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Record W7111673668

Training to Enhance Adaptation and Management for Wheelchair users (TEAM Wheels)

2025· other· W7111673668 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2025
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsTrainerControl (management)Adaptation (eye)WheelchairData collectionRandomized controlled trialSession (web analytics)Process (computing)Baseline (sea)
DOInot available

Abstract

fetched live from OpenAlex

This study will use a three-site (Winnipeg, Vancouver, and Quebec City) randomized controlled trial to compare differences in current wheelchair training practice and a 1-month, peer-led (virtual due to SARS-CoV-2; COVID-19) eHealth training program (TEAM Wheels). Subjects will randomly be assigned to the TEAM Wheels or control group using a 1:1 allocation ratio between groups. To support balance between groups and masking of assignment, our statistician will create a computerized randomization process with undisclosed block size. Once subjects are enrolled, baseline data will be collected and entered into a secure database. A site coordinator or assistant will then obtain the participant's group assignment and coordinate the first in-person peer trainer session. For treatment group assignments this will occur as soon as it is practical and for control group assignments this will be scheduled after blinded post-treatment data collection is complete. To address bias, subjects will be instructed not to discuss their program. The treatment group will receive the TEAM Wheels program over a 4-week period. An initial meeting (Session 1) will be arranged via teleconference (MS Teams). The peer trainer is an experienced Manual Wheelchair (MWC) user trained to deliver the TEAM Wheels program. At least 2 peers will be hired and trained at each site to offer multiple trainer attributes. We will intentionally include a male and female, one being at least 50 years of age. Participants will pre-select a peer trainer based on a biosketch to optimize training effect (e.g., preference for age, sex factors); comparability in age has been identified as preferential among older adults and influential to self-efficacy. Following Session 1, participants engage in 4 weeks of training with the eHealth home program. They are instructed to practice for 75 to 150 minutes per week. Consistent with motor learning principles, we encourage training in 15-30 minute blocks 1-2 times per day, 3-5 days per week. The peer trainer will arrange with the participant the remaining two virtual sessions, approximately one week apart. Control Group. The control group receives no specific intervention over the course of the 4-week period. This reflects "usual practice" or the typical experience of a MWC user in their provincial context. Control group participants placed on the wait-list will receive the TEAM Wheels program, as described, following completion of the study (i.e. after post-treatment data collection). The site Research Coordinator will make telephone or email contact with control group participants at the end of weeks 2 and 4 during the study period to deter attrition/drop-out. When contact is made at week 4, the Research Coordinatort will schedule an appointment for post-treatment data collection (week 7). Any formal MWC training received during the wait-list period will be documented for potential post-hoc analysis as a confounding variable; however, research evidence and the investigators' clinical experience confirm that in all 3 provinces formal training is not provided once MWC users are discharged from hospital. Assessments. The outcome measures will be collected at baseline (pre-randomization) and post-intervention. A Research Assistant/Coordinator at each site will contact the participant via MS Teams videoconference at baseline and subsequent data collection points to administer the outcome measures. Participants will be shown a video to help them apply an Actigraph device (i.e. small battery-operated accelerometer) to the participant's wheelchair spokes and after 2 weeks will either retrieve it or provide a self-addressed stamped envelope for the participant to return via post. Post-treatment data will be collected at week 7 to incorporate a 2-week window for consolidation of learning following the 4-week intervention. Follow-up (retention) data will be collected from treatment group participants 6 months later (week 31). Outcome measures. At baseline, descriptive characteristics including age, sex, gender, marital status, the highest level of education, primary diagnoses related to MWC use, Wheel diameter, and length of time using the MWC will be collected. Five outcome measures will be administered at baseline, post-treatment, and 6-month follow-up (for treatment group participants). Wheelchair Skills Test - Questionnaire (WST-Q). To address environmental barriers, MWC users must learn specific mobility skills such as managing inclines, thresholds, and doorways. This is of considerable importance since training also involves learning to recognize risks and limitations. WST-Q evaluates 34 discrete skills; respondents rate their capacity (i.e. ability) with each skill as well as performance frequency. Capacity is rated as Yes (2), Yes with difficulty (1), or