- Email: [email protected]
Rasch Analyses of the Wheelchair Use Confidence Scale for Power Wheelchair Users
Accepted Manuscript Rasch analyses of the Wheelchair Use Confidence Scale for power wheelchair users Brodie M. Sakakibara, PhD, William C. Miller, PhD, FCAOT, Paula W. Rushton, PhD, Jan Miller Polgar, PhD PII:
S0003-9993(17)31120-6
DOI:
10.1016/j.apmr.2017.09.004
Reference:
YAPMR 57031
To appear in:
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
Received Date: 9 June 2017 Revised Date:
28 August 2017
Accepted Date: 6 September 2017
Please cite this article as: Sakakibara BM, Miller WC, Rushton PW, Polgar JM, Rasch analyses of the Wheelchair Use Confidence Scale for power wheelchair users, ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION (2017), doi: 10.1016/j.apmr.2017.09.004. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Rasch analyses of the Wheelchair Use Confidence Scale for power wheelchair users Brodie M. Sakakibara, PhD1-3; William C. Miller, PhD, FCAOT3,4; Paula W. Rushton, PhD5,6; Jan Miller Polgar, PhD7. Faculty of Health Sciences, Simon Fraser University; 2Department of Physical Therapy, University of British Columbia; 3Rehabilitation Research Program, Vancouver Coastal Health Research Institute; 4Department of Occupational Therapy and Occupational Sciences, University of British Columbia; 5School of Rehabilitation, Faculty of Medicine, Université de Montréal; 6Centre de réadaptation Marie Enfant, CHU; 7School of Occupational Therapy, University of Western Ontario;.
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This work was supported by the Canadian Institutes of Health Research (Postdoctoral Scholarship to BMS and Team Grant AMG 100925 to CanWheel), Michael Smith Foundation for Health Research (Postdoctoral Fellowship to BMS). Copies of the Wheelchair Use Confidence Scales may be obtained from: http://millerresearch.osot.ubc.ca/tools/mobility-outcome-tools-2/wheelchair-useconfidence-scale-wheelcon/ Running head: Rasch analyses of the WheelCon-P Word count main text: 3270 Word count abstract: 249
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Corresponding author: Paula W. Rushton, PhD Centre de réadaptation Marie Enfant, CHU Sainte-Justine, 5200 rue Bélanger, Montréal, QC, H1T 1C9, Canada, Tel: 514-374-1710 x 8003; Fax: 514-723-7116; Email: [email protected]
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Abstract
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Objective: To examine the dimensionality of the Wheelchair Use Confidence Scale for
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power wheelchair users (WheelCon-P); identify items that do not fit the Rasch Rating
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Scale model as well as redundant items for elimination; and determine the standard errors
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of measurement and reliability estimates for the entire range of measurements.
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Design: Secondary analysis of cross-sectional data.
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Setting: Community.
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Participants: Volunteer participants (n=189) from British Columbia, Ontario, Quebec,
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and Nova Scotia, Canada were recruited for this study. The mean age of the sample was
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56.7 (SD=13.0) years, and the mean years of wheelchair use experience was 20.4
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(SD=16.4) years. The sample was evenly divided by sex. The three most common
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diagnoses accounting for wheelchair use were: multiple sclerosis (20.1%), spinal cord
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injury (19.0%) and stroke (10.6%).
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Intervention: None.
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Measurement: 59-item WheelCon-P.
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Results: Principal components analyses confirmed the presence of two self-efficacy
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dimensions: mobility and social situation. Eleven mobility items, and five social situation
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items fit the Rasch Rating Scale model. Three items misfit the model using all 16 items
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(i.e., WheelCon-P Short Form). In each of the mobility, social situation, and WheelCon-P
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Short Form range of measurements, the two lowest and two highest measures had internal
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consistency reliability estimates below 0.70; all other measures had reliability estimates
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above 0.70.
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Conclusion: The WheelCon-P is comprised of two self-efficacy dimensions related to
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mobility and social situations. The scores from the WheelCon-P Short Form, and the 11-
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item mobility and 5-item social situation dimensions using a 0 to 10 response scale have
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good reliability.
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Key words: self-efficacy; wheelchairs; measurement; Rasch analyses; principal
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components analyses; wheelchair confidence.
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List of Abbreviations:
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1. WheelCon-P: Wheelchair Use Confidence Scale for power wheelchair users
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2. PCA: principal components analysis
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3. ZSTD: standardized fit statistics
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4. SEM: standard error of measurement
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The Wheelchair Use Confidence Scale for Manual Wheelchair Users (WheelCon-M)1, 2 is
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a 65-item questionnaire used to measure confidence (i.e., self-efficacy) with using a
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manual wheelchair in a variety of challenging situations related to the physical
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environment and performing activities, as well as self-efficacy related to knowledge and
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problem solving, advocacy, social situations and managing emotions. The validity of the
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WheelCon-M measurements has been examined using several rigorous methods
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including qualitative interviews,2 hypothesis testing,1 test re-test examinations,1 as well as
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quantitative techniques based on both Classical Test1 and Item Response3 theories. As a
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result, the WheelCon-M has been used to develop a body of evidence demonstrating
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wheelchair use self-efficacy as an important clinical focus and outcome.4-10
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The validity of evidence derived from the WheelCon-M measurements is specific to
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manual wheelchair users, and therefore is of little relevance for the advancement of
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research in people who use powered wheelchairs for mobility. However, similar to
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research among individuals with mobility disabilities demonstrating the health,
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functional, and quality of life benefits after acquiring a manual wheelchair,11-13 research
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shows the positive effects of power wheelchair use on similar outcomes.14 It is then
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plausible that self-efficacy specific to powered wheelchair use will have implications on
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rehabilitation outcomes similar to that previously reported among people who use manual
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wheelchairs.7, 8 Interestingly, power wheelchair users do not optimize the use of their
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wheelchair despite having adequate operational skills.15 This leads to speculation that: (i)
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many of these individuals may not achieve desired levels of community or social
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participation; and (ii) improvements to wheelchair use self-efficacy may facilitate more
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desired levels of participation, given that self-efficacy is a more accurate predictor of
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behaviour than ability.16
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Recently, Rushton et al. reported on the modification of the WheelCon-M into a version
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applicable for power wheelchair users, the WheelCon-P.17 Investigations are beginning to
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report on the use of the WheelCon-P as an important outcome measure,15, 18, 19 thereby
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warranting further rigorous examination of the WheelCon-P’s measurement properties.
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The objectives of this study are to: 1) examine the dimensionality of the WheelCon-P; 2)
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identify items that do not fit the Rasch Rating Scale model20 as well as redundant items
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that could be considered for elimination (i.e., to create a WheelCon-P Short Form); 3) and
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determine the standard errors of measurement and reliability estimates for the entire
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range of measurements.
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METHODS
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Study Design and Participants
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Data used in this secondary analysis were combined from two independent studies15, 18
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with similar inclusion criteria: power wheelchair-users; ≥19 years of age; communicates
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in English or French; and able to provide informed consent.
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Volunteer participants were recruited from British Columbia (Vancouver), Ontario
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(Toronto, London), Quebec (Montreal, Quebec City), and Nova Scotia (Halifax), Canada
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between 2010 and 2014 using letters of information sent by clinicians and wheelchair
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vendors. Advocacy/community groups also provided study information to their
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membership. After providing informed consent, participants met with a trained research
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assistant for data collection. The ethics boards from all relevant institutions approved the
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studies.
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Measures
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The 59-item WheelCon-P was used to capture the power wheelchair use self-efficacy
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construct.17 The items focus on self-efficacy related to knowledge of the wheelchair and
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problem solving, emotions, performance of mobility skills, activities performed as well as
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social and advocacy interactions. Item responses range from 0 to 100. A mean score is
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derived with higher scores indicating higher self-efficacy.
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A demographic information form was used to collect data on personal, health, and
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wheelchair-related variables, and the Wheelchair Skills Test-Questionnaire for power
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wheelchair users21 to characterize capacity to use a power wheelchair. Total scores on the
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Wheelchair Skills Test-Questionnaire range from 0 to 100, with higher scores indicating
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better ability to use the power wheelchair.21
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Data analyses
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Descriptive statistics were used to characterize the sample. Results from categorical
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variables were calculated as percentages and continuous variables as means and standard
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deviations.
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For this study’s analyses, we divided the WheelCon-P items into two broad conceptual
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areas based on whether the item asked about physical (n=42 items, labelled as the
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mobility items) or social (n=17 items, labelled as the social situation items) aspects of
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wheelchair use. The division of items was done to increase the specificity of our analyses,
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and also because our previous evaluation of the WheelCon-M items had a similar
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division.3 Furthermore, we modified the 0 to 100 response format to a 0 to 10 format (0 =
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not confident and 10 = completely confident), as has been done in previous literature.3, 22
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We used the modified total scores for all analyses on each of the conceptual areas.
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Testing Rasch Assumptions
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Unidimensionality: Principal Components Analyses (PCA) along with promax rotation
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were used to assess for ‘essential’ unidimesionality23 (i.e., one dominant dimension in the
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presence of one or more minor dimensions with small influences on measurement). Prior
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to PCA, we conducted parallel analyses to determine how many statistically significant
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dimensions were in each of the mobility and social situation dimensions,24, 25 and thus
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how many dimensions to force in the PCA. The inter-item correlation matrices were then
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examined to confirm the presence of underlying dimensions to be analyzed. Adequate
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levels of inter-item correlations were determined if 20% of the correlations were above
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0.3026 and the Kaiser-Meyer-Olkin Measure of Sampling Adequacy value was >0.70.26
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After performing the PCAs, items not meeting the minimal loading value of 0.38,
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calculated using the formula 5.15/√(n-2),26 were considered for elimination. Essential
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unidimensionality was considered satisfied if the first dimension explained ≥30% of the
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variance26 and if the first to second eigenvalue ratio ≥3.0.27
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Local independence: We examined the correlation coefficients of the inter-item residuals.
