Rivermead Mobility Index (RMI)
Purpose
The Rivermead Mobility Index (RMI) was developed from the Rivermead Motor Assessment Gross Function subscale
as a means to quantify mobility disability in clients with stroke
, balance, and transfers (Forlander & Bohannon, 1999).
In-Depth Review
Purpose of the measure
The Rivermead Mobility Index (RMI) was developed from the Rivermead Motor Assessment Gross Function subscale
as a means to quantify mobility disability in clients with stroke
, balance, and transfers (Forlander & Bohannon, 1999).
Available versions
The RMI was published in 1991 by Collen, Wade, Robb and Bradshaw and is based on the gross function section of the Rivermead Motor Assessment.
Features of the measure
Items:
The RMI includes fifteen mobility items: 14 self-reported and 1 direct observation (standing unsupported). The 15 items are hierarchically arranged and fulfill Guttmann scaling criteria, suggesting all items are ordered according to ascending difficulty. To clarify, if the client succeeds in completing the most difficult item, this suggests he/she will succeed in easier items. Similarly, failure on an item suggests the client will be unable to complete the remaining more challenging items (Hsieh, Hsueh, & Mao, 2000). However, Franchignoni et al. (2003) identified potential difficulties in the order of the first three scale items. They reported that more patients could perform the third task (sitting balance) than either of the preceding two items (turning over in bed and lying to sitting). Given this, the authors suggested caution in interpreting the RMI as a true hierarchical scale.
The RMI can be administered using self-report or proxy report. It consists of the following 15 questions: (Forlander & Bohannon, 1999; Franchignoni et al. 2003).
- Turning over in bed: Do you turn over from your back to your side without help?
- Lying to sitting: From lying in bed, do you get up to sit on the edge of the bed on your own?
- Sitting balance: Do you sit on the edge of the bed without holding on for 10 seconds?
- Sitting to standing: Do you stand up from any chair in less than 15 seconds and stand there for 15 seconds, using hands and/or an aid, if necessary?
- Standing unsupported: ask client to stand without aid and observe standing for 10 seconds without any aid.
- Transfer: Do you manage to move from bed to chair and back without any help?
- Walking inside (with an aid if necessary): Do you walk 10 meters, with an aid if necessary, but with no standby help?
- Stairs: Do you manage a flight of stairs without help?
- Walking outside (even ground): Do you walk around outside, on pavements, without help?
- Walking inside, with no aid: Do you walk 10 meters inside, with no caliper, splint, or other aid (including furniture or walls) without help?
- Picking up off floor: Do you manage to walk five meters, pick something up from the floor, and then walk back without help?
- Walking outside (uneven ground): Do you walk over uneven ground (grass, gravel, snow, ice, etc) without help?
- Bathing: Do you get into/out of a bath or shower to wash yourself unsupervised and without help?
- Up and down four steps: Do you manage to go up and down four steps with no rail, but using an aid if necessary?
- Running: Do you run 10 meters without limping in four seconds (fast walk, not limping, is acceptable)?
Scoring:
Each item is coded 0 or 1, depending on whether the client can complete the task according to specific instructions. A score of 0 = a ‘no’ response; a score of 1 = a ‘yes’ response. A total score is determined by summing the points allocated for all items. A maximum score of 15 is possible: higher scores indicate better mobility performance. (Franchignoni et al., 2003; Hsueh, Wang, Sheu & Hsieh, 2003).
Time:
The RMI takes 3 to 5 minutes to administer (Hsieh et al., 2000).
Subscales:
None.
Equipment:
Only a pencil and the test are needed.
Training:
None typically reported.
Alternative forms of the Rivermead Mobility Index
Modified Rivermead Mobility Index (MRMI): In 1996, Lennon and Hastings proposed the MRMI to increase the sensitivity
of the RMI. The MRMI includes 8 items on which patients are scored by rater’s direct observation. Scores are based on a 6-point scale and ranges from 0 to 40, where higher scores indicate better performance.
Client suitability
Can be used with:
- Clients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., including those with poor mobility status.
- Clients with head injury or multiple sclerosis.
Should not be used in:
- The RMI should not be administered to clients with severe cognitive impairments due to the 14 self-reported items.
