walk test in a sample of 221 individuals with acute stroke, whereby 71% of participants (n=211) hit no cones.

Reliability

Internal consistency:
Internal consistency of the Cone Evasion Walk test has not been measured.

Test-retest:
Test-retest reliability of the Cone Evasion Walk test has not been measured.

Intra-rater:
Sjoholm et al. (2019) examined intra-rater reliability of the Cone Evasion Walk test in a sample of 20 individuals with acute stroke using Intraclass Correlation Coefficient (ICC) with 95% Confidence Interval (CI). Ten physiotherapists viewed the video recording of participants’ performance of one run of the CEW on two occasions. Scoring consistency between the two sessions was good to excellent (ICC = 0.89-0.98) for the total scores and the four subscores. Overall percentage of agreement was 70-96%.

Inter-rater:
Sjoholm et al. (2019) examined inter-rater reliability of the Cone Evasion Walk test in a sample of 20 individuals with acute stroke using Intraclass Correlation Coefficient (ICC) with 95% Confidence Interval (CI). Participants’ performance of a single run of the CEW was videorecorded and viewed by ten physiotherapists. Inter-rater scoring consistency for the total score and four subscores was good to excellent (ICC = 0.88-0.97).

Validity

 Content:

Face validity of the CEW test was established in two phases: (i) interpretations of the test instructions and assessment procedures were reviewed by nine physiotherapists practicing in the field of neurological disorders at two group meetings; and (ii) four physiotherapists subsequently pilot-tested the assessment over a 1-year period. This resulted in modified instructions regarding administration and scoring (Sjohom et al., 2019).

Criterion:

Concurrent:
Concurrent validity of the Cone Evasion Walk test has not been measured.

Predictive:
Sjoholm et al. (2019) examined predictive validity of the Cone Evasion Walk test in a sample of 221 individuals with acute stroke using linear regression analysis. There were weak correlation between number of cones touched and number of falls (r=0.18, p=0.01) and between number of cones touched and number of days from admission to first fall incident (r=-0.28, p=0.02). When only people who touched the cones were included in the analysis, the correlation between number of cones touched and number of falls was weak (r=0.31, p=0.02). The correlation between the number of cones touched and the number of falls became more robust when only those who touched the cones, in the same population, were included in the analysis.

Construct:

Convergent/Discriminant:
Sjoholm et al. (2019) examined construct validity of the Cone Evasion Walk test by comparison with the Functional Ambulation Classification (FAC), Timed Up and Go (TUG) test and TUG Cognitive test (TUG-Cog), Montreal Cognitive Assessment Serial 7s attention task (MoCA-S7), and the Star Cancellation Test in a sample of 221 individuals with acute stroke, using Spearman’s rank correlation coefficient. There was a weak correlation between the CEW test and the TUG (r=0.45, p<0.05), and weak to moderate correlations with the FAC, MoCA-S7 and SCT (r=-0.67, -0.36, -0.36 respectively, p<0.05). The total number of cones touched on the left side showed a weak correlation with the proportion of stars cancelled on the left side (r=-0.23, p<0.05), and the right side (r=0.23, p<0.05). There was no significant correlation between the number of cones touched on the right side and the proportion of stars cancelled on either the left or the right. There was no significant correlation between the CEW and TUG-Cog.

Known Group:
Sjoholm et al. (2019) examined known-group validity of the Cone Evasion Walking test in a sample of 143 individuals with acute left hemisphere stroke (n=64) and right hemisphere stroke (n=79). Differences between groups were examined using Fisher’s exact test. Among individuals with a right hemisphere stroke, significantly more participants hit cones on the left side than the right (p=0.001). Among individuals with a left hemisphere stroke, significantly more participants hit cones on the right side than on the left (p<0.01).

Responsiveness:

Sensitivity & Specificity:
Sensitivity and Specificity of the Cone Evasion Walk test has not been measured.

References

Sjöholm, H., Hägg, S., Nyberg, L., Rolander, Bo, Kammerlind, A., (2019). The Cone Evasion Walk test: Reliability and validity in acute stroke. Physiotherapy Research International, 24(1), e1744. https://doi.org/10.1002/pri.1744

Sjöholm, H., Hägg, S., Nyberg, L., Rolander, Bo, Kammerlind, A., (2019). Corrigendum. Physiotherapy Research International, 24: e1801. https://doi.org/10.1002/pri.1801

Sjöholm, H., Hägg, S., Nyberg, L., Lind, J., & Kammerlind, A. (2022). Exploring possible risk factors for time to first fall and 6-month fall incidence in persons with acute stroke. SAGE Open Medicine, 10: 1-11. https://doi.org/10.1177/20503121221088093

See the measure

How to obtain the Cone Evasion Walk test

The original Swedish version of the Cone Evasion Walk test can be found here.

Test protocol in English can be found here.

Table of contents

Fugl-Meyer Assessment of Sensorimotor Recovery After Stroke (FMA)

Evidence Reviewed as of before: 07-11-2010
Author(s)*: Lisa Zeltzer, MSc OT
Editor(s): Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc

Purpose

The Fugl-Meyer Assessment (FMA) is a stroke-specific, performance-based impairment index. It is designed to assess motor functioning, sensation, balance, joint range of motion and joint pain in patients with post-stroke hemiplegia (Fugl-Meyer, Jaasko, Leyman, Olsson, & Steglind, 1975; Gladstone, Danells, & Black, 2002). It is applied clinically and in research to determine disease severity, describe motor recovery, and to plan and assess treatment.

In-Depth Review

Items:

The scale is comprised of five domains and there are 155 items in total:

  • Motor function (in the upper and lower extremities)
  • Sensation (evaluates light touch on two surfaces of the arm and leg, and position sense for 8 joints)
  • Balance (contains 7 tests, 3 seated and 4 standing)
  • Joint range of motion (8 joints)
  • Joint pain

The motor domain includes items assessing movement, coordination, and reflex action of the shoulder, elbow, forearm, wrist, hand, hip, knee, and ankle. Items in the motor domain have been derived from Twitchell’s 1951 description of the natural history of motor recovery following stroke and integrates Brunnstrom’s stages of motor recovery (Gladstone et al. 2002; Poole & Whitney, 2001). Items of the FMA are intended to assess recovery within the context of the motor system. Functional tasks are not incorporated into the evaluation (Chae, Labatia, & Yang, 2003).

Time:

Sections of the FMA are often administered separately, however it takes approximately 30-35 minutes to administer the total FMA (Poole & Whitney, 2001). The average length of time for FMA administration of the Motor function, Sensation and Balance subscores have reported to range from 34 to 110 minutes, with a mean administration time of 58 minutes (Malouin, Pichard, Bonneau, Durand & Corriveau, 1994). When the motor scale is administered on its own, it takes approximately 20 minutes to complete.

A major criticism of the FMA is that it is a lengthy measure to administer (Gladstone et al., 2002). Sometimes it takes longer than 35 minutes to complete, such as when it is administered to aphasic or severely affected patients (Kusoffsky, Wadell, & Nilsson, 1982; Dettmann, Linder, & Sepic, 1987).

Scoring:

Scoring is based on direct observation of performance. Scale items are scored on the basis of ability to complete the item using a 3-point ordinal scale where 0=cannot perform; 1=performs partially; and 2=performs fully. The total possible scale score is 226.

Points are divided among the domains as follows:

  • Motor function score: ranges from 0 (hemiplegia) to 100 points (normal motor performance). Divided into 66 points for upper extremity and 34 points for the lower extremity.
  • Sensation score: ranges from 0 to 24 points. Divided into 8 points for light touch and 16 points for position sense.
  • Balance score: ranges from 0 to 14 points. Divided into 6 points for sitting and 8 points for standing.
  • Joint range of motion score: ranges from 0 to 44 points.
  • Joint pain score: ranges from 0 to 44 points.

Classifications for impairment severity have been proposed based on FMA Total motor scores (out of 100 points):

Source: Finch, Brooks, Stratford, & Mayo, 2002

Fugl-Meyer (1980) Fugl-Meyer et al. (1975) Duncan, Goldstein, Horner, Landsman, Samsa, & Matchar (1994)
< 50 = Severe 0-35 = Very Severe
50-84 = Marked ≤ 84 = Hemiplegia 36-55 = Severe
85-94 = Moderate 85-95 = Hemiparesis 56-79 = Moderate
95-99 = Slight 96-99 = Slight motor dyscoordination > 79 = Mild

Each of the five FMA domains can be separated to test a specific construct. For example, to assess upper extremity function, the subsections specifically dealing with upper extremity movement, sensation, joint motion and pain can be examined without administering the rest of the scale. Scoring of the FMA will depend on the number of items included in the subsection selected for testing.

Crow et al. (2008) proposed a shortened method of administration for the upper and lower extremity portions of the FMA. Using Guttman analysis the authors determined that scale items in the upper and lower limb sections fulfill the criteria for a valid hierarchy. Clinically this means that rather than administering the entire test, a clinician may choose to begin administering at a point in the scale that appears appropriate to the observed level of patient recovery. If a patient is able to accomplish all of the remaining scale items in the section, they are awarded a full score for that section. Likewise, when the individual being tested is unable to accomplish all the scale items in a given section, a score of 0 is given for any remaining untested, more advanced, items. This method of assessment reduces the time required to perform the test. Full guidelines for hierarchical testing procedures are provided by Crow et al. (2008)

Equipment:

The FMA requires a mat or bed, a few small objects and several different tools for the assessment of sensation, reflexes, and range of motion:

Materials needed (Poole & Whitney, 2001; Sullivan et al., 2011):

  • Scrap of paper
  • Ball
  • Cotton ball
  • Pencil
  • Reflex hammer
  • Cylinder (small can or jar)
  • Goniometer
  • Stopwatch
  • Blindfold
  • Chair
  • Bedside table

Subscales:

There are five domains that can be assessed independently: Motor function; Sensation; Balance; Joint range of motion; and Joint pain. Sensation and Joint pain are more subjective in nature and are used less frequently (Gladstone et al., 2002). Sullivan et al. (2011) published a FMA manual of procedures, which includes training procedures for clinical practice and research trials, in an effort to standardize assessment procedures.

Training:

The FMA should be administered by a trained physical therapist, occupational therapist or other rehabilitation professional on a one-to-one basis with the patient (Gladstone et al., 2002).

Guidelines provided by Fugl-Meyer et al. (1975) suggest that the client should be instructed verbally and/or with a demonstration of the test. The evaluator is permitted to assist the patient in the testing of the wrist and hand to stabilize the arm (Fugl-Meyer et al., 1975). In patients confined to their beds, the joint range of shoulder abduction should be performed only to 90 degrees and extension of the hip to 0 degrees.

Alternative Forms of Fugl-Meyer Assessment (FMA)

In 1975, Fugl-Meyer, Jaasko, Leyman, Olsson, and Steglind published the FMA.

Revision to balance subscore

Subsequent to problems reported with sitting balance items (Malouin et al., 1994), Hseuh et al. (2001 as reported in Mao, Hsueh, Tang, Sheu, & Hsieh, 2002) proposed slight modifications to the scoring of the two problematic reaction items. In this modified version, patients receive a score of 0 if they lose balance easily, 1 if they partially lose balance, and 2 if they maintain sitting balance well when firmly pushed on the affected or non-affected side. The validity of the modified FMA-Balance was found to be excellent (r = 0.84).

12-item short form

Hseih et al. (2007) developed a 12-item short form of the FMA based on the upper and lower extremity domains of the FMA. Items were retained on the basis of representativeness of Brunnstrom staging and item difficulty assessed via Rasch analysis.

Client suitability

Can be used with:

  • Acute and chronic patients post-stroke in settings from an acute care hospital (Wood-Dauphinee, Williams, & Shapiro, 1990) to the community (Nadeau, Arsenault, Gravel & Bourbonnais, 1999).
  • Although it takes longer to administer, the FMA can be applied to severely affected patients or patients with aphasia.

Should not be used in:

  • Patients who need a proxy to complete. As with other impairment indices, the FMA is scored by direct observation and therefore it cannot be used with proxy respondents.
  • The FMA should not be used to detect fine or complex movements or coordination, as it measures gross limb movement only. A scale that employs a finer evaluation of isolated movements and the complete range of motor function of the upper limb only is the Motor Status Score. This scale has been found to be a reliable and valid assessment of upper limb impairment and disability following stroke (Ferraro et al., 2002).
  • As an assessment of motor recovery within the context of the motor system, the FMA may separate motor recovery from functional recovery. Therefore, the FMA may not be responsive to functional improvements in chronic populations (van der Lee et al., 2001). In these instances, a more appropriate tool for assessing functional improvements in chronic populations is the Action Research Arm Test (assesses upper extremity function only).

In what languages is the measure available?

  • English
  • French canadian (Arsenault, Dutil, Lambert, Corriveau, Guarna, & Drouin, 1988)

Summary

What does the tool measure? Motor function, sensation, balance, joint range of motion and joint pain.
What types of clients can the tool be used for? Patients with post-stroke hemiplegia
Is this a screening or assessment tool? Assessment
Time to administer It takes approximately 30-35 minutes to administer the total FMA. Administration of the motor, sensation and balance subscores range from 34 to 110 minutes, with a mean administration time of 58 minutes. When the motor scale is administered on its own, it takes approximately 20 minutes to complete.
Versions
  • Modified FMA-Balance subscore
  • 12-item short form
Other Languages Translated and validated in French
Measurement Properties
Reliability Internal consistency:
Out of three studies examining internal consistency, all three reported excellent internal consistency.

Test-retest:
Out of six studies examining test-retest reliability, five reported excellent test-retest reliability. Two studies examined item-level agreement and found that light touch items on the FMA Sensation subscale ranged from poor to adequate; the Joint pain subscale was found to have only adequate reliability, however total FMA test-retest remained excellent in these studies. The study that examined longitudinal stability of the FMA items, as calculated using Rasch Analysis, reported that scores across two testing occasions are comparable.

Inter-rater:
Out of four studies examining inter-rater reliability, all four reported excellent inter-rater reliability (with the exception of the Balance subscore, which was found to be poor in one study).

Validity Content:
Items in a modified 30-items FMA reflect the same construct, except for the item hook grasp. Based on a Guttman Scale Analysis, the motor functioning subscales can be arranged in a hierarchical sequence, allowing the use of a shortened method of administration of the FMA.

Criterion:
Predicted Motor Assessment Scale scores at 180 days after stroke onset. FMA lower extremity (FMA-LE) admission subscores predicted the rehabilitation discharge Functional Independence Measure mobility and locomotion scores. FMA admission scores predicted the rehabilitation discharge Barthel Index scores. FMA-LE scores were poor predictors of mean steps per day.
Excellent correlations with Barthel Index, Motor Assessment Scale (except sitting balance items on both scales), Sensory Organization Balance Test, Action Research Arm Test, DeSouza scale, Chedoke-McMaster Stroke Assessment scale, Berg Balance Scale, Postural Assessment Scale for Stroke, Stroke Rehabilitation Assessment of Movement (STREAM), the shortened versions of the FMA and STREAM, performance assessments of walking velocity and velocity index, and Arm Motor Ability Test.

Construct:
The FMA lower extremity subscore was able to distinguish between patients who needed assistance in walking and between three levels of self-care ability (dependent, partly dependent, and independent). Excellent correlations between the FMA and Barthel Index (except with FMA Sensastion subscale); the FMA Motor upper extremity subscale and the Action Research Arm Test; the FMA and Bobath Assessment of upper extremity; the FMA and Functional Independence Measure; the FMA Motor subscale and various measures of gait.

Floor/Ceiling Effects

A poor ceiling effect has been found with the Sensation subscore. A poor floor effect has been found with the modified Balance subscore of the FMA at 14 days after stroke. Another study reported an excellent floor effect and an adequate ceiling effect for the FMA motor scores both at admission and discharge from a rehabilitation program.

Does the tool detect change in patients?

Out of 5 studies examined, 1 reported that the FMA has a large ability to detect change, 1 reported moderate, 1 reported small to moderate, and 2 reported a small ability to detect change.

Acceptability Administration of the entire FMA is lengthy. The test is scored by direct observation and cannot be completed by proxy respondent.
Feasibility The FMA must be administered by a trained physical or occupational therapist. It does not require any specialized equipment and can be administered across a variety of settings and has been tested for use in longitudinal assessments.
How to obtain the tool?

The FMA can be obtained by following the link below (from the Institute of Rehabilitation Medicine, University of Goteberg, Goteberg, Sweden).
http://www.neurophys.gu.se/sektioner/klinisk_neurovetenskap_och_rehabilitering/neurovetenskap/rehab_med/fugl-meyer/

A version of the measure is also provided in Fugl-Meyer et al. (1975), and in the book by Dittmar, S. S. and Gresham, G. E. (1997) entitled Functional assessment and outcome measures for the rehabilitation health professional.

The FMA manual of procedures developed by Sullivan et al. (2011), can be obtained by following the link below:
http://stroke.ahajournals.org/cgi/content/full/STROKEAHA.110.592766/DC1

Psychometric Properties

Overview

The FMA has been used as the gold standard against which the validity of other measures has been assessed. However, the reliability and validity of the Balance subscore (the sitting balance items in particular) of the FMA has been shown to be questionable. As mentioned in the available versions section, revisions to the scoring of the Balance subscore appear to have resulted in an increase in reliability (Mao et al. 2002), however, further testing of the modification is required. The Sensation subscore of the FMA has also been criticized for poor face, construct and predictive validity and responsiveness (Lin, Hsueh, Sheu, & Hsieh, 2004).

Floor/Ceiling Effects

Lin et al. (2004) examined the psychometric properties of the FMA Sensation subscore and found that these subscore had large ceiling effects at each assessment time. At 14-30 days post-stroke, 44.4% of the patients achieved the highest score, at 30-90 days, 48.9%, at 90-180 days, 62.7% and at 14-180 days, 72.1%.

Mao et al. (2002) compared the psychometric properties of the Berg Balance Scale, the modified Balance subscore of the FMA, and the Postural Assessment Scale for Stroke Patients in 123 stroke patients followed up prospectively 14, 30, 90, and 180 days after stroke onset. The modified Balance subscore of the FMA showed large floor effects (29.3%) at 14 days after stroke.

Hsueh, Hsu, Sheu, Lee, Hsieh and Lin (2009) analyzed the floor and ceiling effects for the FMA, the shortened version of the FMA, the Stroke Rehabilitation Assessment of Movement (STREAM), and the shortened version of the STREAM in 50 clients with chronic stroke. Participants were assessed at admission and discharge from a rehabilitation ward. At admission, the FMA and the shortened version of the STREAM demonstrated an excellent floor effect and ceiling effect with no participants scoring the minimum or maximum scores. The other measures showed adequate floor and ceiling effects with 2 to 18% of patients scoring the lowest or highest scores. At discharge, the FMA and the shortened version of the STREAM demonstrated an excellent floor effect with 0% of participants scoring 0. The other measures showed adequate floor and ceiling effects, with the proportion of patients scoring the minimum and maximum scores ranging from 1 to 20%.

Reliability

Lin et al. (2004) examined the internal consistency of the FMA in 176 patients with stroke from 14 to 180 days after stroke. Cronbach’s alphas for the FMA at four time points post-stroke were excellent, ranging from alpha = 0.94 to 0.98. The inter-rater reliability of the total score of the FMA was also excellent, with an intraclass correlation coefficient (ICC) of 0.93. However, item-level agreement for light touch items on the FMA Sensation subscale ranged from poor to adequate (weighted kappa ranged from 0.30 to 0.55).

Platz, Pinkowski, van Wijck, Kim, di Bella, and Johnson (2005) tested the test-retest and the inter-rater reliabilities of the FMA upper extremity items (including items from the Motor function, Sensation and passive Joint motion/Joint pain subscores), the Action Research Arm Test, and the Box and Block Test in patients with upper limb paresis either from stroke (n=37), multiple sclerosis (n=14), or from traumatic brain injury (n=5). Test-retest reliability of the FMA, calculated using ICC’s, was excellent (ICC = 0.97 for Total motor score; ICC = 0.81 for Sensation, ICC = 0.95 for passive Joint motion/Joint pain). Inter-rater reliability for the FMA upper extremity subscore as calculated using the ICC was also excellent (ICC = 0.99 for Total motor score; ICC = 0.98 for Sensation; and ICC = 0.98 for passive Joint motion/Joint pain).

Mao et al. (2002) compared the psychometric properties of the Berg Balance Scale, the modified Balance subscore of the FMA, and the Postural Assessment Scale for Stroke Patients, in 123 patients with stroke followed up prospectively 14, 30, 90, and 180 days after stroke onset. The median of weighted kappa statistics for each item of the FMA Balance subscore was 0.79 (ranging from 0.71 to 0.95), indicating excellent individual item agreement. The ICC for the total score of the FMA Balance subscore was 0.92 (ranging from 0.88 to 0.95), indicating excellent total score agreement. The Cronbach’s alpha for the FMA Balance subscore ranged from alpha = 0.85 to 0.91 on all follow-up times, indicating high internal consistency.

Duncan, Propst, and Nelson (1983) examined the test-retest reliability and the inter-rater reliability of the FMA in 18 patients with chronic stroke. Inter-rater reliability was examined with 5 different therapists. Pearson correlations between therapists for each component of the FMA Motor domain upper extremity subscale were found to be excellent, ranging from r = 0.96 to r = 0.97. The Motor domain lower extremity subscale correlations were also excellent, ranging from r = 0.83 to r = 0.95. The Total score correlation was high (r = 0.99). Only the reflex and coordination subscores in the upper extremity were found to be unreliable as they were significantly different between the raters across the test times.

To assess the test-retest reliability of the FMA in Duncan et al. (1983), one therapist evaluated patients on three separate occasions at 3-week intervals. Pearson correlations were excellent for the Total FMA score (r = 0.98 to r = 0.99), Motor domain upper extremity subscore (r = 0.995 to r = 0.996), Motor domain lower extremity subscore (r = 0.96), Sensation subscore (r = 0.95 to r = 0.96), Joint range of motion/Joint pain subscore (r = 0.86 to r = 0.99) and Balance subscore (r = 0.89 to r = 0.98). No significant differences across evaluation times were found (as assessed by a repeated measures analysis of variance).

Sanford, Moreland, Swanson, Stratford, and Gowland (1993) examined the inter-rater reliability of the FMA in 12 patients between 6 days to 6 months post-stroke. Patients were evaluated one day apart by three physical therapists. The inter-rater reliability of the FMA was found to be excellent, with an overall ICC of 0.96 for the Total score. The ICCs for the Motor domain upper extremity subscore, Motor domain lower extremity subscore, Balance, Sensation, and Joint range of motion were excellent (0.97, 0.92, 0.93, 0.85 and 0.85, respectively). The ICC for the Joint pain subscore was the least reliable, but still adequate, with an ICC of 0.61.

Beckerman, Vogelaar, Lankhorst, and Verbeek (1996) examined the test-retest reliability of the FMA in 49 patients with chronic stroke. Patients were evaluated twice by one therapist, three weeks apart. The ICC for the Motor domain lower extremity subscore was excellent (ICC = 0.86), but was found to be poor for the Balance subscore (ICC = 0.34). Although the test-retest reliability of the Balance subscore was not found to be very reliable, indicating that the patients’ performance was inconsistent, the inter-rater agreement was high.

Van der Lee, Beckerman, Lankhorst and Bouter (2001) examined the test-retest reliability of the FMA Motor domain upper extremity subscore in 22 patients with chronic stroke. Two baseline measurements were performed before treatment, as well as a follow-up measurement after 2 weeks. Using limits of agreement as a measure of test-retest reliability, a mean difference on test-retest within a stable population during the baseline period (14-20 days) on the Motor domain upper extremity subscore was small (0.8 points).

Woodbury, Velozo, Richards, Duncan, Studenski, and Lai (2008) investigated the test-retest reliability of the FMA through longitudinal stability of the upper extremity items in 377 clients with stroke with a mean age of 60.2 years (SD 11.2). Longitudinal stability reflects the invariance of an item-difficulty hierarchy of a measure across 2 testing occasions. Assessments with a slightly modified FMA (the 3 reflex items were removed with the remaining 30 items arranged in a hierarchical sequence) were performed at admission and at 6 months post-stroke. Longitudinal equivalence of the FMA item structure was analyzed by estimating the relationship between item-difficulty calibrations at baseline and 6 months follow-up. Intraclass Correlation Coefficient (ICC) was performed and showed excellent reliability (ICC = 0.95). Consistency of item-difficulty calibrations across testing occasions disregarding clients’ characteristics such as age and gender, as calculated using Differential Item Functioning (DIF), showed that only two items on the FMA (1: shoulder flexion to 180° with elbow extended and 2: movement of the arm with normal speed) had a large DIF, which implied that those two items were unstable between assessments. Despite those items, the authors reported that the scores across testing occasions could still be compared as a repeat Rasch analysis with the unstable items removed found a small difference on the FMA scores (0.06 logits).

Hsueh et al. (2009) analyzed the test-retest reliability of the FMA, the STREAM, and their shortened versions in 60 clients with chronic stroke. Participants were assessed twice within a 1 week interval. Test-retest reliability, as calculated using Intraclass Correlation Coefficient was excellent for all four measures: FMA (ICC = 0.98), the shortened version of the FMA (ICC = 0.96), the STREAM (ICC = 0.98) and the shortened version of the STREAM (ICC = 0.97).

Sullivan et al. (2011) developed a standardized measurement method and rater training program for the FMA and then used inter-rater and intra-rater reliability to examine the effectiveness of the program. After attending the training program, 17 physiotherapists and one expert rater (with 30 years experience) evaluated 15 patients with subacute stroke. The initial assessments were video-recorded and later reviewed by the expert rater. The intra-rater reliability of the expert rater, as calculated using ICC was excellent for all domains of the FMA (ranging from ICC = 0.95 to 1.0). The inter-rater reliability between the expert rater and trained therapists, as calculated using ICC, was also excellent for all domains of the FMA (ranging from ICC = 0.87 to 0.99).

Validity

Content:

Woodbury, Velozo, Richards, Duncan, Studenski, and Lai (2008) investigated the content validity of the upper extremity items of the FMA in 377 clients with stroke with a mean age of 60 years (SD 11,2). Assessments with a slightly modified FMA (the 3 reflex items were removed with the remaining 30 items arranged in a hierarchical sequence) were performed at admission and at 6 months post-stroke. At the follow-up evaluation, the 30-item Fugl-Meyer Assessment, as calculated using Rasch Analysis, showed an acceptable fit statistics, except for the item hook grasp. This result suggests that all items reflect the same construct, except for the item hook grasp.

Crow & Harmeling-van der Wel (2008) analyzed the content validity of the motor functioning domain of the FMA in 62 clients with stroke by performing a Guttmann Scale Analysis. Each motor functioning subscale of the FMA, excluding the reflex items, was arranged in a hierarchical sequence of difficulty according to the total number of passes per item. All subscales, when analyzed separately, exceed the critical values for two indices: coefficient of reproducibility (> 0,9) and coefficient of scalability (>0,7). When analyzing across all upper and lower extremity items (ignoring the subscales) the coefficient of reproducibility (0,8) and scalability (0,6) were just below the acceptable levels. The results of this study suggest the existence of a valid, cumulative, and unidimensional Guttman scale within each motor functioning subscale. In summary, if the client succeeds in completing the most difficult item in a subscale, this suggests he/she will succeed in the easier items for that same subscale. Similarly, failure on an item suggests the client will be unable to complete the remaining more challenging items in the subscale. Therefore, a shortened method of administration of the FMA can be used with clients with stroke.

Criterion:

There is a lack of information available regarding the criterion validity of the FMA, as the FMA was created at a time when no other similar impairment index existed against which the FMA could be tested (Gowland, Van Hullenaar, & Torresin, 1995; Gowland, Stratford, & Ward, 1993).

Bernspang et al. (1987) used the Pearson correlation coefficient and found that the FMA correlated excellently with self-care ability scores (r = 0.64) in 109 clients measured within 2 weeks of stroke.

