Assessing the Gap Between Current Movement Ability and Preferred Movement Ability as a Measure of Disability

Abstract

Background

If disability is the gap between what an individual can do and what that individual would like to be able to do, then measures that assess only current ability fall short of describing the impact of disability on the individual.

Objective

The aim of this study was to examine a potential measure of disability, the gap between current movement ability and preferred movement ability, as recorded with the Movement Ability Measure (MAM). This investigation was performed by establishing the relationship between self-perceived current ability and other measures and examining the evidence of convergence or divergence between the gap and other measures.

Design

This investigation was a descriptive study.

Methods

Thirty people who had multiple sclerosis and were ambulatory completed the MAM and 18 other measures of bodily function, activity, and participation. Item response theory methods were used to generate logit estimates of average current movement ability and separate abilities in the 6 dimensions of movement on the MAM. Pearson correlations were calculated between estimated abilities from the MAM and scores from measures expected to be associated with these estimated abilities, as well as between the MAM and additional measures in exploratory analyses of relationships.

Results

The average current ability and the separate dimensions correlated moderately to strongly (.5–.8) with many of the measures expected to be related and showed additional moderately strong correlations in exploratory analyses. The average gap between current ability and preferred ability correlated moderately with pain (−.56) and a scale of current ability (.46) but diverged from many of the measures.

Limitations

The limitations of this study included the lack of an intervention to assess the response of the gap to therapy and the use of multiple statistical tests with a small sample.

Conclusions

The evidence supports the convergent validity for current ability on the MAM but mostly the divergence of the gap. Additional research should compare the gap specifically with measures that assess patients' preferences when determining disability.

Determining how best to measure disability necessitates first determining the definition of the term and the consequent purpose for measuring it. Within the classic medical model of disability as the effect of trauma or disease,¹ the purpose of measuring is to determine how far a patient is from “normal” health. When disability is defined as the “inability to engage in any substantial gainful activity,”² the purpose of measuring is to determine who will receive disability insurance benefits. Measurement based on these disability definitions can fit medical or governmental purposes. However, such measurement may not assess what a patient values most or consider “meaningful disability,” which affects what is most critical to a particular patient's abilities and health-related quality of life.³ In this study, we examined a method for measuring disability that incorporates patients' preferences regarding levels of bodily function, activity, and participation. The eventual purpose of such a measure is to help focus rehabilitative efforts.

In a discussion of disability from an individual's perspective, Mitra4(p241) proposed that “an individual is disabled if he or she cannot do or be the things he or she values doing or being.” When this statement is aligned with the terms proposed by the International Classification of Functioning, Disability and Health,⁵ “doing” implies bodily function applied toward the performance or accomplishment of an activity; “being” implies the roles that people assume for participation in life; and what a person “values” is a personal factor that influences choices and satisfaction with bodily function, activity, and participation within that person's environment. From an individual's perspective, then, disability is the gap between what the person has and what the person wants with regard to ability to do or be—in other words, the gap between current bodily function, activity, and participation and preferred bodily function, activity, and participation within the context of the person's life.

Current movement ability and preferred movement ability and the differential (or gap) between them are the descriptions used in the principle tenets of the movement continuum theory of physical therapy; according to the theory, diminishing the size of the gap is the objective of therapeutic efforts.⁶ The deliberate linking of rehabilitation with the constructs of current and preferred abilities and the gap between them ensures that clinicians focus on changing abilities in accordance with patients' preferences. The purpose of measuring the gap, then, is to establish a baseline against which to assess the effectiveness of rehabilitation at narrowing the gap or decreasing the difference between what a patient is able to do or be and what that patient wants to do or be.

Instead of measuring the gap between current ability and preferred ability, previous disability measures^7–10 typically assessed current ability, that is, a person's dependence or difficulty with tasks associated with activity or participation. Current ability was then judged against the ability of a person who is healthy, is independent, or has no difficulty with the specified tasks. The dilemma in using such measures is how to standardize “normal” ability (different for an athlete and a sedentary individual) or determine “meaningful” tasks (questions about housework and gardening may not mean the same for some who are homeless or who live in an apartment, respectively). If disability is considered to be the gap between current ability and preferred ability, then measures that assess only current ability fall short of describing the impact of disability on an individual.