In what languages is the measure available?
English, Italian and Dutch (Franchignoni et al., 2003; Roorda, Green, De Kluis, Molenaar, Bagley, Smith et al. (2008).
Summary
What does the tool measure? | The RMI measures mobility disability in clients with stroke |
What types of clients can the tool be used for? | Clients with stroke |
Is this a screening or assessment tool? |
Assessment |
Time to administer | An average of 3 to 5 minutes. |
Versions | Modified Rivermead Mobility Index. |
Other Languages | Italian and Dutch. |
Measurement Properties | |
Reliability |
Internal consistency Two studies examined the internal consistency coefficient rho. Test-retest: Inter-rater: |
Validity |
Content: One study examined the content validity of the RMI by estimating its coefficient of reproducibility and scalability and confirmed the RMI fulfill the Guttmann scaling criteria. Criterion: Predictive: Construct: |
Floor/Ceiling Effects |
Two studies examined the floor and ceiling effects of the RMI and reported that at earlier phases of the stroke |
Does the tool detect change in patients? |
Three studies have examined the responsiveness |
Acceptability | The RMI should not be administered to clients with severe cognitive impairments due to the 14 self-reported items. |
Feasibility | The administration of the RMI is quick and simple. |
How to obtain the tool? | The RMI can be obtained from the studies by Antonucci et al. (2002), Forlander & Bohannon (1998) or Franchignoni et al. (2003). |
Psychometric Properties
Overview
We conducted a literature search to identify all relevant publications on the psychometric properties of the Rivermead Mobility Index (RMI) in individuals with stroke
Floor/Ceiling Effects
Franchignoni, Tesio, Benevolo, and Ottonello (2003) verified the floor effects for the RMI in 73 individual with sub-acute stroke
was found at admission with 22% of patients scoring 0. When the re-assessment was performed the RMI showed an adequate floor effect
with 9% of patients scoring the minimum score.
Hsueh, Wang, Sheu, and Hsieh (2003) examined floor and ceiling effects for the RMI, the Modified Rivermead Mobility Index (Lennon & Hastings, 1996) and the Stroke
, with 23% of participants scoring 0 and an excellent ceiling effect
of 6% and 1%, respectively as well as an adequate ceiling effect
and an adequate ceiling effect
at all points in time and the ceiling effect
Reliability
Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency.:
Franchignoni et al. (2003) administered the RMI to 73 patients two months following a first ever strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. and found the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the RMI to be excellent, with a Chronbach’s alpha = 0.92.
Roorda, Green, De Kluis, Molenaar, Bagley, Smith et al. (2008) administered the English and Dutch version of the RMI to 420 and 200 clients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., respectively. The internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of both measures was found to be excellent with a reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
coefficient of 0.96 for the English version and of 0.97 for the Dutch version.
Test-retest:
Green, Forster, and Young (2001) evaluated the test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the RMI in twenty-two clients with chronic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Participants were re-assessed with a 1-week interval by the same rater and under the same conditions. Agreement for total scores was investigated using Bland and Altman technique and agreement between items were assessed with kappa statistics. For the RMI total score the agreement was excellent (mean difference = 0.3). Kappa statistics were excellent for turning in bed (kappa = 1.00), walking inside with no aid (kappa = 0.89), walking outside on uneven ground (kappa = 0.83), bathing (kappa = 0.81), and picking objects off the floor (kappa = 0.79), and adequate for stairs (kappa = 0.68), lying to sitting (kappa = 0.64), sitting balance (kappa = 0.64), transfers (kappa = 0.64), walking up and down 4 steps (kappa = 0.67) and walking outside on uneven ground (kappa = 0.49). Kappa values were not provided for the remaining items (sitting to standing, standing unsupported, walking inside with aid, running).
Note: When performing a Bland and Altman analysis, a mean difference close to zero indicates higher agreement between measurements.
Antonucci, Aprile and Paolucci (2002) verified the test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the RMI in 308 clients with subacute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Participants were assessed at admission and discharge from a strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. program of a rehabilitation hospital (the specific time-frame between the two evaluations was not specified). Test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
was calculated using Rasch AnalysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.  It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty. The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
, a type of item-response theory. Rasch AnalysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.  It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty. The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
allows verifying whether the item difficulty is the same across repeated measures. The RMI demonstrated item stability when performed at admission and discharge in that the most difficult and the easiest items remained the same. These findings suggest the RMI scores across testing occasions can be compared.