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Correlation coefficients greater than 0.20 indicated a violation of the local independence
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assumption.28
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Assessing item fit and item elimination – Item mean-square fit statistics were assessed
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using the Rasch Rating Scale Model.20 Infit statistics assess unexpected responses to
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items that have a difficulty level ‘near’ one’s reported self-efficacy estimate, whereas
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outfit statistics assess unexpected responses to items with self-efficacy levels ‘far’ from
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one’s reported self-efficacy.29 Fit statistics follow a chi-square distribution and have an
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expected value of 1. Values substantially greater than 1 reflect more variability than
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expected, and values less than 1 reflect less variability than expected.30 We determined
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acceptable infit and outfit statistics to range between 0.85 to 1.15, and 0.56 to 1.44
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calculated using the formulas 1±2/√N and 1±6/√N, respectively.30 Items with fit statistics
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not within the acceptable ranges were eliminated.
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We performed a two stage fit analysis for each of the Mobility and Social Situation
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conceptual areas. In following Linacre’s recommendations for the diagnosis of misfits,
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items with outfit statistics outside the acceptable range were first examined.29 Because
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these items elicit unexpected outlying responses (e.g. unexpectedly high self-efficacy
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ratings to difficult items by individuals with lower self-efficacy), they were considered
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for elimination first. After removing the items with misfitting outfit statistics, the
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analyses were re-ran on the more model-fitting items, and the infit statistics of the
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remaining items were examined. Similar to items with misfitting outfit statistics, items
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with infit statistics outside the acceptable range were considered for elimination. We then
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examined for potential item redundancy. Items were considered redundant when there
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was overlap in both item difficulty ± SEM and conceptual content. When there was
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redundancy, one item was considered for elimination after discussion with the research
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team.
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After eliminating the misfitting and redundant items, we ran a final Rating Scale model
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for each dimension. Because it is common for items to misfit in the more model-fitting
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context,29 we considered item infit and outfit statistics in the range of 0.50 and 1.50 to be
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productive for measurement.29 Finally, while it is common for psychometric
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investigations to observe evidence for both single and multiple dimensions within a
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measurement tool, researchers and clinicians have been shown to favour the use of total
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scores over subscale scores.31 Furthermore, because research also indicates the
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plausibility that subscale scores yield little unique information beyond total scores,31 for
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exploratory purposes we combined the items from each WheelCon-P dimension and
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analyzed the overall fit using a Rasch Rating Scale model, thereby creating a WheelCon-
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P Short Form. Figure 1 presents the stages in our fit analyses.
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Reliability – SEM and reliability were estimated for the entire range of measurements.
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SEMs were converted into coefficients similar to Cronbach’s alpha using the formula:
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1/1+logit SEM2.32, 33 Reliability estimates ≥0.70 were considered acceptable.34 For ease
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of interpretation, the Rasch measurements in logits were linearly transformed29 into a
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self-efficacy continuum ranging from 0 to 100.
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Winsteps version 3.92.129 and SPSS version 23.0 (IBM, Armonk, NY) were used to
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perform the analyses.
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RESULTS
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Participants
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The mean age of the combined sample (n=189) was 56.7 (SD=13.0) years, and the mean
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years of wheelchair use experience was 20.4 (SD=16.4). The sample was evenly divided
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by sex. The three most common diagnoses accounting for wheelchair use were: multiple
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sclerosis (20.1%), spinal cord injury (n=19.0%) and stroke (n=10.6%). The mean
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Wheelchair Skills Test score was 87.5/100 (SD=10.5). Table 1 presents sample
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characteristics in more detail.
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Testing Rasch Assumptions
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Unidimensionality – Parallel analysis of the 42 mobility self-efficacy items revealed three
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statistically significant dimensions. The subsequent PCA of these dimensions, which had
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sufficient inter-item correlations, resulted in two items that did not load on any dimension
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(i.e., know when to charge wheelchair batteries; can find a place to charge batteries when
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not at home), one dominant dimension accounting for 34.3% of the variance with an
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eigenvalue of 14.4, a second dimension accounting for 10.6% of the variance with an
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eigenvalue of 4.4, and a third dimension accounting for 6.1% of the variance with an
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eigenvalue less of 2.5. Of the 30 items that loaded on the second dimension, 27 also
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cross-loaded onto the first dimension. The three items that were unique to the second
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dimension asked about self-efficacy to: open and go through a spring loaded door; drive
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the wheelchair up a single 5cm step to change levels between rooms; and drive the
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wheelchair down a single 5cm step to change levels between rooms. These three items
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were conceptually deemed to be no different than other items in the first dimension
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asking about moving the wheelchair in various environments and performing activities.
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Thus, given the conceptual relevance of the two non-loading items, similarities between
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the first and second dimensions, and the eigenvalue ratio of 3.3 between the first and
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second dimension, we determined all 42-items to comprise a single dimensional for
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subsequent analyses.
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Parallel analysis of the 17 social situation self-efficacy items revealed two statistically
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significant dimensions. Principal Component Analysis of these dimensions revealed one
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dominant dimension accounting for 39.6% of the variance with an eigenvalue of 6.7, and
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a second dimension accounting for 9.2% of the variance with an eigenvalue of 1.6,
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representing an eigenvalue ratio of 4.2. Thus, we determined a unidimensional 17-item
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solution for subsequent analyses.
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Local independence – All inter-item residual correlations were below 0.20 in both
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dimensions thereby satisfying the local independence assumption.
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Assessing item fit and item elimination
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Mobility self-efficacy – Of the 42 items, 31 items had misfitting outfit (n = 17 items
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related to activities performed when in a wheelchair e.g, can transfer from your
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wheelchair to your bed, can make a meal or snack whil using your wheelchair) and infit
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(n = 14 items related to complex tasks e.g., can open, go through, and then close a door,
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can manoeuvre your wheelchair to press the crosswalk button and cross the street before
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the traffic light changes) statistics. No items were deemed to be redundant. After
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removing the misfitting items, a final Rating Scale Model was applied to the 11
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remaining items. The fit statistics of these 11 items were all within the acceptable range.
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Table 2 presents the fit statistics of the 11 items, organized by increasing difficulty.
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With the exception of the two lowest and two highest measurements, all other measures
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(96% of all measures) had reliability estimates ≥0.70. Measurements in the range of 35.0
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to 52.6 had the highest reliability estimates (0.98) and low SEM, as shown in Figure 2a.
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The mean item difficulty of this dimension was 44.6 (SD=5.5), whereas the sample’s
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mean self-efficacy was 65.4 (SD=17.7).
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Social situation self-efficacy – Of the 17 items, 12 items had misfitting outfit (n = 2 items
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related to using alternative modes of transportation e.g. public transportation and
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airplanes) and infit (n = 10 items related to self-presentation and interaction with others
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e.g., can present yourself as you wish to be seen when you are in public and feel people
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are watching you, can ask people to move out of your way while driving your wheelchair,
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can ask a stranger for help) statistics. After removing these items, a final Rating Scale
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Model was applied to the five remaining items. The fit statistics of these five items were
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within the acceptable range. Table 3 presents the fit statistics of the five items, organized
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by increasing difficulty.
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With the exception of the two lowest and two highest measurements, all other measures
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(92% of all measurements) had reliability estimates ≥0.70. Measurements in the range of
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38.6 to 45.2 had the highest reliability estimates (0.98) and low SEM, as shown in Figure
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2b. The mean item difficulty of this dimension was 44.0 (SD=3.0), whereas the sample’s
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mean social situation self-efficacy was 66.8 (SD=22.8). Table 4 presents the five items
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organized by increasing difficulty.
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The 16-item WheelCon-P Short Form – After combining the items from both dimensions
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and running another Rating Scale Model, one item had an infit statistic greater than 1.5,
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and three items had outfits statistics greater than 1.5, as shown in Table 4. With the
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exception of the two lowest and two highest measurements, all other measures (98% of
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all measurements) had reliability estimates ≥0.70. Measurements in the range of 38.5 to
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52.8 had the highest reliability estimates (0.99) and low SEM, as shown in Figure 2c. The
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mean item difficulty was 46.1 (SD=3.9), whereas the sample’s mean self-efficacy was
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61.9 (SD=15.9).
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Discussion
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Situation specific self-efficacy has been shown to influence choices and decisions,
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efforts, perseverance, and motivation.35 For these reasons, self-efficacy is an important
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consideration in rehabilitation because it may influence an individual’s adherence to
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rehabilitation programs, goal setting, efforts and persistence. Moreover, low self-efficacy
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with manual wheelchair use appears to be a remediable condition that may be improved
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via clinical intervention.9, 10 However, because self-efficacy is situation specific, and up
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until recently there has not been an adequate tool to measure self-efficacy specific to
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power wheelchair use, our knowledge of its relevance and importance in power
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wheelchair related research is at present minimal.
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In this study, we continue our efforts to provide rehabilitation researchers and clinicians
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with robust self-efficacy measurements tools to help ensure optimal research and
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rehabilitation outcomes among wheelchair users.1-3, 17 More specifically, we advance the
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foundational and developmental work of Rushton et al.17 by evaluating the measurement
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properties of the WheelCon-P using contemporary measurement methods. In our
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application of PCA, we confirmed the unidimensionality of the mobility and social
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situation dimensions using multiple criteria. Although parallel analysis provided a general
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indication of the presence of three and two dimensions within the mobility and social
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situation items, respectively, PCA indicated redundancy in item loadings between
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dimensions, as well as non-important eigenvalues in lower level dimensions. As a result,
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we performed subsequent Rasch analyses on single dimension solutions explaining more
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than adequate levels of variability in the mobility (34.3%) and social situation self-
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efficacy (39.6%) responses.
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Our results show a WheelCon-P Short Form with 2 dimensions (11-item mobility and 5-
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item social situations) that can have three possible scores: a composite score, a mobility
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sub-scale score and a social situations sub-scale score. The resulting mobility and social
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situation dimensions are comprised of items asking about distinct forms of self-efficacy.