Nadeau et al. (1999) identified the most important clinical variables for determining gait speed in 16 patients with chronic stroke using Pearson’s correlation coefficients. The FMA Sensation subscore correlated poorly with both comfortable and maximal gait speeds (r = 0.14 and r = 0.05, respectively). Patients with decreased sensation and a score below 12, combined with the strength of the hip flexors, and ankle plantar flexors predicted maximal gait speed. Excellent correlations were found between the FMA Total motor score and comfortable (mean 0.76 meters/second; r = 0.61) and maximal speeds (mean 1.09 meter/second; r = 0.61).

Concurrent:
Wood-Dauphinee et al. (1990) compared the FMA to the Barthel Index in 167 patients with stroke at two time points: the acute stage (3 to 5 days post-stroke), and 5 weeks post-stroke. Using Pearson correlation coefficients, the correlation between the FMA Motor domain upper extremity subscore and the Barthel Index total score was excellent at both the acute stage (r = 0.75) and at 5 weeks (r = 0.82). Similarly, excellent correlations were found between the FMA Motor domain lower extremity subscore and the Barthel Index at the acute stage (r = 0.77) and at 5 weeks (r = 0.89).

Poole and Whitney (1988) examined the concurrent validity of the FMA with the Motor Assessment Scale in 30 patients with stroke. High correlations were found between the total scores on the FMA and the Motor Assessment Scale (r = 0.88), and between specific item scores, except sitting balance (ranging from r = 0.28 to r = 0.92).

Malouin et al. (1994) administered the FMA and the Motor Assessment Scale to 32 patients early after stroke, and reported an excellent Spearman correlation for Total FMA and Total Motor Assessment Scale scores (r = 0.96). The correlations for items from the Motor Assessment Scale and corresponding FMA items were excellent, ranging from r = 0.65 to r = 0.93. The FMA Sensation scores of light touch (r = 0.64) and position sense (r = 0.67) correlated with the Motor Assessment Scale’s Balance score, but not with FMA Sitting balance items (r = 0.12 and -0.10 respectively) suggesting that the FMA sitting balance test is not valid for measuring balance. Standing balance correlations ranged from moderately to highly correlated with both the Motor Assessment Scale and FMA light touch and position sense (ranging from r = 0.43 to r = 0.67).

Di Fabio and Badke (1990) examined standing balance and dynamic weight shifting in 10 patients with stroke using a sensory organization balance test and the FMA. The results of both clinical tests were compared to determine whether the sensory organization balance test correlated with functional ability using the Spearman rank order correlation coefficient. Scores on the lower extremity items and balance items of the FMA correlated excellently with the Sensory Organization Balance Test (r = 0.77).

De Weerdt and Harrison (1985) compared the Motor domain upper extremity subscore of the FMA with the Action Research Arm Test. Both assessments were administered to 53 hospital inpatients with stroke who suffered a motor deficit. The Action Research Arm Test and the FMA were excellently correlated at both 2 weeks (r = 0.91) and at 8 weeks (r = 0.94) post-stroke.

Berglund and Fugl-Meyer (1986) compared the FMA to the DeSouza scale (another assessment of upper limb function) in 50 patients with stroke who suffered a motor deficit. Excellent correlations were found with the Upper extremity Motor scores (r = 0.90). The two tests co-varied, and explained 90% of the variation in the Total scores and 80% of the Motor scores.

Gowland et al. (1993) demonstrated the concurrent validity of the Chedoke-McMaster Stroke Assessment scale with the FMA. The Total score of the impairment inventory of the Chedoke-McMaster Stroke Assessment Scale correlated highly with that of the FMA (r = 0.95). Correlations reported between impairment subscores on the FMA and corresponding subscores from the impairment inventory of the Chedoke-McMaster Stroke Assessment ranged from adequate to excellent (r = 0.76 to r = 0.95).

Mao et al. (2002) compared the Berg Balance Scale, the modified Balance subscore of the FMA, and the Postural Assessment Scale for Stroke, in 123 patients with stroke followed up prospectively at 14, 30, 90, and 180 days after stroke onset. There was excellent concurrent validity (as measured by Spearman correlation coefficient) between the Balance subscore of the FMA and the Berg Balance Scale and Postural Assessment Scale for Stroke at all follow-up times (ranging from r = 0.90 to r = 0.97).

Kusoffsky, Wadell and Nilsson (1982) reported a relationship between sensory functioning and subsequent motor recovery, as excellent correlations between sensory evoked potentials in 16 patients with stroke was observed. The relationship between sensory evoked potentials and the FMA upper extremity subscore was the most strong, and the relationship between the FMA lower extremity subscore was less strong. The strength of the relationship endured regardless of when the FMA was administered.

Feys, Van Hees, Bruyninck, Mercelis and De Weerdt (2000) assessed the role of sensory evoked potentials and motor evoked potentials in the prediction of arm motor recovery in 64 patients with stroke with a motor deficit of the arm. Patients were followed from 2 weeks to 12 months post-stroke. In this study, a poor relationship was found between sensory evoked potentials and the FMA.

Dettmann et al. (1987) administered the FMA and a walking performance test using interrupted light photography and postural maneuvers while standing on a force platform in 15 patients with stroke. Correlations between the FMA Total scores and performance assessments of walking velocity (r = 0.64), cadence (r = 0.58), stride-length (r = 0.53), non-paretic stance (r = 0.59), velocity index (r = 0.67), and platform measures of upright stability (r = 0.52 to r = 0.69) ranged from adequate to excellent.

Poole and Whitney (1988) examined the concurrent validity of the Motor Assessment Scale and the FMA in 30 patients with stroke. Excellent correlations between FMA items and corresponding MAS items were found (ranging from r = 0.64 to r = 0.92). However, one exception was the correlation of the FMA sitting balance with the MAS balance while sitting, which were poorly correlated (r = 0.28).

Chae, Labatia, and Yang (2003) evaluated the concurrent validity of the Arm Motor Ability Test using the FMA as the criterion measure of post-stroke upper limb motor impairment in 30 patients with chronic stroke. Excellent Spearman correlations between upper extremity scores of the FMA and Arm Motor Ability Test functional ability scores (r = 0.94) as well as between upper extremity scores of the FMA and Arm Motor Ability Test quality of movement scores (r = 0.94) were reported.

Hsueh et al. (2009) analyzed the concurrent validity of the FMA, the shortened version of the FMA, the STREAM, and the shortened version of the STREAM in 50 clients with chronic stroke. Excellent Spearman correlations were found between all four measures (ranging from rho = 0.91 to rho = 0.99).

Predictive:
Mao et al. (2002) compared the psychometric properties of the Berg Balance Scale, the modified Balance subscore of the FMA, and the Postural Assessment Scale for Stroke in 123 patients with stroke at 14, 30, 90, and 180 days after stroke onset. Excellent Spearman correlations were found between the scores of the Balance subscore of the FMA at the earlier 3 time points and the Postural Assessment Scale for Stroke scores (ranging from r = 0.80 to r = 0.87), indicating excellent predictive validityof the FMA modified Balance subscore.

Chae, Johnston, Kim, and Zorowitz (1995) found that FMA lower extremity admission subscores predicted the rehabilitation discharge Functional Independence Measure mobility (r = 0.63) and locomotion (r = 0.74) scores in 48 patients at 6 weeks post-stroke.

Hsueh et al. (2009) analyzed whether the motor scores of FMA, of the shortened version of the FMA, the STREAM, and the shortened version of the STREAM measured at admission to a rehabilitation program were able to predict Barthel Index scores at discharge in 50 clients with chronic stroke. Excellent Spearman correlations were found between the Barthel Index scores and the FMA (rho = 0.72), the shortened version of the FMA (rho = 0.74), the STREAM (rho = 0.75) and the shortened version of the STREAM (rho = 0.77). These results suggest that all measures were able to predict Barthel Index scores at discharge.

Fulk, Reynolds, Mondal & Deutsch (2010) examined the predictive validity of the 6MWT and other widely used clinical measures (FMA-LE, self-selected gait-speed, SIS and BBS) in 19 patients with stroke. The FMA-LE was found to be a poor predictor of mean steps per day (r = 0.06; p = 0.798). Although gait speed and balance were related to walking activity, only the 6MWT was found to be a predictor of community ambulation in patients with stroke.

Construct:

Several validation studies have provided good evidence that the FMA is measuring what it is intended to measure. The construct validity of the FMA has been examined by comparing the scale with other measures of stroke recovery that reflect post-stroke independence in activities of daily living or disability level.

Sonde, Gip, Fernaeus, Nilsson, and Viitanen (1998) found that FMA scores reflected changes in upper extremity scores after low frequency transcutaneous electric nerve stimulation. A Mann-Whitney U-test was used to test the significance of the differences in FMA scores at the start and end of the study between the treatment and control groups. This test revealed that the FMA scores differed significantly between the treatment and control groups (Mann-Whitney U = 130.5). Further, the Spearman rank correlation between the FMA scores was excellent (r = 0.95).

Chae, Bethoux, Bohine, Dobos, Davis, and Friedl (1998) assessed the efficacy of neuromuscular stimulation in enhancing the upper extremity motor and functional recovery of 28 patients with stroke. FMA scores reflected changes in upper extremity scores after neuromuscular stimulation. Parametric analyses revealed significantly greater gains in FMA scores for the treatment group immediately following treatment (13.1 versus 6.5), at 4 weeks after treatment (17.9 versus 9.7), and at 12 weeks after treatment (20.6 versus 11.2). Gains were observed in FMA scores but not with Functional Independence Measure scores.

Kraft, Fitts, and Hammond (1992) tested functional improvement in the upper limb of 22 patients with stroke who received either EMG-initiated electrical stimulation of wrist extensors, low-intensity electrical stimulation of wrist extensors combined with voluntary contractions, proprioceptive neuromuscular facilitation exercises, or no treatment. During the course of treatment, FMA scores of patients receiving proprioceptive neuromuscular facilitation improved 18%, patients receiving low-intensity electrical stimulation of wrist extensors combined with voluntary contractions improved 25%, and patients receiving EMG-initiated electrical stimulation of wrist extensors improved 42%. FMA improvement of the treated groups was significant from pre-treatment to post-treatment, and the improvement was maintained at three-month and nine-month follow-up sessions. In contrast, the control group showed no significant change in FMA scores or grip strength.

Feyes, deWeerdt, Seltz, Steck, Spichinger, and Vereeck (1998) randomized 100 patients with stroke to an experimental group that received sensorimotor stimulation for 6 weeks or to a control group. Patients were evaluated before, during, and after the intervention period and at 6 and 12 months after stroke. Only scores on the FMA showed group differences at follow-up. Scores on the Action Research Arm Test and the Barthel Index did not show group differences.

Duncan et al. (1998) randomized 20 patients with mild or moderate stroke who had completed inpatient rehabilitation to receive a home-based exercise program or usual care. The experimental group demonstrated more improvement in the FMA Motor domain upper and lower extremity subscores than did the usual care group. However, the differences in motor recovery were only significant for the Motor domain lower extremity (Motor domain upper extremity mean change in score = 8.4 versus 2.2; Motor domain lower extremity mean change in score = 4.7 versus -0.9).

Malouin et al. (1994) tested 32 patients with the FMA and the Motor Assessment Scale on two consecutive days and found that the FMA distinguished between patients with minimal recovery better than the Motor Assessment Scale. Adequate to excellent negative correlations between score differences and levels of recovery (upper extremity r = -0.50 and lower extremity r = -0.69) were found, indicating that the largest differences between the two measures were in earlier stages of recovery or among more severely affected individuals.

Platz et al. (2005) tested the construct validity of the FMA upper extremity items (including items from the Motor function, Sensation and passive Joint motion/Joint pain subscores), the Action Research Arm Test, the Box and Block Test and the Motricity Index, using the Spearman correlation coefficient, in patients with upper limb paresis either from stroke (n=37), multiple sclerosis (n=14) or from traumatic brain injury (n=5). Excellent correlations were found between the FMA and the Action Research Arm Test (r = 0.93), the Box and Block Test (r = 0.92), and the Motricity Index (r = 0.86). The FMA was also correlated with more general measures of impairment and activity limitation, including the Ashworth Scale, the Hemispheric Stroke Scale and the modified Barthel Index. An excellent correlation was found between the FMA and the Hemispheric Stroke Scale (r = -0.69), and an adequate correlation was found between the FMA and the Ashworth Scale (r = -0.42). Only a poor correlation was found between the FMA and the modified Barthel Index (r = 0.09).
Note: Correlations were negative because a high score on the FMA indicates normal performance, where as a low score on the Hemispheric Stroke Scale or the Ashworth Scale indicates normal performance.

Fugl-Meyer and Jaasko (1980) compared the FMA Motor domain to performance on activities of daily living scale in 64 patients with stroke more than 6 months after hospital discharge. The activities of daily living scale was comprised of 52 items examining independence in feeding, hygiene, dressing, locomotion, housework, and psychosocial functioning. Excellent correlations were found between the degree of motor impairment as measured by the FMA and the activities of daily living scale (activities of daily living total score r = 0.75; hygiene r = 0.89; locomotion r = 0.76; feeding r = 0.72; and dressing r = 0.76).

Convergent:
Mao et al. (2002) compared the psychometric properties of the Berg Balance Scale, the modified Balance subscore of the FMA, and the Postural Assessment Scale for Stroke Patients, in 123 patients with stroke followed up prospectively 14, 30, 90, and 180 days after stroke onset. Excellent correlations were found using the Spearman correlation coefficient between the scores of the FMA Balance domain and the scores of the Berg Balance Scale at all four time points (ranging from r = 0.86 to r = 0.89), indicating excellent convergent validity.

Rabadi and Rabadi (2006) examined 104 inpatients with acute stroke at a rehabilitation unit. The Action Research Arm Test, the Motor domain upper extremity subscore of the FMA, the NIH Stroke Scale, the Functional Independence Measure total score, and Functional Independence Measure activities of daily living subscore were administered. Using the Spearman rank correlation coefficient, the Action Research Arm Test and the Motor domain upper extremity subscore of the FMA correlated excellently with one another, both at admission (r = 0.77) and at discharge (r = 0.87). The Motor domain upper extremity subscore of the FMA and the Functional Independence Measure activities of daily living subscore at the time of admission were adequately correlated (r = 0.54).

Arsenault et al. (1988) treated 62 patients with hemiplegia with the Bobath approach to treatment for a period of three months. During this time they were evaluated on three occasions. Using Spearman’s Rho, the FMA correlated excellently with the Bobath Assessment of upper extremity pre- (r = 0.73) and post-rehabilitation (r = 0.85), with both measures showing change across time periods.

Dettmann et al. (1987) administered the FMA and the Barthel Index to 15 patients with stroke. Patients were assessed at an average of 2 years post-stroke. Pearson correlations between FMA and Barthel Index scores were excellent for the FMA Total score (r = 0.67), the FMA Motor subscore (r = 0.74), the Motor domain upper extremity subscore (r = 0.75), and the Balance subscore (r = 0.76). In this study, the authors measured walking performance using photographic analysis of gait pattern and velocity, and postural stability while standing on a force platform. The FMA Motor domain lower extremity subscore correlated well with most of the gait measurements, and the FMA Balance subscore correlated well with the stability index. The Sensation subscore did not correlate significantly with any of these measures of gait or upright stability.

Shelton, Volpe, and Reding (2000) compared the FMA to the Functional Independence Measure in 172 inpatients in a stroke rehabilitation hospital within 90 days of stroke. Total FMA scores were highly correlated with total Functional Independence Measure scores (r = 0.63). The correlation between the FMA Motor domain upper extremity subscore and the Functional Independence Measure self-care scores was excellent (r = 0.61), as was the correlation between the Motor domain lower extremity subscore of the FMA and the Functional Independence Measure mobility score (r = 0.74).

Lin et al. (2004) examined the convergent validity of the FMA Sensation subscore using Spearman’s Rho in 176 patients with stroke. The FMA Sensation subscore was poor to adequately correlated with the Barthel Index (ranging from r = 0.38 to r = 0.53). FMA Sensation subscore was also poor to adequately correlated to the FMA Motor domain subscore at different post-stroke stages of recovery, indicating low to moderate convergent validity (ranging from r = 0.31 to r = 0.44).

Known groups:
Poole and Whitney (1988) administered the Motor Assessment Scale and the FMA to 30 patients with hemiplegia. The FMA lower extremity subscore was able to distinguish between patients who needed assistance in walking better than gait speed at speeds less than 0.34 meters/second (r = 0.62).

Bernspang, Asplund, Eriksson, and Fugl-Meyer (1987) administered the FMA to 109 patients within two weeks of having an acute stroke. The FMA was found to distinguish between three levels of self-care ability (dependent, partly dependent, and independent).

Responsiveness

Mao et al. (2002) reported a significant change in the modified FMA Balance subscore between times of assessment (14, 30, 90 and 180 days post-stroke). Effect sizes were large in the interval between 14 and 30 days (ES = 0.82) and weakened the further one moved through time from the stroke event (90-180 days was small, ES = 0.33). The overall effect size (14-180 days) was large (ES = 1.14). When patients were grouped by level of stroke severity, the highest overall FMA Balance subscore effect size among severe stroke patients was an ES = 1.57.

Van der Lee et al. (2001) examined 22 patients with chronic stroke who underwent intensive forced-use treatment to improve upper extremity function. A responsiveness ratio (the ratio of the mean change after the experimental intervention and the standard deviation of the mean change during the baseline period) of 2.03 was reported for the Action Research Arm Test and 0.41 for the FMA Motor score. A higher responsiveness ratio indicates greater responsiveness, suggesting that the Action Research Arm Test is more responsive than the FMA to improvement in upper extremity function in response to a forced-use treatment intervention. This was also reflected by the number of patients who improved more than the upper limit of agreement on the Action Research Arm Test during the intervention period, 12 (54.5%), in comparison to only 2 (9.1%) on the FMA, indicating further that the Action Research Arm Test is more responsive to change than the FMA.

Rabadi and Rabadi (2005) assessed the responsiveness of the Action Research Arm Test and the FMA in evaluating recovery of upper extremity function in 104 inpatients with acute stroke. The mean change in score from admission to discharge was 10 ± 15 for the Action Research Arm Test and 10 ± 13 for the FMA Motor score. The responsiveness to change as measured by the standard response mean (SRM) was moderate for both the Action Research Arm Test (SRM = 0.68) and for the FMA Motor score (SRM = 0.74).

Lin et al. (2004) examined the responsiveness of the FMA Sensation subscore using the standardized response mean (SRM) in 176 patients with stroke. Small (90-180 days SRM = 0.27; 14-30 days SRM = 0.42; 30-90 days SRM = 0.43) to moderate (14-180 days SRM = 0.67) responsiveness was reported for the FMA Sensation subscore.

Wood-Dauphinee et al. (1990) compared the FMA to the Barthel Index in 167 patients with stroke assessed shortly after admission to the hospital and 5 weeks later. Using Pearson correlation coefficients, the correlation between mean change scores for FMA Upper and lower extremity Motor subscores and total Barthel Index scores was adequate (r = 0.57). Small effect sizes were reported for the FMA Motor scale from admission to 5 weeks post-stroke (0.2 for upper extremity, 0.19 for lower extremity, 0.33 for balance ability, and 0.24 for Total score). The results of this study suggest that the FMA Motor scale has small responsiveness.

Duncan, Lai and Keighley (2000) examined the speed and extent of recovery in 459 patients over the first 6 months following stroke. Spontaneous improvement was observed for mild, moderate, and severe strokes as measured by the FMA. Within the first month post-stroke, maximum recovery was achieved, and began to plateau around 6 months post-stroke. The recovery curves of the FMA upper extremity and lower extremity Motor subscales’ corresponded to the recover curves of the Barthel Index and the NIH Stroke Scale. If recovery is defined by achieving an FMA score > 90, then 36.8% of the patients in this study were considered to have recovered.

Shelton et al. (2000) found a moderate correlation between the change in Total FMA score with the change in Total Functional Independence Measure score (r = 0.44). Linear regression analysis demonstrated that with every 24-point increase in Functional Independence Measure score, a 10-point increase in FMA Motor score is observed, indicating that improvement in motor impairment is associated with significant functional recovery. Change in both upper and lower extremity FMA Motor subscores correlated poorly with the change in self-care and mobility Functional Independence Measure subscores (r = 0.23 and r = 0.18, respectively).

Hsueh et al. (2009) examined the responsiveness of the FMA, the Stroke Rehabilitation Assessment of Movement (STREAM) and their shortened versions in 50 clients with chronic stroke. Participants were assessed at two points in time: at admission and at discharge from a rehabilitation program. Both the STREAM and the FMA shortened versions demonstrated a moderate effect size of 0.53 and 0.51, while the STREAM and FMA demonstrated a small effect size of 0.45 and 0.38, respectively.

References

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  • Ferraro, M., Demaio, J. H., Krol, J., Trudell, C., Rannekleiv, K., Edelstein, L., Christos, P., Aisen, M., England, J., Fasoli, S., Krebs, H., Hogan, N., Volpe, B. T. (2002). Assessing the Motor Status Score: A Scale for the Evaluation of Upper Limb Motor Outcomes in Patients after Stroke. Neurorehabilitation and Neural Repair, 16(3), 283-289.
  • Feyes, H. M., deWeerdt, W. J., Seltz, B. E., Steck G. A. C., Spichinger, R., Vereeck, L. E. (1998). Effect of therapeutic intervention for hemiplegic upper limb in acute phase after stroke. Stroke, 29, 785-792.
  • Feys, H., Van Hees, J., Bruyninck, F., Mercelis, R., De Weerdt, W. (2000). Value of somatosensory and motor evoked potentials in predicting arm recovery after a stroke. J Neurol Neurosurg Psychiatry,68, 323-331.
  • Finch, E., Brooks, D., Stratford, P. W., Mayo, N. E. (2002). Physical Rehabilitations Outcome Measures. A Guide to Enhanced Clinical Decision-Making (2nd ed.). Canadian Physiotherapy Association, Toronto.
  • Fugl-Meyer, A. R., Jaasko, L., Leyman, I., Olsson, S., Steglind, S. (1975). The post-stroke hemiplegic patient: I. A method for evaluation of physical performance. Scandinavian Journal of Rehabilitation Medicine, 975(7), 13-31.
  • Fugl-Meyer, A. R. (1980) Post-stroke hemiplegia assessment of physical properties. Scandinavian Journal of Rehabilitation Medicine, 7, 85-93.
  • Fugl-Meyer, A. R., Jaasko, L. (1980). Post-stroke hemiplegia and ADL-performance. Scand J Rehabil Med Suppl. 7, 140-152.
  • Fulk, G. D., Reynolds, C., Mondal, S., & Deutsch, J. E. (2010). Predicting home and community walking activity in people with stroke. Arch Phys Med Rehabil, 91, 1582-1586.
  • Gladstone, D. J., Danells, C. J., Black, S. E. (2002). The Fugl-Meyer Assessment of Motor Recovery after Stroke: A critical review of its measurement properties. Neurorehabilitation and Neural Repair, 16, 232-240.
  • Gowland, C., Van Hullenaar, S., Torresin, W. (1995). Chedoke-McMaster stroke assessment: development, validation and administration manual. Hamilton (ON), Canada: Chedoke-McMaster Hospitals and McMaster University.
  • Gowland, C., Stratford, P., Ward, M. (1993). Measuring physical impairment and disability with the Chedoke-McMaster Stroke Assessment. Stroke, 24, 58-63.
  • Hsieh, Y.W., Hsueh, I.P., Chou, Y.T., Sheu, C.F., Hseih, C.L. & Kwakkel, G. (2007). Development and validation of a short form of the Fugl-Meyer motor scale in patients with stroke. Stroke, 38, 3052-3054.
  • Hsueh, I. P., Hsu, M. J., Sheu, C. F., Lee, S., Hsieh, C. L., Lin, J. H. (2009). Psychometric comparisons of 2 versions of the Fugl-Meyer Motor Scale and 2 versions of the Stroke Rehabilitation Assessment of Movement. Neurorehabil Neural Repair, 22, 737.
  • Hsueh, I. P., Mao, H. F., Huang, H. L., Hsieh, C. L. (2001). Comparisons of responsiveness and predictive validity of two balance measures in stroke inpatients receiving rehabilitation [in Chinese]. Formos J Med, 5, 261-268.
  • Kraft, G. H., Fitts, S. S., Hammond, M. C. (1992). Techniques to improve function of the arm and hand. Archives of Physical Medicine and Rehabilitation, 73, 220-227.
  • Kusoffsky, A., Wadell, I., Nilsson, B. Y. (1982). The relationship between sensory impairment and motor recovery in patients with hemiplegia. Scand J Rehabil Med, 14(1), 27-32.
  • Lin, J-H., Hsueh, I-P., Sheu, C-F., Hsieh, C-L. (2004). Psychometric properties of the sensory scale of the Fugl-Meyer Assessment in stroke patients. Clinical Rehabilitation, 18, 391-397.
  • Lin, F. M., Sabbahi, M. (1999). Correlation of spasticity with hyperactive stretch reflexes and motor dysfunction in hemiplegia. Arch Phys Med Rehabil, 80(5), 526-530.
  • Malouin, F., Pichard, L., Bonneau, C., Durand, A., Corriveau, D. (1994) Evaluating motor recovery early after stroke: comparison of the Fugl-Meyer Assessment and the Motor Assessment Scale. Arch Phys Med Rehabil, 75(11), 1206-1212.
  • Mao, H. F., Hsueh, I. P., Tang, P. F., Sheu, C. F., Hsieh, C. L. (2002). Analysis and comparison of the psychometric properties of three balance measures for stroke patients. Stroke, 33, 1022-1027.
  • Nadeau, S., Arsenault, A. B., Gravel, D. Bourbonnais, D. (1999). Analysis of the clinical factors determining natural and maximal gait speeds in adults with a stroke. American Journal of Physical Medicine & Rehabilitation, 78(2), 123-130.
  • Nilsson, L., Carlsson, J., Grimby, G., Nordholm, L. (1998). Assessment of walking balance and sensorimotor performance of hemiparetic patients in the acute stages after stroke. Physiother Theory Pract, 14, 149-157.
  • Platz, T., Pinkowski, C., van Wijck, F., Kim, I-H., di Bella, P., Johnson, G. (2005). Reliability and validity of arm function assessment with standardized guidelines for the Fugl-Meyer Test, Action Research Arm Test and Box and Block Test: a multicentre study. Clinical Rehabilitation, 19, 404-411.
  • Poole, J.L. & Whitney, S.L. (1988). Motor Assessment Scale for stroke patients: Concurrent validity and interrater reliability. Archives of Physical Medicine and Rehabilitation, 69, 195-197.
  • Poole, J. L., Whitney, S. L. (2001). Assessments of Motor Function Post Stroke: A Review. Physical & Occupational Therapy in Geriatrics, 19(2), 1-22.
  • Rabadi, M. H., Rabadi, F. M. (2006). Comparison of the Action Research Arm Test and the Fugl-Meyer Assessment as measures of upper-extremity motor weakness after stroke. Arch Phys Med Rehabil, 87, 962-966.
  • Sanford J, Moreland J, Swanson LR, Stratford PW, Gowland C. (1993). Reliability of the Fugl-Meyer assessment for testing motor performance in patients following stroke. Phy Ther, 73, 447-54.
  • Shelton, F. N. A. P., Volpe, B. T., Reding, M. J. (2000). The effect of motor impairment on disability
  • following stroke [abstract]. Stroke, 31(1), 291.
  • Sonde, L., Gip, C., Fernaeus, S.E., Nilsson, C.G., & Viitanen, M. (1998). Stimulation with low frequency (1.7 Hz) transcutaneous electric nerve stimulation (low TENS) increase motor function of the post-stroke paretic arm. Scandinavian Journal of Rehabilitation Medicine, 30, 95-99.
  • Sullivan, K.T., Tilson, J.K., Cen, S.Y., Rose, D.K., Hershberg, J., Correa, A., et al. (2011). Fugl-Meyer Assessment of sensorimotor function after stroke. Standardized training procedure for clinical practice and clinical trials. Stroke, 42, 427-432.
  • Teasell, R., Foley, N. C., & Salter K. (2011). EBRSR: Evidence-Based Review of Stroke Rehabilitation. 13th ed. London (ON): EBRSR.
  • Tyson, S., DeSouza, L. (2002). A systematic review of methods to measure balance and walking post-stroke. Part 1: Ordinal Scales. Physical Therapy Reviews; 7, 173-186.
  • Woodbury, M.L, Velozo, C.A., Richards, L.G., Duncan, P.W., Studenski, S. & Lai, S. (2008). Longitudinal stability of the Fugl-Meyer Assessment of the Upper Extremity. Archives of Physical Medicine and Rehabilitation, 89, 1563-1569.
  • Wood-Dauphinee, S. L., Williams, J. I., Shapiro, S. H. (1990). Examining outcome measures in a clinical study of stroke, Stroke, 21, 731-739.
  • van der Lee, J. H., Beckerman, H., Lankhorst, G. J., Bouter, L. M. (2001). The responsiveness of the Action Research Arm Test and the Fugl-Meyer Assessment Scale in chronic stroke patients. Journal of Rehabilitation Medicine, 33(3), 110-113.