No (0); performance is rated as Always (2), Sometimes (1), or Never (0). Total skill Capacity (0-100%) and Performance (0-100%) scores are calculated. The WST has demonstrated excellent reliability for test-retest (ICC=0.90), intra-rater (ICC=0.96), and inter-rater (ICC=0.97) administration. Wheelchair Outcome Measure (WhOM). The rehabilitation literature strongly suggests that intervention outcomes should include not only externally defined measures but also measures of user-identified activities of relevance and perceived satisfaction with performance. A 2008 review of wheelchair-specific outcomes found the WhOM was the only tool that included activities selected and weighted by the user and featured participation in social roles.Two published literature reviews identify the WhOM as the most client-centred and psychometrically robust tool among participation outcomes for wheelchair users. WhOM is administered as a semi-structured interview. Respondents identify 10 activities (5 performed inside and 5 performed outside of the home), rating their satisfaction with performance on an 11-point scale (0-10) for each activity. The WhOM demonstrates good reliability (Test-retest ICC = 0.83-0.88; Inter-rater ICC = 0.90-0.91) and validity (correlations with LIFE-H: rs = 0.3-0.5) in use among individuals with spinal cord injury and older adults (Test-retest ICC = 0.77-1.00; correlation with QUEST rs = 0.36 -0.45). Wheelchair Use Confidence Scale-(WheelCon-SF). Self-efficacy has been identified as a key component in the performance of wheelchair mobility skills. Incorporating the principles of cognitive theory, including self-efficacy, can promote program adherence and skill acquisition. Preliminary research has suggested that standardized training can increase wheelchair confidence among older adults. WheelCon-SF is a self-report questionnaire with 21 statements related to confidence using a wheelchair in various activities and environments. Items are rated on a scale from 0 ("not confident") to 10 ("completely confident"), providing a total mean score (0-10). The WheelCon-SF is more responsive than the original 65-item version; a recent study reported high test-retest reliability (ICC=0.98) and internal consistency (Cronbach's alpha = 0.95). The Short-Form 36 (SF-36) Health Survey Questionnaire is a measure of health status across the following domains: physical function, physical limitations, emotional limitations, pain, social function, energy, perceived health, and mental health. The literature identifies inherent wording bias of the mobility-related SF-36 test items, which presume ambulation as a norm so we opted to use the Enabled version that explicitly acknowledges the use of a mobility aid and replaces the words "climbing" and "walking" with "going". Short Form-36E (Enabled) is specific to the study population of manual wheelchair users and will provide detailed and specific data related to HRQL. Objective Wheelchair Mobility. To triangulate measurement of improvement in mobility and community engagement, accelerometry data (ActigraphTM, Pensacola FL) will be used to objectively measure MWC activation over a 10-day period at baseline, post-treatment, and follow-up data collection points. The Actigraph is attached to a rear wheel on the MWC; a battery provides up to 14 days of passive data collection without impeding MWC operation. Data loggers have demonstrated valid and reliable measurement of MWC movement, with accuracy beyond 90%. A tri-axial accelerometer records acceleration forces during MWC use, downloadable as a .csv file. Algorithms developed by our team convert data into total and mean values of distance, speed, and 'bout' frequency (meaningful transitions between functional activities), parameters that reflect mobility patterns and activity of MWC users which we expect to change as a result of improvements in skill and participation. Program details TEAM Wheels is a 4-week, community-based, tailored program integrating eHealth and peer-led components to optimize learning while limiting the time demands of health care professionals. The eHealth component is a 10" computer tablet with a custom training application. The tablet mounts conveniently on the lap for "in-chair" training, enabling MWC users to learn and practice mobility skills in authentic contexts of home and community. The interactive application includes a structured curriculum with over 200 video clips featuring education, peer demonstration, and training activities. The peer-led component involves experienced MWC users with specialized training who can leverage their own experience and ability to relate as influential peers. The peer trainer conducts 3 virtual/teleconference (MS Teams) sessions with the participant, negotiating individualized goals, introducing wheelchair skills and management strategies, and providing an orientation to the eHealth home program. Peer trainers monitor eHealth training activity, which the tablet uploads to a secure website, intervening or modifying the program when required. Additional communication can be initiated between MWC user and peer trainer using a v

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.294
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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