Chen, Hsieh, Lo, Liaw, Chen, and Lin (2007) examined the test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the RMI in 50 clients with chronic stroke
of the RMI, assessed with the Intraclass Correlation Coefficient (ICC)Intraclass correlation (ICC) is used to measure inter-rater reliability for two or more raters. It may also be used to assess test-retest reliability. ICC may be conceptualized as the ratio of between-groups variance to total variance., was found to be excellent< (ICC = 0.96).
Intra-rater:
No studies have examined the intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
of the RMI.
Inter-rater.
Collen, Wade, Robb, and Bradshaw (1991) estimated the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the RMI in 43 patients either with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (n = 9), head injury (n = 13) or neurosurgery (n =1). Agreement as calculated using the Bland and Altman Technique was excellent (Coefficient of reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
= 2.0/15).
Note: When using the Bland and Altman analysis, the coefficient of reliability
is double the standard deviation and indicates, in this study, that between raters, total scores in the RMI can range a maximum of 2 points out of 15.
Hsueh et al. (2003) assessed the inter-rater reliability
of the RMI in 40 patients with stroke
on individual items was calculated using weighted kappa and the inter-rater agreement of the total score was analyzed with ICC. Inter-rater reliability
on individual items ranged from poor to excellent (weighted kappa = 0.37 to 0.94) and inter-rater agreement on the total score was excellent (ICC = 0.92).
Validity
Content:
Content validity
with Guttman scaling is evaluated on the extent to which total scores predict the number of consecutive items passed. In a study of 38 patients with subacute stroke
Criterion:
Concurrent:
In a study by Hsueh et al. (2003), the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the RMI was examined against the Modified Rivermead Mobility Index (MRMI – Lennon & Hastings, 1996) and the StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. Rehabilitation Assessment of Movement (STREAM – Daley et al., 1997) in 57 individuals with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Correlations were calculated at 4-points in time (14, 30, 90 and 180 days after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.) using Spearman’s rho and Intraclass Correlation Coefficient (ICC)Intraclass correlation (ICC) is used to measure inter-rater reliability for two or more raters. It may also be used to assess test-retest reliability. ICC may be conceptualized as the ratio of between-groups variance to total variance.. Correlations between the RMI and the MRMI were excellent for all time points (rho = 0.78; rho = 0.90; rho = 0.90; rho = 0.93), as well as between the RMI and the STREAM (rho = 0.69; rho = 0.87; rho = 0.82; rho = 0.85). When the ICC was used, adequate correlations between the RMI and MRMI (ICC = 0.50; ICC = 0.59; ICC = 0.53; ICC = 0.55) and between the RMI and STREAM were found (ICC = 0.59; ICC = 0.71; ICC = 0.68; ICC = 0.68) at all times.
Predictive:
Hsieh et al. (2000) estimated the ability of the RMI measured at admission to a rehabilitation program to predict Barthel Index (Mahoney & Barthel, 1965) scores at discharge. Predictive validity
of the RMI measured in 38 patients with acute stroke using Spearman’s rho was excellent (rho=0.77).
Note: In this study, admission scores were obtained on average 24 days after stroke
Sommerfeld & von Arbin (2001) examined whether the RMI, Barthel Index (Mahoney & Barthel, 1965), sensory ability, aphasia
An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person's intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada), type and side of brain lesion, previous stroke
of the RMI was assessed in 115 patients with acute stroke
Hsueh et al. (2003) analyzed if the RMI, the MRMI (Lennon & Hastings, 1996), and the STREAM (Daley et al., 1997) measured at 14, 30 and 90 days after a stroke
Construct:
Collen et al. (1991) estimated the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the RMI with the Barthel Index (Mahoney & Barthel, 1965), the Berg Balance Scale (Berg, Wood-Dauphinee, Williams & Maki, 1989), the 6-Minute Walk Test (Butland, Pang, Gross, Woodcock, & Geddes, 1982), gaitThe pattern of walking, which is often characterized by elements of progression, efficiency, stability and safety.
speed and number of falls in 43 patients either with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (n = 9), head injury (n = 13) or neurosurgery (n =1). Excellent correlations were found between the RMI and the Barthel Index (r = 0.91), gaitThe pattern of walking, which is often characterized by elements of progression, efficiency, stability and safety.
speed (r = 0.82), the Berg Balance Scale (r = 0.67) and the 6-Minute Walk Test (r = 0.63). The RMI and number of falls had a poor correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
(r = 0.30).