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Whereas the mobility items ask about self-efficacy using the various functions of the
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power wheelchair and negotiating indoor and outdoor environments, the social situation
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items ask about self-efficacy related to advocating for one-self, knowledge, and problem
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solving. By separating the WheelCon-P items into two situation specific dimensions,
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researchers will be able to develop more robust and precise models of rehabilitation
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outcomes using the specific forms of powered wheelchair use self-efficacy measures as
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predictor variables. Importantly, the results of these predictive models will inform the
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development of targeted interventions to enhance mobility or social situation self-efficacy
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in power wheelchair users. Furthermore, our measures will allow clinicians to more
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efficiently assess and subsequently provide targeted therapeutic interventions to remedy
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different forms of low self-efficacy. Although we also provide a composite measure of
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self-efficacy with adequate reliability (i.e., the WheelCon-P Short Form), these
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measurements do not function as well as those from the individual mobility and social
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situation dimensions, as indicated by the number of misfitting items. We anticipate that
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the more specific mobility and social situation dimensions will be used more frequently
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than the composite short form, however, we provide the short form as an efficient
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alternative for those valuing the original 59-item WheelCon-P.
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A key property of Rasch models is sample invariance. This property allows for the item
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and respondent characteristics to be estimated independent of each other.30, 36 As such, we
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are able to determine the ‘difficulty’ of each item and mean difficulty of the items
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combined, as well as the self-efficacy level of each person and mean self-efficacy of the
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sample. Our findings indicate that the mean difficulty of items in each of the mobility,
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social situation, and short form scales are lower than the mean self-efficacy of the
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sample. For example, the mean difficulty of the mobility self-efficacy items was 44.6 and
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the mean self-efficacy of the sample was 65.4. This finding is an indication that the scales
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may assess the self-efficacy constructs more reliably among power wheelchair users with
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lower self-efficacy than the individuals in this sample. Our sample had a mean age of 56
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years, and was comprised of people who were very experienced with using a power
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wheelchair (i.e., 20 years) along with a high ability to use their wheelchair (i.e.,
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wheelchair skills test score of 87.5/100). Age, experience, and ability are well-known
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predictors of self-efficacy, with younger age, and more experience and ability predictive
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of higher self-efficacy.35 Therefore, it is plausible that our self-efficacy scales will
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provide more reliable measurements in power wheelchair users who are older and have
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less experience and skills with using their wheelchair than our sample.
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Limitations
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This study has several limitations. First, the raw data, collected using a 0 to 100 response
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format, was converted to at 0 to 10 response format for all analyses, as has been done in
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previous literature.3, 22 The reliability estimates are therefore based on recoded
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measurements. Research to evaluate the functioning of the 0 to 10 response format is
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warranted in future studies. Next, while the use of the subscale and total scores is
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informed by our findings, further investigation on their utility and differences in unique
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information provided is warranted and should be explored in any research proposing their
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use. Moreover, the PCA and Rasch analyses only examined the internal structure of the
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measurement scales. Future studies to validate the self-efficacy measurements against
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other constructs are necessary, as are test-retest investigations. Furthermore, our results
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are based primarily on quantitative statistical techniques. As a result, items of conceptual
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interest may have been removed. Finally, our sample size may be considered small for
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Rasch analyses to determine appropriate item fit. However, because we used very
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conservative fit parameters (derived using our sample size) in our analyses, we are
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confident that each of the items in the self-efficacy dimensions provide robust self-
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efficacy measurements
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Conclusion
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The WheelCon-P is comprised of two dimensions related to mobility and social situation
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self-efficacy. The scores from the 16-item WheelCon-P Short Form, and the 11-item
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Mobility and 5-item Social situation self-efficacy dimensions using a 0 to 10 response
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scale have good reliability. The usefulness of any of the measurements depends on the
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research question or clinical situation in which they are being considered.
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References
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1. Rushton PW, Miller WC, Kirby RL, Eng JJ. Measure for the assessment of confidence with manual wheelchair use (WheelCon-M) version 2.1: reliability and validity. J Rehabil Med. 2013;45(1):61-7. 2. Rushton PW, Miller WC, Lee Kirby R, Eng JJ, Yip J. Development and content validation of the Wheelchair Use Confidence Scale: a mixed-methods study. Disabil Rehabil Assist Technol. 2011;6(1):57-66. 3. Sakakibara BM, Miller WC, Rushton PW. Rasch analyses of the wheelchair use confidence scale. Arch Phys Med Rehabil. 2015;96(6):1036-44. 4. Miller W, Sakakibara B, Rushton P, editors. The prevalence of low confidence with using a wheelchair and its relationship to wheelchair skills. Gerontologist; 2012: OXFORD UNIV PRESS INC JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA. 5. Sakakibara BM, Miller WC. Prevalence of low mobility and self-management self-efficacy in manual wheelchair users and the association with wheelchair skills. Arch Phys Med Rehabil. 2015;96(7):1360-3. 6. Sakakibara BM, Miller WC, Eng JJ, Backman CL, Routhier F. Preliminary examination of the relation between participation and confidence in older manual wheelchair users. Arch Phys Med Rehabil. 2013;94(4):791-4. 7. Sakakibara BM, Miller WC, Routhier F, Backman CL, Eng JJ. Association between self-efficacy and participation in community-dwelling manual wheelchair users aged 50 years or older. Phys Ther. 2014;94(5):664-74. 8. Sakakibara BM, Miller WC, Eng JJ, Backman CL, Routhier F. Influences of wheelchair-related efficacy on life-space mobility in adults who use a wheelchair and live in the community. Phys Ther. 2014;94(11):1604-13. 9. Sakakibara BM, Miller WC, Souza M, Nikolova V, Best KL. Wheelchair skills training to improve confidence with using a manual wheelchair among older adults: a pilot study. Arch Phys Med Rehabil. 2013;94(6):1031-7. 10. Best KL, Miller WC, Huston G, Routhier F, Eng JJ. Pilot Study of a Peer-Led Wheelchair Training Program to Improve Self-Efficacy Using a Manual Wheelchair: A Randomized Controlled Trial. Arch Phys Med Rehabil. 2016;97(1):37-44. 11. Rousseau-Harrison K, Rochette A, Routhier F, Dessureault D, Thibault F, Cote O. Perceived impacts of a first wheelchair on social participation. Disabil Rehabil Assist Technol. 2012;7(1):37-44. 12. Shore S, Juillerat S. The impact of a low cost wheelchair on the quality of life of the disabled in the developing world. Med Sci Monit. 2012;18(9):Cr533-42. 13. Shore SL. Use of an economical wheelchair in India and Peru: impact on health and function. Med Sci Monit. 2008;14(12):Ph71-9. 14. Auger C, Demers L, Gelinas I, Jutai J, Fuhrer MJ, DeRuyter F. Powered mobility for middle-aged and older adults: systematic review of outcomes and appraisal of published evidence. Am J Phys Med Rehabil. 2008;87(8):666-80. 15. Kirby RL, Miller WC, Routhier F, Demers L, Mihailidis A, Polgar JM, et al. Effectiveness of a Wheelchair Skills Training Program for Powered Wheelchair Users: A Randomized Controlled Trial. Arch Phys Med Rehabil. 2015;96(11):2017-26.e3.
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16. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191-215. 17. Rushton PW, Smith E, Miller WC, Vaughan K. Measuring wheelchair confidence among power wheelchair users: an adaptation of the WheelCon-M using focus groups and a think aloud process. Disabil Rehabil Assist Technol. 2017;12(1):39-46. 18. Mortenson WB, Demers L, Rushton PW, Auger C, Routhier F, Miller WC. Exploratory Validation of a Multidimensional Power Wheelchair Outcomes Toolkit. Arch Phys Med Rehabil. 2015;96(12):2184-93. 19. Rushton PW, Routhier F, Miller WC. Measurement properties of the WheelCon for Powered Wheelchair Users. Arch Phys Med Rehabil. March 2017;Submitted. 20. Andrich D. A rating formulation for ordered response categories. Psychometrika. 1978;43(4):561-73. 21. Rushton PW, Kirby RL, Routhier F, Smith C. Measurement properties of the Wheelchair Skills Test-Questionnaire for powered wheelchair users. Disabil Rehabil Assist Technol. 2016;11(5):400-6. 22. Sakakibara BM, Miller WC, Backman CL. Rasch analyses of the Activitiesspecific Balance Confidence Scale with individuals 50 years and older with lower-limb amputations. Arch Phys Med Rehabil. 2011;92(8):1257-63. 23. Nandakumar R. Traditional Dimensionality versus Essential Dimensionality. Journal of Educational Measurement. 1991;28(2):99-117. 24. Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika. 1965;30(2):179-85. 25. O'Connor BP. SPSS and SAS programs for determining the number of components using parallel analysis and velicer's MAP test. Behav Res Methods Instrum Comput. 2000;32(3):396-402. 26. Norman GR, Streiner DL. Biostatistics: the bare essentials: PMPH-USA; 2008. 27. Gorsuch RL. Factor Analysis: second edition. Hillsdale, NJ: Lawrence Erlbaum; 1983. 28. Velozo CA, Seel RT, Magasi S, Heinemann AW, Romero S. Improving measurement methods in rehabilitation: core concepts and recommendations for scale development. Arch Phys Med Rehabil. 2012;93(8):S154-S63. 29. Linacre J. A User’s Guide to WINSTEPS MINISTEP Rasch-Model Computer Programs. 2009. Google Scholar. 2010. 30. De Ayala RJ. The theory and practice of item response theory: Guilford Publications; 2013. 31. Reise SP, Moore TM, Haviland MG. Bifactor models and rotations: exploring the extent to which multidimensional data yield univocal scale scores. J Pers Assess. 2010;92(6):544-59. 32. Masse LC, Heesch KC, Eason KE, Wilson M. Evaluating the properties of a stage-specific self-efficacy scale for physical activity using classical test theory, confirmatory factor analysis and item response modeling. Health Educ Res. 2006;21 Suppl 1:i33-46. 33. Jette AM, Tulsky DS, Ni P, Kisala PA, Slavin MD, Dijkers MP, et al. Development and initial evaluation of the spinal cord injury-functional index. Arch Phys Med Rehabil. 2012;93(10):1733-50.
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34. Nunnally JC, Bernstein I. Psychometric theory 3rd ed. 1994 McGraw-Hill. New York, NY. 1994. 35. Bandura A. Self-efficacy: The exercise of control: Macmillan; 1997. 36. Streiner DL, Norman GR. Health measurement scales: a practical guide to their development and use 4 edition Oxford University Press. New York. 2008.