The literature contains several potential choices for assessing disability in terms of differences between current ability and preferred ability. Goal attainment scaling¹¹ and the Patient-specific Functional Scale¹² both facilitate the documentation of progress from current ability toward a patient's goals as expressed by patient-specified tasks. Both show evidence of reliability and validity.^12–19 Neither goal attainment scaling nor the Patient-specific Functional Scale explicitly records any gaps remaining at the end of rehabilitation between outcomes achieved and patient-preferred abilities. In addition, the patient specificity of different tasks in both measures limits their usefulness for comparisons across cases.

The Movement Ability Measure (MAM) (MovementAbility.com),²⁰ which is based on the movement continuum theory,⁶ is a standardized measure designed to assess the gap between self-perceived current movement ability and preferred movement ability. Respondents using the MAM designate which of 6 levels of movement they now have and which level they would like to have for 24 items across 6 dimensions of movement. The dimensions of movement are flexibility, strength, accuracy, speed, adaptability, and endurance.²¹ The dimensions of the MAM align with the constructs of bodily function, and the items assess the ability to perform normal activities or to participate in highly physical or competitive work, sports, or leisure activities. The Appendix shows 2 items from the MAM.

Investigation of the MAM has resulted in evidence of both reliability and validity in adults who are healthy and in people entering an episode of outpatient physical therapy.²⁰ Outpatients at physical therapy clinics have shown an average decrease in the size of the gap between current movement ability and preferred movement ability with physical therapy,²² and the progress that they showed through changes in MAM responses corresponded to their clinicians' characterization of successful versus partially successful therapy episodes.²³ In addition, evidence has supported the concurrent and convergent validity of average current ability on the MAM (across all dimensions) with other self-report indicators of health and movement problems²⁰ as well as the construct validity and clinical utility of the gap between current ability and preferred ability.²² To date, however, the MAM has not been compared with the actual performance of movement by people.

The performance of movement logically relates to the construct of self-perceived current movement ability, although differences in self-perception will affect the strength of the association. Many performance-based measures associated with the 6 dimensions of movement could provide data that might converge with MAM responses regarding current ability.²¹ In contrast, few standardized measures document a person's preferred movement ability, and no other measure provides for a calculation of the gap between current movement ability and preferred movement ability. The lack of suitable comparison measures restricts the degree of convergence expected. We assume, however, that people prefer less pain or discomfort and that higher overall health-related quality of life relates to a smaller gap between current movement ability and preferred movement ability. Patterns of convergence or divergence with various measures of movement, discomfort, and quality of life might provide insight into the use of the gap between current movement ability and preferred movement ability as a measure of disability.

To investigate the relationship between MAM responses and actual performance, we chose to examine people with multiple sclerosis (MS) because they can show deficits in any of the 6 dimensions of movement. Demyelination in MS impairs the conduction of neural impulses in multiple locations throughout the central nervous system. Multiple sclerosis is the most common progressive neurologic disease in young adults,²⁴ affecting approximately 2.5 million people worldwide. The prevalence of balance and mobility deficits in people with MS is 84% to 97%.^25,26 Most people with MS remain ambulatory for an average of 20 years after diagnosis,²⁶ resulting in an extended period of time to function with some form of balance or mobility deficit but with a disease-specific possibility of further degeneration at any time. Thus, people with MS may have an interesting perspective on current and preferred abilities.

The purpose of this study was to examine the gap between current movement ability and preferred movement ability, as recorded with the MAM, as a potential measure of disability. First, we established the relationship between self-perceived current ability and scores from performance-based and other self-report measures in people with MS who were ambulatory. Second, we examined the convergence or divergence between the gap and other measures. The hypotheses were that average current ability (across all dimensions), as recorded with the MAM, would correlate significantly with activity and participation measures, that ability in the 6 dimensions of movement on the MAM would correlate with measures of bodily function and their associated activities, and that the gap between current movement ability and preferred movement ability would correlate with measures indicating patient-valued differences between abilities and desires.

Method

This investigation was a descriptive study, conducted as part of a cross-sectional study aimed at determining factors that contribute to walking difficulty in people with MS.

Participants

All participants were recruited from clinics and the National Multiple Sclerosis Society in the greater St Louis, Missouri, area. All participants provided informed consent.

Participants were included if they had a diagnosis of MS, including relapsing-remitting, secondary progressive, and primary progressive types; were 18 to 65 years old; had minimal to moderate deficits, as evidenced by an Expanded Disability Status Scale (EDSS)⁷ score ranging from 0.0 to 6.0; and, for those with relapsing-remitting MS, had not had an exacerbation requiring clinical intervention for at least 6 months. Participants were excluded if they had lower-extremity orthopedic conditions that limited ambulation or if they were pregnant.