See the measure

How to obtain the FMA?

The FMA can be obtained by following the link below (from the Institute of Rehabilitation Medicine, University of Goteberg, Goteberg, Sweden).

http://www.neurophys.gu.se/sektioner/klinisk_neurovetenskap_och_rehabilitering/neurovetenskap/rehab_med/fugl-meyer/

or through this link form the University of Gothenburg: https://neurophys.gu.se/english/departments/clinical_neuroscience_and_rehabilitation/rehabilitation-medicine/fugl-meyer

A version of the measure is also provided in Fugl-Meyer et al. (1975), and in the book by Dittmar, S. S. and Gresham, G. E. (1997) entitled Functional assessment and outcome measures for the rehabilitation health professional.

Table of contents

GAITRite

Evidence Reviewed as of before: 22-10-2012
Author(s)*: Katie Marvin, MSc. PT
Editor(s): Annabel McDermott, OT; Nicol Korner-Bitensky, PhD OT
Expert Reviewer: Suzanne Kuys, PhD; B Physiotherapy (Hons)

Purpose

The GAITRite system was developed in response to the need for an objective way to quantify gait and ambulatory status. The GAITRite System measures spatio-temporal parameters of gait such as cadence, step length and velocity, providing clinically relevant information that is useful in devising treatment plans and evaluating treatment outcomes. The system tracks parameters over time and can be used to generate progress and status reports.

In-Depth Review

Purpose of the measure

The GAITRite System was developed in response to the need for an objective way to quantify gait and ambulatory status. Spatio-temporal parameters of gait, such as cadence, step length and velocity, are recorded and calculated using the GAITRite System and software. The GAITRite System tracks parameters over time and can be used to generate progress and status reports, providing clinically relevant information that is useful in devising treatment plans and evaluating treatment outcomes. While visual assessment of gait is more commonly used clinically, studies have demonstrated poor reliability.

According to producers of the GAITRite system (2010), the system can aid in the following tasks:

  • Documentation of gait patterns prior to any intervention
  • Measurement of functional ambulation immediately following treatment/intervention
  • Documentation of the effect of intervention
  • Identification of the relationship between objective gait parameters and subjective findings
  • Refinement of proper alignment and fit of prosthetics & orthotics
  • Selection of appropriate assistive devices
  • Objective measurement to justify ongoing intervention

Available versions

There are no other available versions.

Features of the measure

Items:

An electronic walkway (61cm wide x 288cm long – additional custom sizes are available), containing a total of 18,432 sensors sensor pads, is connected to the USB port of Windows® XP/Vista/7 personal computer (CIR Systems, Inc., 2010).

What to consider before beginning:

  • Assess patients’ balance and gait abilities prior to having them walk across the GAITRite walkway, to ensure adequate support is provided during assessment.
  • Barefoot testing is not recommended.

Scoring and Score Interpretation:

The GAITRite System provides spatio-temporal parameters of gait; it does not provide a score.

Time:

The setup of the GAITRite System is reported to be time efficient. The GAITRite System administration time is dependent on patient ambulation speed and efficiency.

Training requirements:

The GAITRite System has been reported to yield highly accurate and reliable data regardless of the examiner. However, in order to ensure consistency in testing protocol, the manufacturers of GAITRite System, CIR Systems, offer an Examiner Accreditation course. Examiners who successfully complete the accreditation process are awarded an accreditation certificate valid for a period of 1 year. Do you know how long the course is?
Please contact CIR Systems for further details.

Equipment:

For further information regarding equipment and set-up, please refer to the GAITRite Electronic Walkway Technical Reference guide:
http://www.gaitrite.com/Downloads/GAITRite_Measurement_Definitions.pdf

Alternative Forms of GAITRite

There are no alternative forms of the GAITRite System reported, however there are different model numbers.

Client suitability

Can be used with:

  • Patients with stroke.
  • Patients requiring assistive devices and ambulatory aids such as crutches, walkers, or canes (GAITRite, 2010).
  • Patients utilizing biped and quadruped locomotion (CIR Systems, Inc., 2012).

Should not be used in:

  • None reported.

Languages of the measure

The GAITRite system is not a language based assessment tool.

Summary

What does the tool measure? Spatio-temporal parameters of gait.
What types of clients can the tool be used for? The GAITRite system can be used with, but is not limited to, clients with stroke.
Is this a screening or assessment tool? Assessment
Time to administer The time to administer is dependent on familiarity of system set-up and use, and patient ambulatory status.
Versions There are no alternative versions.
Other Languages Not applicable.
Measurement Properties
Reliability Test-retest :
One study found excellent test re-test reliability of the GAITRite system among patients with (stage of) stroke.
Validity Concurrent:
One study found moderate to excellent concurrent validity of the GAITRite system with the Clinical Stride Analyzer in a healthy population.
Floor/Ceiling Effects No studies have examined the floor or ceiling effects of the GAITRite system in clients with stroke.
Does the tool detect change in patients? No studies have examined the responsiveness of the GAITRite system in clients with stroke. However, the GAITRite system has the capacity to track parameters over time and can be used to generate progress and status reports.
Acceptability There is no placement of devices on the patient allowing the patient to ambulate as close to their usual as possible.
Feasibility The GAITRite system is portable and can be laid over any flat surface (CIR Systems, Inc., 2010).
How to obtain the tool?

For further information on the GAITRite system, please contact:

CIR Systems, Inc
376 Lafayette Ave, Suite 202
Sparta, NJ 07871

Toll Free: (888) 482-2362
Phone: (973) 862-6151
Fax: (973) 862-6451
Email: sales@gaitrite.com

Psychometric Properties

Overview

A literature search was conducted to identify all relevant publications on the psychometric properties of the GAITRite System. One study involving patients with stroke, and another involving healthy adults were identified and reviewed for the purposes of this module.

Floor/Ceiling Effects

No studies have investigated the floor or ceiling effects of the GAITRite System in patients with stroke.

Reliability

Internal constancy:
No studies have investigated the internal consistency of the GAITRite System in patients with stroke.

Test-retest:
Kuys, Brauer and Ada (2011) examined the test-retest reliability of the GAITRite System in measuring spatio-temporal parameters of gait (i.e gait speed, cadence, step length (paretic and non-paretic limb), step time (paretic and non-paretic limb), stance phase as a percentage of the gait cycle (paretic and non-paretic limb) in a group of 21 people following stroke undergoing inpatient rehabilitation. Participants were asked to walk the distance of the GAITRIte walkway two separate times within 48 hours, at a self-selected speed. Test-retest reliability was found to be excellent for all spatio-temporal parameters in the overall group (ICC=0.72-0.94), as calculated using Intraclass Correlation Coefficient. Patients were also categorized as ‘poor’ and ‘better’ ambulators, using the Motor Assessment Scale score (MAS) (poor: MAS Item 5 score 3 – 4, average gait speed = 0.54 m/s; better: MAS Item 5 score 5 – 6, average gait speed = 0.79 m/s). The test-retest reliability was found to be stronger for poorer ambulators compared to better ambulators (ICC ≥ 0.57 vs ICC ≥ 0.41). Results of this study indicate that test-retest reliability of the GAITRite System is slightly higher for individuals with more limited mobility.

Intra-rater:
No studies have investigated the intra-rater reliability of the GAITRIte System in patients with stroke.

Inter-rater:
No studies have investigated the inter-rater reliability of the GAITRite System in patients with stroke.

Validity

Content:

No studies have investigated the content validity of the GAITRIte System in patients with stroke.

Criterion:

Concurrent:
Bilney, Morris and Webster (2002) compared the concurrent validity of the GAITRite System with the Clinical Stride Analyzer (CSA) for quantification of the spatio-temporal gait parameters (gait speed, cadence, stride length, single leg support time – right and left, double limb support as a percentage of the gait cycle – right and left) in 25 healthy subjects. The CSA was selected as the criterion measure due to its wide clinical use in measuring spatiotemporal parameters of gait. Subjects were asked to walk the GAITRite walkway over three trials at three different speeds: self-selected speed, fast and slow speed. Excellent concurrent validity was found between the two measures for speed, cadence and stride length (ICC=0.99) at self-selected, slow and fast speeds, as calculated using Intraclass Correlation Coefficient (ICC). Concurrent validity for quantification of single leg stance phase was found to be moderate to excellent (ICC = 0.52-0.86 across the three gait speeds); and double limb support as a percentage of gait cycle was also found to have moderate to excellent concurrent validity (ICC = 0.44-0.57) between the two measures.

Predictive:
No studies have investigated the predictive validity of the GAITRIte System in patients with stroke.

Construct:

Convergent/Discriminant:
No studies have investigated the convergent or discriminant validity of the GAITRite System in patients with stroke.

Known Groups:
No studies have investigated the known groups validity of the GAITRite System in patients with stroke.

Sensitivity/ Specificity:
No studies have investigated the sensitivity/specificity of the GAITRite System in patients with stroke.

Responsiveness:

No studies have investigated the responsiveness of the GAITRite System in patients with stroke.

References

  • Bilney, B., Morris, M. & Webster, K. (2003). Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait. Gait and Posture, 17, 68-74.
  • Kuys, S.S., Brauer, S.G. & Ada, L. (2011). Test-retest reliability of the GAITRite System in people with stroke undergoing rehabiliation. Disability and Rehabilitation, 33 (19-20), 1848. 1853.

See the measure

For further information regarding obtaining a GAITRite system, please contact CIR Systems, Inc.:

CIR Systems, Inc.
376 Lafayette Ave, Suite 202
Sparta, NJ 07871

Toll Free: (888) 482-2362
Phone: (973) 862-6151
Fax: (973) 862-6451
Email: sales@gaitrite.com

Table of contents

Motor Assessment Scale (MAS)

Evidence Reviewed as of before: 07-11-2010
Author(s)*: Lisa Zeltzer, MSc OT
Editor(s): Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc

Purpose

The Motor Assessment Scale (MAS) is a performance-based scale that was developed as a means of assessing everyday motor function in patients with stroke (Carr, Shepherd, Nordholm, & Lynne, 1985). The MAS is based on a task-oriented approach to evaluation that assesses performance of functional tasks rather than isolated patterns of movement (Malouin, Pichard, Bonneau, Durand, & Corriveau, 1994).

In-Depth Review

Purpose of the measure

The Motor Assessment Scale (MAS) is a performance-based scale that was developed as a means of assessing everyday motor function in patients with stroke (Carr, Shepherd, Nordholm, & Lynne, 1985). The MAS is based on a task-oriented approach to evaluation that assesses performance of functional tasks rather than isolated patterns of movement (Malouin, Pichard, Bonneau, Durand, & Corriveau, 1994).

Available versions

In 1985, Janet H. Carr and Roberta B. Shepherd published the MAS.

Features of the measure

Items:

The MAS is comprised of 8 items corresponding to 8 areas of motor function. Patients perform each task 3 times and the best performance is recorded.

  • Supine to side lying
  • Supine to sitting over the edge of a bed
  • Balanced sitting
  • Sitting to standing
  • Walking
  • Upper-arm function
  • Hand movements
  • Advanced hand activities

Also included is a single item, general tonus, intended to provide an estimate of muscle tone on the affected side (Carr et al., 1985).

Scoring:

All items (with the exception of the general tonus item) are assessed using a 7-point scale from 0 – 6. A score of 6 indicates optimal motor behavior. For the general tonus item, the score is based on continuous observations throughout the assessment. A score of 4 on this item indicates a consistently normal response, a score > 4 indicates persistent hypertonus, and a score < 4 indicates various degrees of hypotonus (Carr et al., 1985).

Item scores (with the exception of the general tonus item) can be summed to provide an overall score out of a possible 48 points (Malouin et al., 1994). Successfully completing a higher-level item suggests that the individual is able to perform the lower level items that correspond to lower scores, and thus these lower items can be skipped from the assessment (Sabari et al., 2005).

A major criticism of the MAS is that the general tonus item is difficult to assess, as there are no guidelines regarding the testing of tone, where it should be tested or how to score the item when the tone varies between the leg, arm, and trunk (Poole & Whitney, 1988). For this reason, this item is often omitted (Malouin et al., 1994; Loewen & Anderson, 1990).

Another issue with the MAS is that scoring hierarchies are not always consistent. Sabari et al. (2005) used Rasch analysis to examine the validity of the scoring hierarchies for the Upper Arm Function, Hand Movements and Advanced Hand Activities’ subscales and found that only the Upper Arm Function subscale demonstrated an appropriate hierarchy in terms of task difficulty. A later study by Miller, Slade, Pallant and Galea (2010), validated the test item difficulty hierarchy in the Upper Arm Function and Hand Movements subscales, but not the Advanced Hand Activities subscale. For example, some studies have reported that patients who could complete the most difficult task of the Advanced Hand Activities category (holding a comb and combing hair at the back of head) were unable to complete an easier item (drawing horizontal lines) (Poole & Whitney, 1988; Malouin et al., 1994), meaning that the items are not ordered according to their estimated difficulty (Miller et al., 2010).

Equipment:

Although a number of items are required to administer the MAS, the equipment is easy to acquire. The following equipment is needed:

  • Stopwatch
  • Eight Jellybeans
  • Polystyrene cup
  • Rubber ball
  • Stool
  • Comb
  • Spoon
  • Pen
  • Two Teacups
  • Water
  • Prepared sheet for drawing lines
  • Cylindrical object like a jar
  • Table

Subscales:

The upper limb items of the MAS can be used independent of the rest of the scale.

Training:

The instructions for the proper administration of the MAS are provided directly on the scale itself. Carr et al. (1985) recommend a short instruction and practice period, where the MAS is administered to at least six patients prior to using the test in a formal setting.

Time:

Carr et al. (1985) state that the MAS should take approximately 15 minutes to complete, however, other studies have reported administration times ranging from 15 to 60 minutes (Poole & Whitney, 1988; Malouin et al., 1994).

Alternative form of the Motor Assessment Scale

  • Modified Motor Assessment Scale (MMAS). Loewen and Anderson (1988) modified item descriptions and deleted the general tonus item. In a study on 7 patients with stroke, the MMAS demonstrated acceptable inter-rater reliability. This modified version is still scored on a 7-point scale from 0 – 6.
  • Upper Limb/Extremity Motor Assessment Scale (UL-MAS or UE-MAS). In this form of the MAS, only the three upper limb items are used as a scale to assess upper limb function. In a study evaluating this version, substantial reliability and validity (Cronbachs alpha = 0.83; Spearmans rho = 0.70) (Lannin, 2004; Hsueh & Hsieh, 2002).

Client suitability

Can be used with:

  • Patients with stroke.

Should not be used in:

  • Patients who require a proxy to complete. As with other impairment indices, the MAS is scored by direct observation and should not be used with proxy respondents.
  • When assessing severely affected patients or patients with aphasia, we recommend that although it takes longer to administer, the Fugl-Meyer Assessment of Sensorimotor Recovery After Stroke (FMA) – another measure to assess motor functioning in patients with stroke – should be used instead of the MAS.

In what languages is the measure available?

  • English (Carr et al., 1985)
  • Norwegian (Kjendahl, Jahnsen, & Aamodt, 2005)

Summary

What does the tool measure? Everyday motor functioning
What types of clients can the tool be used for? Patients with stroke
Is this a screening or assessment tool? Assessment
Time to administer Studies have reported administration times ranging from 15 to 60 minutes.
Versions Upper Limb/Extremity Motor Assessment Scale (UL-MAS or UE-MAS); Modified Motor Assessment Scale (MMAS)
Other Languages English and Norwegian
Measurement Properties
Reliability Internal consistency:
No studies have examined the internal consistency of the MAS.

Test-rest:
Only one study has examined the test-rest reliability of the MAS, reporting excellent test-retest.

Intra-rater:
No studies have examined the intra-rater reliability of the MAS.

Inter-rater:
Out of two studies that examined the inter-rater reliability of the MAS, both reported excellent inter-rater (with the exception of the general tonus item, which demonstrated poor inter-rater reliability).

Validity Content:
No formal content validation is available. Items and scoring options are based on observations of the improvement of a large number of patients.

Criterion:
Excellent correlations between the MAS and the Fugl-Meyer Assessment.

Construct:
Excellent correlations between the MAS and Mobility items from the Mobility Scale for Acute Stroke Patients and adequate correlations between the MAS and a simple measure of functional sitting balance (sitting arm raise and forward reach tests).

Does the tool detect change in patients?

One study found minimal floor and ceiling effects for the UL-MAS in acute/subacute post-stroke patients. In another study, large floor and ceiling effects for Upper Arm Function and Hand Movements items and substantial floor effects for Advanced Hand Activities were found; however, the study has been criticized for inclusion of participants that were as long as 6 years post-stroke.

One study examined the ability of the MAS to detect change and found that the walking item had a large ability to detect change, and the arm items had a small ability to detect change.

Acceptability

The MAS is a fairly simple and short measure to administer. A proxy respondent is not appropriate for this performance-based measure. For severely affected patients or patients with aphasia, we recommend administering the Fugl-Meyer Assessment of Sensorimotor Recovery After Stroke (FMA) rather than the MAS.

Feasibility A short instruction and practice period is recommended prior to administering the test in a formal setting. A number of items are required as equipment for the MAS, however all items are readily available.
How to obtain the tool?

The MAS is available for free and can be found in Carr et al. (1985). Click here to view a copy of the MAS.

Psychometric Properties

Overview

For the purposes of this review, we conducted a literature search to identify all relevant publications on the psychometric properties of the MAS.

Floor and Ceiling Effects

Sabari et al. (2005) used Rasch analysis to examine the validity of the scoring hierarchies of the Upper Limb subscales of the MAS and found large floor and ceiling effects for subscales 6 and 7 (31 and 28 percent for both respectively) and large floor effects for subscale 8 (38 percent). Participants were a mean of 104 days post-stroke, within a range of 3 days to 6.4 years.

In a later study, Miller, Slade, Pallant and Galea (2010) used Rasch analysis to evaluate the psychometric properties of the Upper Limb subscales of the MAS (UL-MAS) in post-stroke patients and found adequate floor and ceiling effects (14 and 9 percent respectively). Participants were a mean of 64.8 days post stroke, within a range of 4 to 193 days. Miller at al. questioned the clinical applicability of results from Sabari et al. because some participants were as long as 6 years post-stroke and in clinic the MAS is generally administered in the acute/subacute phase.

Reliability

Internal consistency:
No studies have examined the internal consistency of the MAS.

Test-retest:
Carr et al. (1985) evaluated the test-retest reliability of the MAS in 14 patients with stroke who were examined by the same rater on two occasions, with a 4-week interval between assessments. Test-retest correlations were excellent, ranging from r=0.87 to r=1.00 (the average correlation was r=0.98).

Intra-rater:
No studies have examined the intra-rater reliability of the MAS.

Inter-rater:
Carr et al. (1985) selected 5 patients at various stages of recovery for inter-rater reliability testing. Twenty physical therapists and physical therapy undergraduate students were raters (the general tonus item was excluded from the evaluation). Overall, the MAS was found to have excellent inter-rater reliability, with a mean correlation of r = 0.95. The greatest agreement was achieved on the balanced sitting item (r = 0.99), and the least agreement was on the sitting to standing item (r = 0.89).

Poole and Whitney (1988) examined the inter-rater reliability of the MAS in 24 patients with stroke. Two examiners observed and scored each subject independently. The inter-rater reliability for the total MAS (r = 0.99), and for the individual items (ranging from r = 0.92 to r = 1.00) was excellent, with the exception of the general tonus item, which demonstrated poor reliability (r = 0.29).

Validity

Content:

Carr et al. (1985) based items and scoring options of the MAS on observations of the improvement of a large number of patients. Thus, no formal content validation is available (Carr et al., 1985).

Criterion:

Concurrent:
Malouin, Pichard, Bonneau, Durand and Corriveau (1994) assessed the concurrent validity of the MAS in comparison to the Fugl-Meyer Assessment early after stroke and reported excellent Spearman’s correlations for total scores (r = 0.96, excluding the general tonus item). Correlations between MAS items and corresponding Fugl-Meyer Assessment items were excellent (ranging from r = 0.65 to r = 0.93). The MAS Balance score correlations with the Fugl-Meyer Assessment-Sensation scores of light touch and position sense were excellent (r = 0.64 and r = 0.67, respectively), but correlations with the Fugl-Meyer Assessment Balance items were poor (r = 0.12 and r = -0.10, respectively).

Poole and Whitney (1988) assessed the concurrent validity of the MAS in comparison to the Fugl-Meyer Assessment in a more chronic population and found similar results to Malouin et al. (1994). Excellent Spearman’s correlations were found for total score (r = 0.88), and for individual items (ranging from r = 0.64 to r = 0.92), with the exception of sitting balance, which correlated poorly (r = 0.28).

Construct:

Miller at al. (2010) examined the construct validity of test item 72 (radial deviation of the wrist). Radial deviation is no longer thought to be an isolated movement occurring at the wrist and is now believed to occur as a part of a coordinated synergy (Mason, Gomez & Ebner, 2001 as cited in Miller, Slade, Pallant & Galae, 2010) or program of movement (Marotta, Medendorp & Crawford, 2003 as cited in Miller et al., 2010). In addition, radial deviation is often reduced in individuals over 65 years, thus impacting results for item 72. The evidence suggests that item 72 adds little meaning to the assessment of motor recovery in patients with stroke.

Convergent/Discriminant:

Simondson et al. (2003) examined the convergent validity of a new scale, the Mobility Scale for Acute Stroke Patients with other established scales (MAS, Functional Ambulation Classification system, Functional Independence Measure, Barthel Index). Mobility items from the Mobility Scale for Acute Stroke Patients had an excellent correlation with corresponding items on the MAS (r = 0.89), demonstrating the convergent validity of the MAS.

Tyson and DeSouza (2004) examined the convergent validity of the MAS in 48 patients post-stroke. It was found that a simple measure of functional sitting balance (sitting arm raise and forward reach tests) correlated adequately with the sitting item of the MAS (r = 0.33 and r = 0.54).

Known groups:
No studies have examined the known groups validity of the MAS.

Responsiveness

Dean and Mackey (1992) reported significant differences between mean scores for each item on the MAS from admission to discharge from stroke rehabilitation after an average of 71 days of rehabilitation.

Nugent, Schurr and Adams (1994) found an adequate correlation (r = 0.45) between the number of repetitions of a weight-bearing exercise (designed to strengthen the leg extensor muscles) and the change in the MAS score for the walking item among 25 patients receiving inpatient rehabilitation. To be included in the study, subjects had to have a score greater than 0 but less than 6 on the walking item of the MAS. All of the patients who practiced the exercise achieved independent walking for at least a 3m distance, which gave a final MAS score of three or greater.

English and Hillier (2006) examined the responsiveness of the MAS in 61 rehabilitation inpatients with stroke. The ability of the MAS to detect change was limited in this sample. The MAS item 5 (walking) showed a large effect size (ES) (ES = 1.02) and was able to detect change amongst lower functioning subjects (12 patients showed no change). The other items of the MAS were less responsive, in particular, the effect sizes for the arm items (items 6 to 8) change scores were small (ES ranged from 0.36 to 0.5) and between 44.3 and 63.9% of subjects did not change on these measures. In addition, over 80% of subjects were rated at the extremes of the scales on all three of the arm items. These findings suggest that clinicians should be cautious in choosing the MAS to measure change in patients as for some subgroups and for certain items, clinical change is unlikely to be detected by this tool.

References

  • Carr, J. H., Shepherd, R. B., Nordholm, L., Lynne, D. (1985). Investigation of a new motor assessment scale for stroke patients. Phys Ther, 65, 175-180.
  • Dean, C. M., Mackey, F. M. (1992). Motor assessment scale scores as a measure of rehabilitation outcome following stroke. Aust J Physiother, 38, 31-35.
  • English, C. K., Hillier, S. L. (2006). The sensitivity of three commonly used outcome measures to detect change amongst patients receiving inpatient rehabilitation following stroke. Clinical Rehabilitation, 20, 52-55.
  • Hsueh, I-P., Hsieh, C-L. (2002).Responsiveness of two upper extremity function instruments for stroke inpatients receiving rehabilitation. Clinical Rehabilitation, 16(6), 617-624.
  • Kjendahl, A., Jahnsen, R., Aamodt, G. (2005). Motor Assessment Scale in Norway: Translation and inter-rater reliability. Advances in Physiotherapy, 7(1), 7-12.
  • Lannin, N. A. (2004). Reliability, validity and factor structure of the upper limb subscale of the Motor Assessment Scale (UL-MAS) in adults following stroke. Disability & Rehabilitation, 26(2), 109-116.
  • Loewen, S. C., Anderson, B. A. (1988). Reliability of the Modified Motor Assessment Scale and the Barthel Index. Phys Ther, 68, 1077-1081.
  • Loewen, S. C., Anderson, B. A. (1990). Predictors of stroke outcome using objective measurement scales. Stroke, 21, 78-81.
  • Malouin, F., Pichard, L., Bonneau, C., Durand, A., Corriveau, D. (1994). Evaluating motor recovery early after stroke: comparison of the Fugl-Meyer Assessment and the Motor Assessment Scale. Arch Phys Med Rehabil, 75(11), 1206-1212.
  • Miller, K.J., Slade, A.L., Pallant, J.F., Galea, M.P. (2010). Evaluation of the psychometric properties of the upper limb subscales of the Motor Assessment Scale using a Rasch analysis model. J Rehabil Med, 42, 315-322.
  • Poole, J. L., Whitney, S. L. (1988). Motor assessment scale for stroke patients: concurrent validity and interrater reliability. Arch Phys Med Rehabil, 69(3), 195-197.
  • Sabari, J. S., Lim, A. L., Velozo, C. A., Lehman, L., Kieran, O., Lai, J. S. (2005). Assessing arm and hand function after stroke: a validity test of the hierarchical scoring system used in the motor assessment scale for stroke. Arch Phys Med Rehabil, 86(8), 1609-1615.
  • Simondson, J. A., Goldie, P., Greenwood, K. M. (2003). The mobilityscaleforacute stroke patients: Concurrent validity. Clinical Rehabilitation, 17(5), 558-564.

See the measure

How to obtain a copy of the MAS?

The MAS is available for free and can be found in Carr et al. (1985).

Click here to view a copy of the MAS.

Table of contents

Postural Assessment Scale for Stroke Patients (PASS)

Evidence Reviewed as of before: 22-10-2012
Author(s)*: Annabel McDermott, OT
Editor(s): Nicol Korner-Bitensky, PhD OT
Expert Reviewer: Professor Charles Benaim

Purpose

The Postural Assessment Scale for Stroke Patients (PASS) assesses balance in lying, sitting and standing positions. It was designed specifically for patients with stroke and is suitable for all individuals regardless of postural performance.

