Williams, PhD, Epworth Rehabilitation at
Citation Williams, G. (2006).
The High Level Mobility Assessment Tool. The Center for
Outcome Measurement in Brain Injury. http://www.tbims.org/
combi/himat ( accessed
psychometrics properties of the HiMAT were investigated throughout
the development phase.
validity and Unidimensionality
The content of the HiMAT was initially generated from a review of
existing mobility scales and by surveying expert opinion (Williams
et al., 2005a). Rasch analysis was then used to establish content
validity and unidimensionality of the items that were generated
(Williams et al., 2005b).
the initial stages, a literature review was conducted on adult and
paediatric neurological mobility scales to identify which items
had previously been reported as “high-level” mobility
items. The review identified 18 different items from 31 mobility
scales. To further extend the pool of high-level mobility items,
a consensus method was used to survey the opinions of expert physiotherapists
and physical educators. Expert clinicians generated 157 items that
were collated and condensed to 88 items for ranking on a questionnaire
by excluding items with excessive equipment demands or items that
were too dependent on upper limb or cognitive involvement. This
meant that items such as running whilst throwing and catching a
ball or climbing a ladder were excluded. Fifteen items on the questionnaire
were rated as very important by 80% of expert clinicians. These
included walking forwards, on slopes and different surfaces, changing
direction as well as walking long distances and stair use. Running
items included forwards, backwards, on slopes and different surfaces,
changing direction, stopping and starting as well as running long
distances. Balancing in single limb stance was also included. Some
items from the literature review that were not rated very important
by 80% of expert clinicians were added to the 15 ‘very important’
items, resulting in a group of 20 high-level mobility items that
were prepared for testing on TBI clients.
investigate the content validity and unidimensionality of the high-level
mobility items that would ultimately form the HiMAT, a three-stage
process was used. Firstly, internal consistency was investigated
using Cronbach’s alpha. Internal consistency, which provides
an estimate of the extent to which the items measure the same domain,
was very high (Cronbach’s alpha of .99). Second, principal
axis factoring was performed to identify items that were linearly
correlated (indicating unidimensionality) with each other. Principal
axis factoring led to the identification and exclusion of the balance
items and two hopping items on the less-affected leg. Finally, the
remaining items were further scrutinized using Rasch analysis.
analysis is a powerful tool in the initial stages of scale development,
particularly for establishing content validity and supporting construct
validity. Rasch analysis compares individual response patterns to
those of the entire sample to estimate both an individual’s
ability and item difficulty (Williams et al., 2005b). Rasch analysis
provides a framework, with guidelines, for verifying rating scale
categorization to ensure efficient measurement. Misfitting items
are identified, and excluded, by high weighted mean square fit statistics.
In the development of the HiMAT, the more stringent upper limit
of 1.3 was applied. Items with weighted mean square fit statistics
exceeding 1.3 were excluded from further analysis.
Discriminability Once misfitting items were excluded, Rasch analysis was
used to investigate the discriminative ability of the remaining
items (Williams et al., 2005b). The item estimates assigned to each
item identify the level of difficulty of each task. These estimates
establish a hierarchy of difficulty. Clustering is a term used to
describe items with similar levels of difficulty. Where items clustered,
redundant items were excluded. Redundant items were identified and
excluded and the more practicable and feasible item was retained.
Item practicability and feasibility were assessed by considering
the time, equipment and location required to test each item. For
example, walking, walking on grass and the 6-minute endurance test
all had a very similar level of difficulty. In this case, the walking
item was retained as it does not require access to a flat grassed
surface and is quicker to administer than a 6-minute endurance test.
This process led to the exclusion of seven items, leaving 13 items
on the final version of the HiMAT. Both the easiest and most difficult
items were retained during the exclusion process so that the range
of ability quantified by the HiMAT was maintained. Only redundant
items that clustered in the middle of the scale, providing little
discriminative information, were excluded.
investigation was performed to determine if summed raw HiMAT scores
provided a valid measure of motor ability (Williams et al., 2005b).