Procedure

A study neurologist administered the EDSS when the participants volunteered for the study to determine eligibility for participation. Participants completed multiple measures of bodily function, activity, and participation. Data were collected during 2 testing sessions, with a mean interval of 8.0 (SD=4.1) days between sessions. All measures except the strength assessment with a Biodex System IV dynamometer (Biodex Medical Systems, Shirley, New York) were completed during the first testing session. The MAM is described elsewhere.²⁰ The other measures are briefly described here.

Measures of bodily function included measures of the presence and severity of spasticity, weakness, somatosensory loss, ataxia, and pain.

Spasticity.

The Modified Ashworth Scale (MAS)²⁷ was used to record the spasticity of the hip adductor, knee flexor, knee extensor, and ankle plantar flexor muscles. Scores on the MAS range from 0 to 4, with higher scores indicating greater spasticity. Because the MAS includes a score of 1+, the MAS scores for each muscle group were transformed into a 6-point ordinal scale ranging from 0 to 5, where a score of 1+ was equivalent to a score of 2.²⁸ The values for the muscle groups in each leg were averaged to produce a composite MAS score for the right and left lower extremities. The frequency of scores was also documented.

Weakness.

A handheld dynamometer (Lafayette Instrument Co, Lafayette, Indiana) was used to measure maximal isometric force using standard manual muscle testing positioning.²⁹ The muscle groups tested were the hip flexor, hip extensor, hip abductor, knee extensor, knee flexor, and ankle dorsiflexor. Three discrete trials of maximal isometric force production (in pounds) were collected for each muscle group and converted to newtons for subsequent analysis. The mean maximal isometric force (in newtons) for each muscle group was calculated, and the values for the muscle groups and legs were summed to produce a composite value for analysis. The Standing Heel-Rise Test³⁰ was used to assess plantar-flexion strength. The number of heel-rises for each lower limb was recorded, and the values were averaged to produce a mean value for analysis.

A Biodex System IV dynamometer was used to measure the maximal voluntary isometric torque (MVIT) of the knee extensor and flexor, dorsiflexor, and plantar flexor muscles.³¹ The MVIT for the knee was collected with the participants in a seated position with the knee in 60 degrees of flexion. The MVIT for the ankle was collected with the participants in a supine position with the knee in full extension and the ankle in 0 degrees of dorsiflexion. All participants were provided an opportunity to become familiar with the performance requirements for the tasks by performing submaximal isometric contractions. For each muscle group, participants performed 3 discrete trials at maximal torque. There was a 1-minute rest period between the 5-second trials. Torque values (ft-lb) were corrected for the effects of gravity and the weight of the limb and were converted to newton-meters for subsequent analysis. The mean MVIT (in newton-meters) for each muscle group was calculated, and the values for the muscle groups were summed to produce a composite MVIT value for analysis.

Somatosensory loss.

A 5-piece Semmes-Weinstein monofilament set (2.83, 3.61, 4.31, 4.56, and 6.65 log forces) (North Coast Medical Inc, Morgan Hill, California) was used to assess the light touch sensation threshold at 5 locations on each lower limb.³² Filament 2.83 is considered to represent “normal” sensitivity in most areas of the body, and filament 6.65 is considered to represent a loss of protective sensation.³³ The smallest monofilament sensed at each location was recorded and given an ordinal score based on a previously described scale.^28,34 The values for each site for each limb were averaged to produce a composite light touch sensation score for the right and left lower limbs, where a score of 0 represented normal somatosensation of the lower limb and a score of 4 represented marked somatosensory loss (eg, the ability to sense only deep pressure at each location). A 128-Hz Rydell-Seiffer tuning fork was used to assess the vibration perception threshold of each great toe.³⁵ The tuning fork values range from 0 to 8, representing maximal to minimal vibration of the tuning fork, respectively. At the great toe, vibration perception threshold values greater than or equal to 4.5 are considered normal for adults younger than 40 years old, and values greater than or equal to 4.0 are considered normal for adults 41 to 60 years of age.³⁵

Ataxia.

The Scale for the Assessment and Rating of Ataxia (SARA) was used to measure the severity of ataxia.³⁶ The SARA has 8 items that yield a total score of 0 (no ataxia) to 40 (most severe ataxia): gait, stance, sitting, speech disturbance, finger chase, nose-finger test, fast alternating hand movements, and heel-shin slide. Limb kinetic functions (items 5–8) are rated independently for both sides, and the arithmetic mean of both sides is included in the SARA total score.³⁶

Pain.