In-Depth Review

Purpose of the measure

The Postural Assessment Scale for Stroke Patients (PASS) is comprised of 12 items of increasing difficulty that measure balance in lying, sitting and standing. It was designed specifically for patients with stroke, regardless of postural competence (Barros de Oliveira et al., 2008; Mao et al., 2002). The PASS measures the patient’s ability to maintain stable postures as well as equilibrium in changes of position (Di Monaco et al., 2010). It includes items not assessed by the Berg Balance Scale (Blum & Korner-Bitensky, 2008) and demonstrates better psychometric properties than the Berg Balance Scale and the Fugl-Meyer Assessment modified balance subscale (Mao et al., 2002).

Available versions

The PASS was developed in 1999 by Benaim et al. as an adaptation of the Fugl-Meyer Assessment balance subscale (Benaim et al., 1999). It was originally developed in French and has since been translated into English and Swedish (SwePASS). Short forms of the PASS, with fewer items (5-item SFPASS) and/or smaller scoring scales (PASS-3P), have also been developed.

Features of the measure

Items:

The PASS consists of 12 items of graded difficulty:

Maintaining a posture

  • Sitting without support (sitting on the edge of a 50cm-high examination table with feet touching the floor)
  • Standing with support (feet position free, no other constraints)
  • Standing without support (feet position free, no other constraints)
  • Standing on nonparetic leg (no other constraints)
  • Standing on paretic leg (no other constraints)

Changing Posture

  • Supine to affected side lateral
  • Supine to nonaffected side lateral
  • Supine to sitting up on edge of table
  • Sitting on edge of table to supine
  • Sit-to-stand (without any support, no other constraints)
  • Stand-to-sit (without any support, no other constraints)
  • Standing, picking up a pencil from the floor (without any support, no other constraints) (Barros de Oliveira et al., 2008)

Scoring:

The PASS consists of a 4-point scale where items are scored from 0 – 3. The total score ranges from 0 – 36 (Barros de Oliveira et al., 2008).

Item 1: Sitting without support

  • 0 = cannot sit
  • 1 = can sit with slight support (e.g. by 1 hand)
  • 2 = can sit for more than 10 seconds without support
  • 3 = can sit for 5 minutes without support

Item 2: Standing with support

  • 0 = cannot stand, even with support
  • 1 = can stand with strong support of 2 people
  • 2 = can stand with moderate support of 1 person
  • 3 = can stand with support on only 1 hand

Item 3: Standing without support

  • 0 = cannot stand without support
  • 1 = can stand without support for 10 seconds or leans heavily on 1 leg
  • 2 = can stand without support for 1 minute or stands slightly asymmetrically
  • 3 = can stand without support for more than 1 minute and at the same time perform arm movements above the shoulder level

Items 4 and 5: Standing on the nonparetic / paretic leg

  • 0 = cannot stand on the leg
  • 1 = can stand on the leg for a few seconds
  • 2 = can stand on the leg for more than 5 seconds
  • 3 = can stand on the leg for more than 10 seconds

Items 6 – 10

  • 0 = cannot perform the activity
  • 1 = can perform the activity with much help
  • 2 = can perform the activity with little help
  • 3 = can perform the activity without help

Description of tasks:

Items are graded by difficulty, whereby lying and sitting items are easier than standing items. Items 6 (supine to the affected side lateral) and 7 (supine to nonaffected side lateral) are the easiest items; item 5 (standing on the paretic leg) is the most difficult item of the assessment (Benaim et al., 1999).

Time:

The PASS takes 1 to 10 minutes to administer (Benaim et al., 1999).

Training requirements:

No special training is required, although clinicians should have an understanding of balance impairment and related safety issues following stroke.

Chien et al. (2007b) note that the different scoring criteria for several items of the PASS may pose difficulties for less-trained assessors, and recommends the simpler SFPASS as an alternative.

Equipment:

  • 50cm-high examination table (e.g. Bobath plane)
  • Chronometer
  • Pen

Alternative forms of the PASS

Chien et al. (2007b) developed a short form PASS (SFPASS) by conducting an item analysis of the PASS in a sample of 278 patients with stroke, and selecting items with the best measurement properties (i.e. highest internal consistency and greatest responsiveness). The SFPASS focuses on assessment of bed mobility and sit-to-stand. The SFPASS comprises 5 items (Liaw et al., 2012):

  • Standing on the nonparetic leg
  • Supine to sitting up on the edge of the table
  • Sitting on the edge of the table to supine
  • Sitting to standing up
  • Standing up to sitting down

SFPASS items are scored on a 3-point scale and total scores range from 0 to 15. The SFPASS is simpler and quicker to administer than the PASS (Liaw et al., 2012).

Persson et al. (2011) developed a Swedish version of the PASS (SwePASS) in response to perceived need to clarify scoring criteria and item descriptions. The SwePASS defines the scoring criteria “much help” as “support from 2 persons”, and “little help” as “support from 1 person”. Items 4, 7 and 10 have been clarified or modified. The SwePASS comprises the same 12 items as the PASS, and the same ordinal scale scoring (0-3), with a maximum score of 36.

Client suitability

Can be used with:

  • Patients with stroke, regardless of postural competencies.

Should not be used in:

  • None reported

In what languages is the measure available?

  • French
  • English
  • Swedish

Summary

What does the tool measure? Balance
What types of clients can the tool be used for? Patients following stroke, regardless of balance performance
Is this a screening or assessment tool? Assessment
Time to administer 10 minutes
Versions
  • wePASS (Swedish version)
  • SFPASS (5-item, 3-scale short form)
  • PASS-3P (12-item, 3-scale form)
Other Languages French, Swedish
Measurement Properties
Reliability Internal consistency:
– Three studies have reported excellent internal consistency of the PASS.
– One study reported excellent internal consistency of PASS trunk control items (PASS-TC).
– One study reported adequate to excellent internal consistency of the SFPASS.

Test-retest:
– Three studies reported adequate to excellent intra-rater reliability of individual PASS items and excellent test-retest reliability of PASS total scores. Further, one study reported small limits of agreement using Bland-Altman plots, indicating high stability with low natural variation.
– One study reported excellent test-retest reliability of individual items and total score of the SFPASS.

Intra-rater:
One study reported adequate to excellent same-day intra-rater reliability of the SwePASS in patients with acute stroke.

Inter-rater:
– Two studies reported adequate to excellent inter-rater reliability of individual PASS items and excellent inter-rater reliability of the PASS total score.
– One study reported excellent inter-rater reliability of the PASS-TC.
– One study reported excellent inter-rater reliability of the SwePASS.

Validity Content:
No studies have reported on the content validity of the PASS.

Criterion:
Concurrent:
Four studies examined the concurrent validity of the PASS and reported excellent concurrent validity with the Berg Balance Scale, FMA modified balance scale (FMA-B), Trunk Impairment Scale (TIS), SFPASS and PASS-3P.

Predictive:
– Six studies reported that the PASS shows adequate to excellent predictive validity for function at 90 days post-stroke or on discharge from rehabilitation, but poor predictive validity of function after 1 year. Two studies reported excellent predictive validity of mobility at 180 days post-stroke or on discharge from rehabilitation.
– One study reported that the PASS-TC shows excellent predictive validity of ADL function at 6 months post-stroke and is a stronger predictor of function than the BI or Fugl-Meyer Assessment (FMA) motor test.
– Two studies reported that the SFPASS shows adequate to excellent predictive validity for function on discharge from rehabilitation or at 90 days post-stroke.

Construct:
Convergent/Discriminant:
– Four studies examined the convergent validity of the PASS and reported excellent correlations with the BI; FIM total score, transfer tasks and locomotor tasks; and motricity scores of the upper and lower limb. Adequate negative correlations were found with the star cancellation test of spatial inattention; pressure sensitivity of the upper and lower limb; and measurement of postural stabilization and postural orientation with respect to gravity. The PASS demonstrated no significant correlation with the Ashworth Scale.
– One study reported that the PASS-TC demonstrates excellent convergent validity with the BI and FMA-B.
– Two studies have examined the convergent validity of the SFPASS or PASS-3P and reported that both measures show excellent correlations with the BI and FIM.

Known Groups:
No studies have reported on the known-groups validity of the PASS.

Floor/Ceiling Effects Three studies have reported no floor or ceiling effect of the PASS from acute to chronic stages of stroke recovery. However, one study reported a poor floor effect at 90 days post-stroke.
Does the tool detect change in patients? – Six studies have examined responsiveness and found that the PASS is able to detect change in stroke. The PASS demonstrates good responsiveness before 90 days post-stroke but low responsiveness at later stages of recovery. Further, the PASS is more responsive to detecting change in moderate to severe stroke than mild stroke.
– Three studies have examined responsiveness in the PASS-3P or SFPASS and reported that both measures are able to detect change in acute and subacute stroke.

Sensitivity & specificity:
No studies have reported on the sensitivity or the specificity of the PASS.

Acceptability The PASS was designed for patients with stroke, regardless of balance function.
Feasibility The PASS is quick and simple test to administer, and requires minimal equipment and no specialized training.
How to obtain the tool? The tool is available on line: http://www.brightonrehab.com/wp-content/uploads/2012/02/Postural-Assessment-Scale-for-Stroke-Patients-PASS.pdf

Psychometric Properties

Overview

A literature search was conducted to identify all relevant publications on the psychometric properties of the Postural Assessment Scale for Stroke Patients (PASS). Eleven papers were reviewed.

Floor/Ceiling Effects

Benaim et al. (1999) examined the frequency distribution and density trace of PASS scores in 58 patients at 30 and 90 days post-stroke. While a uniform distribution was noted at 30 days post-stroke, there was a pronounced peak around the highest values at 90 days as 38% of patients had achieved the maximum score. Testing on 30 age-matched healthy subjects revealed that 90% of participants achieved the maximum score.

Mao et al. (2002) examined the floor and ceiling effect of the PASS on a sample of patients with stroke at 14, 30, 90 and 180 days post-stroke. Floor and ceiling effects were adequate at all time points (floor effect range 2.2-3.8%; ceiling effect range 3.3-17.5%).

Chien et al. (2007b) examined the floor and ceiling effects of the PASS among 287 patients at 14 days post-stroke, and a second cohort of 197 patients. The PASS demonstrated no significant floor effects (6.3%, 6.1% respectively) or ceiling effects (2.8%, 1.7% respectively) in either cohort.

Chien et al. (2007b) also examined the floor and ceiling effects of the 5-item SFPASS among 287 patients at 14 days post-stroke, and a second cohort of 197 patients. The SFPASS demonstrated no significant ceiling effect in either cohort (7.0%, 8.4%). A poor floor effect (20.2%) was seen in the first cohort, but was not evident in the second cohort (16.2%).

Yu et al. (2012) reported no significant floor or ceiling effect of the PASS among 85 patients with stroke (most with acute stroke and severe disability) on admission to (<15%) or discharge from (<10%) a rehabilitation ward.

Reliability

Internal constancy:
Benaim et al. (1999) reported excellent internal consistency of the PASS (α=0.95) when examined on a sample of 58 patients with stroke using Cronbach α-coefficient. The authors concluded that the PASS is homogenous and is likely to produce consistent responses. Further, there was a strong correlation between the sums of maintaining-position and changing-position items (r=0.86, p<0.001).

Mao et al. (2002) examined the internal consistency of the PASS on a sample of 112 patients with stroke at 14, 30, 90 and 180 days post-stroke, using Cronbach’s α coefficient. Excellent internal consistency was reported at all time points (α range = 0.94-0.96).

Hsieh et al. (2002) examined the internal consistency of the trunk control items of the PASS (PASS-TC: items 1, 6, 7, 8, 9) in a sample of 182 patients with acute stroke. Results from two raters indicated excellent internal consistency of the PASS-TC (α=0.93-0.94), measured using Cronbach’s α.

Chien et al. (2007b) examined the internal consistency of the PASS on a sample of 287 patients at 14 days post-stroke, and a second cohort of 197 patients. Excellent internal consistency (α=0.96) was reported in both cohorts, measured using Cronbach’s α.

Chien et al. (2007b) also examined the internal consistency of the SFPASS on a sample of 287 patients at 14 days post-stroke, and a second cohort of 197 patients. Internal consistency was adequate in the first cohort (α=0.66) and excellent in the second cohort (α=0.93), as measured using Cronbach’s α.

Chien et al. (2007b) noted that the high internal consistency of the PASS may indicate redundancy among items.

Test-retest:
Benaim et al. (1999) measured test-retest reliability of the PASS on 12 patients with stroke, using α-coefficient for individual items and Pearson product moment correlation for the total score. The authors reported adequate to excellent reliability for individual items (average α=0.72, range 0.45 – 1) and excellent reliability for the total score (r=0.98, p<0.001). Further, a Bland-Altman plot showed that differences between scorings were weak (0.5) and homegenous (differences were within or very near the 95% confidence limits of the mean).

Chien et al. (2007a) examined the 2-week test-retest reliability of the PASS among 20 patients with chronic stroke, and reported excellent test-retest reliability (ICC=0.84), measured using a 1-way random effects model intraclass correlation coefficient (ICC).

Liaw et al. (2008) examined 7-day test-retest reliability of the PASS in a sample of 52 patients with chronic stroke, using the intraclass coefficient for relative reliability (i.e. the degree to which individuals maintain their position in a sample with repeated measures), and Bland-Altman plots and standard error of measurement (SEM) for absolute reliability (i.e. the degree to which repeated measurements vary for individuals). Relative test-retest reliability was excellent (ICC=0.97). Bland-Altman plots revealed small limits of agreement (-2.72 to 3.52), indicating high stability with low natural variation. The SEM was small (1.14%), indicating that the PASS is useful to identify real change.

Liaw et al. (2012) examined the 7-day test-retest reliability of the SFPASS among a sample of 52 patients with chronic stroke, using the weighted α statistic for individual items and intraclass correlation coefficient (ICC) for the total score. The authors reported adequate to excellent test-retest reliability for individual items (mean α=0.78, range 0.66 – 0.84) and excellent reliability for total scores (ICC=0.93, 95% CI 0.88-0.96). Bland-Altman plots of the differences between measurements from the two test sessions against the mean of the two test sessions for each patient revealed small limits of agreement (1.99 to -2.33), indicating high stability with low natural variation. Standard error of measurement (SEM) was 5.2%, representing a small and acceptable level of measurement error.
Note: When performing a Bland and Altman analysis, a mean difference close to zero indicates higher agreement between measurements.

Intra-rater:
Persson et al. (2011) examined the same-day intra-rater reliability of the SwePASS in a sample of 114 patients with acute stroke. The inter-rater reliability of items was excellent (r=0.88-0.98) when measured using Spearman’s rank correlation, and adequate to excellent (α=0.70-0.93) when measured using Kappa coefficient.

Inter-rater:
Benaim et al. (1999) measured inter-rater reliability of the PASS using α-coefficient for individual item reliability and Pearson product moment correlation for total score reliability. Two clinicians assessed patients with stroke on the same day, with a total sample of 12 patients. The authors reported adequate to excellent inter-rater reliability for individual items (average α=0.88, range 0.64-1) and excellent inter-rater reliability for the total score (r=0.99, p<0.001). Further, a Bland and Altman plot for inter-rater reliability showed that differences between scorings were weak (0.5) and homegenous (differences were within or very near the 95% confidence limits of the mean).

Mao et al. (2002) examined the inter-rater reliability of the PASS using α-coefficient for individual item reliability and Pearson product moment correlation for total score reliability. Two clinicians assessed patients at 14 days post-stroke on the same day, with a total sample of 112 patients. Inter-rater reliability for individual items was adequate to excellent (median α=0.88, range 0.61-0.96) and inter-rater reliability for the total score was excellent (ICC=0.97, 95% CI 0.95-0.98).

Hsieh et al. (2002) examined the inter-rater reliability of the trunk control items of the PASS (PASS-TC: items 1, 6, 7, 8, 9) in a sample of 182 patients with acute stroke. Results indicated excellent inter-rater reliability of the PASS-TC (ICC=0.97), measured using intraclass correlation coefficient.

Persson et al. (2011) examined the same-day inter-rater reliability of the SwePASS in a sample of 114 patients with acute stroke, using Spearman’s rank correlation. The inter-rater reliability of items was excellent (r=0.77-0.99).

Validity

Content:

No studies have reported on the content validity of the PASS.

Criterion:

Concurrent :
Mao et al. (2002) examined the concurrent validity of the PASS, Berg Balance Scale (BBS) and the Fugl-Meyer Assessment modified balance scale (FMA-B), using Spearman’s α correlation coefficient. A sample of 123 patients with stroke was followed at 14, 30 (n=110), 90 (n=93), and 180 (n=80) days after stroke onset. There was excellent concurrent validity between the PASS and the FMA-B (α=0.95-0.97) and between the PASS and the BBS (α= 0.92-0.95) at all time points.

Wang et al. (2004) examined the concurrent validity of the PASS, Berg Balance Scale (BBS) and modified versions of both assessments that used 3-level scales (12-item PASS-3P, 14-item BBS-3P) in a sample of 77 patients with stroke, using Spearman’s α correlation coefficient and Intraclass Correlation Coefficient. There was excellent concurrent validity between all measures (rho α 0.91, P<0.0001); of note, agreement between the PASS and the BBS (α=0.94, P<0.0001), and between the PASS and the PASS-3P (α=0.94, P<0.0001; ICC=0.97, 95% CI 0.96-0.98.) was excellent.

Chien et al. (2007b) examined the concurrent validity of the PASS and the 5-item SFPASS in a sample of 287 patients at 14 days post-stroke, using a random effects model intraclass correlation coefficient (ICC). There was excellent concurrent validity between the PASS and the 5-item SFPASS (ICC= 0.98; 96% variance). This result was repeated in a subsequent cohort of 179 patients (ICC=0.98). Further, Bland-Altman plots revealed no systematic trend between the difference and mean score of the PASS and the 5-item SFPASS (mean difference 1.6, limits of agreement range from -3.7 to 6.8). This suggests that the PASS and the SFPASS can be used interchangeably.

Di Monaco et al. (2010) reported excellent concurrent validity between the PASS and the Trunk Impairment Scale (TIS) (α=0.849, P<0.001), measured in a sample of 60 patients on admission to inpatient rehabilitation.

Predictive:
Benaim et al. (1999) examined the predictive validity of the PASS by comparing PASS scores at 30 days post-stroke with FIM scores at 90 days post-stroke on a sample of 58 patients. Correlations between the PASS and FIM total score (r=0.75, p<0.001), transfer items (r=0.74, p<0.006) and locomotion items (r=0.71, p<0.001) indicate that it is possible to predict functional recovery from PASS scores at 30 days post-stroke.

Mao et al. (2002) examined the predictive validity of the PASS, Berg Balance Scale and the Fugl-Meyer Assessment modified balance scale at 14, 30 and 90 days post-stroke by comparison with the Motor Assessment Scale walking subscale score at 180 days post-stroke, in a sample of 123 patients. The PASS demonstrated excellent predictive validity at all time points (α=0.86-0.90), as measured using Spearman’s p correlation coefficient.

Hsieh et al. (2002) examined the predictive validity of the trunk control items of the PASS (PASS-TC: items 1, 6, 7, 8, 9) in a sample of 169 patients by comparing PASS-TC scores taken at 14 days post-stroke with Barthel Index (BI) and Frenchay Activities Index (FAI) scores taken at 6 months post-stroke. The PASS-TC demonstrated excellent predictive validity (r=0.68, p<0.001), as measured using Pearson correlation coefficient. The PASS-TC was found to be a stronger predictor of comprehensive ADL function than the Barthel Index or the Fugl-Meyer motor test.

Wang et al. (2004) examined the predictive validity of the PASS and a modified version of the PASS that used a 3-level scale (12-item PASS-3P) in patients with stroke by comparing scores taken at 14 (n=226) and 30 days (n=202) post-stroke with Barthel Index (BI) scores taken at 90 days post-stroke, using Spearman’s α correlation coefficient. Both versions of the PASS demonstrated excellent predictive validity at 14 days (p=0.78) and 30 days (p=0.82) post-stroke.

Chien et al. (2007a) examined the predictive validity of the PASS in a sample of 32 patients with stroke by comparing PASS score taken within 3 months of the stroke with Barthel Index and Frenchay Activities Index scores taken approximately 1 year later. Results indicated poor predictive validity (r2=0.24), as measured using Pearson correlation coefficient.

Chien et al. (2007b) examined the predictive validity of the PASS and SFPASS in a sample of 218 patients with stroke by comparing scores on each test at 14 days post-stroke with Barthel Index (BI) scores at 90 days post-stroke. Results indicated adequate predictive validity of the PASS (r=0.49) and the SFPASS (r=0.48). The authors replicated the process on a second cohort of 179 patients by comparing PASS and SFPASS scores on admission to rehabilitation with BI scores on discharge from hospital. Results revealed excellent predictive validity of the PASS (r=0.83) and the SFPASS (r=0.82), as measured using product-moment correlations.

Di Monaco et al. (2010) examined the predictive validity of the PASS and the Trunk Impairment Scale (TIS) by comparing scores on admission to inpatient rehabilitation with FIM discharge scores, in a sample of 60 patients with stroke. Results indicated excellent predictive validity of the PASS (α=0.687, p<0.001), as measured using Spearman rank correlation. PASS admission scores were also significantly associated with FIM change scores (P<0.001), FIM effectiveness (P=0.017) and destination at discharge (P=0.032).

Yu et al. (2012) examined the predictive validity of the PASS and the Balance Computerized Adaptive Test (Balance CAT) by comparing scores on admission to a rehabilitation ward with Barthel Index (BI) and Stroke Rehabilitation Assessment of Movement mobility subscale (MO-STREAM) discharge scores in a sample of 85 patients with stroke. Correlations between PASS and BI scores (α =0.62, r2=0.39, p<0.001) and between PASS and MO-STREAM scores (α =0.80, r2=0.63, p<0.001) indicated sufficient predictive validity of the PASS, as measured using α and r2 from a simple linear regression analysis. This indicates that PASS scores at admission can predict discharge function and mobility.

Construct:

Convergent/Discriminant :
Benaim et al. (1999) examined correlations between PASS performance and clinical scales of functional status, motricity, spasticity, spatial inattention and somatosensory threshold among 58 patients at 30 days post-stroke, using Pearson correlation coefficients. Excellent correlations were found with FIM total score (r=0.73), transfer tasks (r=0.82) and locomotor tasks (r=0.73); and motricity scores of the lower limb (r=0.78) and upper limb (r=0.63). Adequate negative correlations were found with the star cancellation test of spatial inattention (r=-0.53) and pressure sensitivity of the lower limb (r=-0.45) and upper limb (r=-0.42). There was no significant correlation with spasticity, measured using the Ashworth Scale. The authors also examined the correlation between PASS performance and equilibrium, measured using a rocking platform, among a smaller sample of 31 patients at 90 days post-stroke, and reported adequate negative correlations with measurement of postural stabilization (r=-0.48) and postural orientation with respect to gravity (r=0.36).

Mao et al. (2002) examined the convergent validity of the PASS, Berg Balance Scale and the Fugl-Meyer Assessment modified balance scale by comparison with the Barthel Index (BI), using Spearman’s p correlation coefficient. A sample of 123 patients with stroke was followed at 14, 30 (n=110), 90 (n=93), and 180 (n=80) days after stroke onset. There was excellent convergent validity between the PASS and the BI (α=0.88-0.92) at all time points.

Hsieh et al. (2002) examined the convergent validity of the trunk control items of the PASS (PASS-TC: items 1, 6, 7, 8, 9) by comparison with the Barthel Index (BI) and Fugl-Meyer balance test (FM-B), in a sample of 182 patients at 14 days post-stroke. The PASS-TC demonstrated excellent convergent validity with the BI (r=0.89) and the FM-B (r=0.73), using Pearson correlation coefficient.

Wang et al. (2004) examined the convergent validity of the PASS and the PASS-3P by comparison with the Barthel Index (BI), in a sample of 77 patients with stroke. The PASS and the PASS-3P both demonstrated excellent convergent validity with the BI (α=0.84, (α=0.82 respectively), measured using Spearman p correlation coefficient.

Chien et al. (2007b) examined the convergent validity of the PASS and the 5-item SFPASS by comparison with the Barthel Index (BI) and FIM in a sample of 287 patients at 14 days post-stroke. The PASS and the SFPASS both demonstrated excellent correlations with the BI (PASS r=0.87; SFPASS r=0.86) and the FIM (PASS r=0.75; SFPASS r=0.75).

Known Group:
No studies have reported on the known-groups validity of the PASS.

Responsiveness

Mao et al. (2002) examined the responsiveness of the PASS in a sample of 123 patients with stroke by comparing scores taken at 14, 30 (n=110), 90 (n=93) and 180 (n=80) days post-stroke. There was a significant change in PASS scores at all stages (14-30 days, 30-90 days, 90-180 days, 14-90 days and 14-180 days post-stroke), measured using Wilcoxon matched-pairs signed-rank tests. Effect size was large at the interval between 14-30 days post-stroke (ES=0.89), became moderate in the interval between 30-90 days (ES=0.64) and low in the interval 90-180 days (ES=0.31). The overall effect size (14-180 days) was large (ES=1.12). These results indicate that the PASS demonstrates good responsiveness before 90 days post-stroke but low responsiveness at later stages of recovery. The authors also examined responsiveness according to stroke severity and found that the PASS is more responsive to detecting change in moderate to severe stroke than mild stroke across most time intervals. The overall effect size (14-180 days) was largest among patients with severe stroke (ES=1.54).

Wang et al. (2004) examined the responsiveness of the PASS and the PASS-3P in patients with stroke by comparing scores taken at 14 days (n=202), 30 days (n=167) and 90 days (n=167) post-stroke. There was a significant change in PASS and PASS-3P scores at all stages (14-30 days, 30-90 days and 14-90 days post-stroke), measured using Wilcoxon matched-pairs signed-rank tests. Both measures demonstrated a large effect size in the interval 14-30 days post-stroke (SRM=0.84 and 0.86 respectively) and 14-90 days post-stroke (SRM=1.02 and 1.04 respectively), but only a moderate effect size in the interval 30-90 days post-stroke (SRM=0.65 and 0.67 respectively), measured using standardized response mean (SRM). The authors examined responsiveness of the PASS and the PASS-3P according to severity of stroke – mild (Fugl-Meyer Assessment score ≥ 80), moderate (FMA score 36-79) and severe stroke (FMA score 0-35). Both measures showed a moderate effect size among patients with mild stroke (PASS SRM range 0.43-0.78; PASS-3P SRM range 0.46-0.78), moderate to large effect size among patients with moderate stroke (PASS SRM range 0.52-1.12; PASS-3P SRM range 0.56-1.19), and a large effect size among patients with severe stroke (PASS SRM range 0.92-1.35; PASS-3P SRM range 0.92-1.34). The effect size of both measures was consistently larger in the intervals 14-30 days post-stroke and 14-90 days post-stroke, than 30-90 days post-stroke.

Chien et al. (2007a) examined the responsiveness of the PASS in a sample of 40 patients with subacute stroke, measured using Cohen’s effect size. The PASS was administered twice over a 2-week interval, during which time patients received an intensive rehabilitation program that comprised postural training and weight shift exercises for more than 2 hours per day, 5 days a week. The effect size after 2 weeks was small (d=0.41). The minimal detectable change (MDC) (i.e. the threshold value that determines whether score changes are beyond chance) was 2.22 (95% CI) at an individual score level, and 0.50 (95% CI) at a group score level.

Chien et al. (2007b) examined the responsiveness of the PASS in a sample of 262 patients with stroke. The change score from 14 days post-stroke to 30 days post-stroke was significant (4.9, p<0.01) and the effect size was small (ES=0.42). A small effect size (ES=0.43) was also seen in a subsequent cohort of 179 patients who were assessed at admission to rehabilitation and again on discharge from hospital.