Summed raw scores were compared to the logit scores obtained for
each individual. The correlation between the summed raw scores and
the logit scores was very high (r =.98). This result means that
summed raw scores adequately reflected true change for the majority
of the range of ability that the HiMAT quantifies.
Concurrent validity Concurrent
validity refers to the comparison between measures that assess the
same construct. This approach to validation is used to compare a
new measure, such as the HiMAT, against existing measures. The HiMAT
was compared to the motor component of the Functional Independence
Measure (FIM) and the gross function component of the Rivermead
Motor Assessment (RMA). The FIM was chosen because it represents
the most frequently used measure of physical performance in TBI
rehabilitation. Despite its intended use as a ‘burden of care’
measure for inpatient rehabilitation, it is frequently used to report
long-term outcome following TBI. The RMA contains more high-level
items, such as running, stair climbing and hopping, than existing
adult mobility scales. This scale was originally developed in the
stroke population, but is yet to be validated in TBI.
investigate concurrent validity, 103 patients were concurrently
scored on the HiMAT, motor FIM and gross function RMA. Correlations,
using Pearson’s r, were calculated between the HiMAT, the
motor FIM and the gross function component of the RMA to investigate
concurrent validity. The correlation between the HiMAT and the motor
FIM was only moderately strong (r = .53, p<.01) due to a substantial
ceiling effect the motor FIM suffers when compared to the HiMAT.
More specifically, the motor FIM was unable to discriminate motor
performance for 90 (87.4%) of the 103 patients, yet these patients
had a mean score on the HiMAT of only 32.6/54 (SD = 13.8, range
5-54) (Williams et al., 2006b).
HiMAT and gross function RMA had a much stronger correlation (r
= .87, p < .01), but the gross function RMA also had a substantial
ceiling effect when compared to the HiMAT. Fifty-three patients
(51.5%) scored the maximum score of 13/13 on the gross function
RMA, yet had a mean score of only 41.7/54 on the HiMAT (SD = 8.8,
range 24-54) (Williams et al., 2006b).
reliability Inter-rater reliability was investigated by three physiotherapists
concurrently and independently scoring the performances of 17 people
with TBI. The three physiotherapists had an average of nine years
of clinical experience in neurological physiotherapy. Since the
HiMAT was developed as a simple and easy to use clinical tool for
physiotherapists, two of the three physiotherapists used to investigate
inter-rater reliability had no prior knowledge or training on the
HiMAT, but were provided with an instruction sheet just prior to
testing. Investigation of live inter-rater reliability, rather than
rating from videotaped recordings, is essential as it reflects the
real-life conditions experienced by clinicians in the workplace.
intraclass correlation coefficient (ICC: 2,1) was used to assess
inter-rater reliability for each of the items. The ICCs calculated
to determine the inter-rater reliability of the three examiners
were very high (ICCs = .99) for each of the individual items on
the HiMAT. Total scores on the HiMAT were also calculated from the
coded scores for each of the physiotherapists and assessed using
an ICC(2,1). The inter-rater reliability of the total HiMAT scores
was also very high at .99 (Williams et al., 2006a). This result
demonstrates that the HiMAT has high inter-rater reliability and
supports the user friendliness of the HiMAT as this result was achieved
even though two of the therapists had no prior knowledge or training.
(intra-rater) reliability To investigate intra-rater reliability 20 people with TBI
were asked to return for repeat testing two days following their
initial test. To ensure that natural recovery was unlikely to occur
between the initial and repeat tests, only participants who had
sustained their TBI more than 18 months prior to testing were asked
to return for repeat testing.
different calculations were performed to investigate retest reliability.
An ICC(2,1) was calculated on the total HiMAT scores. The retest
HiMAT ICC was very high (ICC = .99).
To determine if a systematic error had occurred, a paired t-test
was used on the groups’ total HiMAT scores. A paired t-test
showed a mean improvement of 1.0 point (t =3.82, p<.001, range
–1 to +3) on the HiMAT at retest, indicating a systematic
improvement had occurred. This means that on average, people with
TBI improve by 1 point when retested two days later. Although this
improved score is significant, it is small and well within the confidence
intervals for detecting clinically important change.
