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)
Parties du corps testées Type de test Test Éléments comportementaux notés
Membre supérieur Unilatéral Finger-to-Nose (FTN) Spatial : Stabilité, souplesse, précision
Temporel : Vitesse
Tronc et bras Unilatéral Arm-Trunk Coordination test (ATC) Spatial : Précision, coordination inter-articulations
Membre supérieur (dextérité fine) Unilatéral Finger Opposition (FOT) Spatial : Sélectivité
Temporel : Temps
Coordination inter-membres = les deux membres supérieurs Bilatéral Alternate movements of two upper limbs (ILC-2) Spatial : Compensation
Temporel : Synchronicité/temps
Membre inférieur Unilatéral Lower Extremity MOtor COordination Test (LEMOCOT) Spatial : Souplesse, précision
Temporel : Vitesse
Coordination des quatre membres = membres supérieurs et membres inférieurs Bilatéral Alternate movements of both hands and feet (ILC-4) Temporel : Temps/complexité

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

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

  • Arsenault, A. B., Dutil, E., Lambert, J., Corriveau, H., Guarna, F., Drouin, G. (1988). An evaluation of the hemiplegic subject based on the Bobath approach. Part III. A validation study. Scand J Rehabil Med, 20(1), 13-16.
  • Beckerman, Vogelaar, T. W., Lankhorst, G. J., Verbeek, A. L. (1996). A criterion for stability of the function of the lower extremity in stroke patients using the Fugl-Meyer Assessment Scale. Scand J Rehabil Med, 28, 3-7.
  • Berglund, K., Fugl-Meyer, A.R. (1986). Upper extremity function in hemiplegia: A cross validation study of two assessment methods. Scandinavian Journal of Rehabilitation Medicine, 18, 155-157.
  • Bernspang, B., Asplund, K., Eriksson, S., Fugl-Meyer, A. R. (1987). Motor and perceptual impairments in acute stroke patients: effects on self-care ability. Stroke, 18, 1081-1086.
  • Chae, J., Johnston, M., Kim, H., Zorowitz, R. (1995). Admission motor impairment as a predictor of physical disability after stroke rehabilitation. Am J Phys Med Rehabil, 74(3), 218-223.
  • Chae, J., Bethoux, F., Bohine, T., Dobos, L., Davis, T., Friedl, A. (1998). Neuromuscular stimulation for upper extremity motor and functional recovery in acute hemiplegia. Stroke, 29(5), 975-979.
  • Chae, J., Labatia, I., Yang, G. (2003). Upper limb motor function in hemiparesis: Concurrent validity of the arm motor ability test. Am J Phys Med Rehabil, 82, 1-8.
  • Crow, J.L., Harmeling-van der Wel, B.C. (2008). Hierarchical properties of the motor function sections of the Fugl-Meyer Assessment Scale for people after stroke: a retrospective study. Physical Therapy, 88(12), 1554-1567.
  • Dettmann, M. A., Linder, M. T., Sepic, S. B. (1987). Relationships among walking performance, postural stability, and functional assessments of the hemiplegic patient. Amer J Phys Med, 66, 77-90.
  • De Weerdt, W., Harrison, M. A. (1985). Measuring recovery of arm-hand function in stroke patients: a comparison of the Brunnstrom-Fugl-Meyer test and the Action Research Arm test. Physiother Canada, 37, 65-70.
  • Di Fabio, R. P., Badke, M. B. (1990). Relationship of sensory organization to balance function in patients with hemiplegia. Phys Ther, 70(9), 542-548.
  • Duncan, P. W., Lai, S. M. Keighley, J. (2000). Defining post-stroke recovery: implications for design and interpretation of drug trials. Neuropharmacology, 39(5), 835-41.
  • Duncan, P. W., Propst, M., Nelson, S. G. (1983). Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. Phys Ther, 63(10), 1606-1610.
  • Duncan, P., Richards, L., Wallace, D., Stoker-Yates, J., Pohl, P., and Luchies, C. (1998). A randomized, controlled pilot study of a home-based exercise program for individuals with mild and moderate stroke. Stroke, 29, 2055-2060.
  • Duncan, P. W., Goldstein, L. B., Horner, R. D., Landsman P. B, Samsa, G. P., Matchar, D. B. (1994). Similar motor recovery of upper and lower extremities after stroke. Stroke, 25, 1181-1188.
  • 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