Chien et al. (2007b) examined the responsiveness of the 5-item SFPASS in a sample of 262 patients with stroke. The change score from 14 to 30 days post-stroke was significant (5.4, p<0.01) and the effect size was small (ES=0.44). A small effect size (ES=0.42) was also seen in a subsequent cohort of 179 patients who were assessed at admission to rehabilitation and again on discharge from hospital.

Chien et al. (2007b) reported on the Standard Error of Measurement (i.e. an estimate of the dispersion of scores that would be obtained if the measure was administered to a patient multiple times) of the PASS and the 5-item SFPASS in a cohort of 287 patients at 14 days post-stroke. The SEM of the PASS was 2.4 (4.7, 95% CI). The SEM of the 5-item SFPASS in the same cohort was 3.4 (6.7, 95% CI). This score is lower than 10% of the highest possible score of 36, which indicates that the measurement error does not exceed clinical importance.

Liaw et al. (2008) examined the smallest real difference (SRD – the smallest change threshold that indicates a real improvement for a single individual) of the PASS in a sample of 52 patients with chronic stroke. Participants were assessed by the same clinician on 2 occasions, 7-days apart. The SRD was 3.2, indicating that a change of more than 4 points in the total score for the PASS in chronic stroke patients is not likely to be attributable to chance variation or measurement error.

Liaw et al. (2012) examined the minimal detectable change (MDC) of the Short Form PASS (SFPASS) in a sample of 52 patients with chronic stroke. Participants were assessed by the same clinician on two occasions, 7 days apart. Results indicate that a change in an individual’s SFPASS scores greater than 2.16 points can be interpreted as true change (95% CI).

Yu et al. (2012) examined the internal and external responsiveness of the PASS in a sample of 85 patients with stroke. There was a significant change in PASS scores from admission to discharge (Wilcoxon Z=7.7, p<0.001), and the effect size was large (d=0.87), indicating adequate internal responsiveness. External responsiveness was calculated by comparing PASS change scores (admission to discharge) with change scores from the Barthel Index (BI) and the mobility subscale of the Stroke Rehabilitation Assessment of Movement (MO-STREAM), using α and r2 from a simple linear regression analysis. Results revealed a fair association between PASS and BI changes scores (α =0.44, r2=0.20, p<0.001) and a moderate association between PASS and MO-STREAM change scores ((α =0.77, r2=0.59, p<0.001) indicating sufficient external responsiveness of the PASS to changes in function and mobility following stroke.

Sensitivity & specificity:
No studies have reported on the sensitivity or the specificity of the PASS.

References

  • Barros de Oliveira, C., Torres de Medeiros, I.R., Ferreira Frota, N.A., Greters, M.E., & Conforto, A.B. (2008). Balance control in hemiparetic stroke patients: main tools for evaluation. Journal of Rehabilitation Research and Development, 45(8), 1215-26.
  • Benaim, C., Perennou, D.A., Villy, J., Rousseaux, M., & Pelissier, J.Y. (1999). Validation of a standardized assessment of postural control in stroke patients: The Postural Assessment Scale for Stroke Patients (PASS). Stroke, 30, 1862-8.
  • Blum, L. & Korner-Bitensky, N. (2008). Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review. Physical Therapy, 88, 559-66.
  • Chien, C-W., Hu, M-H., Tan, P-F., Sheu, C-F., & Hsieh, C-L. (2007a). A comparison of psychometric properties of the Smart Balance Master system and the Postural Assessment Scale for Stroke in people who have had mild stroke. Archives of Physical Medicine and Rehabilitation, 88, 374-80.
  • Chien, C-W., Lin, J-H., Wan, C-H., Hsueh, I-P., Sheu, C-F., & Hsieh, C-L. (2007b). Developing a short form of the Postural Assessment Scale for People with Stroke. Nuerorehabilitation and Neural Repair, 21, 81-90.
  • Di Monaco, M., Trucco, M., Di Monaco, R., Tappero, R., & Cavanna, A. (2010). The relationship between initial trunk control or postural balance and inpatient rehabilitation outcome after stroke: a prospective comparative study. Clinical Rehabiltiation, 24, 543-54.
  • Hseih, C-L., Sheu, C-F., Hsueh, I-P., & Wang, C-H. (2002). Trunk control as an early predictor of comprehensive activities of daily living function in stroke patients. Stroke, 33, 2626-30.
  • Liaw, L-J., Hsieh, C-L., Hsu, M-J., Chen, H-M., Lin, J-H., & Lo, S-K. (2012). Test-retest reproducibility of two short-form balance measures used in individuals with stroke. International Journal of Rehabilitation Research, in press. Epub ahead of print retrieved from http://journals.lww.com/intjrehabilres/Abstract/publishahead/Test_retest_reproducibility_of_two_short_form.99818.aspx
  • Liaw, L-J., Hsieh, C-L., Lo, S-K., Chen, H-M., Lee, S., & Lin, J-H. (2008). The relative and absolute reliability of two balance performance measures in chronic stroke patients. Disability and Rehabilitation, 30(9), 656-61.
  • Mao, H-F., Hsueh, I-P., Tang, P-F., Sheu, C-F., & Hsieh, C-L. (2002). Analysis and comparison of the psychometric properties of three balance measures for stroke patients. Stroke, 33, 1022-7.
  • Persson, C.U., Hansson, P-O., Danielsson, A., & Sunnerhagen, K.S. (2011). A validation study using a modified version of Postural Assessment Scale for Stroke Patients: Postural stroke study in Gothenburg (POSTGOT). Journal of NeuroEngineering and Rehabilitation, 8, 57-64.
  • Wang, C.H., Hsueh, I.P., Sheu, C.F., Yao, G., & Hsieh, C.L. (2004). Psychometric properties of 2 simplified 3-level balance scales used for patients with stroke. Physical Therapy, 84(5), 430-8.
  • Yu, W-H., Hsueh, I-P., Hou, W-H., Wang, Y-H., & Hsieh, C-L. (2012). A comparison of responsiveness and predictive validity of two balance measures in patients with stroke. Journal of Rehabilitation Medicine, 44, 176-80.

See the measure

How to obtain the PASS?

The PASS is available on line at: http://www.brightonrehab.com/wp-content/uploads/2012/02/Postural-Assessment-Scale-for-Stroke-Patients-PASS.pdf

Table of contents

Postural Reactions Test

Evidence Reviewed as of before: 15-12-2022
Author(s)*: Annabel McDermott, OT
Editor(s): Annie Rochette, PhD OT
Expert Reviewer: Hanna Sjöholm, PT

Purpose

The Postural Reactions Test measures all postural reactions required for establishing and maintaining balance. The Postural Reactions Test measures equilibrium and righting reactions in sitting, and protective reactions in sitting and standing.

In-Depth Review

Purpose of the measure

The Postural Reactions Test measures all postural reactions required for establishing and maintaining balance. The Postural Reactions Test measures equilibrium and righting reactions in sitting, and protective reactions in sitting and standing (Sjoholm et al., 2018).

The Postural Reactions Test was developed from literature, clinical experience and in collaboration with patients and physiotherapists (Sjoholm et al., 2018).

Available versions

There is one version of the Postural Reactions Test.

Features of the measure

Items:

The Postural Reactions Test measures equilibrium and righting reactions in sitting, and protective reactions in sitting and standing. The four reactions can be assessed and scored independently of each other (Sjoholm et al., 2018).

Equilibrium reactions and righting reactions are assessed as the assessor leans the patient to the side, or the patient leans by themselves.

  • Equilibrium reactions are observed as a movement of the opposite side arm and/or leg.
  • Righting reactions are observed as a movement of the head to the opposite side.

Protective reactions are assessed as the assessor gives the patient a push to the side hard enough to move the centre of gravity outside the patients’ support area.

  • Protective reactions while sitting are observed in the arm on the side toward which the patient is pushed.
  • Protective reactions while standing are observed in the legs.

Scoring:

Equilibrium and righting reactions

  • Score 0 = no reaction or an uncertain reaction is observed
  • Score 1 = A definite reaction is observed.

Protective reactions – sitting

  • Score 0 = No active reaction of the shoulder or arm to prevent a fall
  • Score 1 = A slow movement to prevent a fall by putting out the hand or more than the hand, although balance might not be regained
  • Score 2 = A fast movement to prevent a fall by putting out only the hand, and balance is regained by doing so.

Protective reactions – standing

  • Score 0 = The patient does not take any steps with either leg before the assessor has to catch the patient to prevent a fall
  • Score 1 = The patient takes more than one step to regain balance or takes only one step but does not regain balance, sot that the assessor has to catch the patient to prevent a fall
  • Score 2 = The patient takes one step with the right or left leg and successfully regains balance.

If the assessor is uncertain whether there is a postural reaction, the lowest score (equal to ‘no reaction’) is given.

What to consider before beginning:

Sitting assessments can be performed while the patient is sitting on a bed or an examining table, with the hands in the lap and the feet either supported or unsupported. Leg crossing is not allowed.

Protective reactions in standing are more easily triggered if the patient is standing with the feet together.

Time:

The Postural Reactions Test takes 5-10 minutes to administer.

Training requirements:

No training requirements have been specified for the Postural Reactions Test.

The assessor must be prepared to prevent the patient from falling.

Equipment:

The Postural Reactions Test does not require specific equipment.

Client suitability

Can be used with:

Individuals with acute stroke
Individuals with limited verbal comprehension (Sjoholm et al., 2018).

Should not be used with:

None stated

Languages of the measure

Swedish
English

Summary

What does the tool measure? Postural reactions
What types of clients can the tool be used for? The Postural Reactions Test can be used with individuals with acute stroke.
Is this a screening or assessment tool? Screening
Time to administer 5-10 minutes
ICF Domain Function
Versions There is one version of the Postural Reactions Test
Languages Swedish
English
Measurement Properties
Reliability Internal consistency:
No studies have examined internal consistency of the Postural Reactions Test.
Test-retest:
No studies have examined test-retest reliability of the Postural Reactions Test.
Intra-rater:
One study has shown good intra-rater reliability of the Postural Reactions Test.
Inter-rater:
One study has shown good inter-rater reliability of the Postural Reactions Test.
Validity Content:
Face validity of the Postural Reactions Test was established through review and pilot-testing by clinical physiotherapists.
Criterion:
Concurrent:
No studies have examined concurrent reliability of the Postural Reactions Test.
Predictive:
One study showed that impaired protective reactions in sitting are decisive risk factors for early falls.
Construct:
Convergent/Discriminant:
No studies have examined convergent/discriminant validity of the Postural Reactions Test.
Known Groups:
No studies have examined known group validity of the Postural Reactions Test.
Floor/Ceiling Effects No studies have reported on floor/ceiling effects of the Postural Reactions Test. However, a floor effect is possible when used with individuals with good postural stability.
Does the tool detect change in patients? No studies have reported on the responsiveness of the Postural Reactions Test.
Acceptability The Postural Reactions Test is non-invasive and quick to administer.
Feasibility The Postural Reactions Test is suitable for administration in various settings. The assessment is quick to administer and requires minimal specialist equipment or training.
How to obtain the tool? The Postural Reactions Test can be accessed here.
Swedish version (The Postural Reactions Test (Sv inkl ref)) (1)
English version (The Postural Reactions Test (Eng inkl ref) (1))

Psychometric Properties

Overview

The Postural Reactions Test was developed in consultation with a convenience sample of physiotherapists and stroke patients (Sjoholm et al., 2018).

A literature search was conducted to identify all relevant publications on the psychometric properties of the Postural Reactions Test pertinent to use with participants following stroke. Two studies were identified.

Floor/Ceiling Effects

No studies have reported on floor/ceiling effects.

Reliability

Internal consistency:
Internal consistency of the Postural Reactions Test has not been measured.

Test-retest:
Test-retest reliability of the Postural Reactions Test has not been measured.

Intra-rater:
Sjoholm et al. (2018) examined intra-rater reliability of the Postural Reactions Test in a sample of 20 patients with acute stroke. Ten physiotherapists viewed a video recording of participants’ performance of the Postural Reactions Test, on two occasions at least 2 weeks apart. The medians and quartiles of the two viewing sessions were calculated and the overall proportions of agreement (%) between the two sessions was calculated. The overall percentage of agreement was 86-93%.

Inter-rater:
Sjoholm et al. (2018) examined inter-rater reliability of the Postural Reactions Test in a sample of 20 patients with acute stroke. Participants’ performance of the Postural Reactions Test was videorecorded and viewed by ten physiotherapists. The most common score for each participant – and the number of physiotherapists who gave that score – was noted; then the median and quartiles were calculated for how many physiotherapists had scored the most common value for all participants. Results showed that 9-10 out of 10 physiotherapists scored the same value.

Validity

Content:

Face validity of the Postural Reactions Test was established in two phases: (i) systematic feedback regarding test instructions and assessment [procedures was gathered from 9 clinical physiotherapists at three group meetings]; and (ii) physiotherapists subsequently pilot-tested the assessment over a 1-year period. This resulted in modified instructions regarding administration and scoring (Sjoholm et al., 2018).

Criterion

Concurrent:
Concurrent validity of the Postural Reactions Test has not been measured.

 Predictive:
Sjoholm et al. (2022) examined ability of the Postural Reactions Test to predict number of days to first fall and 6-month fall incidence in a sample of 242 patients with acute stroke, using Cox proportional hazard regression analysis and Negative binomial regression analysis (respectively) and 95% Confidence Interval (CI), with significance at p<0.0005 using Bonferroni correction. Participants with a score of 0 (worst side) had more than triple the risk of early falls (HR=3.59, CI 2.07-6.23, p=0.000) than participants with a protective reaction sitting score of 2 (worst side). Participants with no intact protective reactions in sitting on either side had more than double the risk of early falls (HR=2.63, CI 1.66-4.17, p=0.000) than participants with intact protective reactions in sitting on both sides. Comparison between participants with a protective reaction sitting score of 2 (worst side), vs. 1 (worst side), and participants with intact protection reactions in sitting on both sides vs. one side were not significant. Results were not significant for risk of multiple falls (Nberg analysis). Predictive analysis of impairments in protective reactions in standing were not significant.

Construct:

Convergent/Discriminant:
Convergent/discriminant validity of the Postural Reactions Test has not been measured.

Known Group:
Known group validity of the Postural Reactions Test has not been measured.

Responsiveness:

Sensitivity& Specificity:
Sensitivity/Specificity of the Postural Reactions Test has not been measured.

References

Sjöholm, H., Hägg, S., Nyberg, L., & Kammerlind, A. (2018). Reliability of test procedures for postural reactions in people with acute stroke. International Journal of Therapy & Rehabilitation, 25(11), 576-586.

Sjöholm, H., Hägg, S., Nyberg, L., Lind, J., & Kammerlind, A. (2022). Exploring possible risk factors for time to first fall and 6-month fall incidence in persons with acute stroke. SAGE Open Medicine, 10: 1-11. https://doi.org/10.1177/20503121221088093

See the measure

The Postural Reactions Test can be found here in English and in Swedish.

Table of contents

Rivermead Mobility Index (RMI)

Evidence Reviewed as of before: 24-12-2008
Author(s)*: Sabrina Figueiredo, BSc
Editor(s): Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc; Katie Marvin, MSc, PT Candidate

Purpose

The Rivermead Mobility Index (RMI) was developed from the Rivermead Motor Assessment Gross Function subscale as a means to quantify mobility disability in clients with stroke. The RMI is clinically relevant in testing functional abilities such as gait, balance, and transfers (Forlander & Bohannon, 1999).

In-Depth Review

Purpose of the measure

The Rivermead Mobility Index (RMI) was developed from the Rivermead Motor Assessment Gross Function subscale as a means to quantify mobility disability in clients with stroke. The RMI is clinically relevant in testing functional abilities such as gait, balance, and transfers (Forlander & Bohannon, 1999).

Available versions

The RMI was published in 1991 by Collen, Wade, Robb and Bradshaw and is based on the gross function section of the Rivermead Motor Assessment.

Features of the measure

Items:

The RMI includes fifteen mobility items: 14 self-reported and 1 direct observation (standing unsupported). The 15 items are hierarchically arranged and fulfill Guttmann scaling criteria, suggesting all items are ordered according to ascending difficulty. To clarify, if the client succeeds in completing the most difficult item, this suggests he/she will succeed in easier items. Similarly, failure on an item suggests the client will be unable to complete the remaining more challenging items (Hsieh, Hsueh, & Mao, 2000). However, Franchignoni et al. (2003) identified potential difficulties in the order of the first three scale items. They reported that more patients could perform the third task (sitting balance) than either of the preceding two items (turning over in bed and lying to sitting). Given this, the authors suggested caution in interpreting the RMI as a true hierarchical scale.

The RMI can be administered using self-report or proxy report. It consists of the following 15 questions: (Forlander & Bohannon, 1999; Franchignoni et al. 2003).

  1. Turning over in bed: Do you turn over from your back to your side without help?
  2. Lying to sitting: From lying in bed, do you get up to sit on the edge of the bed on your own?
  3. Sitting balance: Do you sit on the edge of the bed without holding on for 10 seconds?
  4. Sitting to standing: Do you stand up from any chair in less than 15 seconds and stand there for 15 seconds, using hands and/or an aid, if necessary?
  5. Standing unsupported: ask client to stand without aid and observe standing for 10 seconds without any aid.
  6. Transfer: Do you manage to move from bed to chair and back without any help?
  7. Walking inside (with an aid if necessary): Do you walk 10 meters, with an aid if necessary, but with no standby help?
  8. Stairs: Do you manage a flight of stairs without help?
  9. Walking outside (even ground): Do you walk around outside, on pavements, without help?
  10. Walking inside, with no aid: Do you walk 10 meters inside, with no caliper, splint, or other aid (including furniture or walls) without help?
  11. Picking up off floor: Do you manage to walk five meters, pick something up from the floor, and then walk back without help?
  12. Walking outside (uneven ground): Do you walk over uneven ground (grass, gravel, snow, ice, etc) without help?
  13. Bathing: Do you get into/out of a bath or shower to wash yourself unsupervised and without help?
  14. Up and down four steps: Do you manage to go up and down four steps with no rail, but using an aid if necessary?
  15. Running: Do you run 10 meters without limping in four seconds (fast walk, not limping, is acceptable)?

Scoring:

Each item is coded 0 or 1, depending on whether the client can complete the task according to specific instructions. A score of 0 = a ‘no’ response; a score of 1 = a ‘yes’ response. A total score is determined by summing the points allocated for all items. A maximum score of 15 is possible: higher scores indicate better mobility performance. (Franchignoni et al., 2003; Hsueh, Wang, Sheu & Hsieh, 2003).

Time:

The RMI takes 3 to 5 minutes to administer (Hsieh et al., 2000).

Subscales:

None.

Equipment:

Only a pencil and the test are needed.

Training:

None typically reported.

Alternative forms of the Rivermead Mobility Index

Modified Rivermead Mobility Index (MRMI): In 1996, Lennon and Hastings proposed the MRMI to increase the sensitivity of the RMI. The MRMI includes 8 items on which patients are scored by rater’s direct observation. Scores are based on a 6-point scale and ranges from 0 to 40, where higher scores indicate better performance.

Client suitability

Can be used with:

  • Clients with stroke, including those with poor mobility status.
  • Clients with head injury or multiple sclerosis.

Should not be used in:

  • The RMI should not be administered to clients with severe cognitive impairments due to the 14 self-reported items.

In what languages is the measure available?

English, Italian and Dutch (Franchignoni et al., 2003; Roorda, Green, De Kluis, Molenaar, Bagley, Smith et al. (2008).

Summary

What does the tool measure? The RMI measures mobility disability in clients with stroke
What types of clients can the tool be used for? Clients with stroke, head injury or multiple sclerosis.
Is this a screening or assessment tool? Assessment
Time to administer An average of 3 to 5 minutes.
Versions Modified Rivermead Mobility Index.
Other Languages Italian and Dutch.
Measurement Properties
Reliability Internal consistency:
Two studies examined the internal consistency of the RMI and reported excellent internal consistency using Chronbach’s alpha and reliability coefficient rho.

Test-retest:
– Three studies have examined the test-retest reliability of the RMI and reported adequate to excellent test-retest reliability using Intraclass Correlation Coefficient (ICC) and Kappa Statistics.
– One study, using Rasch Analysis reported that item difficulty on the RMI is the same across repeated measures.

Inter-rater:
Two studies examined the inter-rater reliability of the RMI and reported poor to excellent inter-rater reliability using Bland and Altman Technique, ICC and weighted Kappa.

Validity Content:
One study examined the content validity of the RMI by estimating its coefficient of reproducibility and scalability and confirmed the RMI fulfill the Guttmann scaling criteria.

Criterion:
Concurrent:
One study examined the concurrent validity of the RMI and reported excellent correlations between the RMI and the Modified Rivermead Mobility Index and the Stroke Rehabilitation Assessment of Movement (STREAM) using Spearman’s rho. When using ICC an adequate correlation between these three mobility measures was found.

Predictive:
Three studies examined the predictive validity of the RMI and reported that the RMI measured at admission or up to 90 days after stroke was able to predict Barthel Index scores at discharge from a rehabilitation program. Also, at admission, RMI scores > than 4 was an excellent predictor of an early discharge home.

Construct:
Convergent:
Four studies examined convergent validity of the RMI and reported excellent correlations between the RMI and the Barthel Index, the Berg Balance Scale, the 6-Minute Walk Test, the motor scales of the FIM, the Trunk Control Test and gait speed. Adequate correlations were reported between the RMI and the leg section of the Motricity Index. Poor correlations were reported between the RMI and number of falls and cognitive scales of the FIM. Correlations were calculated using Pearson correlation and Spearman’s rho. One study examined the convergent validity of the Dutch version of the RMI and reported excellent correlations between the Dutch RMI and the Dutch version on the Barthel Index using Spearman’s rho.

Floor/Ceiling Effects

Two studies examined the floor and ceiling effects of the RMI and reported that at earlier phases of the stroke, floor effects were poor. When the RMI is measured 180 days after stroke ceiling effects were adequate.

Does the tool detect change in patients?

Three studies have examined the responsiveness of the RMI and reported that the RMI has a large Standardized Response Mean, a large effect size and is able to detect minimal clinically important differences in clients with stroke.

Acceptability The RMI should not be administered to clients with severe cognitive impairments due to the 14 self-reported items.
Feasibility The administration of the RMI is quick and simple.
How to obtain the tool? The RMI can be obtained from the studies by Antonucci et al. (2002), Forlander & Bohannon (1998) or Franchignoni et al. (2003).

Psychometric Properties

Overview

We conducted a literature search to identify all relevant publications on the psychometric properties of the Rivermead Mobility Index (RMI) in individuals with stroke. We identified twelve studies. The RMI appears to be responsive in clients with stroke.

Floor/Ceiling Effects

Franchignoni, Tesio, Benevolo, and Ottonello (2003) verified the floor effects for the RMI in 73 individual with sub-acute stroke. Participants were assessed at admission to a rehabilitation program and then again after 5 weeks. A poor floor effect was found at admission with 22% of patients scoring 0. When the re-assessment was performed the RMI showed an adequate floor effect with 9% of patients scoring the minimum score.

Hsueh, Wang, Sheu, and Hsieh (2003) examined floor and ceiling effects for the RMI, the Modified Rivermead Mobility Index (Lennon & Hastings, 1996) and the Stroke Rehabilitation Assessment of Movement (STREAM – Daley, Mayo, Wood-Dauphinee, Danys, & Cabot, 1997) in 57 clients with stroke. Participants were assessed at 4 time points: 14, 30, 90 and 180 days after stroke. Within 14 days after stroke, the RMI demonstrated a poor floor effect, with 23% of participants scoring 0 and an excellent ceiling effect, with no participants reaching the maximum score. At the thirtieth and ninetieth day after stroke, the RMI showed an adequate floor effect of 6% and 1%, respectively as well as an adequate ceiling effect of 2% and 3%, respectively. The RMI, when measured 180 days after stroke, demonstrated an excellent floor effect and an adequate ceiling effect of 2%. The MRMI and the STREAM showed an excellent floor effect at all points in time and the ceiling effect ranged from excellent at day 14 to adequate at day 30, day 60 and day 180, with 3%, 6%, and 7% of patients scoring the highest score, respectively.

Reliability

Internal consistency:
Franchignoni et al. (2003) administered the RMI to 73 patients two months following a first ever stroke and found the internal consistency of the RMI to be excellent, with a Chronbach’s alpha = 0.92.

Roorda, Green, De Kluis, Molenaar, Bagley, Smith et al. (2008) administered the English and Dutch version of the RMI to 420 and 200 clients with stroke, respectively. The internal consistency of both measures was found to be excellent with a reliability coefficient of 0.96 for the English version and of 0.97 for the Dutch version.

Test-retest:
Green, Forster, and Young (2001) evaluated the test-retest reliability of the RMI in twenty-two clients with chronic stroke. Participants were re-assessed with a 1-week interval by the same rater and under the same conditions. Agreement for total scores was investigated using Bland and Altman technique and agreement between items were assessed with kappa statistics. For the RMI total score the agreement was excellent (mean difference = 0.3). Kappa statistics were excellent for turning in bed (kappa = 1.00), walking inside with no aid (kappa = 0.89), walking outside on uneven ground (kappa = 0.83), bathing (kappa = 0.81), and picking objects off the floor (kappa = 0.79), and adequate for stairs (kappa = 0.68), lying to sitting (kappa = 0.64), sitting balance (kappa = 0.64), transfers (kappa = 0.64), walking up and down 4 steps (kappa = 0.67) and walking outside on uneven ground (kappa = 0.49). Kappa values were not provided for the remaining items (sitting to standing, standing unsupported, walking inside with aid, running).
Note: When performing a Bland and Altman analysis, a mean difference close to zero indicates higher agreement between measurements.

Antonucci, Aprile and Paolucci (2002) verified the test-retest reliability of the RMI in 308 clients with subacute stroke. Participants were assessed at admission and discharge from a stroke program of a rehabilitation hospital (the specific time-frame between the two evaluations was not specified). Test-retest reliability was calculated using Rasch Analysis, a type of item-response theory. Rasch Analysis allows verifying whether the item difficulty is the same across repeated measures. The RMI demonstrated item stability when performed at admission and discharge in that the most difficult and the easiest items remained the same. These findings suggest the RMI scores across testing occasions can be compared.

Chen, Hsieh, Lo, Liaw, Chen, and Lin (2007) examined the test-retest reliability of the RMI in 50 clients with chronic stroke. Participants were assessed twice by the same rater with a 7-day interval. The test-retest reliability of the RMI, assessed with the Intraclass Correlation Coefficient (ICC), was found to be excellent< (ICC = 0.96).

Intra-rater:
No studies have examined the intra-rater reliability of the RMI.

Inter-rater.
Collen, Wade, Robb, and Bradshaw (1991) estimated the inter-rater reliability of the RMI in 43 patients either with stroke (n = 9), head injury (n = 13) or neurosurgery (n =1). Agreement as calculated using the Bland and Altman Technique was excellent (Coefficient of reliability = 2.0/15).

Note: When using the Bland and Altman analysis, the coefficient of reliability is double the standard deviation and indicates, in this study, that between raters, total scores in the RMI can range a maximum of 2 points out of 15.

Hsueh et al. (2003) assessed the inter-rater reliability of the RMI in 40 patients with stroke at a rehabilitation unit. The RMI was administered by 2 examiners within 24 hours of each other. Examiners were blinded to each other’s scores. Inter-rater reliability on individual items was calculated using weighted kappa and the inter-rater agreement of the total score was analyzed with ICC. Inter-rater reliability on individual items ranged from poor to excellent (weighted kappa = 0.37 to 0.94) and inter-rater agreement on the total score was excellent (ICC = 0.92).