The standard error of measurement (SEM) was also calculated to determine
the 95% confidence intervals (CI) for determining the minimal detectable
change (MDC95) on the HiMAT according to the
= mean difference ± 1.96 x SEM
detectable change values are a reflection of clinically important
change and the likelihood that true change has occurred. To calculate
the SEM, the standard deviations from the pre-test and post-test
scores were pooled according to the equation outlined by Mendenhall,
McClave, and Ramey (1977). The MDC95 for the
HiMAT was calculated at +/- 2.66 points. Considering the mean difference
between test and retest (1 point), this means that to be 95% confident
that clinically important change (improvement or deterioration)
has occurred, participants have to improve by 4 points or deteriorate
by at least 2 points (Williams et al., 2006a).
HiMAT is highly reliable, but clinicians need to be aware that people
with TBI tend to achieve improved HiMAT scores when retested after
two days. This improvement is most likely to be from improved confidence
in attempting challenging tasks gained from the first testing session,
and most unlikely to be attributed to neural recovery. This highlights
the importance of the familiarization trials before testing so a
lack of confidence does not impact on motor performance.
consistency Internal consistency of the 13 HiMAT items was very high
(Cronbach’s alpha of .97) (Williams et al., 2006a).
and Ceiling effects
The HiMAT has specifically been designed to quantify high-level
mobility. It is only appropriate for patients who are able to walk
independently without a gait aid for at least 20 meters. Due to
the floor effect, the HiMAT is more appropriate in the latter stages
of inpatient rehabilitation and throughout outpatient and community
integration rehabilitation. To date, the HiMAT has no demonstrable
ceiling effect. In comparison to other scales of motor performance
it is much less susceptible to a ceiling effect and is better able
to discriminate high-level mobility (Williams et al., 2006b).
Responsiveness refers to the ability of a measure to detect clinically
meaningful change over time, and provides a means for determining
if an individual’s score changes are related to true recovery,
or to natural variation in repeated performances. Multiple methods
have been proposed for investigating responsiveness. Responsiveness
indices can be grouped into two main types. The first type evaluates
the amount of change relative to measurement error. Examples include
the method described by Guyatt, Walter and Norman (1987), and that
suggested by Goldie, Matyas, and Evans (1996). The second type of
index of responsiveness evaluates change in a group of patients
in relation to the variability of change scores in the same group.
This type of responsiveness index, such as that described by Liang,
Fossel, and Larsen (1990), is influenced by varying rates of patient
recovery and response to treatment. Scale responsiveness is an important
concept for clinicians in this age of evidence-based practice where
funding bodies may base payment on demonstrable change. Understanding
and interpreting the responsiveness of a scale enables clinicians
to discriminate true change from measurement error.
investigate responsiveness, 14 people with acute TBI who were initially
tested less than 12 months post-accident returned for repeat testing
3 months later. People less than 12 months post-TBI are still in
their acute recovery phase and are therefore likely to change over
a 3 month period. The 14 people with TBI were tested on the HiMAT,
motor FIM and gross function RMA to compare the ability of each
of these scales to detect change in high-level mobility. Three different
methods were used to evaluate the responsiveness:
The method initially described by Guyatt et al. (1987). It was modified
by Goldie et al. (1996) to take into account the systematic change
that may occur with repeated measures.
The method described by Liang et al. (1990).
The third method, suggested by Goldie et al. (1996), calculates
the proportion of patients that changed by at least as much as the
minimal detectable change (MDC95) score.
of the responsiveness of the HiMAT, motor FIM and gross function
RMA showed that the HiMAT was more responsive to change in high-level
mobility, regardless of the index used to calculate it (Williams
et al., 2006b). This is most likely due to the ability of the HiMAT
to quantify mobility to a much greater extent, indicating it is
less susceptible to a ceiling effect than existing scales.
The HiMAT was specifically developed to be quick and easy to use
with minimal time, equipment and training requirements. Testing
typically requires only 5-15 minutes depending on the patients ability.
Measurements are made with a stopwatch and tape measure which are
routinely available and utilised in clinical settings.
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