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Table 1: Sample characteristics Study 118 (n=91)
Study 215 (n=98)
Combined (n=189)
mean±sd/frequency (%) 53.0±13.3 19.2±15.9 86.7±11.4
56.7±11.6 245.4±196.9 87.5±10.5**
44 (48.4) 47 (51.6)
51 (52.0) 47 (48.0)
95 (50.3) 94 (49.7)
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60.7±7.6 21.8±17.0 88.6±9.1*
15 (15.3) 19 (19.4) 6 (6.1) 5 (5.1) 3 (3.1) 50 (51.0)
36 (19.0) 38 (20.1) 20 (10.6) 8 (4.2) 8 (4.2) 79 (41.8)
44 (48.4)
42 (42.9)
86 (45.5)
26 (28.6)
48 (49.0)
74 (39.2)
65 (66.3) 95 (96.9) 42 (42.9) 69 (70.4)
134 (70.9) 184 (97.4) 86 (45.5) 128 (67.7)
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21 (23.1) 19 (20.9) 14 (15.4) 3 (3.3) 5 (5.5) 29 (31.5)
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Age Wheelchair-use experience (years) Wheelchair skills (0-100) Sex: Male Female Diagnosis: Spinal cord injury Multiple sclerosis Stroke Lower extremity amputation Arthritis Other (e.g., spina bifida, Cerebral Palsy, Parkinson’s disease) Requires assistance with power wheelchair Received formal training to use the power wheelchair Power wheelchair usage: Home Community Work Recreation *n=70; **n=168
69 (75.8) 89 (97.8) 44 (48.4) 59 (64.8)
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Table 2: Mobility self-efficacy items in order by difficulty: Fit statistics
Std score (SE)
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Infit Mnsq (ZSTD) 1.06 (0.30) 1.02 (0.20) 0.94 (-0.30)
Outfit Mnsq (ZSTD) 0.62 (-1.60) 0.64 (-1.70) 0.85 (-0.70)
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33.55 (1.46)
36.36 (1.24)
SC
41.36 (0.92)
43.28 (0.82)
1.02 (0.20) 1.25 (1.50)
1.23 (1.20) 0.96 (-0.10)
45.59 (0.72)
1.04 (0.03)
0.97 (-0.10)
46.75 (0.68)
1.04 (0.30)
1.14 (0.80)
48.25 (0.64)
1.02 (0.02)
1.12 (0.70)
48.96 (0.62)
1.29 (2.00) 1.23 (1.70)
1.35 (2.00) 1.28 (1.70)
52.72 (0.56)
1.26 (2.00)
1.35 (2.20)
44.63 (0.82)
1.11 (0.80)
1.05 (0.40)
44.65 (0.76)
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Mobility self-efficacy Items (n=11) Difficulty (SE) How confident are you that you can: 14 …drive your wheelchair along a dry, -0.79 flat paved sidewalk? (0.10) 15 …drive your wheelchair up a standard -0.59 (0.09) ramp, built to code (5° incline)? 1 …use all of the functions on your -0.23 controller, such as drive modes, tilt or (0.07) lift? 2 …select the correct drive mode to use -0.10 in different environments? (0.06) 36 …stop suddenly to avoid hitting a 0.00 moving object, such as a small child (0.05) or a dog? 26 …drive your wheelchair across 3m 0.07 (10ft) of flat, freshly mowed, dry (0.05) grass? 27 …move your wheelchair from the 0.15 sidewalk to the grass, with a 3cm (1”) (0.05) height difference? 34 …drive your wheelchair through a 0.26 crowd of people without hitting (0.05) anyone? 5 …manoeuvre your wheelchair in 0.31 small spaces, such as the bathroom? (0.04) 51 …continue to drive your wheelchair 0.35 in a situation that is making you feel (0.04) anxious or nervous? 29 …drive your wheelchair along a dirt 0.58 path or trail with some tree roots and (0.04) rocks? Mean 0.00 (0.06) SE=standard error; ZSTD=standardized fit statistic
49.50 (0.61)
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Table 3: Social situation self-efficacy items in order by difficulty: Fit statistics Social situation self-efficacy
How confident are you that you can: 44 …use strategies, such as humour, that will help people feel comfortable if they are unsure how to act because you use a wheelchair?
Outfit
Mnsq (ZSTD)
Mnsq (ZSTD)
Difficulty (SE)
Std score (SE)
-0.23 (0.05)
39.76 (1.01)
1.12 (0.70)
1.08 (0.50)
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Items (n=5)
Infit
…advocate for changes you want in your home, such as a roll-in shower?
-0.16 (0.05)
41.14 (0.94)
0.92 (-0.40)
0.76 (-1.30)
58
…advocate for your needs at work or school?
0.06 (0.04)
45.19 (0.80)
0.92 (-0.50)
0.83 (-1.00)
53
…know what to do if your wheelchair has suddenly stopped working?
0.16 (0.04)
47.01 (0.73)
1.25 (1.80)
1.39 (2.30)
59
…advocate for changes in your community, such as adding an accessible bus route in your neighbourhood?
0.16 (0.04)
47.06 (0.73)
0.94 (-0.40)
0.97 (-0.10)
0.00 (0.05)
44.03 (0.84)
1.03 (0.20)
1.01 (0.10)
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57
Mean
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SE=standard error; ZSTD=standardized fit statistic
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Table 4: WheelCon-P Short Form items in order by difficulty and fit statistics WheelCon-P Short Form Difficulty (SE)
How confident are you that you can:
Std score (SE)
Outfit
Mnsq Mnsq (ZSTD) (ZSTD)
RI PT
Items (n=16)
Infit
-0.69 (0.10)
36.28 (1.38)
1.06 (0.30)
0.62 (-1.50)
15 …drive your wheelchair up a standard ramp, built to code (5° incline)?
-0.52 (0.08)
38.72 (1.15)
0.95 (-0.10)
0.76 (-1.10)
1
…use all of the functions on your controller, such as drive modes, tilt or lift?
-0.23 (0.06)
2
…select the correct drive mode to use in different environments?
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14 …drive your wheelchair along a dry, flat paved sidewalk?
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42.87 (0.83)
0.93 (-0.30)
0.85 (-0.70)
44.40 (0.73)
1.00 (0.10)
1.22 (1.00)
44 …use strategies, such as humour, that will help people feel comfortable if they are unsure how to act because you use a wheelchair?
-0.08 (0.05)
44.87 (0.70)
1.01 (0.10)
0.92 (-0.30)
36 …stop suddenly to avoid hitting a moving object, such as a small child or a dog?
-0.04 (0.05)
45.48 (0.67)
1.05 (0.40)
0.75 (-1.30)
57 …advocate for changes you want in your home, such as a roll-in shower?
-0.02 (0.05)
45.79 (0.66)
1.14 (0.80)
0.97 (-0.10)
26 …drive your wheelchair across 3m (10ft) of flat, freshly mowed, dry grass?
0.01 (0.05)
46.20 (0.64)
0.85 (-0.09)
0.84 (-0.80)
27 …move your wheelchair from the sidewalk to the grass, with a 3cm (1”) height difference?
0.07 (0.04)
47.09 (0.60)
0.86 (-0.90)
1.02 (0.20)
34 …drive your wheelchair through a crowd of people without hitting anyone?
0.15 (0.04)
48.23 (0.56)
0.85 (-1.10)
1.11 (0.70)
58 …advocate for your needs at work or school?
0.16 (0.04)
48.26 (0.57)
1.36 (2.40)
1.41 (2.10)
5
0.19 (0.04)
48.80 (0.54)
1.18 (1.40)
1.55* (2.80)
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-0.12 (0.05)
…manoeuvre your wheelchair in small spaces, such as the bathroom?
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0.22 (0.04)
49.17 (0.53)
0.92 (-0.60)
1.09 (0.60)
53 …know what to do if your wheelchair has suddenly stopped working?
0.25 (0.04)
49.60 (0.52)
1.29 (2.20)
1.73* (3.70)
59 …advocate for changes in your community, such as adding an accessible bus route in your neighbourhood?
0.25 (0.04)
49.36 (0.52)
1.53* (3.70)
1.79* (3.90)
29 …drive your wheelchair along a dirt path or trail with some tree roots and rocks?
0.39 (0.03)
51.55 (0.48)
1.05 (0.50)
1.26 (1.60)
0.00 (0.05)
46.06 (0.69)
1.06 (0.50)
1.10 (0.60)
SC
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Mean
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51 …continue to drive your wheelchair in a situation that is making you feel anxious or nervous?
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TE D
SE=standard error; ZSTD=standardized fit statistic; *misfitting item
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Figure 1: Stages of the fit analyses Social Situation self-efficacy dimension (17-items)
Rasch model* 1: Outfit analysis
17-items removed
2-items removed
Rasch model 2: Infit analysis
14-items removed
10-items removed
Rasch model 3: Final analysis on resulting items
11-items
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Mobility self-efficacy dimension (42-items)
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5-items
Rasch model 4: WheelCon-P Short Form
16-items
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* subsequent Rasch models were applied to more model-fitting items
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Figure 2: Reliability and SEM of the Mobility self-efficacy, Social situation selfefficacy, and WheelCon-P Short Form measurements a. Mobility self-efficacy 30
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1.00
25
15
0.40
-
10
0.20 0.00 20
40
60
80
5 0
100
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0
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Reliability
20
0.60
SEM -
–
0.80
Measurements
b. Social situation self-efficacy 1.00
TE D
25
0.60
20
0.40
15
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10
0.20
5
AC C
0.00
0
c. WheelCon-P Short Form
0 20
40
60
Measurements
80
100
-
Reliability
30
SEM -
–
0.80
35
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1.00
30 25
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0.40
10
0.20
0.00 0
20
40
60
SC
5
80
AC C
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TE D
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Measurements
100
0
-
Reliability
20 0.60
SEM -
–
0.80
S0003-9993(17)31120-6
DOI:
10.1016/j.apmr.2017.09.004
Reference:
YAPMR 57031
To appear in:
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
Received Date: 9 June 2017 Revised Date:
28 August 2017
Accepted Date: 6 September 2017
Please cite this article as: Sakakibara BM, Miller WC, Rushton PW, Polgar JM, Rasch analyses of the Wheelchair Use Confidence Scale for power wheelchair users, ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION (2017), doi: 10.1016/j.apmr.2017.09.004. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Rasch analyses of the Wheelchair Use Confidence Scale for power wheelchair users Brodie M. Sakakibara, PhD1-3; William C. Miller, PhD, FCAOT3,4; Paula W. Rushton, PhD5,6; Jan Miller Polgar, PhD7. Faculty of Health Sciences, Simon Fraser University; 2Department of Physical Therapy, University of British Columbia; 3Rehabilitation Research Program, Vancouver Coastal Health Research Institute; 4Department of Occupational Therapy and Occupational Sciences, University of British Columbia; 5School of Rehabilitation, Faculty of Medicine, Université de Montréal; 6Centre de réadaptation Marie Enfant, CHU; 7School of Occupational Therapy, University of Western Ontario;.