The Faces Numeric Pain Scale was used to rate pain on the day of testing.³⁷ With this scale, people rate pain by choosing cartoon faces and numeric values. The scale ranges from 0 (“no pain”) to 10 (“hurts worst”).

Activity-level measures included assessments of walking, balance, and accidental falls.

Walking.

Walking endurance was assessed with the Six-Minute Walk Test.³⁸ The distance walked each minute and the total distance walked were recorded. The 25-Foot Timed Walk Test was used to assess maximal walking speed.³⁹ The command was as follows: “Walk as fast as you can but safely.” The time to walk 25 ft (7.69 m) was recorded for 2 trials, and the average time for the 2 trials was used for analysis. The 12-item Multiple Sclerosis Walking Scale (MSWS-12) was used to assess self-perceived limitations in walking due to MS.⁴⁰ The scores on the 12 items were summed to generate a total score and transformed into a scale with a range of 0 to 100, where higher scores indicated greater self-perceived walking problems due to MS.

Balance.

The Berg Balance Scale (BBS),⁴¹ the Dynamic Gait Index (DGI),^42–44 and the Four-Square Step Test (FSST)⁴⁵ were used to assess balance. The BBS is a standardized scale of standing balance that rates performance on 14 different tasks examining an individual's ability to sit, stand, reach, maintain single-leg stance, and turn. The score on the BBS ranges from 0 to 56 points, where a score of 56 indicates normal standing balance. The DGI is a standardized scale of dynamic balance and mobility function that rates performance on 8 different tasks, including walking, walking with head turns, pivoting, walking over objects, walking around objects, and going up stairs. The score on the DGI ranges from 0 to 24 points, where a score of 24 indicates normal dynamic balance. The FSST is a standardized clinical tool used to assess dynamic balance. The FSST requires an individual to step forward, backward, and rapidly to the right and left over a low obstacle while the time to complete the test is measured. The better time from 2 timed trials was used for analysis.

Accidental falls.

Participants self-reported the number of falls that occurred during the 12 months immediately preceding participation in the study.

Standardized, self-report questionnaires were used to document participation and personal factors. Participation-level measures included assessments of health-related quality of life, the impact of some aspect of the disease on participation, and assessments of multiple dimensions targeting bodily function and activity constructs as well as participation. The measure of personal factors was an assessment of self-confidence.

Participation.

The 54-item Multiple Sclerosis Quality of Life Scale (MSQOL-54) was used to assess multiple dimensions of health-related quality of life.⁴⁶ Scores on 4 MSQOL-54 subscales (pain, health distress, quality of life, and physical function) and the physical health composite scale were calculated and used for analysis. Scores on each MSQOL-54 subscale ranged from 0 to 100, where a higher score indicated greater self-perceived limitations in health-related quality of life.

The Modified Fatigue Impact Scale (MFIS) was used to self-assess fatigue. The MFIS is a 21-item questionnaire that provides an assessment of the effects of fatigue on physical, cognitive, and psychosocial functioning.^47,48 Scores on the 21 items were summed to generate a total score. Scores on the MFIS ranged from 0 (no impact of fatigue) to 84 (severe impact of fatigue).

Personal factors.

The Activities-specific Balance Confidence Scale was used to assess the self-perceived level of confidence in maintaining balance while performing 16 activities of daily living.⁴⁹ Each task was rated with an 11-point scale consisting of whole numbers from 0 to 10. The scores for each task were summed, and the result was divided by 16 to generate percent confidence (0%–100%) in maintaining balance.

Data Analyses

Responses on the MAM were analyzed with item response theory methods and ConQuest software.⁵⁰ Other sources provide an overview of item response theory methods and the associated terminology.^51–53 The responses of all participants to the 24 items on the MAM were used to estimate the probabilities and the natural log of the odds (logits) of each participant responding in a particular way to these items. The estimated logit values (with associated standard errors) designated the location of each participant on an interval scale for each movement ability dimension. Analyses were performed with a multidimensional model,⁵⁴ anchoring item locations on those determined from a multidimensional analysis of 318 respondents representing a broad range of movement abilities.²¹ The average logit value for the 6 dimensions was used as the average current movement ability. The gap between current movement ability and preferred movement ability was calculated by subtracting the logit value for current ability from the logit value for preferred ability.²²

Although the MAM logit values were on an interval scale, many of the measures used in this study were on ordinal scales. Our sample of 30 participants was not sufficiently large to generate stable item locations with item response theory methods, and larger samples on which to anchor item locations for these scales were not accessible. For this descriptive study, scales were treated as continuous.