Validity

Content:

Content validity with Guttman scaling is evaluated on the extent to which total scores predict the number of consecutive items passed. In a study of 38 patients with subacute stroke, critical values for two indices, coefficient of reproducibility (> 0.9) and coefficient of scalability (> 0.7), were all exceeded. The results of this study confirm the existence of a valid, cumulative, and unidimensional Guttman scale (Hsieh, Hsueh & Mao, 2000).

Criterion:

Concurrent:
In a study by Hsueh et al. (2003), the concurrent validity of the RMI was examined against the Modified Rivermead Mobility Index (MRMI – Lennon & Hastings, 1996) and the Stroke Rehabilitation Assessment of Movement (STREAM – Daley et al., 1997) in 57 individuals with stroke. Correlations were calculated at 4-points in time (14, 30, 90 and 180 days after stroke) using Spearman’s rho and Intraclass Correlation Coefficient (ICC). Correlations between the RMI and the MRMI were excellent for all time points (rho = 0.78; rho = 0.90; rho = 0.90; rho = 0.93), as well as between the RMI and the STREAM (rho = 0.69; rho = 0.87; rho = 0.82; rho = 0.85). When the ICC was used, adequate correlations between the RMI and MRMI (ICC = 0.50; ICC = 0.59; ICC = 0.53; ICC = 0.55) and between the RMI and STREAM were found (ICC = 0.59; ICC = 0.71; ICC = 0.68; ICC = 0.68) at all times.

Predictive:
Hsieh et al. (2000) estimated the ability of the RMI measured at admission to a rehabilitation program to predict Barthel Index (Mahoney & Barthel, 1965) scores at discharge. Predictive validity of the RMI measured in 38 patients with acute stroke using Spearman’s rho was excellent (rho=0.77).
Note: In this study, admission scores were obtained on average 24 days after stroke. Discharge scores were collected on average 60 days after stroke.

Sommerfeld & von Arbin (2001) examined whether the RMI, Barthel Index (Mahoney & Barthel, 1965), sensory ability, aphasia, type and side of brain lesion, previous stroke, social status, living with another person, gender and age measured 10 days after stroke were able to predict an early discharge home, within three months after stroke onset. Length of stay in hospital was recorded from medical charts. Predictive validity of the RMI was assessed in 115 patients with acute stroke, 65 years and older. Compared to the other variables, a RMI score >4 was the best predictor of an early discharge home, followed by a Barthel Index score >35 and living with another person.

Hsueh et al. (2003) analyzed if the RMI, the MRMI (Lennon & Hastings, 1996), and the STREAM (Daley et al., 1997) measured at 14, 30 and 90 days after a stroke were able to predict the Barthel Index (Mahoney & Barthel, 1965) scores measured at 180 days after stroke in 57 individuals using Spearman’s rho. Within 14 days after stroke, adequate predictions regarding the Barthel Index scores were estimated from the 3 mobility measures. At day 30, the RMI was an adequate predictor of the Barthel Index scores while the MRMI and the STREAM were excellent predictors. At day 90, all three measures were excellent in predicting the Barthel Index scores measured 180 days after stroke.

Construct:

Collen et al. (1991) estimated the convergent validity of the RMI with the Barthel Index (Mahoney & Barthel, 1965), the Berg Balance Scale (Berg, Wood-Dauphinee, Williams & Maki, 1989), the 6-Minute Walk Test (Butland, Pang, Gross, Woodcock, & Geddes, 1982), gait speed and number of falls in 43 patients either with stroke (n = 9), head injury (n = 13) or neurosurgery (n =1). Excellent correlations were found between the RMI and the Barthel Index (r = 0.91), gait speed (r = 0.82), the Berg Balance Scale (r = 0.67) and the 6-Minute Walk Test (r = 0.63). The RMI and number of falls had a poor correlation (r = 0.30).

Hsieh et al. (2000) assessed the convergent validity of the RMI by comparing it to the Barthel Index (Mahoney & Barthel, 1965) and the Berg Balance Scale (Berg et al., 1989) in 38 inpatients with subacute stroke. Correlations as calculated using Spearman’s rho were excellent between the RMI and the Barthel Index (rho = 0.70) and between the RMI and the Berg Balance Scale (rho = 0.85).

Franchignoni et al. (2003) evaluated the convergent validity of the RMI with the motor and cognitive scales of the FIM (Keith, Granger, Hamilton, & Sherwin, 1987), the leg section of the Motricity Index (Demeurisse, Demol, & Robaye, 1980) and with the Trunk Control Test (Collin & Wade, 1990) in 73 patients with subacute stroke. In this study, the correlation using Spearman’s rho was excellent between the RMI and the Trunk Control Test (rho = 0.89) and the motor scales of the FIM (rho = 0.73), adequate between the RMI and the leg section of the Motricity Index (rho = 0.49), and poor between the RMI and the cognitive scales of the FIM (rho = 0.10).

Hsueh et al. (2003) analyzed the convergent validity of the RMI by comparing it to the Barthel Index (Mahoney & Barthel, 1965) in 57 participants with stroke. Correlations were calculated using Spearman’s rho at 4-points in time: 14, 30, 90 and 180 days after stroke. Excellent correlations between the RMI and the Barthel Index were found at all times (rho =0.72, rho = 0.88, rho = 0.86, rho = 0.88), respectively.

Roorda et al. (2008) examined the convergent validity of the Dutch version of the RMI by comparing it to the Dutch version of the Barthel Index in 91 clients. Correlations as calculated using Spearman’s rho was excellent (rho = 0.84).

Known groups:
No studies have examined the known groups validity of the RMI.

Responsiveness

Hsieh et al. (2000) assessed the ability of the RMI to detect minimal clinically important differences in 38 individuals with acute stroke. In this study, a clinically important difference was defined as an improvement of 3 or more points on the RMI. From admission to discharge, 76% of participants improved by more than 3 RMI points, suggesting the RMI was able to detect a minimal clinically important difference.

Franchignoni et al. (2003) estimated the responsiveness of the RMI. Seventy-three clients with subacute stroke were assessed at admission to a rehabilitation centre and then again five weeks later. The RMI demonstrated large responsiveness with an effect size of 0.89.

Hsueh et al. (2003) verified the responsiveness on the RMI, the MRMI (Lennon & Hastings, 1996) and the Stroke Rehabilitation Assessment of Movement (STREAM – Daley et al., 1997) in 57 participants with stroke. Responsiveness as calculated using Standardized Response Mean (SRM) was assessed between day 14 and 30, day 30 and 90, day 90 and 180, and finally between day 14 and 90. Except for the time-frame between day 90-180, where a small responsiveness was found (SRM < 0.5), all the 3 mobility measures showed a large responsiveness (SRM > 0.8), suggesting that the RMI, the MRMI, and the STREAM were able to detect change.

References

  • Antonucci, G., Aprile, T., & Paolucci, S. (2002). Rasch Analysis of the Rivermead Mobility Index: A study using mobility measures of first-stroke inpatients.
    Arch Phys Med Rehabil, 83, 1442-1449.
  • Berg, K.O., Wood-Dauphinee, S., Williams, J. L., Maki, B. (1989). Measuring balance in the elderly: Validation of an instrument. Physiotherapy Canada, 41(6), 304-311.
  • Butland, R. J., Pang, J., Gross, E. R., Woodcock, A. A., & Geddes, D. M. (1982). Two-, six-, and 12-minute walking tests in respiratory disease. Br Med J (Clin Res Ed), 284(6329), 1607-1608.
  • Chen, H.M, Hsieh, C.L., Lo, S.K., Liaw, L.J, Chen, S.M, Lin, J.H. (2007). The test-retest reliability of 2 mobility performance tests in patients with chronic stroke. Neurorehabil Neural Repair, 21, 347-352.
  • Collen, F.M., Wade, D.T., Robb, G.F., Bradshaw, C.M. (1991). The Rivermead Mobility Index: a further development of the Rivermead Motor Assessment. Int Disabil Stud, 13(2), 50-54.
  • Collin, C., Wade, D. (1990). Assessing motor impairment after stroke: A pilot reliability study. Journal of Neurology, Neurosurgery, and Psychiatry, 53, 576-579.
  • Daley, K., Mayo, N.E., Wood-Dauphinee, S., Danys, I., & Cabot, R. (1997). Verification of the Stroke Rehabilitation Assessment of Movement (STREAM). Physiotherapy Canada, 49, 269-278.
  • Demeurisse, G., Demol, O., & Robaye, E. (1980). Motor evaluation in vascular hemiplegia. European Neurology, 19(6), 382-389.
  • Forlander, D.A. & Bohannon, R.W. (1999). Rivermead Mobility Index: a brief
    review of research to date. Clinical Rehabilitation, 13, 97-100.
  • Franchignoni, F. Tesio, L., Benevolo, E., Ottonelo, M. (2003). Psychometric properties of the Rivermead Mobility Index in Italian stroke rehabilitation inpatients. Clinical Rehabilitation, 17, 273-282.
  • Green, J., Forster, A., & Young, J. (2001). A test-retest reliability study of the Barthel Index, the Rivermead Mobility Index, the Nottingham Extend Activities of
    Daily Living Scale and the Frenchay Activities Index in stroke patients. Disability and Rehabilitation, 23(15), 670-676.
  • Hébert, R., Carrier, R., & Bilodeau, A. (1988). The functional autonomy measurement system (SMAF): description and validation of an instrument for the measurement of handicaps. Age Ageing, 17, 293-302.
  • Hsieh, C.L., Hsueh, I.P., Mao, H.F. (2000). Validity and responsiveness of the
    Rivermead Mobility Index in stroke patients. Scand J Rehab Med, 32, 140-142.
  • Hsueh, I.P, Wang, C.H., Sheu, C.F., Hsieh, C.L. (2003) Comparison of Psychometric
    properties of three mobility measures for patients with stroke. Stroke, 34, 1741-1745.
  • Keith, R. A., Granger, C. V., Hamilton, B. B., Sherwin, F. S. (1987). The Functional Independence Measure: A new tool for rehabilitation. Adv Clin Rehabil, 1, 6-18.
  • Lennon, S. & Johnson, L. (2000). The modified Rivermead Mobility Index: validity and reliability. Disability and Rehabilitation, 22(18), 833-839
  • Lennon, S.M.& Hastings, M. (1996). Key physiotherapy indicators for quality
    of stroke care. Physiotherapy, 82, 655-664.
  • Mahoney, F. I., Barthel, D. W. (1965). Functional evaluation: The Barthel Index. Md State Med J, 14, 61-5.
  • Roorda, L.D., Green, J., De Kluis, K.R.A., Molenaar, I.W., Bagley, P., Smith, J., Geurfs, A.C.H. (2008). Excellent cross-cultural validity, intra-test reliability, and construct validity of the Dutch Rivermead Mobility Index in patients after stroke undergoing rehabilitation. J Rehabil Med, 40, 727-732.
  • Sommerfeld, D.K. & von Arbin, M.H. (2001). Disability test 10 days after acute stroke to predict early discharge home in patients 65 years and older. Clinical
    Rehabilitation
    , 15, 528-534.

See the measure

How to obtain the RMI?

The RMI can be obtained from the studies by Antonucci et al. (2002), Forlander & Bohannon (1998) or Franchignoni et al. (2003). It is also available on the Shirley Ryan Ability Lab website.

Table of contents

Rivermead Motor Assessment (RMA)

Evidence Reviewed as of before: 22-03-2011
Author(s)*: Lisa Zeltzer, MSc OT; Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc; Katie Marvin, MSc; PT Candidate

Purpose

The Rivermead Motor Assessment (RMA) assesses the motor performance of patients with stroke and was developed for both clinical and research use.

In-Depth Review

Purpose of the measure

The Rivermead Motor Assessment (RMA) assesses the motor performance of patients with stroke and was developed for both clinical and research use.

Available versions

The RMA was developed by Lincoln and Leadbitter in 1979.

Features of the measure

Items:

The RMA consists of test items in three sections that are ordered hierarchically, that is, the first items are easier and become increasingly more difficult toward the end of the evaluation.

The three sections test:

  • Gross function (13 items)

(e.g. walking with and without out an aid, negotiating stairs with and without the rail, walking, turning and retrieving an object, and running).

  • Leg and trunk movements (10 items)

(e.g. standing on one leg and flexing the knee in a weight bearing position).

  • Arm movements (15 items)

(e.g. control items such as pronating/supinating the forearm and bouncing a ball, and functional items such as cutting putty, grasping and releasing objects, and tying a bow).

The items are scored as pass or fail. Traditionally, when three consecutive attempts to complete an item are failed within a given subsection, the test is stopped as it is assumed that all subsequent items in the subsection will also be failed, so not all items in the section need to be administered (known as ‘Guttman scaling’). However, recent studies suggest that the hierarchical ordering of the items in all three subscales differ from that proposed by the developers (Adams, Ashburn, Pickering & Taylor, 1997; Adams Pickering, Ashburn & Lincoln, 1997; Kurtais et al., 2009) and as a result, it has been recommended that all items in each of the subscales be administered. In an effort to avoid over-burdening patients and to reduce administration time, the ceiling effect of three consecutive failures should be applied (Kurtais et al., 2009).

For patients with an additional disability, for example, an amputation, the principle of stopping after 3 consecutive errors should not be applied (Lincoln & Leadbitter, 1979).

As an example of the RMA items and Guttman scaling, below are the items for the Gross Function subscale of the RMA.

Can the patient:

1. Sit unsupported (without holding on edge of bed feet unsupported)

2. Transfer from lying to sitting on side of bed (using any method)

3. Transfer from sitting to standing

4. Transfer from wheelchair to chair towards unaffected side (may use hands)

5. Transfer from wheelchair to chair towards affected side (may use hands)

6. Walk 10 meters indoors with an aid (any walking aid, no standby help)

7. Climb flight of stairs independently (any method, may use banister and aid)

8. Walk 10 meters indoors without an aid (no standby help or walking aid)

9. Walk 10 meters, pick up beanbag from floor, turn and carry back (may use aid to walk)

10. Walk outside 40 meters (may use walking aid, no standby help)

11. Walk up and down 4 steps (may use any aid but may not hold on to railing)

12. Run 10 meters (must be symmetrical)

13. Hop on affected leg 5 times on the spot (must hop on ball of foot without stopping to regain balance, no help with arms)

Scoring:

Each item on the RMA is coded 0 or 1, depending on whether the client does the activity according to specific instructions. A score of 0 = a ‘no’ response; a score of 1 = a ‘yes’ response. Each subscale is scored by summing the points allocated for all items within that subscale.

If a patient refuses to perform an item (e.g. out of anxiety), score a ‘0’ for that item.

Time:

The ambulatory client with a recovering upper extremity takes approximately 45 minutes to assess; more severely disabled patients take less time (Lincoln & Leadbitter, 1979).

Subscales:

The RMA has three subscales: Upper Limb/Extremity (‘Arm’); Lower Limb/Extremity (‘Leg’) and Trunk; Gross Function.

Equipment:

  • Block of 20 cm height
  • Pencil
  • Volleyball
  • Tennis ball
  • Piece of paper
  • Fork and knife
  • Plate and container (use box of putty as container)
  • Beanbag
  • Cord
  • Putty
  • Watch with chronometer
  • Non-slip mat

Training:

No specialized training is required to administer the RMA. However, the RMA should be administered by a physiotherapist with knowledge on how to safely manage those with stroke. The RMA is a risky assessment where a patient could fall if not supervised by someone with stroke expertise.

Alternative forms of the Rivermead Motor Assessment

The Rivermead Mobility Index (RMI) (Collen, Wade, & Bradshaw, 1991).

The RMI was developed from the RMA Gross Function subscale. This measure focuses on body mobility and is comprised of a series of 14 questions and one direct observation. The RMI covers a range of activities from turning over in bed to running and has been reported to be a reliable and valid measure of mobility in patients with stroke (Collen et al., 1991; Hsieh, Hsueh, & Mao, 2000).

Client suitability

Can be used with:

  • Patients with acute and chronic stroke.

Should not be used with:

  • In individuals with chronic stroke aged 65 and older, Guttman scaling is only retained with the gross function subscale (Adams, Pickering, Ashburn, & Lincoln, 1997) and therefore should be used with caution in these individuals as they may not be able to perform some of the specific tasks (e.g. a patient with osteo-arthritis may not be able to climb stairs) but may be able to perform subsequent tasks that are deemed more challenging (e.g. walking for an extended period of time).
  • Guttman scaling (i.e. the notion that if the patient agrees with any specific item on the list, they will also agree with all previous questions) may not be appropriate to assess function in the hemiplegic stroke client. This method of test administration is also not appropriate in assessing the kind of loss in function owing to focal lesions that arise in stroke clients, in whom impairment of some function may be unrelated to impairment of other functions

In what languages is the measure available?

The RMA is only available in English (United Kingdom).

Summary

What does the tool measure? Motor performance
What types of clients can the tool be used for? Patients with stroke.
Is this a screening or assessment tool? Assessment
Time to administer The RMA takes approximately 45 minutes to administer to an ambulatory client with a recovering upper extremity (less time with more severely disabled patients).
Versions Rivermead Mobility Index (RMI), developed from the RMA Gross Function subscale.
Other Languages None
Measurement Properties
Reliability Internal consistency:
One study examined the internal consistency of the RMA and reported excellent internal consistency for all subscales of the RMA.

Test-rest:
One study examined the test-rest reliability of the RMA and reported adequate test-retest reliability of the Gross Function subscale and excellent test-retest reliability for the Leg and Trunk, and Arm subscales.

Intra-rater:
No studies have examined the intra-rater reliability of the RMA.

Inter-rater:
One study examined the inter-rater reliability of the RMA and reported that on the Gross Function and Leg and Trunk subscales, there were no significant differences on average scores for all patients across all raters. For the Arm subscale, there was significant difference across raters, attributed to only one of the raters.

Validity Criterion:
Concurrent:
Excellent correlations with the Barthel Index at initial, 1 month and 1 year follow-up.

Predictive:
A low RMA gross motor score at 6 weeks post-stroke has been reported as predictive of failure to walk at 18 months post-stroke.

Construct:
Convergent/Discriminant:
Excellent correlations between the RMA Upper Extremity subscale and the Motricity Index Upper Extremity subscale. Excellent correlations between the RMA and the total score of the Functional Independence Measure (FIM) and with the FIM Motor subscale, and adequate correlations between the RMA and the FIM Cognitive subscale. Excellent correlations between the verbal method of completing the Gross Function subscale of the RMA and the typical performance method of completion.

Floor/Ceiling Effects One study examined the ceiling effect of the Gross Function subscale of the RMA and reported a poor ceiling effect.
Does the tool detect change in patients? Two studies examined the responsiveness of the RMA. The RMA was found it to be responsive to change in clients with stroke and it was reported that a total score difference of plus or minus 3 is likely to represent a clinically relevant change in functional level.
Acceptability The RMA should be used with caution with individuals with chronic stroke aged 65 and older as they may not be able to perform some of the specific tasks but may be able to perform subsequent tasks that are deemed more challenging. Guttman scaling may not be appropriate to assess function in the hemiplegic stroke client or to assess the loss in function owing to focal lesions that arise in stroke clients, in whom impairment of some functions may be unrelated to impairment of other functions.
Feasibility The RMA takes approximately 45 minutes to administer and is typically administered by a physical therapist. The measure is simple to administer and consists of test items in three sections (Upper Limb/Extremity; Lower Limb/Extremity and Trunk; Gross Function) that are ordered hierarchically does not require any formal training or specialized equipment.
How to obtain the tool? Please click here to obtain a copy of the RMA.

Psychometric Properties

Overview

We conducted a literature search to identify all relevant publications on the psychometric properties of the Rivermead Motor Assessment (RMA).

Floor/Ceiling Effects

Williams, Robertson, Greenwood, Goldie, and Morris (2006) examined the concurrent validity of a new measure, the High-Level Mobility Assessment Tool (HiMAT) and the Gross Function subscale of the RMA in 103 patients following traumatic brain injury. The Gross Function subscale of the RMA was found to have a poor ceiling effect, with 51.5% of patients achieving the maximum score.

Reliability

Internal consistency:
Kurtais et al. (2009) investigated the internal consistency of the RMA in 107 patients with stroke. Internal consistency of the RMA, as calculated using Cronbach’s alpha was excellent for all RMA subscales (Gross Function α = 0.93; Leg and Trunk α = 0.88; and Arm α = 0.95).

Test-retest:
Lincoln and Leadbitter (1979) had 7 raters examine 10 patients with acute stroke (4-week interval) and reported adequate test-retest reliability of the Gross Function subscale (r = 0.66), and excellent correlations for the Leg and Trunk, and Arm subscales (r = 0.93, and r = 0.88, respectively) of the RMA.

Inter-rater:
Lincoln and Leadbitter (1979) examined the inter-rater reliability of the RMA by having 7 raters evaluate 7 patients who were administered the RMA by videotape. Analysis of variance (ANOVA) of the scores obtained indicated that for all three subscales, variability between patients was higher than the variability between raters (F tests from ANOVA are reported but no ICCs). On the Gross Function and Leg and Trunk subscales, there were no significant differences on average scores for all patients across all raters. For the Arm subscale, there was significant difference across raters, attributed to only one of the seven raters. Revised scoring instructions were therefore produced for the Arm subscale, but further testing is required.

Validity

Content:

Content validity with Guttman scaling is evaluated on the extent to which total scores predict the number of consecutive items passed. In a study of 51 patients with stroke, critical values for two indices, coefficient of reproducibility and coefficient of scalability, were all exceeded. The results of this study confirm the existence of a valid, cumulative, and unidimentional Guttman scale (Lincoln & Leadbitter, 1979).

Criterion:

Concurrent:
Endres, Nyary, Banhidi, and Deak (1990) administered the RMA and the Barthel Index to 53 patients who presented with a stroke and who took part in a rehabilitation program. Scores on the RMA correlated excellently with scores on the Barthel Index at initial (r = 0.84), 1 month (r = 0.78), and 1 year (r = 0.63) follow-up.

Predictive.
Collin and Wade (1990) reported that a low RMA Gross Motor score at 6 weeks post-stroke was found to be predictive of failure to walk at 18 months post-stroke.

Construct:

Convergent/Discriminant:
Collin and Wade (1990) examined the convergent validity of the RMA with two different tests: the Motricity Index (Collin & Wade, 1990), the Trunk Control Test (Collin & Wade, 1990). They believed the Motricity Index and the Trunk Control Test were the tests requiring comparison, and the RMA was used as the “established” measure. The correlations between the Motricity Index Upper Extremity subscale scores and the RMA Upper Extremity subscale scores across 3 time periods (6, 12, and 18 weeks after stroke) were excellent (r = 0.76, 0.73, and 0.74, respectively).

Soyuer and Soyuer (2005) examined the convergent validity of the RMA with the Functional Independence Measure (FIM – Keith, Granger, Hamilton, & Sherwin, 1987) in 100 patients with ischemic stroke. The assessments were conducted 7-10 days and 3 months post-stroke. At 7-10 days post-stroke, the total score for the RMA had an excellent correlation with the total score on the FIM (r = 0.87) and with the FIM Motor subscale (r = 0.90). The total score of the RMA had an adequate correlation with the FIM Cognitive subscale (r = 0.46). At 3 months post-stroke the total RMA had an excellent correlation with the total score on the FIM (r = 0.88) and with the Motor subscale of the FIM (r = 0.89). The RMA had an adequate correlation with the Cognitive subscale of the FIM (r = 0.52).

Sackley and Lincoln (1990) examined the convergent validity of a verbal method of completing the Gross Function subscale of the RMA with the typical performance method of completion in 49 patients with chronic stroke. An excellent correlation was found between these two methods of administration (r = 0.98).

Kurtais et al. (2009) examined the convergent validity of the RMA with the Functional Independence Measure (FIM) in 107 patients with stroke (mean 5.6 months post-stroke). Assessments were performed at admission and discharge from a rehabilitation unit. The Gross Function and Leg and Trunk subscales of the RMA had excellent correlation with all three sections of the FIM (Motor; Self-Care; and Mobility) on admission and discharge (ranging from 0.702 to 0.865); however, the Arm subscale of the RMA was found to only have adequate correlation with all three sections of the FIM at both admission and discharge from the rehabilitation unit (0.386-0.483).

Known groups:
Endres et al. (1990) administered the RMA to 53 patients with stroke participating in a rehabilitation program. Patients were grouped according to RMA motor deficit scores at entry (RMA score 0-9; 10-15; and >15). Adequate correlations were found between RMA score and infact size at initial (r = -0.52), 1 month (r = -0.47), and 1 year (r = -0.53) follow-up sessions.

Responsiveness

Collen, Wade, and Batshaw (1990) reported that a total score difference of ±3 points in the RMA is likely to represent a clinically relevant change in functional level.

Kurtais et al. (2009) examined the responsiveness of the RMA (adapted for use in a Turkish population) in 107 patients with stroke (mean 5.6 months post-stroke). Assessments were performed at admission and discharge from a rehabilitation unit. The effect size and standard response mean (SRM) were calculated for all three subscales of the RMA (Gross Function; Leg and Trunk; and Arm). Moderate effect size was found for the Gross Function subscale (0.51) and small effect sizes for the Leg and Trunk and Arm subscales (0.45 and 0.38 respectively). The Gross Function, Leg and Trunk and Arm subscales had SRMs of 0.83, 0.86 and 0.60 respectively.

References

  • Adams, S. A., Ashburn, A., Pickering, R. M., Taylor, D. (1997). The scalability of the Rivermead Motor Assessment in acute stroke patients. Clin Rehabil, 11, 42-51.
  • Adams, S. A., Pickering, R. M., Ashburn, A., Lincoln, N. B. (1997). The scalability of the Rivermead Motor Assessment in nonacute stroke patients. Clin Rehabil, 52-59.
  • Barer, D., Nouri, F. (1989). Measurement of activities of daily living. Clin Rehabil, 3, 179-187.
  • Collin, C., Wade, D. (1990). Assessing motor impairment after stroke: A pilot reliability study. Journal of Neurology, Neurosurgery, and Psychiatry, 53, 576-579.
  • Collen, F. M., Wade, D. T., Bradshaw, C. A. (1990). Mobility after stroke: Reliability of measures of impairment and disability. Int Disabil Stud, 12, 6-9.
  • Collen, F. M., Wade, D. T., Robb, G. F., Bradshaw, C. M. (1991). The Rivermead Mobility Index: A further development of the Rivermead motor assessment. Int Disabil Stud, 13, 50-54.
  • Collin, C., Wade, D. (1990). Assessing motor impairment after stroke: a pilot reliability study. J Neurol Neurosurg Psychiatry, 53(7), 576-579.
  • Endres, M., Nyary, I., Banhidi, M., Deak, G. (1990). Stroke rehabilitation: A method and evaluation. International Journal of Rehabilitation Research, 13, 225-236.
  • Hsieh, C-L., Hsueh, I-P., Mao, H-F. (2000). Validity and responsiveness of the Rivermead Mobility Index in stroke patients. Journal of Rehabilitation Medicine, 32(3), 140-142.
  • Keith, R. A., Granger, C. V., Hamilton, B. B., Sherwin, F. S. (1987). The functional independence measure: A new tool for rehabilitation. Adv Clin Rehabil, 1, 6-18.
  • Kurtais, Y., Kucukdeveci, A., Elhan, A., Yilmaz, A., Kalli, T., Sonel Tur, B. et al. (2009). Psychometric properties of the Rivermead Motor Assessment: Its utility in stroke. Journal of Rehabilitation Medicine, 41, 1055-1061.
  • Lincoln, N. B., Leadbitter, D. Assessment of motor function in stroke patients. Physiotherapy, 65, 48-51.
  • Sackley, C., Lincoln, N. (1990). The verbal administration of the gross function section of the Rivermead Motor Assessment. Clin Rehabil, 4, 301-303.
  • Soyuer, F., Soyuer, A. (2005). Ischemic stroke: Motor impairment and disability with relation to age and lesion location (Turkish). Journal of Neurological Sciences, 22(1), 43-49.
  • Streiner, D. L., Norman, G. R. (1989). Health measurement scales: A practical guide to their development and use. Oxford: Oxford University Press.
  • Tyson, S., DeSouza, L. (2002). A systematic review of methods to measure balance and walking post-stroke. Part 1: Ordinal scales. Physical Therapy Reviews, 7, 173-186.
  • Williams, G., Robertson, V., Greenwood, K., Goldie, P., Morris, M. E. (2006). The concurrent validity and responsiveness of the high-level mobility assessment tool for measuring the mobility limitations of people with traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 87(3), 437-442.