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This work was supported by the Canadian Institutes of Health Research (Postdoctoral Scholarship to BMS and Team Grant AMG 100925 to CanWheel), Michael Smith Foundation for Health Research (Postdoctoral Fellowship to BMS). Copies of the Wheelchair Use Confidence Scales may be obtained from: http://millerresearch.osot.ubc.ca/tools/mobility-outcome-tools-2/wheelchair-useconfidence-scale-wheelcon/ Running head: Rasch analyses of the WheelCon-P Word count main text: 3270 Word count abstract: 249
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Corresponding author: Paula W. Rushton, PhD Centre de réadaptation Marie Enfant, CHU Sainte-Justine, 5200 rue Bélanger, Montréal, QC, H1T 1C9, Canada, Tel: 514-374-1710 x 8003; Fax: 514-723-7116; Email: [email protected]
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Abstract
2
Objective: To examine the dimensionality of the Wheelchair Use Confidence Scale for
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power wheelchair users (WheelCon-P); identify items that do not fit the Rasch Rating
4
Scale model as well as redundant items for elimination; and determine the standard errors
5
of measurement and reliability estimates for the entire range of measurements.
6
Design: Secondary analysis of cross-sectional data.
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Setting: Community.
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Participants: Volunteer participants (n=189) from British Columbia, Ontario, Quebec,
9
and Nova Scotia, Canada were recruited for this study. The mean age of the sample was
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1
56.7 (SD=13.0) years, and the mean years of wheelchair use experience was 20.4
11
(SD=16.4) years. The sample was evenly divided by sex. The three most common
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diagnoses accounting for wheelchair use were: multiple sclerosis (20.1%), spinal cord
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injury (19.0%) and stroke (10.6%).
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Intervention: None.
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Measurement: 59-item WheelCon-P.
16
Results: Principal components analyses confirmed the presence of two self-efficacy
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dimensions: mobility and social situation. Eleven mobility items, and five social situation
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items fit the Rasch Rating Scale model. Three items misfit the model using all 16 items
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(i.e., WheelCon-P Short Form). In each of the mobility, social situation, and WheelCon-P
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Short Form range of measurements, the two lowest and two highest measures had internal
21
consistency reliability estimates below 0.70; all other measures had reliability estimates
22
above 0.70.
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10
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Conclusion: The WheelCon-P is comprised of two self-efficacy dimensions related to
24
mobility and social situations. The scores from the WheelCon-P Short Form, and the 11-
25
item mobility and 5-item social situation dimensions using a 0 to 10 response scale have
26
good reliability.
27
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Key words: self-efficacy; wheelchairs; measurement; Rasch analyses; principal
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components analyses; wheelchair confidence.
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List of Abbreviations:
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1. WheelCon-P: Wheelchair Use Confidence Scale for power wheelchair users
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2. PCA: principal components analysis
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3. ZSTD: standardized fit statistics
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4. SEM: standard error of measurement
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2
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The Wheelchair Use Confidence Scale for Manual Wheelchair Users (WheelCon-M)1, 2 is
37
a 65-item questionnaire used to measure confidence (i.e., self-efficacy) with using a
38
manual wheelchair in a variety of challenging situations related to the physical
39
environment and performing activities, as well as self-efficacy related to knowledge and
40
problem solving, advocacy, social situations and managing emotions. The validity of the
41
WheelCon-M measurements has been examined using several rigorous methods
42
including qualitative interviews,2 hypothesis testing,1 test re-test examinations,1 as well as
43
quantitative techniques based on both Classical Test1 and Item Response3 theories. As a
44
result, the WheelCon-M has been used to develop a body of evidence demonstrating
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wheelchair use self-efficacy as an important clinical focus and outcome.4-10
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36
46
The validity of evidence derived from the WheelCon-M measurements is specific to
48
manual wheelchair users, and therefore is of little relevance for the advancement of
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research in people who use powered wheelchairs for mobility. However, similar to
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research among individuals with mobility disabilities demonstrating the health,
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functional, and quality of life benefits after acquiring a manual wheelchair,11-13 research
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shows the positive effects of power wheelchair use on similar outcomes.14 It is then
53
plausible that self-efficacy specific to powered wheelchair use will have implications on
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rehabilitation outcomes similar to that previously reported among people who use manual
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wheelchairs.7, 8 Interestingly, power wheelchair users do not optimize the use of their
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wheelchair despite having adequate operational skills.15 This leads to speculation that: (i)
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many of these individuals may not achieve desired levels of community or social
58
participation; and (ii) improvements to wheelchair use self-efficacy may facilitate more
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59
desired levels of participation, given that self-efficacy is a more accurate predictor of
60
behaviour than ability.16
61
Recently, Rushton et al. reported on the modification of the WheelCon-M into a version
63
applicable for power wheelchair users, the WheelCon-P.17 Investigations are beginning to
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report on the use of the WheelCon-P as an important outcome measure,15, 18, 19 thereby
65
warranting further rigorous examination of the WheelCon-P’s measurement properties.
66
The objectives of this study are to: 1) examine the dimensionality of the WheelCon-P; 2)
67
identify items that do not fit the Rasch Rating Scale model20 as well as redundant items
68
that could be considered for elimination (i.e., to create a WheelCon-P Short Form); 3) and
69
determine the standard errors of measurement and reliability estimates for the entire
70
range of measurements.
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METHODS
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Study Design and Participants
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Data used in this secondary analysis were combined from two independent studies15, 18
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with similar inclusion criteria: power wheelchair-users; ≥19 years of age; communicates
76
in English or French; and able to provide informed consent.
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72
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Volunteer participants were recruited from British Columbia (Vancouver), Ontario
79
(Toronto, London), Quebec (Montreal, Quebec City), and Nova Scotia (Halifax), Canada
80
between 2010 and 2014 using letters of information sent by clinicians and wheelchair
81
vendors. Advocacy/community groups also provided study information to their
4
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82
membership. After providing informed consent, participants met with a trained research
83
assistant for data collection. The ethics boards from all relevant institutions approved the
84
studies.
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Measures
87
The 59-item WheelCon-P was used to capture the power wheelchair use self-efficacy
88
construct.17 The items focus on self-efficacy related to knowledge of the wheelchair and
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problem solving, emotions, performance of mobility skills, activities performed as well as
90
social and advocacy interactions. Item responses range from 0 to 100. A mean score is
91
derived with higher scores indicating higher self-efficacy.
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86
92
A demographic information form was used to collect data on personal, health, and
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wheelchair-related variables, and the Wheelchair Skills Test-Questionnaire for power
95
wheelchair users21 to characterize capacity to use a power wheelchair. Total scores on the
96
Wheelchair Skills Test-Questionnaire range from 0 to 100, with higher scores indicating
97
better ability to use the power wheelchair.21
98
Data analyses
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99
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93
100
Descriptive statistics were used to characterize the sample. Results from categorical
101
variables were calculated as percentages and continuous variables as means and standard
102
deviations.
103
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For this study’s analyses, we divided the WheelCon-P items into two broad conceptual
105
areas based on whether the item asked about physical (n=42 items, labelled as the
106
mobility items) or social (n=17 items, labelled as the social situation items) aspects of
107
wheelchair use. The division of items was done to increase the specificity of our analyses,
108
and also because our previous evaluation of the WheelCon-M items had a similar
109
division.3 Furthermore, we modified the 0 to 100 response format to a 0 to 10 format (0 =
110
not confident and 10 = completely confident), as has been done in previous literature.3, 22
111
We used the modified total scores for all analyses on each of the conceptual areas.
112
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Testing Rasch Assumptions
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Unidimensionality: Principal Components Analyses (PCA) along with promax rotation
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were used to assess for ‘essential’ unidimesionality23 (i.e., one dominant dimension in the
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presence of one or more minor dimensions with small influences on measurement). Prior
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to PCA, we conducted parallel analyses to determine how many statistically significant
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dimensions were in each of the mobility and social situation dimensions,24, 25 and thus
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how many dimensions to force in the PCA. The inter-item correlation matrices were then
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examined to confirm the presence of underlying dimensions to be analyzed. Adequate
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levels of inter-item correlations were determined if 20% of the correlations were above
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0.3026 and the Kaiser-Meyer-Olkin Measure of Sampling Adequacy value was >0.70.26
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After performing the PCAs, items not meeting the minimal loading value of 0.38,
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calculated using the formula 5.15/√(n-2),26 were considered for elimination. Essential
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unidimensionality was considered satisfied if the first dimension explained ≥30% of the
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variance26 and if the first to second eigenvalue ratio ≥3.0.27
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Local independence: We examined the correlation coefficients of the inter-item residuals.
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Correlation coefficients greater than 0.20 indicated a violation of the local independence
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assumption.28
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Assessing item fit and item elimination – Item mean-square fit statistics were assessed
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using the Rasch Rating Scale Model.20 Infit statistics assess unexpected responses to
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items that have a difficulty level ‘near’ one’s reported self-efficacy estimate, whereas
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outfit statistics assess unexpected responses to items with self-efficacy levels ‘far’ from
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one’s reported self-efficacy.29 Fit statistics follow a chi-square distribution and have an
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expected value of 1. Values substantially greater than 1 reflect more variability than
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expected, and values less than 1 reflect less variability than expected.30 We determined
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acceptable infit and outfit statistics to range between 0.85 to 1.15, and 0.56 to 1.44
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calculated using the formulas 1±2/√N and 1±6/√N, respectively.30 Items with fit statistics
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not within the acceptable ranges were eliminated.