Once current ability and the gap between current ability and preferred ability were determined from the MAM, statistical analyses included calculations (with Microsoft Excel, Microsoft Corp, Redmond, Washington; SPSS, SPSS Inc, Chicago, Illinois; and PSPP, Free Software Foundation Inc, Boston, Massachusetts) of Pearson correlations between current ability and other measures and between the gap and other measures. Measures that were expected to be related to average current ability, each of the separate movement dimensions, and the average gap are shown in Table 1.

Table 1.

Measures Expected to Have Significant Relationships With Movement Ability Measure Responses^a

^aEDSS=Expanded Disability Status Scale, SARA=Scale for the Assessment and Rating of Ataxia, MFIS=Modified Fatigue Impact Scale, MSQOL-Pain=pain subscale of the 54-item Multiple Sclerosis Quality of Life Scale (MSQOL-54), ABC=Activities-specific Balance Confidence Scale, MSQOL-QOL=quality-of-life subscale of the MSQOL-54, MSWS-12=12-item Multiple Sclerosis Walking Scale, MSQOL-HD=health distress subscale of the MSQOL-54, MSQOL-PHC=physical health composite scale of the MSQOL-54.

^b As measured with a Biodex System IV dynamometer.

^c The Faces Numeric Pain Scale was originally intended to be analyzed against the average gap, but the participants in the present study had a minimal range of scores on this measure; therefore, the MSQOL-Pain was substituted for analysis.

Within each dimension and for the average current ability and the average gap, the family-wise alpha value was set at .05. Because several measures were examined for their relationship with the MAM, the Bonferroni correction was applied. This procedure resulted in significance levels set at P=.01 for the average current ability (with 5 measures expected to show a relationship), P=.0125 for the average gap (when 4 measures were examined), and P=.017 (when 3 measures were examined) and P=.025 (when 2 measures were examined) for the separate movement dimensions. Other associations were also examined in exploratory analyses, with the significance level set at P=.005 for up to 10 different measures examined. Significant correlations were also examined with scatterplots to determine whether 1 or 2 outliers unduly magnified the strength of the correlations.

Role of the Funding Source

Dr Wagner was supported by a grant (K12 HD055931) from Comprehensive Opportunities in Rehabilitation Research Training (CORRT) through the National Center for Medical Rehabilitation Research at the National Institute of Child Health and Human Development and the National Institute of Neurological Disorders and Stroke.

Results

Thirty people with MS were tested. Demographic data are shown in Table 2. Data from the MAM and other tests and measures are summarized in Table 3.

Table 2.

Demographic Data for 30 Participants With Multiple Sclerosis (MS)

^a Reported as mean (standard deviation), range.

^b Reported as number (percentage) of participants unless noted otherwise.

Table 3.

Summary of Data Collected from Participants With Multiple Sclerosis (MS)

^a SARA=Scale for the Assessment and Rating of Ataxia, MSWS-12=12-item Multiple Sclerosis Walking Scale, MSQOL-Pain=pain subscale of the 54-item Multiple Sclerosis Quality of Life Scale (MSQOL-54), MSQOL-HD=health distress subscale of the MSQOL-54, MSQOL-QOL=quality-of-life subscale of the MSQOL-54, MSQOL-PF=physical function subscale of the MSQOL-54, MSQOL-PHC=physical health composite scale of the MSQOL-54, ABC=Activities-specific Balance Confidence Scale.

^b Gap values for separate dimensions were not analyzed for correlations with other measures.

^c Frequency: 8 had spasticity score of 0 in all muscle groups tested, 8 had spasticity scores of ≤2 in 1 or 2 muscle groups of 1 leg, 9 had spasticity scores of ≤2 in both legs or in more than 2 muscle groups of 1 leg, and 5 had spasticity scores of ≥3 in at least 1 muscle group.

^d Sum of handheld dynamometry values for right and left hip, knee, and ankle.

^e Sum of torque values obtained with a Biodex System IV dynamometer for right and left knee and ankle.

Some participants did not complete all of the assessments. Six participants (20%) did not complete the handheld dynamometer assessment of strength or the assessment of light touch sensation because of time constraints. Four participants (13%) did not complete the clinical assessment of balance because this assessment was added to the protocol after their participation in the study. Three participants (10%) declined to answer questions related to sexual function on the MSQOL-54. One participant (3%) did not complete the Biodex assessment of ankle strength because of limited ankle range of motion. The participants who did not complete all of the tests did not differ from the remaining participants in age, body mass index, or overall clinical functional ability, as measured with the EDSS (Mann-Whitney U test; P>.05).