See the measure

How to obtain the RMA?

Please click here to obtain a copy of the RMA.

Table of contents

Six-Minute Walk Test (6MWT)

Evidence Reviewed as of before: 07-11-2011
Author(s)*: Mahnaz Hamidzadeh; Lisa Zeltzer, MSc OT
Editor(s): Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc

Purpose

The Six-Minute Walk Test (6MWT) (Butland, Pang, Gross, Woodcock, & Geddes, 1982) is a functional walking test in which the distance that a client can walk within six minutes is evaluated. This test has been used to assess individuals with stroke (Kosak & Smith, 2005), head injury (Rossier & Wade, 2001), and Parkinson’s disease (Garber & Friedman, 2003), as well as pulmonary and cardiac diseases.

Please, refer also to the iWalkAssess app: The latest evidence-informed approach to walking assessment post-stroke (Click for the iWalk Toolkit)

In-Depth Review

Purpose of the measure

The Six-Minute Walk Test (6MWT) (Butland, Pang, Gross, Woodcock, & Geddes, 1982) is a functional walking test in which the distance that a client can walk within six minutes is evaluated. This test has been used to assess individuals with stroke (Kosak & Smith, 2005), head injury (Rossier & Wade, 2001), and Parkinson’s disease (Garber & Friedman, 2003), as well as pulmonary and cardiac diseases.

Available versions

There are 5 versions of walking tests available in the stroke population, the 12-, 6-, 5-, 3-, and 2-Minute Walk Tests. The differences between the 12-, 6-, and 2-Minute Walk Tests are summarized in the table below.

Version of walking test in Stroke Purpose Strength Limitation
12MWT (Kosak & Smith, 2005)
  • To evaluate the level of physical fitness of healthy individuals.
  • Adapted to assess disability in patients with chronic bronchitis.
  • Compared to the 2 and 6MWTs, the 12MWT was the most responsive to change during post-stroke rehabilitation (Kosak & Smith, 2005).
  • Exhausting for patients.
6MWT (Kosak & Smith, 2005)
  • To evaluate exercise tolerance among individuals with respiratory diseases. Derived from the 12 MWT.
  • Easy to administer
  • Better tolerated than 12MWT
  • More reflective of performance in ADLs than the other walking tests (Solway, Brooks, Lacasse & Thomas, 2001)
  • Good measure of endurance
  • Does not assess balance, quality of movement, use of assistive devices and amount of physical assistance needed (Barak & Duncan, 2006)
  • Described as a test of functional capacity, endurance, fatigability and cardiovascular fitness
  • Stroke-specific impairments (ie muscle weakness, spasticity, balance, hemiparesis) may influence distance walked (Barak & Duncan, 2006).
2MWT (Kosak & Smith, 2005)
  • To assess exercise tolerance in chronic air flow limitation.
  • Highly correlated with the 6 and 12 MWTs.
  • A valid measure of self-selected walking speed.
  • The most time efficient.
  • Compared to the 6 and 12 MWTs, the 2MWT was the least responsive to change for stroke over the course of inpatient rehabilitation (Kosak & Smith, 2005).

There are two more adaptations of the 6MWT that have been used in patients with stroke: 3MWT (Sakai, Tanaka, & Holland, 2002), and 5MWT (Teixeira da Cunha-Filho et al., 2003)

Features of the measure

Items:
There are no actual items to the 6MWT.

The 6MWT is a simple test that requires a 100-ft, quiet, indoor, flat, straight rectangular hallway. The walking course must be 30m in length. The length of the 30m corridor must be marked by colored tape at every 3m. The turnaround must be marked with a cone. Some studies have used 20 and 50m corridors.

(American Thoracic Society “ATS (http://ajrccm.atsjournals.org/cgi/reprint/166/1/111?ijkey=58e74d53a3942c7bf82e79d2495f8b944bf3f0c2) statement: guidelines for the six-minute walk test,” 2002).

To prepare for the 6MWT, the client should be encouraged to:

  • Wear comfortable clothing
  • Wear appropriate walking shoes
  • Use their usual walking aides during the test (cane, walker, etc.)
  • Take their usual medications
  • Avoid engaging in vigorous exercise 2 hours prior to testing

To prepare for the 6MWT, clinicians may wish to:

  • Have the client stand and rate their baseline dyspnea and overall fatigue using the Borg scale. The Borg scale is a 15 or 12 grade rating scale of perceived exertion – the client’s perception of physical effort or strain.
  • Pulse oximetery is optional. If it is conducted, baseline heart rate, and oxygen saturation should be measured and recorded.

(“ATS statement: guidelines for the six-minute walk test,” 2002)

According to the American Thoracic Society (ATS) protocol, patients should be instructed in the following way:
“The object of this test is to walk as far as possible for 6 minutes. You will walk back and forth in this hallway. Six minutes are a long time to walk, so you will be exerting yourself. You will probably get out of breath or become exhausted. You are permitted to slow down, to stop, and to rest as necessary. You may lean against the wall while resting, but resume walking as soon as you are able. You will be walking back and forth around the cones. You should pivot briskly around the cones and continue back the other way without hesitation. Now I’m going to show you. Please watch the way I turn without hesitation.”

Demonstrate by walking one lap yourself. Walk and pivot around a cone briskly. Then say:
“Are you ready to do that? I will write down each time you turn around at this starting line. Remember that the object is to walk as far as possible for 6 minutes, but don’t run or jog. Start now or whenever you are ready.”

The patient should be positioned at the starting line. The clinician should stand near the starting line during the test. As soon as the patient starts to walk, the timer should be started.

No conversations should take place during the walk. An even tone of voice should be used when providing the standard phrases of encouragement (see below). The patient should be supervised. The clinician should remain focused and not lose count of the laps.

After the first minute, the patient should be told the following (in an even tone):
“You are doing well. You have 5 minutes to go.”

When the timer shows 4 minutes remaining, the patient should be told the following:
“Keep up the good work. You have 4 minutes to go.”

When the timer shows 3 minutes remaining, the patient should be told the following:
“You are doing well. You are halfway done.”

When the timer shows 2 minutes remaining, the patient should be told the following:
“Keep up the good work. You have only 2 minutes left.”

When the timer shows only 1 minute remaining, the patient should be told the following:
“You are doing well. You have only 1 minute to go.”

Other words of encouragement or body language (eg. to speed up) should not be used.

Please note:

  • Do not provide a “warm-up” period.For at least 10 minutes before the beginning of the test, the client should sit in a chair located near the starting position. During this time, the clinician should review the contraindications (see Client Suitability section of module), the appropriateness of the client’s clothing and shoes, and complete the first part of the worksheet (see below).(“ATS statement: guidelines for the six-minute walk test,” 2002)
    The following elements should be present on the 6MWT worksheet and report:
    Lap counter: __ __ __ __ __ __ __ __ __ __ __ __ __ __ __
    Patient name: ____________________ Patient ID# ___________
    Walk # ______ Tech ID: _________ Date: __________
    Gender: M F Age: ____ Race: ____ Height: ___ft ____in, ____ meters
    Weight: ______ lbs, _____kg Blood pressure: _____ / _____
    Medications taken before the test (dose and time): __________________
    Supplemental oxygen during the test: No Yes, flow ______ L/min, type _____
    Baseline End of Test
    Time ___:___ ___:___
    Heart Rate _____ _____
    Dyspnea ____ ____ (Borg scale)
    Fatigue ____ ____ (Borg scale)
    SpO2 ____ % ____%
    Stopped or paused before 6 minutes? No, Yes, reason: _______________
    Other symptoms at end of exercise: angina, dizziness hip, leg, or calf pain
    Number of laps: ____ (_60 meters) _ final partial lap: _____ meters _
    Total distance walked in 6 minutes: ______ meters
    Predicted distance: _____ meters Percent predicted: _____%
    Tech comments:
    Interpretation (including comparison with a pre-intervention 6MWT).
  • A lap counter (or pen and paper) should be used to note the number of laps that the client is able to walk during the 6 minutes.

Upon completion of the test:

  • Clients should be asked to rate their post walk dyspnea and overall fatigue levels using the Borg scale.
  • The following should be asked: “What, if anything, kept you from walking farther?”
  • If using a pulse oximeter, measure SpO2 and pulse rate from the oximeter and then remove the sensor.
  • The number of laps should be recorded on the worksheet.
  • The total distance walked, rounded to the nearest meter, should be calculated and recorded on the worksheet.
  • The client should be congratulated for good effort and should be offered a drink of water (if not on a liquid restricted diet due to dysphagia).

Scoring:

  • The lap counter or pen and paper should be used to note the number of laps that the patient is able to walk during the 6MWT.
  • Distance walked, and the number and duration of rests during the 6 minutes should be measured.
  • Scores range from 0 meters or feet for patients who are non-ambulatory to the maximum biological limits for normal healthy individuals (approximately 900 meters or 2953 feet).

Time:
Six minutes.

Subscales:
None.

Equipment: (“ATS statement: guidelines for the six-minute walk test,” 2002)

  1. Stopwatch (countdown timer).
  2. Pulse oximeter when indicated (optional).
  3. A chair at the end of track in case patients are tired and wish to rest midway through the test.
  4. Two small cones to mark the turnaround points.
  5. Other safety equipment (source of oxygen, telephone, automated electronic defibrillator).

Training:
There is no need for training of clinicians as long as they comply with the 6MWT protocol.

Alternative forms of the Six-Minute Walk Test

  • 12MWT and 2MWT are also valid and reliable measures in clients with stroke (Kosak & Smith, 2005). The other versions of MWTs that have also been used in a stroke population include the 3MWT and 5MWT.

Client suitability

Can be used with: Patients with stroke (acute, subacute, and chronic)

Other groups tested with this measure:

  • Chronic Obstructive Pulmonary Disease (Steele et al., 2000),
  • Heart failure (Guyatt, Sullivan et al., 1985)
  • Peripheral arterial disease (Montgomery & Gardner, 1998),
  • Fibromyalgia (King et al., 1999; Pankoff, Overend, Lucy, & White, 2000; Pankoff, Overend, Lucy, & White, 2000),
  • Cystic fibrosis (Gulmans, van Veldhoven, de Meer, & Helders, 1996),
  • Renal failure (Fitts & Guthrie, 1995),
  • Elderly individuals ( King, Judge, Whipple, & Wolfson, 2000),
  • Healthy adults (Harada, Chiu, & Stewart, 1999),
  • Individuals with pacemakers (Langenfeld et al., 1990),
  • Transplant candidates with end stage lung disease (Cahalin, Pappagianopoulos, Prevost, Wain, & Ginns, 1995).

Should not be used in: (“ATS statement: guidelines for the six-minute walk test,” 2002; Enright, 2003)

  • Absolute contraindications for the 6MWT include: unstable angina and myocardial infarction (MI) in the previous month.
  • Relative contraindications: resting heart rate> 120, systolic blood pressure (BP) > 180mm Hg, and diastolic BP > 100 mm Hg.
  • Testing should be performed in a location where a rapid appropriate response to emergency is possible.
  • Supplies that must be available in rehabilitation and hospital settings include oxygen, sublingual nitroglycerine, aspirin, and albuterol. A telephone should be in place to enable an emergency call.
  • The clinician should be certified in cardiopulmonary resuscitation with a minimum of basic life support.
  • If a client is on chronic oxygen therapy, oxygen should be given at the standard rate or as directed by a physician or a protocol.
  • Reasons for immediately stopping a 6MWT include the following: (1) chest pain, (2) intolerable dyspnea, (3) leg cramps, (4) staggering, (5) diaphoresis, and (6) pale or ashen appearance. If the test is stopped for any of the above reasons, the patients should sit or lie supine as necessary depending on the severity of events. Based on judgment of clinician, blood pressure, pulse rate, oxygen saturation, and physician evaluation should be obtained.

NOTE: Care should be taken to evaluate safety in ambulation prior to testing to ensure that the patient is safe to walk alone without supervision before the test is chosen as an assessment.

In what languages is the measure available?

No information available.

Summary

What does the tool measure? It is a functional walking test that determines the distance that a client can walk within six minutes.
What types of clients can the tool be used for? Patients with stroke, head injury, Parkinson’s, pulmonary and cardiac diseases, elderly individuals and healthy adults.
Is this a screening or assessment tool? Assessment.
Time to administer 6 minutes
Versions 12MWT, 5MWT, 3MWT, 2MWT
Other Languages Not applicable.
Measurement Properties
Reliability Test-retest:
Four studies examined the test-retest reliability of the 6MWT and reported excellent test-retest reliability (ICC = 0.97 – 0.99).

Intra-rater:
One study examined the intra-rater and inter-rater reliability of the 6MWT and found the test to have adequate intra-rater (ICC = 0.74) and excellent inter-rater (ICC = 0.78) reliabilities.

Validity Criterion:
Concurrent:
– Three studies examined the concurrent validity of the 6MWT and reported excellent correlations with Vo2max gold standard; with five-meter walk velocities for preferred speed and fast speed; and with the Locomotion subscale of the Functional Independence Measure (FIM).
– Two studies reported adequate correlations between the 6MWT and Vo2peak and exercise test duration, and between the 6MWT and the Motor subscale of the FIM and the total FIM.

Predictive:
One study examined the predictive validity of the 6MWT in patients with stroke and found it to be an excellent predictor of mean steps per day.

Construct:
Convergent:
Four studies examined the convergent validity of the 6MWT and found excellent correlations with the 2 MWT, the 5 MWT, the 12 MWT, the Berg Balance Scale, and the Reintegration to Normal Living (RNL) Index as well as an adequate relationship with the Quadriceps Eccentric Paretic Strength.

Does the tool detect change in patients? Six studies have used the 6MWT to demonstrate the effectiveness of various exercise interventions and found an increase in the distance walked ranging from 28.21m to 102.8m post-intervention. One study directly examined the responsiveness of the 6MWT and reported that the 6MWT has a large standardized response mean (SRM), indicating that it is a sensitive measure in clients with stroke.
Acceptability

The 6MWT has been used in acute, sub-acute and chronic stroke populations.
Note: Care should be taken to evaluate safety in ambulation prior to testing to ensure that the patient is safe to walk alone without supervision before the test is chosen as an assessment.

Feasibility The 6MWT requires no specialized training to administer and only simple equipment is required (a stop-watch, Borg Scale, and pulse oximeter when necessary). It is a simple test that required 100-ft, quiet, indoor, flat, straight rectangular hallway. The walking course must be 30m in length and for 30m the length of corridor must be marked every 3m with colored tape.
How to obtain the tool?

Detailed instructions for administration as found in the 6MWT module are sufficient information for administering the 6MWT.

Psychometric Properties

Overview

We conducted a literature search to identify all relevant publications on the psychometric properties of the 6MWT in individuals with stroke.

Floor/Ceiling Effects

The 6MWT is a continuous variable without ceiling effects (Kosak & Smith, 2005).

Reliability

Test-retest:
Eng, Dawson, and Chu (2004) examined the test-retest reliability of the 6MWT in 12 community-dwelling individuals with chronic stroke. The test-rest reliability of the 6MWT was found to be excellent for distance covered in meters (ICC = 0.99) and for the submaximal exercise variable Vo2 (ml/kg.min) (ICC = 0.96).

Flansbjer, Holmback, Downham, Patten, and Lexell (2005) studied the reliability of gait performance tests in 50 men and women with hemiparesis after stroke (chronic stroke). They reported the 6MWT had excellent test-retest reliability (ICC = 0.99) with smallest real differences of 13% (SRD) when compared to the Timed Up & Go, gait speed tests, and stair climbing ascend and descend tests.

Fulk, Echternach, Nof, and O’Sullivan (2008) examined the test-retest reliability of the 6MWT in 37 clients undergoing inpatient rehabilitation post-stroke. Clients were on average 33.7 days post-stroke and a mean age of 66.3 years. Clients were administered the 6MWT twice, with 1-3 days between trials. The 6MWT was found to have excellent test-retest reliability (ICC = 0.97).

Liu, Drutz, Kumar, McVicar, Weinberger, Brooks et al. (2008) investigated whether a practice effect as verified by various criteria including test-retest reliability occurred across 2 trials of the 6-minute walking test on 91 people with stroke. Participants were administered the 6MWT twice with 30-minutes between trials. Test-retest reliability calculated using Intraclass Correlation Coefficients (ICC) was excellent (ICC = 0.98).

Intra-rater & Inter-rater:
Kosak and Smith (2005) examined the inter- and intra-rater reliability of the 6MWT in 18 clients enrolled in an inpatient stroke rehabilitation program (28 ± 34 days post-stroke). The intra-rater reliability was found to be adequate (ICC = 0.74). The inter-rater reliability was also found to be excellent (ICC = 0.78).

Validity

Criterion:
Concurrent:
The 6MWT had an excellent correlation with Vo2 max in patients with stroke (r = 0.66) (Vo2 max is the maximum volume of the oxygen that the body can consume during intense whole body exercise, while breathing air at sea level) (Eng et al., 2004; Pang, Eng, & Dawson, 2005).

Tang, Sibley, Bayley, McIlroy, and Brooks (2006) administered the 6MWT to 36 individuals with stroke (sub-acute) and reported excellent correlations between the 6MWT and the Five Meter Walk Velocity for preferred (r = 0.79), and fast speed (r = 0.82). This suggests that the speed selected by the patient during the 6MWT was strongly related to velocities chosen during the Five Meter Walk Distance (Kelly, Kilbreath, Davis, Zeman, & Raymond, 2003; Tang et al., 2006).

Tang et al. (2006) found an adequate correlation between the 6MWT and both a record of patients’ average oxygen uptake during cardiopulmonary exercise test (Vo2peak) (r = 0.56) and exercise test duration (r = 0.60) in 36 clients with stroke. This suggests that even though the 6MWT may challenge the cardiorespiratory system, it appears to be more strongly influenced by walking speed rather than cardiorespiratory capacity (Tang, Sibley, Bayley, McIlroy, & Brooks, 2006).

Fulk et al. (2008) examined the concurrent validity of the 6MWT using Pearson product moment correlations and Spearman Rank correlation coefficients in 37 clients undergoing inpatient rehabilitation post-stroke. Clients were on average 33.7 days post-stroke and a mean age of 66.3 years. The 6MWT was compared to subscales of the Functional Independence Measure (FIM) (Keith, Granger, Hamilton & Sherwin, 1987). The 6MWT had an excellent correlation with discharge locomotion (walk) FIM scores (Spearman r = 0.69), and with discharge locomotion (walk) + stairs FIM scores (Spearman r = 0.69). The 6MWT had adequate correlations with discharge motor FIM scores (Pearson r = 0.52), and discharge total FIM scores (Pearson r = 0.45).

Predictive:
Fulk, Reynolds, Mondal & Deutsch (2010) examined the predictive validity of the 6MWT and other widely used clinical measures (FMA LE, self-selected gait-speed, SIS and BBS) in 19 patients with stroke. The 6MWT was found to be an excellent predictor of mean steps per day (r = 0.68; P = 0.001). Although gait speed and balance were related to walking activity, only the 6MWT was found to be a predictor of community ambulation in patients with stroke.

Construct:
Convergent:
Kosak and Smith (2005) compared the 2MWT to the 6MWT in 18 clients with stroke. An excellent correlation was found between these two measures (r = 0.997).

Kosak and Smith (2005) compared the 12MWT to the 6MWT in 18 clients with stroke. An excellent correlation was found between these two measures (r = 0.99).

Patterson et al. (2007) administered both the Berg Balance Scale (BBS) (Patterson, Forrester, Rodgers, Ryan, Ivey, Sorkin, et al., 2007) and the 6MWT to 74 clients (43 men, 31 women) with chronic hemiparetic stroke. An excellent relationship was reported between the BBS and the 6MWT (r = 0.69).

Patterson et al. (2007) compared quadriceps eccentric paretic strength to the 6MWT in 74 individuals (43 men, 31 women) with chronic hemiparetic stroke. An adequate relationship was reported between the 6MWTand quadriceps strength (r = 0.57).

Pang, Eng, and Miller (2007) administered the Reintegration to Normal Living Index (RNL) and the 6MWT to 63 clients with chronic stroke. An adequate correlation was reported between these two measures (r = 0.35).

Fulk et al. (2008) examined the convergent validity of the 6MWT by comparing it to the 5MWT in 37 clients undergoing inpatient rehabilitation post-stroke. Clients were on average 33.7 days post-stroke and a mean age of 66.3 years. Using Pearson product moment correlation, the 5MWT and the 6MWT were found to have an excellent correlation (r = 0.89).

Known groups:
Not available.

Responsiveness

The table below summarizes studies that have examined the responsiveness of the 6MWT among individuals with stroke.

Authors Name Type of study Result of Study
(Kosak & Smith, 2005) Cross-sectional N=18 clients with stroke An inpatient stroke rehabilitation program (standard protocol as set out by the American Association of Cardiovascular and Pulmonary Rehabilitation) lasting 3.9 + 2 weeks of observation indicated that the responsiveness to change for the 6MWT as measured by standardized response mean (SRM) score was 1.52. This translates into a 2.4 fold increase in the distance walked by clients enrolled in this rehabilitation program.
(Duncan et al., 1998) RCT, pilot study N=20 clients with stroke The results of an 8-week home-based exercise program indicated a change of 59.4 meters on the 6MWT (mean changes = 195 ft) compared with 34.7 meters (mean changes = 114 ft) following usual care.
(Dean, Richards, & Malouin, 2000) RCT, pilot study N=12 clients with stroke A 4-week exercise class was offered to improve locomotor tasks (Dean et al., 2000). Participants achieved a change of 42.1 meters (SD = 119.0) in the 6MWT compared with only a 4.7 meter change following equal intensity of in upper-extremity (UE) intervention.
(Visintin, Barbeau, Korner-Bitensky, & Mayo, 1998) RCT, N=100 clients with stroke After 6 weeks of treadmill training with body weight support, the mean change in the distance walked in 6 minutes following the intervention was 102.8 meters (SD = 67.4) compared with 58.8 meters (SD = 72.2) in the control group.
(Salbach et al., 2004) RCT, N=91 stroke patients The efficacy of a task-oriented intervention in comparison to usual care in enhancing competence in walking with stroke was evaluated. Clients with a mild, moderate or severe walking deficit at baseline improved an average of 36 (SD = 96), 55 (SD = 56) and 18 m (SD = 23), respectively, in 6MWT performance at post-intervention.
(Duncan et al., 2003) RCT, N=100 stroke patients (Subacute phase) The efficacy of therapeutic exercise for individuals with subacute stroke was compared to usual care. The intervention group improved in 6MWT performance by an average of 28.2 meters (12.52%) more than the usual care group.
(Tanne, Tsabari, Chechik, Toledano, Orion, Schwammenthal, et al., 2008) RCT, N=52 post-minor ischemic stroke Three-month outpatient exercise program. Improvement in exercise capacity in the intervention group in comparison to the control group was demonstrated using the 6MWT (from 444 ± 90 at baseline to 557 ± 99 meters post-intervention in the exercise group; from 438 ± 101 at baseline to 418 ± 126 in the control group).

References

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  • Barak, S., & Duncan, P. W. (2006). Issues in selecting outcome measures to assess functional recovery after stroke. NeuroRx, 3(4), 505-524.
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  • Dean, C. M., Richards, C. L., & Malouin, F. (2000). Task-related circuit training improves performance of locomotor tasks in chronic stroke: a randomized, controlled pilot trial. Arch Phys Med Rehabil, 81(4), 409-417.
  • Duncan, P., Richards, L., Wallace, D., Stoker-Yates, J., Pohl, P., Luchies, C., et al. (1998). A randomized, controlled pilot study of a home-based exercise program for individuals with mild and moderate stroke. Stroke, 29(10), 2055-2060.
  • Duncan, P., Studenski, S., Richards, L., Gollub, S., Lai, S. M., Reker, D., et al. (2003). Randomized clinical trial of therapeutic exercise in subacute stroke. Stroke, 34(9), 2173-2180.
  • Eng, J. J., Dawson, A. S., & Chu, K. S. (2004). Submaximal exercise in persons with stroke: test-retest reliability and concurrent validity with maximal oxygen consumption. Arch Phys Med Rehabil, 85(1), 113-118.
  • Enright, P. L. (2003). The six-minute walk test. Respir Care, 48(8), 783-785.
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  • Flansbjer, U. B., Holmback, A. M., Downham, D., Patten, C., & Lexell, J. (2005). Reliability of gait performance tests in men and women with hemiparesis after stroke. J Rehabil Med, 37(2), 75-82.
  • Fulk, G. D., Echternach, J. L., Nof, L., & O’Sullivan, S. (2008). Clinometric properties of the six-minute walk test in individuals undergoing rehabilitation poststroke. Physiotherapy Theory and Practice, 24(3), 195-204.
  • Fulk, G. D., Reynolds, C., Mondal, S., & Deutsch, J. E. (2010). Predicting home and community walking activity in people with stroke. Arch Phys Med Rehabil, 91, 1582-1586.
  • Garber, C. E., & Friedman, J. H. (2003). Effects of fatigue on physical activity and function in patients with Parkinson’s disease. Neurology, 60(7), 1119-1124.
  • Gulmans, V. A., van Veldhoven, N. H., de Meer, K., & Helders, P. J. (1996). The six-minute walking test in children with cystic fibrosis: reliability and validity. Pediatr Pulmonol, 22(2), 85-89.
  • Guyatt, G. H., Sullivan, M. J., Thompson, P. J., Fallen, E. L., Pugsley, S. O., Taylor, D. W., et al. (1985). The 6-minute walk: a new measure of exercise capacity in patients with chronic heart failure. Can Med Assoc J, 132(8), 919-923.
  • Guyatt, G. H., Thompson, P. J., Berman, L. B., Sullivan, M. J., Townsend, M., Jones, N. L., et al. (1985). How should we measure function in patients with chronic heart and lung disease? J Chronic Dis, 38(6), 517-524.
  • Harada, N. D., Chiu, V., & Stewart, A. L. (1999). Mobility-related function in older adults: assessment with a 6-minute walk test. Arch Phys Med Rehabil, 80(7), 837-841.
  • Keith, R. A, Granger, C. V., Hamilton, B. B., & Sherwin, F. S. (1987). The Functional Independence Measure: a new tool for rehabilitation. In: Eisenberg, M.G. & Grzesiak, R.C. (Ed.), Advances in clinical rehabilitation (pp. 6-18). New York: Springer Publishing Company.
  • Kelly, J. O., Kilbreath, S. L., Davis, G. M., Zeman, B., & Raymond, J. (2003). Cardiorespiratory fitness and walking ability in subacute stroke patients. Arch Phys Med Rehabil, 84(12), 1780-1785.
  • King, M. B., Judge, J. O., Whipple, R., & Wolfson, L. (2000). Reliability and responsiveness of two physical performance measures examined in the context of a functional training intervention. Phys Ther, 80(1), 8-16.
  • King, S., Wessel, J., Bhambhani, Y., Maikala, R., Sholter, D., & Maksymowych, W. (1999). Validity and reliability of the 6 minute walk in persons with fibromyalgia. J Rheumatol, 26(10), 2233-2237.
  • Kosak, M., & Smith, T. (2005). Comparison of the 2-, 6-, and 12-minute walk tests in patients with stroke. J Rehabil Res Dev, 42(1), 103-107.
  • Langenfeld, H., Schneider, B., Grimm, W., Beer, M., Knoche, M., Riegger, G., et al. (1990). The six-minute walk–an adequate exercise test for pacemaker patients? Pacing Clin Electrophysiol, 13(12 Pt 2), 1761-1765.
  • Liu, J., Drutz, C., Kumar, R., McVicar, L., Weinberger, R., Brooks, D., Salbach, N.M. (2008). Use of the six-minute walk test poststroke: Is there a practice effect? Arch Phys Med Rehabil., 89(9), 1686-1692.
  • McGavin, C. R., Gupta, S. P., & McHardy, G. J. (1976). Twelve-minute walking test for assessing disability in chronic bronchitis. Br Med J, 1(6013), 822-823.
  • Montgomery, P. S., & Gardner, A. W. (1998). The clinical utility of a six-minute walk test in peripheral arterial occlusive disease patients. J Am Geriatr Soc, 46(6), 706-711.
  • Pang, M. Y., Eng, J. J., & Dawson, A. S. (2005). Relationship between ambulatory capacity and cardiorespiratory fitness in chronic stroke: influence of stroke-specific impairments. Chest, 127(2), 495-501.
  • Pankoff, B., Overend, T., Lucy, D., & White, K. (2000). Validity and responsiveness of the 6 minute walk test for people with fibromyalgia. J Rheumatol, 27(11), 2666-2670.
  • Pankoff, B. A., Overend, T. J., Lucy, S. D., & White, K. P. (2000). Reliability of the six-minute walk test in people with fibromyalgia. Arthritis Care Re, 13(5), 291-295.
  • Patterson, S. L., Forrester, L. W., Rodgers, M. M., Ryan, A. S., Ivey, F. M., Sorkin, J. D., et al. (2007). Determinants of walking function after stroke: differences by deficit severity. Arch Phys Med Rehabil, 88(1), 115-119.
  • Pearson, O. R., Busse, M. E., van Deursen, R. W., & Wiles, C. M. (2004). Quantification of walking mobility in neurological disorders. QJM, 97(8), 463-475.
  • Rossier, P., & Wade, D. T. (2001). Validity and reliability comparison of 4 mobility measures in patients presenting with neurologic impairment. Arch Phys Med Rehabil, 82(1), 9-13.
  • Sakai, T., Tanaka, K., & Holland, G. J. (2002). Functional and locomotive characteristics of stroke survivors in Japanese community-based rehabilitation. Am J Phys Med Rehabil, 81(9), 675-683.
  • Salbach, N. M., Mayo, N. E., Wood-Dauphinee, S., Hanley, J. A., Richards, C. L., & Cote, R. (2004). A task-orientated intervention enhances walking distance and speed in the first year post stroke: a randomized controlled trial. Clin Rehabil, 18(5), 509-519.
  • Solway, S., Brooks, D., Lacasse, Y., Thomas, S. (2001). A qualitative systematic overview of the measurement properties of functional walk tests used in the cardiorespiratory domain. Chest,119, 256-270.
  • Steele, B. G., Holt, L., Belza, B., Ferris, S., Lakshminaryan, S., & Buchner, D. M. (2000). Quantitating physical activity in COPD using a triaxial accelerometer. Chest, 117(5), 1359-1367.
  • Tang, A., Sibley, K. M., Bayley, M. T., McIlroy, W. E., & Brooks, D. (2006). Do functional walk tests reflect cardiorespiratory fitness in sub-acute stroke? J Neuroeng Rehabil, 3, 23.
  • Teixeira da Cunha-Filho, I., Henson, H., Qureshy, H., Williams, A. L., Holmes, S. A., & Protas, E. J. (2003). Differential responses to measures of gait performance among healthy and neurologically impaired individuals. Arch Phys Med Rehabil, 84(12), 1774-1779.
  • Tanne, D., Tsabari, R., Chechik, O., Toledano, A., Orion, D., Schwammenthal, Y., et al. (2008) Improved exercise capacity in patients after minor ischemic stroke undergoing a supervised exercise training program. IMAJ, 10, 113-116.
  • Visintin, M., Barbeau, H., Korner-Bitensky, N., & Mayo, N. E. (1998). A new approach to retrain gait in stroke patients through body weight support and treadmill stimulation. Stroke, 29(6), 1122-1128.