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We performed a two stage fit analysis for each of the Mobility and Social Situation
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conceptual areas. In following Linacre’s recommendations for the diagnosis of misfits,
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items with outfit statistics outside the acceptable range were first examined.29 Because
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these items elicit unexpected outlying responses (e.g. unexpectedly high self-efficacy
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ratings to difficult items by individuals with lower self-efficacy), they were considered
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for elimination first. After removing the items with misfitting outfit statistics, the
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analyses were re-ran on the more model-fitting items, and the infit statistics of the
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remaining items were examined. Similar to items with misfitting outfit statistics, items
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with infit statistics outside the acceptable range were considered for elimination. We then
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examined for potential item redundancy. Items were considered redundant when there
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was overlap in both item difficulty ± SEM and conceptual content. When there was
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redundancy, one item was considered for elimination after discussion with the research
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team.
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After eliminating the misfitting and redundant items, we ran a final Rating Scale model
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for each dimension. Because it is common for items to misfit in the more model-fitting
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context,29 we considered item infit and outfit statistics in the range of 0.50 and 1.50 to be
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productive for measurement.29 Finally, while it is common for psychometric
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investigations to observe evidence for both single and multiple dimensions within a
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measurement tool, researchers and clinicians have been shown to favour the use of total
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scores over subscale scores.31 Furthermore, because research also indicates the
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plausibility that subscale scores yield little unique information beyond total scores,31 for
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exploratory purposes we combined the items from each WheelCon-P dimension and
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analyzed the overall fit using a Rasch Rating Scale model, thereby creating a WheelCon-
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P Short Form. Figure 1 presents the stages in our fit analyses.
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Reliability – SEM and reliability were estimated for the entire range of measurements.
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SEMs were converted into coefficients similar to Cronbach’s alpha using the formula:
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1/1+logit SEM2.32, 33 Reliability estimates ≥0.70 were considered acceptable.34 For ease
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of interpretation, the Rasch measurements in logits were linearly transformed29 into a
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self-efficacy continuum ranging from 0 to 100.
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Winsteps version 3.92.129 and SPSS version 23.0 (IBM, Armonk, NY) were used to
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perform the analyses.
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RESULTS
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Participants
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The mean age of the combined sample (n=189) was 56.7 (SD=13.0) years, and the mean
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years of wheelchair use experience was 20.4 (SD=16.4). The sample was evenly divided
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by sex. The three most common diagnoses accounting for wheelchair use were: multiple
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sclerosis (20.1%), spinal cord injury (n=19.0%) and stroke (n=10.6%). The mean
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Wheelchair Skills Test score was 87.5/100 (SD=10.5). Table 1 presents sample
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characteristics in more detail.
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Testing Rasch Assumptions
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Unidimensionality – Parallel analysis of the 42 mobility self-efficacy items revealed three
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statistically significant dimensions. The subsequent PCA of these dimensions, which had
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sufficient inter-item correlations, resulted in two items that did not load on any dimension
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(i.e., know when to charge wheelchair batteries; can find a place to charge batteries when
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not at home), one dominant dimension accounting for 34.3% of the variance with an
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eigenvalue of 14.4, a second dimension accounting for 10.6% of the variance with an
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eigenvalue of 4.4, and a third dimension accounting for 6.1% of the variance with an
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eigenvalue less of 2.5. Of the 30 items that loaded on the second dimension, 27 also
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cross-loaded onto the first dimension. The three items that were unique to the second
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dimension asked about self-efficacy to: open and go through a spring loaded door; drive
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the wheelchair up a single 5cm step to change levels between rooms; and drive the
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wheelchair down a single 5cm step to change levels between rooms. These three items
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were conceptually deemed to be no different than other items in the first dimension
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asking about moving the wheelchair in various environments and performing activities.
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Thus, given the conceptual relevance of the two non-loading items, similarities between
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the first and second dimensions, and the eigenvalue ratio of 3.3 between the first and
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second dimension, we determined all 42-items to comprise a single dimensional for
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subsequent analyses.
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Parallel analysis of the 17 social situation self-efficacy items revealed two statistically
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significant dimensions. Principal Component Analysis of these dimensions revealed one
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dominant dimension accounting for 39.6% of the variance with an eigenvalue of 6.7, and
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a second dimension accounting for 9.2% of the variance with an eigenvalue of 1.6,
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representing an eigenvalue ratio of 4.2. Thus, we determined a unidimensional 17-item
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solution for subsequent analyses.
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Local independence – All inter-item residual correlations were below 0.20 in both
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dimensions thereby satisfying the local independence assumption.
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Assessing item fit and item elimination
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Mobility self-efficacy – Of the 42 items, 31 items had misfitting outfit (n = 17 items
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related to activities performed when in a wheelchair e.g, can transfer from your
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wheelchair to your bed, can make a meal or snack whil using your wheelchair) and infit
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(n = 14 items related to complex tasks e.g., can open, go through, and then close a door,
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can manoeuvre your wheelchair to press the crosswalk button and cross the street before
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the traffic light changes) statistics. No items were deemed to be redundant. After
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removing the misfitting items, a final Rating Scale Model was applied to the 11
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remaining items. The fit statistics of these 11 items were all within the acceptable range.
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Table 2 presents the fit statistics of the 11 items, organized by increasing difficulty.
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With the exception of the two lowest and two highest measurements, all other measures
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(96% of all measures) had reliability estimates ≥0.70. Measurements in the range of 35.0
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to 52.6 had the highest reliability estimates (0.98) and low SEM, as shown in Figure 2a.
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The mean item difficulty of this dimension was 44.6 (SD=5.5), whereas the sample’s
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mean self-efficacy was 65.4 (SD=17.7).
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Social situation self-efficacy – Of the 17 items, 12 items had misfitting outfit (n = 2 items
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related to using alternative modes of transportation e.g. public transportation and
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airplanes) and infit (n = 10 items related to self-presentation and interaction with others
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e.g., can present yourself as you wish to be seen when you are in public and feel people
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are watching you, can ask people to move out of your way while driving your wheelchair,
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can ask a stranger for help) statistics. After removing these items, a final Rating Scale
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Model was applied to the five remaining items. The fit statistics of these five items were
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within the acceptable range. Table 3 presents the fit statistics of the five items, organized
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by increasing difficulty.
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With the exception of the two lowest and two highest measurements, all other measures
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(92% of all measurements) had reliability estimates ≥0.70. Measurements in the range of
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38.6 to 45.2 had the highest reliability estimates (0.98) and low SEM, as shown in Figure
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2b. The mean item difficulty of this dimension was 44.0 (SD=3.0), whereas the sample’s
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mean social situation self-efficacy was 66.8 (SD=22.8). Table 4 presents the five items
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organized by increasing difficulty.
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The 16-item WheelCon-P Short Form – After combining the items from both dimensions
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and running another Rating Scale Model, one item had an infit statistic greater than 1.5,
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and three items had outfits statistics greater than 1.5, as shown in Table 4. With the
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exception of the two lowest and two highest measurements, all other measures (98% of
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all measurements) had reliability estimates ≥0.70. Measurements in the range of 38.5 to
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52.8 had the highest reliability estimates (0.99) and low SEM, as shown in Figure 2c. The
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mean item difficulty was 46.1 (SD=3.9), whereas the sample’s mean self-efficacy was
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61.9 (SD=15.9).
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Discussion
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Situation specific self-efficacy has been shown to influence choices and decisions,
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efforts, perseverance, and motivation.35 For these reasons, self-efficacy is an important
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consideration in rehabilitation because it may influence an individual’s adherence to
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rehabilitation programs, goal setting, efforts and persistence. Moreover, low self-efficacy
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with manual wheelchair use appears to be a remediable condition that may be improved
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via clinical intervention.9, 10 However, because self-efficacy is situation specific, and up
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until recently there has not been an adequate tool to measure self-efficacy specific to
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power wheelchair use, our knowledge of its relevance and importance in power
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wheelchair related research is at present minimal.
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In this study, we continue our efforts to provide rehabilitation researchers and clinicians
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with robust self-efficacy measurements tools to help ensure optimal research and
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rehabilitation outcomes among wheelchair users.1-3, 17 More specifically, we advance the
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foundational and developmental work of Rushton et al.17 by evaluating the measurement
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properties of the WheelCon-P using contemporary measurement methods. In our
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application of PCA, we confirmed the unidimensionality of the mobility and social
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situation dimensions using multiple criteria. Although parallel analysis provided a general
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indication of the presence of three and two dimensions within the mobility and social
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situation items, respectively, PCA indicated redundancy in item loadings between
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dimensions, as well as non-important eigenvalues in lower level dimensions. As a result,
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we performed subsequent Rasch analyses on single dimension solutions explaining more
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than adequate levels of variability in the mobility (34.3%) and social situation self-
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efficacy (39.6%) responses.
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Our results show a WheelCon-P Short Form with 2 dimensions (11-item mobility and 5-
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item social situations) that can have three possible scores: a composite score, a mobility
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sub-scale score and a social situations sub-scale score. The resulting mobility and social
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situation dimensions are comprised of items asking about distinct forms of self-efficacy.
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Whereas the mobility items ask about self-efficacy using the various functions of the
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power wheelchair and negotiating indoor and outdoor environments, the social situation
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items ask about self-efficacy related to advocating for one-self, knowledge, and problem
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solving. By separating the WheelCon-P items into two situation specific dimensions,
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researchers will be able to develop more robust and precise models of rehabilitation
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outcomes using the specific forms of powered wheelchair use self-efficacy measures as
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predictor variables. Importantly, the results of these predictive models will inform the
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development of targeted interventions to enhance mobility or social situation self-efficacy
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in power wheelchair users. Furthermore, our measures will allow clinicians to more
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efficiently assess and subsequently provide targeted therapeutic interventions to remedy
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different forms of low self-efficacy. Although we also provide a composite measure of
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self-efficacy with adequate reliability (i.e., the WheelCon-P Short Form), these
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measurements do not function as well as those from the individual mobility and social
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situation dimensions, as indicated by the number of misfitting items. We anticipate that
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the more specific mobility and social situation dimensions will be used more frequently
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than the composite short form, however, we provide the short form as an efficient
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alternative for those valuing the original 59-item WheelCon-P.