The use of item response theory methods to analyze MAM responses resulted in average standard errors of 0.90 to 1.33 logits for the movement abilities in the different dimensions. This result means that individual differences of more than 2.7 logits in individual dimension abilities indicated differences exceeding those that could be expected from measurement error. The association between logit values and raw scores on the MAM is described elsewhere.²⁰

Individual participants varied in their patterns of MAM responses. Figures 1, 2, and 3 show movement ability plots for 3 participants. Participant 16 had an average gap of 6.70 logits between responses for self-perceived movement ability “now” and responses for the movement ability that this participant “would like” to have. Movement ability “now” for this participant (Fig. 1) was lower than that for the other 2 participants (Figs. 2 and 3). The largest gap for participant 16 was observed in the movement dimension speed, with a logit value of 9.01. Participant 26 had an average gap of 4.53 logits—smaller than the values for the other 2 participants. Participant 28 had an average gap of 6.00 logits even though this participant's movement ability “now” (average current ability=3.66 logits) was similar to the movement ability that participant 16 “would like” to have (average preferred ability=4.07 logits). Pearson correlations between MAM responses and other measures are shown in Table 4.

Figure 1.

Movement ability plot (MAP) based on self-report with the Movement Ability Measure for participant 16. The scale for all axes of the MAP is based on the range of logits (−10 to 10) displayed in the population on which the sample was anchored.

Figure 2.

Movement ability plot (MAP) based on self-report with the Movement Ability Measure for participant 26. The scale for all axes of the MAP is based on the range of logits (−10 to 10) displayed in the population on which the sample was anchored.

Figure 3.

Movement ability plot (MAP) based on self-report with the Movement Ability Measure for participant 28. The scale for all axes of the MAP is based on the range of logits (−10 to 10) displayed in the population on which the sample was anchored.

Table 4.

Pearson Correlations (P Values) for Movement Ability Measure Dimensions and Specified Measures^a

^aValues in bold type represent correlations with measures expected to have significant relationships with Movement Ability Measure responses. Values in italic type represent correlations with measures or subscale scores resulting from exploratory analyses.

^b EDSS=Expanded Disability Status Scale, ABC=Activities-specific Balance Confidence Scale, MSWS-12=12-item Multiple Sclerosis Walking Scale, MSQOL-PHC=physical health composite scale of the 54-item Multiple Sclerosis Quality of Life Scale (MSQOL-54), SARA=Scale for the Assessment and Rating of Ataxia, MFIS=Modified Fatigue Impact Scale, MSQOL-Pain=pain subscale of the MSQOL-54, MSQOL-HD=health distress subscale of the MSQOL-54, MSQOL-QOL=quality-of-life subscale of the MSQOL-54, MSQOL-PF=physical function subscale of the MSQOL-54.

^c The Faces Numeric Pain Scale was originally intended to be analyzed against the average gap, but the participants in the present study had a minimal range of scores on this measure; therefore, the MSQOL-Pain was substituted for analysis.

Average Current Ability

Average self-perceived current ability correlated fairly strongly (r=.65–.83) with other self-report measures (MSWS-12, Activities-specific Balance Confidence Scale, MFIS, MSQOL-54 physical health composite scale score, MSQOL-54 physical function subscale score, and MSQOL-54 pain subscale score) and moderately (r=−.56, P=.001) with self-reported falls. Average current ability correlated fairly strongly with the EDSS (r=−.62) and showed a nonsignificant correlation with the BBS (r=.40).

Flexibility and Adaptability

Self-perceived flexibility did not correlate with spasticity, as measured with the MAS. Self-perceived adaptability did not correlate with sensory loss, as measured with the Semmes-Weinstein light touch sensation scores or the tuning fork vibration scores. However, adaptability and flexibility did correlate with the DGI (r=.64 for both) and with the Six-Minute Walk Test (r=.51 and .70, respectively). Flexibility also correlated with the FSST and handheld dynamometry but not significantly with the 25-ft timed walk (r=−.46).

Strength and Accuracy

Self-perceived strength correlated, as expected, with the number of heel-rises performed and the composite values obtained by handheld dynamometry but not with peak torque. Strength and accuracy correlated significantly with the Six-Minute Walk Test (r=.55 and .54, respectively). Self-perceived accuracy correlated with the FSST, the DGI, and the SARA total score. Further examination of the individual items of the SARA revealed mixed results for accuracy, with r=−.62 (P=.000) for stance but lower, nonsignificant correlations with the values for the other SARA items.