See the measure

How to obtain the 6MWT:

Detailed instructions for administration as found in this module are sufficient information for administering the 6MWT.

By clicking here, you can access a video showing how to administer the assessment.

Table of contents

Timed Up and Go (TUG)

Evidence Reviewed as of before: 19-08-2008
Author(s)*: Lisa Zeltzer, MSc OT; Geneva Zaino Bsc PT
Editor(s): Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc

Purpose

The Timed Up and Go (TUG) is a screening tool used to test basic mobility skills of frail elderly patients (60-90 years old). The TUG can be used with, but is not limited to, persons with stroke.

In-Depth Review

Purpose of the measure

The TUG is a general physical performance test used to assess mobility, balance and locomotor performance in elderly people with balance disturbances. More specifically, it assesses the ability to perform sequential motor tasks relative to walking and turning (Schoppen, Boonstra, Groothoff, de Vries, Goeken, & Eisma, 1999; Morris, Morris, & Iansek, 2001).

Available versions

The “Get Up and Go” test (the original TUG) was developed by Mathias, Nayak, and Issacs in 1986.

The TUG was published by Podsiadlo and Richardson in 1991 to address the issues of poor inter-rater reliability observed with intermediate scores in the “Get Up and Go”. The TUG incorporates time as the measuring component to assess general balance and function.

Features of the measure

Items:

There are no actual items in the TUG. The individual must stand up from a chair (which should not be leaned up against a wall), walk a distance of 3 meters, turn around, walk back to the chair and sit down – all performed at a comfortable and safe pace (Figure 1). One practice trial is permitted to allow the individual to familiarize him/herself with the task. Timing commences with the verbal instruction “go” and stops when the client returns to seated position. The individual wears their regular footwear and is permitted to use their walking aid (cane/walker) with its use indicated on the data collection form. No physical assistance is given.

Figure 1.

Scoring:

Performance of the TUG is rated on a scale from 1 to 5 where 1 indicates “normal function” and 5 indicates “severely abnormal function” according to the observer’s perception of the individual’s risk of falling (Podsiadlo & Richardson, 1991). The score consists of the time taken to complete the test activity, in seconds.

Steffen, Hacker and Mollinger (2002) reported that on average, healthy individuals between the ages of 60-80 years complete the TUG in 10 seconds or less. Males between the ages of 80-89 years old take on average 10 ± 1 seconds to complete, and women take 11 ± 3 seconds to complete. Formal norms have not yet been established for patients with stroke.

Standardized cut-off scores to predict risk of falling have not yet been established. In one study, a cut-off score of ? 13.5 seconds has been shown to predict falling in community-dwelling frail elders, but this score has not been verified in other studies (Shumway-Cook et al., 2000).

Scoring and interpretation of the TUG
Score Interpretation
< 10s Completely independent

With or without walking aid for ambulation and transfers

< 20s Independent for main transfers

With or without walking aid, independent for basic tub or shower transfers and able to climb most stairs and go outside alone

> 30s Requires assistance

Dependent in most activities

(Adapted from Podsiadlo & Richardson, 1991)

Subscales:

None typically reported.

Equipment:

The TUG does not require any specialized equipment and can therefore be accomplished in community as well as institutional settings.

  • Standard chair with armrests (46cm seat height and 63-65cm armrest height)
  • Tape measure
  • Brightly colored tape or cone to mark off the 3m path 3m path free from obstruction
  • Stopwatch or wrist watch with a second hand to time the performance.

Training:

Minimal training is required to score the test or interpret the results. The assessor should be aware of safety issues during mobility in individuals with stroke.

Time:

The TUG requires 1 to 2 minutes to administer (Finch, Brooks, Stratford, & Mayo, 2002).

Alternative forms of the TUG

  • TUG Cognitive (Shumway-Cook, Brauer, & Woollacott, 2000). In the TUG Cognitive, patients must complete the task while counting backwards from a randomly selected number between 20 and 100.
  • TUG Manual (Lundin-Olsson et al., 1998). In the TUG Manual, patients must complete the task while carrying a full cup of water. Lundin-Olsson et al. (1998) found that frail older adults who had a time difference of greater than 4.5 seconds between the TUG Manual and the TUG were more prone to falls during the following 6 months.

Client suitability

Can be used with:

Patients with stroke

  • The TUG can be administered to geriatric clients ? 65 years old with any diagnosis (e.g. arthritis, stroke, vertigo, Parkinson’s disease, cerebellar disorders and general deconditioning) (Shumway-Cook & Woollacott, 2001; Hayes & Johnson, 2003; Morris et al., 2001).
  • The TUG can also be used with patients ? 18 years old with an acute neurological diagnosis (Shumway-Cook & Woollacott, 2001).
  • Clients must be able to walk approximately 6 meters with or without an assistive device but without the assistance of another person.
  • Clients must have sufficient vision to walk to the 3-meter line.
  • Non-English speakers must receive appropriate translation.

Should not be used in:

  • The TUG is not appropriate for clients with severe cognitive impairments that prevent understanding of the tasks. Rockwood, Awalt, Carver, and MacKnight (2000) found that in cognitively impaired frail elderly individuals, 35.5% were unable to physically perform the test.
  • Severely affected patients such as those who cannot leave a seated position. There may be a floor effect with these patients. Instead, you may wish to consider the Postural Assessment Scale for Stroke Patients (PASS), which was designed as a balance assessment for patients with stroke and is applicable for all patients with stroke, even those with the most severe postural performance (Benaim, Pérennou, Villy, Rousseaux, & Pelissier, 1999).
  • Since the TUG is administered through direct observation of task completion. A proxy respondent cannot complete it.
  • The TUG is a limited measure assessing few aspects of balance. For a more comprehensive measure of balance, the Postural Assessment Scale for Stroke Patients (PASS) (Benaim et al., 1999) or the Berg Balance Scale (Berg, Wood-Dauphinee, Williams, & Maki, 1992) is suggested.

In what languages is the measure available?

Given the simplicity of the instructions, the TUG can be administered in different languages with informal translations (Tremblay, Savard, Casimiro, & Tremblay, 2004).

Summary

What does the tool measure? Basic mobility and balance in frail elderly patients
What types of clients can the tool be used for? Elderly patients (60-90 years old), patients with stroke
Is this a screening or assessment tool? Screening
Time to administer 1-2 minutes
Versions TUG Cognitive, TUG Manual
Other Languages Can be completed in any language
Measurement Properties
Reliability Internal consistency:
No studies have examined the internal consistency of the TUG.

Test-retest:
Out of seven studies examining the test-retest reliability of the TUG.

Intra-rater:
Out of two studies examining the intra-rater reliability of the TUG.

Inter-rater:
Out of five studies examining the inter-rater reliability of the TUG, and one reported no significant difference in scoring between two raters, suggesting high inter-rater reliability.

Validity Content:
Not available.

Criterion:
No gold standard exists.

Predictive:
TUG has been found to predict nursing home placement and risk of falling.

Construct:
Excellent correlations between the TUG and the Older Americans Resources and Services Instrumental Activities of Daily Living Scale (OARS IADL), OARS Activities of Daily Living (OARS ADL), Frailty Scale, Berg Balance Scale, Tinetti Balance Scale, measures of gait speed (one study reported adequate correlation), and 6-Minute Walk Test (6MWT). Adequate correlations with the Barthel Index, Functional Independence Measure, Groningen Activity Restriction Scale, Sickness Impact Profile.

Known groups:
The TUG can distinguish between elderly patients using different ambulatory aids, the presence of cognitive impairment, patients with Parkinson’s disease who were on the medication levodopa and those patients who were not on levodopa, and healthy elderly individuals from patients with stroke.

Does the tool detect change in patients?

In one study, 35.5% of frail elderly individuals with cognitive impairment were unable to physically perform the test, which may be indicative of a large floor effect.

Although the TUG has been developed as a screening ability to detect change. Another study reported that out of a number of gait speed measures, the TUG was the most able to detect change.

Acceptability TUG is a short and simple measure that takes only a few minutes to complete and requires only a few basic movements. The TUG has been found to have less reliability among patients with cognitive impairment.
Feasibility TUG requires no specialized equipment. Although only minimal training is required, the assessor must be aware of safety issues during mobility in individuals with stroke.
How to obtain the tool? The TUG can be obtained by contacting the developer, Diane Podsiadlo, CLSC NDG, 2525 Boulevard Cavendish, Bureau 110, Montreal, QC, H4B 2Y4. Fax: 514-485-6406

Psychometric Properties

Overview

There is a paucity of literature published on the reliability and validity of the TUG in patients with stroke. For the purposes of this review, we conducted a literature search to identify all relevant publications on the psychometric properties of the TUG.

Floor and Ceiling Effects

Rockwood et al. (2000) found that in frail elderly individuals with cognitive impairment, 35.5% were unable to physically perform the test. This may be indicative of the presence of a large floor effect with the TUG.

Reliability

Internal consistency:
Not reported

Test-retest:
Podsiadlo and Richardson (1991) reported excellent test-retest reliability of the TUG in frail elderly patients (ICC = 0.99).

Steffen et al. (2002) administered the TUG to 97 community-dwelling older adults. The test-retest reliability of the TUG was found to be excellent in this population (ICC = 0.97).

Thompson and Medley (1995) examined the test-retest reliability of the TUG in elderly individuals without any health problems and found excellent test-retest correlations ranging from 0.81 to 0.99.

Rockwood et al. (2000) examined the test-retest reliability of the TUG as part of the Canadian Study of Health and Aging. Adequate test-retest reliability was reported for all participants (ICC = 0.56), for individuals without cognitive impairment alone (ICC = 0.50), and for those with cognitive impairment alone (ICC = 0.56). The results of this study are substantially lower than the results of previous studies examining the test-retest reliability of the TUG in elderly patients. The authors suggest this may be due to the fact that unlike other similar studies, they did not exclude medically unstable patients in their study, and further, they did not control for certain factors (e.g. the time and setting in which the TUG was readministered).

Morris et al. (2001) examined the test-retest reliability of the TUG in 12 patients with Parkinson’s disease and 12 subjects without Parkinson’s disease. Patients were videotaped and timed by 2 experienced raters. Three experienced clinicians and 3 inexperienced clinicians later rated the videotape. The test-retest reliability of the TUG was found to be excellent (ranging from r = 0.87 to r = 0.99).

Flansbjer, Holmback, Downham, Patten, and Lexell (2005) assessed the test-retest reliability of the TUG in 50 patients with chronic mild to moderate post-stroke hemiparesis. The patients performed the TUG twice, with 7 days between each evaluation. The test-retest reliability of the TUG was found to be excellent (ICC = 0.96).

Ng and Hui-Chan (2005) administered the TUG to 10 healthy elderly subjects and 10 patients with chronic stroke twice, at the same time of day, on different days within one week. The results showed excellent test-retest reliability for both healthy elderly subjects (ICC = 0.97) and patients with stroke (ICC = 0.95). The results of this study and the previous study by Flansbjer et al. (2005) suggest that the TUG is a reliable measure in patients with stroke.

Intra-rater:
Podsiadlo and Richardson (1991) found that the TUG demonstrated excellent intra-rater reliability in frail elderly individuals (ICC= 0.99).

Schoppen et al. (1999) examined the intra-rater reliability of the TUG in elderly patients with a lower-extremity amputation. Patients performed the TUG for one observer at two different occasions with an interval of two weeks. An excellent Spearman correlation was observed between scores obtained by the same rater on two consecutive visits (r = 0.93).
Note: Caution should be taken in interpreting these findings as the Spearman correlation is not the preferred method of assessing intra-rater reliability and may have produced higher reliability coefficients than a more appropriate analysis.

Inter-rater:
Podsiadlo and Richardson (1991) compared the inter-rater reliability of the TUG, the TUG Manual and the TUG Cognitive using same day comparisons of three raters. Excellent inter-rater reliabilities were found for the TUG (ICC = 0.98), the TUG Manual (ICC = 0.99), and the TUG Cognitive (ICC = 0.99).

Siggeirsdottir, Jonsson, Jonsson, and Iwarsson (2002) examined the inter-rater reliability of the TUG in 31 elderly individuals in a retirement home. No significant difference was found between the two raters (mean difference = 0.04s). The results of this study suggest that the TUG has high inter-rater reliability.

Norén, Bogren, Bolin, and Stenstrom (2001) examined the inter-rater reliability of the TUG in patients with peripheral arthritis. The inter-rater reliability among three physiotherapists was found to be excellent (ICC = 0.97).

Schoppen et al. (1999) examined the inter-rater reliability of the TUG in elderly patients with a lower-extremity amputation. The test was performed for two different observers at different times of the same day. An excellent Spearman correlation was found between the scores of the two observers (r = 0.96), demonstrating the excellent inter-rater reliability of the TUG.
Note: Caution should be taken in interpreting these findings as the Spearman correlation is not the preferred method of assessing inter-rater reliability and may have produced higher reliability coefficients than a more appropriate analysis.

Morris et al. (2001) examined the inter-rater reliability of the TUG using three experienced raters and three inexperienced raters. Each rater viewed the sequence of performances for 12 patients with Parkinson’s disease and 12 comparison patients from videotape. Raters viewed the videotapes independently at least one week after testing. ICCs were excellent for both experienced and inexperienced raters, ranging from r = 0.87 to r = 0.99. The results of this study demonstrate the excellent inter-rater reliability of the TUG in patients with Parkinson’s disease.

Validity

Content:

Not available.

Criterion:

No gold standard exists.

Predictive:
Nikolaus, Bach, Oster, and Schlierf (1996) examined predictors of death, nursing home placement and hospital admission in 135 patients admitted to a geriatric hospital and discharged home. In a logistic regression analysis, baseline TUG scores were found to be an independent predictor for nursing home placement.

Schwartz et al. (1999) found that in a sample of elderly Mexican-American women, those with the best and worst performance on the TUG were more likely to fall than those with moderate performance.

Whitney, Marchetti, Schade, and Wrisley (2004) found that patients with vestibular disorders and a history of falls who scored > 11.1 seconds on the TUG were five times more likely to have reported a fall in the previous 6 months.

Construct:

Convergent/Discriminant:
Rockwood et al. (2000) examined the convergent and discriminant validity of the TUG using Phase 2 data from the Canadian Study of Health and Ageing. Both discriminant validity was assessed by comparing the TUG to other functional assessments including: the Older Americans Resources and Services Instrumental Activities of Daily Living Scale (OARS IADL) and OARS Activities of Daily Living (OARS ADL) (Fillenbaum & Smyer, 1981), the Cumulative Illness Rating Scale (CIRS) (Linn, Linn, & Gurel, 1968), and the Frailty Scale (developed for the Canadian Study of Health and Aging-2) using Spearman correlations. The TUG demonstrated excellent correlations with the OARS ADL for all participants, and with participants with cognitive impairment alone (r = -0.69 and r = -0.72 respectively). The OARS IADL also had excellent correlations with the TUG for all participants and with participants with cognitive impairment alone (r = -0.70 and r = -0.70, respectively). The TUG also had an excellent correlation with the Frailty Scale for all participants (r = 0.60). Some correlations are negative because a high score on the TUG indicates abnormal functioning, whereas a high score on some other measures indicates better performance. The TUG correlated poorly with the CIRS (ranging from r = 0.22 to 0.26).

Berg, Maki, Williams, Holliday, and Wood-Dauphinee (1992) compared scores from clinical measures and laboratory tests of balance and mobility in 31 elderly subjects. An adequate correlation between the TUG and the Barthel Index was reported (r = -0.48). Excellent correlations between the TUG and the Berg Balance Scale (r = -0.76) and between the TUG and the Tinetti Balance Scale (Tinetti, 1986) (r = 0.74) were also observed (some correlations are negative because a high score on the TUG abnormal functioning, whereas a high score on other measures indicates better health).

Podsiadlo and Richardson (1989) examined the convergent validity of the TUG in frail elderly individuals and reported an excellent correlation between the TUG and the Berg Balance Scale (r = -0.72), and an adequate correlation between the TUG and gait speed (r = -0.55) and between the TUG and the Barthel Index (r = -0.51).

Brooks, Davis, and Naglie (2006) examined the construct validity of the TUG, and two other measures of physical performance in 52 frail older individuals. Correlations between the TUG and the Functional Independence Measure (Keith, Granger, Hamilton, & Sherwin, 1987) were adequate at both admission (r = -0.59) and at discharge (r = -0.42). Correlations are negative because a high score on the TUG indicates abnormal functioning whereas a high score on the Functional Independence Measure indicates functional independence.

Schoppen et al. (1999) examined the validity of the TUG by comparing it to the Sickness Impact Profile-68 item scale (de Bruin, Diederiks, de Witte, Stevens, & Philipsen, 1994), and the Groningen Activity Restriction Scale (GARS) (Kempen, Doeglas, & Suurmeijer, 1993) in 32 patients over the age of 60 with unilateral transtibial or transfemoral amputation because of peripheral vascular disease. An adequate Spearman correlation was reported between the TUG and the Groningen Activity Restriction Scale (r = 0.39). The TUG also correlated adequately with the total score of the Sickness Impact Profile (r = 0.40) and mobility control and mobility range (r = 0.46 and 0.36). A poor correlation between the TUG and the subscales of the “psychic autonomy and communication” (r = 0.31), “social behavior” (r = 0.19), and “emotional stability” (r = -0.04) of the Sickness Impact Profile was found. The findings confirm that the TUG is not a reflection of mental functioning.

Noren et al. (2001) administered various assessments of balance to 65 patients with peripheral arthritis and found that the Berg Balance Scale (Berg, Wood-Dauphinee, Williams, & Maki, 1989) and the TUG had an excellent correlation (Spearman’s rho = -0.83). The correlation is negative because a high score on the Berg Balance Scale indicates normal balance, whereas a high score on the TUG indicates abnormal functioning.

Ng and Hui-Chan (2005) administered the TUG to 10 healthy elderly participants and 11 patients with chronic stroke. Spearman correlation analyses were conducted to examine the convergent and discriminant validity of the TUG with various measures. No significant associations between the TUG and spasticity of ankle plantarflexors of both affected and unaffected legs were observed. An excellent correlation between the TUG and the peak plantarflexion torque generated by maximum isometric voluntary contraction (MIVC) of the affected plantarflexors was reported (r = -0.86), however the TUG did not correlate with the other MIVC parameters measured. Excellent negative correlations were found between the TUG and gait velocity in both healthy participants and patients with stroke (r = 0.98 and r = 0.99, respectively). For the other gait parameters, the step lengths of both the affected and unaffected legs had excellent correlations with the TUG (ranged from r = -0.67 to r = -0.80). An excellent correlation was found between the distance covered during the 6-Minute Walk Test (6MWT) (Guyatt et al., 1985) and the TUG (r = -0.96). Some correlations are negative because a high score on the TUG indicates abnormal functioning whereas a high score on other measures indicate a high level of performance.

Flansbjer et al. (2005) examined 6 gait performance tests in patients with mild to moderate post-stroke hemiparesis (Comfortable Gait Speed; Fast Gait Speed, Stair Climbing Ascend; Stair Climbing Descend; 6-Minute Walk Test). They found excellent correlations between the TUG and the other gait performance measures examined twice, 7 days apart, ranging from r = -0.84 to r = -0.92 (these correlations are negative because a high score on the TUG indicates abnormal functioning, whereas a high score on other gait measures indicate normal performance). Taken together with the results from the study by Ng and Hui-Chan (2005), the TUG appears to be a valid measure for use in patients with stroke.

Known groups:
Brooks et al. (2006) examined the construct validity of the TUG in 52 frail older individuals. They found that the TUG could distinguish patients using different ambulatory aids. Berg et al. (1992) found that the TUG was able to distinguish between elderly individuals who walked with an aid (cane or walker) versus those who did not use any walking aid (effect size = 1.02).

Rockwood et al. (2000) examined the validity of the TUG using Phase 2 data from the Canadian Study of Health and Ageing. They reported that cognitively unimpaired clients could perform the TUG faster than cognitively impaired clients (12 seconds versus 15 seconds, on average).

Morris et al. (2001) found that the TUG could distinguish between patients with Parkinson’s disease who were on the medication levodopa and those patients who were not on levodopa when compared to individuals without Parkinson’s disease.

Ng and Hui-Chan (2005) found that the TUG was able to distinguish healthy elderly individuals from patients with stroke (mean time to complete the TUG was 9.1 seconds for healthy individuals and 22.6 seconds for patients with stroke).

Sensitivity and Specificity:

Shumway-Cook, Brauer, and Woollacott (2000) compared the specificity of the TUG in predicting falls in community dwelling older adults. The TUG correctly classified 13/15 fallers (87% sensitivity) and 13/15 nonfallers (87% specificity). These results suggest that the TUG is a sensitive and specific measure for identifying elderly individuals who are prone to falls.

Whitney, Marchetti, Schade, and Wrisley (2004) examined the sensitivity and specificity of the TUG in 103 patient charts of those with vestibular disorders and a history of falls. Sensitivity (80%) and specificity (56%) were calculated for TUG scores of > 11.1 seconds.

Responsiveness

Brooks, Davis, and Naglie (2006) examined the responsiveness of the TUG in 52 frail older individuals. The TUG demonstrated a large responsiveness to an intervention that occurred between admission and discharge with a standardized response mean (SRM) of 1.1.

Flansbjer et al. (2005) examined the responsiveness of the TUG in 50 individuals with stroke. The smallest real difference (SRD), representing the smallest change that indicates a real (clinical) improvement, was small (SRD = 23%). In other words, the TUG can be used to detect clinically relevant small changes.

Salbach and colleagues (2001) examined the most responsive measure of gait speed from a variety of measures in 50 post-stroke patients with gait deficits. The TUG demonstrated significant change from 8 – 38 days post-stroke (SRM = 0.73). However, there were significant difficulties in obtaining scores since not all patients could complete the test at both times. The SRM reported reflects scores for only those subjects who were able to perform the test. The responsiveness of the TUG also varied depending on the group of patients tested. In the moderate group, the TUG was rated the third most responsive tool after the 5-minute Walk Test (5mWT) (maximum pace), and the 5mWT (comfortable pace). In the fast group, the TUG was rated the second most responsive tool after the 5mWT.

References

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  • Berg, K., Wood-Dauphinee, S. L., Williams, J. I., Maki, B. E. (1992). Measuring balance in the elderly: Validation of an instrument. Canadian Journal of Public Health, 83(S2), S7-11.
  • Berg, K.O., Wood-Dauphinee, S., Williams, J. L., Maki, B. (1989). Measuring balance in the elderly: Validation of an instrument. Physiotherapy Canada, 41(6), 304-311.
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  • Steffen, T. M., Hacker, T. A., Mollinger, L. (2002). Age-and gender-related test performance in community-dwelling elderly people: Six-Minute Walk Test, Berg Balance Scale, Timed Up & Go Test, and gait speeds. Phys Ther, 82(2), 128-137.
  • Thompson, M., Medley, A. (1995). Performance of Community Dwelling Elderly on the Timed Up and Go test. Physical and occupational therapy in geriatrics, 13, 17-30.
  • Tinetti, M. E. (1986). Performance-oriented assessment of mobility problems in elderly patients, J Am Geriatr Soc, 34, 119-126.
  • Tremblay, L. E., Savard, J., Casimiro, L., Tremblay, M. (2004). Repertoire des Outils d’Evaluation en Francais pour la Readaptation, Regroupement des intervenantes et intervenants francophones en sante et enservices sociaux de l’Ontario, Ottawa.
  • Whitney, S. L., Marchetti, G. F., Schade, A., Wrisley, D. M. (2004). The sensitivity and specificity of the Timed “Up & Go” and the dynamic gait index for self-reported falls in persons with vestibular disorders. Journal of Vestibular Research, 14(5), 397-409.

See the measure

How to obtain the TUG

The TUG can be obtained by contacting the developer, Diane Podsiadlo, CLSCNDG, 2525 Boulevard Cavendish, Bureau 110, Montreal, QC, H4B 2Y4. Fax: 514-485-6406.

By clicking here, you can access a video showing how to administer the assessment.

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