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A key property of Rasch models is sample invariance. This property allows for the item
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and respondent characteristics to be estimated independent of each other.30, 36 As such, we
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are able to determine the ‘difficulty’ of each item and mean difficulty of the items
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combined, as well as the self-efficacy level of each person and mean self-efficacy of the
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sample. Our findings indicate that the mean difficulty of items in each of the mobility,
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social situation, and short form scales are lower than the mean self-efficacy of the
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sample. For example, the mean difficulty of the mobility self-efficacy items was 44.6 and
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the mean self-efficacy of the sample was 65.4. This finding is an indication that the scales
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may assess the self-efficacy constructs more reliably among power wheelchair users with
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lower self-efficacy than the individuals in this sample. Our sample had a mean age of 56
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years, and was comprised of people who were very experienced with using a power
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wheelchair (i.e., 20 years) along with a high ability to use their wheelchair (i.e.,
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wheelchair skills test score of 87.5/100). Age, experience, and ability are well-known
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predictors of self-efficacy, with younger age, and more experience and ability predictive
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of higher self-efficacy.35 Therefore, it is plausible that our self-efficacy scales will
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provide more reliable measurements in power wheelchair users who are older and have
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less experience and skills with using their wheelchair than our sample.
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Limitations
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This study has several limitations. First, the raw data, collected using a 0 to 100 response
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format, was converted to at 0 to 10 response format for all analyses, as has been done in
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previous literature.3, 22 The reliability estimates are therefore based on recoded
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measurements. Research to evaluate the functioning of the 0 to 10 response format is
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warranted in future studies. Next, while the use of the subscale and total scores is
331
informed by our findings, further investigation on their utility and differences in unique
332
information provided is warranted and should be explored in any research proposing their
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use. Moreover, the PCA and Rasch analyses only examined the internal structure of the
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measurement scales. Future studies to validate the self-efficacy measurements against
335
other constructs are necessary, as are test-retest investigations. Furthermore, our results
336
are based primarily on quantitative statistical techniques. As a result, items of conceptual
337
interest may have been removed. Finally, our sample size may be considered small for
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Rasch analyses to determine appropriate item fit. However, because we used very
339
conservative fit parameters (derived using our sample size) in our analyses, we are
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confident that each of the items in the self-efficacy dimensions provide robust self-
341
efficacy measurements
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Conclusion
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The WheelCon-P is comprised of two dimensions related to mobility and social situation
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self-efficacy. The scores from the 16-item WheelCon-P Short Form, and the 11-item
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Mobility and 5-item Social situation self-efficacy dimensions using a 0 to 10 response
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scale have good reliability. The usefulness of any of the measurements depends on the
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research question or clinical situation in which they are being considered.
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References
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1. Rushton PW, Miller WC, Kirby RL, Eng JJ. Measure for the assessment of confidence with manual wheelchair use (WheelCon-M) version 2.1: reliability and validity. J Rehabil Med. 2013;45(1):61-7. 2. Rushton PW, Miller WC, Lee Kirby R, Eng JJ, Yip J. Development and content validation of the Wheelchair Use Confidence Scale: a mixed-methods study. Disabil Rehabil Assist Technol. 2011;6(1):57-66. 3. Sakakibara BM, Miller WC, Rushton PW. Rasch analyses of the wheelchair use confidence scale. Arch Phys Med Rehabil. 2015;96(6):1036-44. 4. Miller W, Sakakibara B, Rushton P, editors. The prevalence of low confidence with using a wheelchair and its relationship to wheelchair skills. Gerontologist; 2012: OXFORD UNIV PRESS INC JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA. 5. Sakakibara BM, Miller WC. Prevalence of low mobility and self-management self-efficacy in manual wheelchair users and the association with wheelchair skills. Arch Phys Med Rehabil. 2015;96(7):1360-3. 6. Sakakibara BM, Miller WC, Eng JJ, Backman CL, Routhier F. Preliminary examination of the relation between participation and confidence in older manual wheelchair users. Arch Phys Med Rehabil. 2013;94(4):791-4. 7. Sakakibara BM, Miller WC, Routhier F, Backman CL, Eng JJ. Association between self-efficacy and participation in community-dwelling manual wheelchair users aged 50 years or older. Phys Ther. 2014;94(5):664-74. 8. Sakakibara BM, Miller WC, Eng JJ, Backman CL, Routhier F. Influences of wheelchair-related efficacy on life-space mobility in adults who use a wheelchair and live in the community. Phys Ther. 2014;94(11):1604-13. 9. Sakakibara BM, Miller WC, Souza M, Nikolova V, Best KL. Wheelchair skills training to improve confidence with using a manual wheelchair among older adults: a pilot study. Arch Phys Med Rehabil. 2013;94(6):1031-7. 10. Best KL, Miller WC, Huston G, Routhier F, Eng JJ. Pilot Study of a Peer-Led Wheelchair Training Program to Improve Self-Efficacy Using a Manual Wheelchair: A Randomized Controlled Trial. Arch Phys Med Rehabil. 2016;97(1):37-44. 11. Rousseau-Harrison K, Rochette A, Routhier F, Dessureault D, Thibault F, Cote O. Perceived impacts of a first wheelchair on social participation. Disabil Rehabil Assist Technol. 2012;7(1):37-44. 12. Shore S, Juillerat S. The impact of a low cost wheelchair on the quality of life of the disabled in the developing world. Med Sci Monit. 2012;18(9):Cr533-42. 13. Shore SL. Use of an economical wheelchair in India and Peru: impact on health and function. Med Sci Monit. 2008;14(12):Ph71-9. 14. Auger C, Demers L, Gelinas I, Jutai J, Fuhrer MJ, DeRuyter F. Powered mobility for middle-aged and older adults: systematic review of outcomes and appraisal of published evidence. Am J Phys Med Rehabil. 2008;87(8):666-80. 15. Kirby RL, Miller WC, Routhier F, Demers L, Mihailidis A, Polgar JM, et al. Effectiveness of a Wheelchair Skills Training Program for Powered Wheelchair Users: A Randomized Controlled Trial. Arch Phys Med Rehabil. 2015;96(11):2017-26.e3.
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16. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191-215. 17. Rushton PW, Smith E, Miller WC, Vaughan K. Measuring wheelchair confidence among power wheelchair users: an adaptation of the WheelCon-M using focus groups and a think aloud process. Disabil Rehabil Assist Technol. 2017;12(1):39-46. 18. Mortenson WB, Demers L, Rushton PW, Auger C, Routhier F, Miller WC. Exploratory Validation of a Multidimensional Power Wheelchair Outcomes Toolkit. Arch Phys Med Rehabil. 2015;96(12):2184-93. 19. Rushton PW, Routhier F, Miller WC. Measurement properties of the WheelCon for Powered Wheelchair Users. Arch Phys Med Rehabil. March 2017;Submitted. 20. Andrich D. A rating formulation for ordered response categories. Psychometrika. 1978;43(4):561-73. 21. Rushton PW, Kirby RL, Routhier F, Smith C. Measurement properties of the Wheelchair Skills Test-Questionnaire for powered wheelchair users. Disabil Rehabil Assist Technol. 2016;11(5):400-6. 22. Sakakibara BM, Miller WC, Backman CL. Rasch analyses of the Activitiesspecific Balance Confidence Scale with individuals 50 years and older with lower-limb amputations. Arch Phys Med Rehabil. 2011;92(8):1257-63. 23. Nandakumar R. Traditional Dimensionality versus Essential Dimensionality. Journal of Educational Measurement. 1991;28(2):99-117. 24. Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika. 1965;30(2):179-85. 25. O'Connor BP. SPSS and SAS programs for determining the number of components using parallel analysis and velicer's MAP test. Behav Res Methods Instrum Comput. 2000;32(3):396-402. 26. Norman GR, Streiner DL. Biostatistics: the bare essentials: PMPH-USA; 2008. 27. Gorsuch RL. Factor Analysis: second edition. Hillsdale, NJ: Lawrence Erlbaum; 1983. 28. Velozo CA, Seel RT, Magasi S, Heinemann AW, Romero S. Improving measurement methods in rehabilitation: core concepts and recommendations for scale development. Arch Phys Med Rehabil. 2012;93(8):S154-S63. 29. Linacre J. A User’s Guide to WINSTEPS MINISTEP Rasch-Model Computer Programs. 2009. Google Scholar. 2010. 30. De Ayala RJ. The theory and practice of item response theory: Guilford Publications; 2013. 31. Reise SP, Moore TM, Haviland MG. Bifactor models and rotations: exploring the extent to which multidimensional data yield univocal scale scores. J Pers Assess. 2010;92(6):544-59. 32. Masse LC, Heesch KC, Eason KE, Wilson M. Evaluating the properties of a stage-specific self-efficacy scale for physical activity using classical test theory, confirmatory factor analysis and item response modeling. Health Educ Res. 2006;21 Suppl 1:i33-46. 33. Jette AM, Tulsky DS, Ni P, Kisala PA, Slavin MD, Dijkers MP, et al. Development and initial evaluation of the spinal cord injury-functional index. Arch Phys Med Rehabil. 2012;93(10):1733-50.
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34. Nunnally JC, Bernstein I. Psychometric theory 3rd ed. 1994 McGraw-Hill. New York, NY. 1994. 35. Bandura A. Self-efficacy: The exercise of control: Macmillan; 1997. 36. Streiner DL, Norman GR. Health measurement scales: a practical guide to their development and use 4 edition Oxford University Press. New York. 2008.