Speed and Endurance

Self-perceived speed correlated with the Six-Minute Walk Test but not with the 25-ft timed walk. Exploratory analyses revealed correlations of speed with the FSST, the DGI, and the composite handheld dynamometry values. Self-perceived endurance correlated significantly with the Six-Minute Walk Test and the MFIS, as expected. Exploratory analyses revealed correlations of endurance with the physical health composite scale of the MSQOL-54, handheld dynamometry, and the DGI.

Average Gap Between Current Movement Ability and Preferred Movement Ability

The gap between current movement ability and preferred movement ability showed significant correlations with the EDSS (r=.46, P=.011) and the pain subscale of the MSQOL-54 (r=−.56, P=.001) but showed only low and nonsignificant correlations with the health distress and quality-of-life subscales of the MSQOL-54. Exploratory analyses revealed nonsignificant correlations with the physical health composite scale of the MSQOL-54, falls, the MSWS-12, and the MFIS.

The correlation of self-perceived current ability with the social function subscale of the MSQOL-54 was r=.60; that for the gap with this subscale was r=−.34. The correlation of self-perceived current ability with the emotional well-being subscale of the MSQOL-54 was r=.24; that for the gap with this subscale was r=−.08. Similarly, the correlation of self-perceived current ability with the role–physical subscale of the MSQOL-54 was r=.68; the correlation with the gap was r=−.22. The correlation of self-perceived current ability with the role–emotional subscale of the MSQOL-54 was r=.17; the correlation with the gap was r=−.05.

Figures 4 and 5 show scatterplots used to observe whether a single outlier unduly strengthened a significant correlation. None of the relationships documented here depended on a single outlier.

Figure 4.

Correlation between average current ability from the Movement Ability Measure and transformed scores from the 12-item Multiple Sclerosis Walking Scale (N=30).

Figure 5.

Correlation between participant locations on the speed dimension of the Movement Ability Measure and the total distance walked on the Six-Minute Walk Test (N=30).

Discussion

Although many relationships between measures were noted in our sample of people with MS, some hypothesized relationships were not significant. Average current ability and the separate dimensions, as recorded with the MAM, correlated moderately to strongly with some of the measures expected to be related and showed correlations with other measures in exploratory analyses of relationships; the average gap between current ability and preferred ability, as calculated from MAM responses, diverged from many of the measures with which it was compared.

The strength of the correlations (r) between the current movement dimensions from the MAM and the measures of bodily function and activity with which they were compared ranged from .4 to .7. These correlations compared favorably with the correlations between other self-report and performance-based measures. The MFIS correlated with the Six-Minute Walk Test at −.33 (P=.075). The BBS (a performance-based measure) correlated with the Activities-specific Balance Confidence Scale at .48 (P=.01) and with the MSWS-12 at −.58 (P=.00). The MSWS-12 correlated with the SARA gait item at .59 (P=.00) and the SARA stance item at .66 (P=.00); the MSWS-12 correlated with the DGI at −.74 and the FSST at .60 (both P=.00). The correlations in the present study provide evidence of the convergent validity of MAM responses regarding current ability and these measures of bodily function, activity, participation, and personal factors in our sample of people with MS. Determining the degree of generalizability of these findings beyond people fitting within the demographics shown in Table 2 will require further research.

The MAM responses regarding current ability can indicate in which dimension of movement a person perceives a lower or higher ability level but do not indicate whether having a low ability level in a dimension is a disability. Figures 1, 2, and 3 show that current movement ability is not a direct indication of what people prefer to have. A low current movement ability level may be associated with a large distance to the preferred movement ability level (Fig. 1). However, a relatively high movement ability level also may be associated with a large distance between the current movement and the movement that a person would like to have (Fig. 3); this distance may be larger than that associated with a substantially lower movement ability level (Fig. 2). The gap between current movement ability and preferred movement ability, shown to be largest in the speed dimension for 9 out of 30 participants, can direct attention toward the dimensions of movement that a person perceives to need the most attention, no matter what current movement ability the person has. Unfortunately, no other measure in the present study asks people what they value most or what they most want to change; therefore, the correlations of the gap (between current movement ability and preferred movement ability) and other measures are moderate, at best, and nonsignificant for most comparisons. Even the MSQOL-54 subscales regarding role limitations, in which respondents indicate whether they are able to accomplish less than they would like, do not correlate strongly with the gap. Wording differences and the coarse granularity with only 7 items and dichotomous response choices may contribute to the lack of correlation, however.