Hsieh et al. (2000) assessed the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the RMI by comparing it to the Barthel Index (Mahoney & Barthel, 1965) and the Berg Balance Scale (Berg et al., 1989) in 38 inpatients with subacute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Correlations as calculated using Spearman’s rho were excellent between the RMI and the Barthel Index (rho = 0.70) and between the RMI and the Berg Balance Scale (rho = 0.85).
Franchignoni et al. (2003) evaluated the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the RMI with the motor and cognitive scales of the FIM (Keith, Granger, Hamilton, & Sherwin, 1987), the leg section of the Motricity Index (Demeurisse, Demol, & Robaye, 1980) and with the Trunk Control Test (Collin & Wade, 1990) in 73 patients with subacute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. In this study, the correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
using Spearman’s rho was excellent between the RMI and the Trunk Control Test (rho = 0.89) and the motor scales of the FIM (rho = 0.73), adequate between the RMI and the leg section of the Motricity Index (rho = 0.49), and poor between the RMI and the cognitive scales of the FIM (rho = 0.10).
Hsueh et al. (2003) analyzed the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the RMI by comparing it to the Barthel Index (Mahoney & Barthel, 1965) in 57 participants with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Correlations were calculated using Spearman’s rho at 4-points in time: 14, 30, 90 and 180 days after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Excellent correlations between the RMI and the Barthel Index were found at all times (rho =0.72, rho = 0.88, rho = 0.86, rho = 0.88), respectively.
Roorda et al. (2008) examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the Dutch version of the RMI by comparing it to the Dutch version of the Barthel Index in 91 clients. Correlations as calculated using Spearman’s rho was excellent (rho = 0.84).
Known groups:
No studies have examined the known groups validity
of the RMI.
Responsiveness
Hsieh et al. (2000) assessed the ability of the RMI to detect minimal clinically important differences in 38 individuals with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. In this study, a clinically important difference was defined as an improvement of 3 or more points on the RMI. From admission to discharge, 76% of participants improved by more than 3 RMI points, suggesting the RMI was able to detect a minimal clinically important difference.
Franchignoni et al. (2003) estimated the responsivenessThe ability of an instrument to detect clinically important change over time.
of the RMI. Seventy-three clients with subacute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. were assessed at admission to a rehabilitation centre and then again five weeks later. The RMI demonstrated large responsivenessThe ability of an instrument to detect clinically important change over time.
with an effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
of 0.89.
Hsueh et al. (2003) verified the responsivenessThe ability of an instrument to detect clinically important change over time.
on the RMI, the MRMI (Lennon & Hastings, 1996) and the StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. Rehabilitation Assessment of Movement (STREAM – Daley et al., 1997) in 57 participants with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. ResponsivenessThe ability of an instrument to detect clinically important change over time.
as calculated using Standardized Response MeanThe standardized response mean (SRM) is calculated by dividing the mean change by the standard deviation of the change scores.
(SRM) was assessed between day 14 and 30, day 30 and 90, day 90 and 180, and finally between day 14 and 90. Except for the time-frame between day 90-180, where a small responsivenessThe ability of an instrument to detect clinically important change over time.
was found (SRM < 0.5), all the 3 mobility measures showed a large responsivenessThe ability of an instrument to detect clinically important change over time.
(SRM > 0.8), suggesting that the RMI, the MRMI, and the STREAM were able to detect change.
References
-
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See the measure
How to obtain the RMI?
The RMI can be obtained from the studies by Antonucci et al. (2002), Forlander & Bohannon (1998) or Franchignoni et al. (2003). It is also available on the Shirley Ryan Ability Lab website.