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Table 1: Sample characteristics Study 118 (n=91)
Study 215 (n=98)
Combined (n=189)
mean±sd/frequency (%) 53.0±13.3 19.2±15.9 86.7±11.4
56.7±11.6 245.4±196.9 87.5±10.5**
44 (48.4) 47 (51.6)
51 (52.0) 47 (48.0)
95 (50.3) 94 (49.7)
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60.7±7.6 21.8±17.0 88.6±9.1*
15 (15.3) 19 (19.4) 6 (6.1) 5 (5.1) 3 (3.1) 50 (51.0)
36 (19.0) 38 (20.1) 20 (10.6) 8 (4.2) 8 (4.2) 79 (41.8)
44 (48.4)
42 (42.9)
86 (45.5)
26 (28.6)
48 (49.0)
74 (39.2)
65 (66.3) 95 (96.9) 42 (42.9) 69 (70.4)
134 (70.9) 184 (97.4) 86 (45.5) 128 (67.7)
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21 (23.1) 19 (20.9) 14 (15.4) 3 (3.3) 5 (5.5) 29 (31.5)
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Age Wheelchair-use experience (years) Wheelchair skills (0-100) Sex: Male Female Diagnosis: Spinal cord injury Multiple sclerosis Stroke Lower extremity amputation Arthritis Other (e.g., spina bifida, Cerebral Palsy, Parkinson’s disease) Requires assistance with power wheelchair Received formal training to use the power wheelchair Power wheelchair usage: Home Community Work Recreation *n=70; **n=168
69 (75.8) 89 (97.8) 44 (48.4) 59 (64.8)
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Table 2: Mobility self-efficacy items in order by difficulty: Fit statistics
Std score (SE)
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Infit Mnsq (ZSTD) 1.06 (0.30) 1.02 (0.20) 0.94 (-0.30)
Outfit Mnsq (ZSTD) 0.62 (-1.60) 0.64 (-1.70) 0.85 (-0.70)
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33.55 (1.46)
36.36 (1.24)
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41.36 (0.92)
43.28 (0.82)
1.02 (0.20) 1.25 (1.50)
1.23 (1.20) 0.96 (-0.10)
45.59 (0.72)
1.04 (0.03)
0.97 (-0.10)
46.75 (0.68)
1.04 (0.30)
1.14 (0.80)
48.25 (0.64)
1.02 (0.02)
1.12 (0.70)
48.96 (0.62)
1.29 (2.00) 1.23 (1.70)
1.35 (2.00) 1.28 (1.70)
52.72 (0.56)
1.26 (2.00)
1.35 (2.20)
44.63 (0.82)
1.11 (0.80)
1.05 (0.40)
44.65 (0.76)
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Mobility self-efficacy Items (n=11) Difficulty (SE) How confident are you that you can: 14 …drive your wheelchair along a dry, -0.79 flat paved sidewalk? (0.10) 15 …drive your wheelchair up a standard -0.59 (0.09) ramp, built to code (5° incline)? 1 …use all of the functions on your -0.23 controller, such as drive modes, tilt or (0.07) lift? 2 …select the correct drive mode to use -0.10 in different environments? (0.06) 36 …stop suddenly to avoid hitting a 0.00 moving object, such as a small child (0.05) or a dog? 26 …drive your wheelchair across 3m 0.07 (10ft) of flat, freshly mowed, dry (0.05) grass? 27 …move your wheelchair from the 0.15 sidewalk to the grass, with a 3cm (1”) (0.05) height difference? 34 …drive your wheelchair through a 0.26 crowd of people without hitting (0.05) anyone? 5 …manoeuvre your wheelchair in 0.31 small spaces, such as the bathroom? (0.04) 51 …continue to drive your wheelchair 0.35 in a situation that is making you feel (0.04) anxious or nervous? 29 …drive your wheelchair along a dirt 0.58 path or trail with some tree roots and (0.04) rocks? Mean 0.00 (0.06) SE=standard error; ZSTD=standardized fit statistic
49.50 (0.61)
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Table 3: Social situation self-efficacy items in order by difficulty: Fit statistics Social situation self-efficacy
How confident are you that you can: 44 …use strategies, such as humour, that will help people feel comfortable if they are unsure how to act because you use a wheelchair?
Outfit
Mnsq (ZSTD)
Mnsq (ZSTD)
Difficulty (SE)
Std score (SE)
-0.23 (0.05)
39.76 (1.01)
1.12 (0.70)
1.08 (0.50)
RI PT
Items (n=5)
Infit
…advocate for changes you want in your home, such as a roll-in shower?
-0.16 (0.05)
41.14 (0.94)
0.92 (-0.40)
0.76 (-1.30)
58
…advocate for your needs at work or school?
0.06 (0.04)
45.19 (0.80)
0.92 (-0.50)
0.83 (-1.00)
53
…know what to do if your wheelchair has suddenly stopped working?
0.16 (0.04)
47.01 (0.73)
1.25 (1.80)
1.39 (2.30)
59
…advocate for changes in your community, such as adding an accessible bus route in your neighbourhood?
0.16 (0.04)
47.06 (0.73)
0.94 (-0.40)
0.97 (-0.10)
0.00 (0.05)
44.03 (0.84)
1.03 (0.20)
1.01 (0.10)
TE D
M AN U
SC
57
Mean
AC C
EP
SE=standard error; ZSTD=standardized fit statistic
ACCEPTED MANUSCRIPT
Table 4: WheelCon-P Short Form items in order by difficulty and fit statistics WheelCon-P Short Form Difficulty (SE)
How confident are you that you can:
Std score (SE)
Outfit
Mnsq Mnsq (ZSTD) (ZSTD)
RI PT
Items (n=16)
Infit
-0.69 (0.10)
36.28 (1.38)
1.06 (0.30)
0.62 (-1.50)
15 …drive your wheelchair up a standard ramp, built to code (5° incline)?
-0.52 (0.08)
38.72 (1.15)
0.95 (-0.10)
0.76 (-1.10)
1
…use all of the functions on your controller, such as drive modes, tilt or lift?
-0.23 (0.06)
2
…select the correct drive mode to use in different environments?
SC
14 …drive your wheelchair along a dry, flat paved sidewalk?
M AN U
42.87 (0.83)
0.93 (-0.30)
0.85 (-0.70)
44.40 (0.73)
1.00 (0.10)
1.22 (1.00)
44 …use strategies, such as humour, that will help people feel comfortable if they are unsure how to act because you use a wheelchair?
-0.08 (0.05)
44.87 (0.70)
1.01 (0.10)
0.92 (-0.30)
36 …stop suddenly to avoid hitting a moving object, such as a small child or a dog?
-0.04 (0.05)
45.48 (0.67)
1.05 (0.40)
0.75 (-1.30)
57 …advocate for changes you want in your home, such as a roll-in shower?
-0.02 (0.05)
45.79 (0.66)
1.14 (0.80)
0.97 (-0.10)
26 …drive your wheelchair across 3m (10ft) of flat, freshly mowed, dry grass?
0.01 (0.05)
46.20 (0.64)
0.85 (-0.09)
0.84 (-0.80)
27 …move your wheelchair from the sidewalk to the grass, with a 3cm (1”) height difference?
0.07 (0.04)
47.09 (0.60)
0.86 (-0.90)
1.02 (0.20)
34 …drive your wheelchair through a crowd of people without hitting anyone?
0.15 (0.04)
48.23 (0.56)
0.85 (-1.10)
1.11 (0.70)
58 …advocate for your needs at work or school?
0.16 (0.04)
48.26 (0.57)
1.36 (2.40)
1.41 (2.10)
5
0.19 (0.04)
48.80 (0.54)
1.18 (1.40)
1.55* (2.80)
AC C
EP
TE D
-0.12 (0.05)
…manoeuvre your wheelchair in small spaces, such as the bathroom?
ACCEPTED MANUSCRIPT
0.22 (0.04)
49.17 (0.53)
0.92 (-0.60)
1.09 (0.60)
53 …know what to do if your wheelchair has suddenly stopped working?
0.25 (0.04)
49.60 (0.52)
1.29 (2.20)
1.73* (3.70)
59 …advocate for changes in your community, such as adding an accessible bus route in your neighbourhood?
0.25 (0.04)
49.36 (0.52)
1.53* (3.70)
1.79* (3.90)
29 …drive your wheelchair along a dirt path or trail with some tree roots and rocks?
0.39 (0.03)
51.55 (0.48)
1.05 (0.50)
1.26 (1.60)
0.00 (0.05)
46.06 (0.69)
1.06 (0.50)
1.10 (0.60)
SC
M AN U
Mean
RI PT
51 …continue to drive your wheelchair in a situation that is making you feel anxious or nervous?
AC C
EP
TE D
SE=standard error; ZSTD=standardized fit statistic; *misfitting item
ACCEPTED MANUSCRIPT
Figure 1: Stages of the fit analyses Social Situation self-efficacy dimension (17-items)
Rasch model* 1: Outfit analysis
17-items removed
2-items removed
Rasch model 2: Infit analysis
14-items removed
10-items removed
Rasch model 3: Final analysis on resulting items
11-items
SC
RI PT
Mobility self-efficacy dimension (42-items)
M AN U
5-items
Rasch model 4: WheelCon-P Short Form
16-items
AC C
EP
TE D
* subsequent Rasch models were applied to more model-fitting items
ACCEPTED MANUSCRIPT
Figure 2: Reliability and SEM of the Mobility self-efficacy, Social situation selfefficacy, and WheelCon-P Short Form measurements a. Mobility self-efficacy 30
RI PT
1.00
25
15
0.40
-
10
0.20 0.00 20
40
60
80
5 0
100
M AN U
0
SC
Reliability
20
0.60
SEM -
–
0.80
Measurements
b. Social situation self-efficacy 1.00
TE D
25
0.60
20
0.40
15
EP
10
0.20
5
AC C
0.00
0
c. WheelCon-P Short Form
0 20
40
60
Measurements
80
100
-
Reliability
30
SEM -
–
0.80
35
ACCEPTED MANUSCRIPT
1.00
30 25
RI PT 15
0.40
10
0.20
0.00 0
20
40
60
SC
5
80
AC C
EP
TE D
M AN U
Measurements
100
0
-
Reliability
20 0.60
SEM -
–
0.80