The data seem to indicate a divergent construct for the gap between current movement ability and preferred movement ability. The measures compared with the gap were those that we assumed might indicate patients' preferences: a disability scale, pain, health distress caused by the diagnosis, a physical health composite scale, number of falls in the past 12 months, walking ability, fatigue, and quality of life. The gap remains the only measure of the distance between “able” and “wanting” to do or be and thus cannot be expected to have strong correlations with measures that do not include such information.

To compare data from our participants with data obtained from other samples, we performed a post hoc unidimensional analysis of MAM responses with ConQuest software⁵⁰ and the Monte Carlo estimation method. Overall current ability and preferred ability logit values were obtained, anchoring on item locations determined from a unidimensional analysis of a group of 318 respondents with a large range of movement abilities.²² The raw scores in the present study for movement ability “now” on the MAM ranged from 39 to 119 (logit values of −7.55 to 3.14; standard errors averaging 0.37 logit), equivalent to movement ability levels of “moves some, needs help” to “moves for normal activities plus extra activities.”²⁰ The overall gap for our participants with MS averaged 6.74 (SD=2.95) logits, considerably larger than the average gap—3.9 (2.6) logits—for the previous sample of people who have a broad range of movement abilities and live in the community.²² When differentiating the average gap for people who specified that they had no movement-related problems—2.69 (1.57) logits—from the average gap for people who have mostly orthopedic problems and are starting an episode of care in physical therapy—6.16 (2.54) logits—the overall gap for our participants with MS seemed most similar to the average gap for people who had movement problems.²² The similarity in the size of the gap may indicate that the physical and psychosocial impacts of MS were not manifested in differences in the ways our participants responded to the MAM items. In the previous study, the gap between current movement ability and preferred movement ability was seen to narrow with physical therapy for people with mostly orthopedic diagnoses; no intervention or follow-up testing was performed in the present study to examine changes in the size of the gap with rehabilitation or with deterioration as the disease progresses.

In addition to the lack of an intervention with which to mark the response of the gap to therapy,⁶ the limitations of the present study included the relatively small sample size (with missing data decreasing the sample size further for some variables), the lack of corroborative data to determine participants' values or preferences regarding movement, and the multiplicity of analyses performed. Designating the primary measures expected to correlate with MAM responses before further exploration and use of the Bonferroni method of correcting the alpha level for multiple analyses helped to limit type I errors, but further research is needed to confirm the results obtained here. One benefit of the multiplicity of measures completed for a single sample was the ability to compare easily across measures for the determination of missing constructs or the duplication of effort.

Further research could investigate alternative methods of assessing the use of a gap between current movement ability and preferred movement ability as a patient-focused measure of disability. Item response theory measurement methods were used to convert current and preferred abilities to the same interval scale in the present study. Other methods of joining current and preferred abilities to calculate the gap between them could work well for measuring disability. Further research could also examine which dimensions of movement have the largest gaps in people with MS; whereas a lack of endurance is thought to be a significant problem in people with MS, Figures 1, 2, and 3 show larger gaps in the dimension of speed than in other dimensions for 3 participants.

Conclusion

In the present study, the data for people who had MS and were ambulatory indicated that the average current ability and individual movement dimensions in the MAM correlated moderately to fairly strongly with many of the measures of bodily function, activity, and participation with which they were compared (r=.5–.8). Thus, the data provided evidence of convergent validity for self-reported current movement ability, as recorded with the MAM, for our sample. The gap between current movement ability and preferred movement ability correlated with EDSS scores at r=.46 (P=.011) and with the pain subscale of the MSQOL-54 at r=−.56 (P=.001). Although the gap showed minimal significant correlations with other measures, no other measures incorporated the idea of patients' preferences when assessing ability; therefore, the divergence of this construct is explainable. Further research that includes assessments before and after therapeutic intervention is indicated to determine whether the gap between current movement ability and preferred movement ability, as measured with the MAM, successfully operationalizes a definition of disability that focuses on patients' values and preferences.

Appendix.

Appendix.

Two Items From the Movement Ability Measure Assessing Endurance and Accuracy^a

^a For each item, respondents are asked to choose the statement that most closely describes their usual ability to move now (the current week) and the statement that most closely describes the ability that they would like to have even if they had to work hard for it.