Mobility and Participation of People With Disabilities Using Mobility Assistive Technologies: Protocol for a Mixed-Methods Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Many community-dwelling individuals living with a disability use mobility assistive technologies (MATs). MAT devices are generally beneficial for individuals with mobility impairments. However, less is known about the specific factors that may foster or deter mobility and community participation. OBJECTIVE The purpose of this protocol is to describe the methodology for a study including three main objectives: (1) to understand the places people using MAT go and the things they do, (2) to identify perceived barriers and facilitators as well as users’ desired environmental modifications, and (3) to understand subjective and objective issues related to environmental accessibility. METHODS A mixed-methods study was conducted in Vancouver and in Quebec City. Qualitative interviews were conducted to address all three objectives. In addition, Objective 1 was achieved through collection of global positioning system (GPS) data and activity diaries with 36 participants per site who represented six types of MAT users (ie, cane, walker, crutches, manual wheelchair, power wheelchair, and scooter). All participants were invited to take part in all aspects of data collection. PhotoVoice was used to address Objectives 2 and 3. Two environmental audits were used to address Objective 2. The Stakeholders’ Walkability/Wheelability Audit in Neighbourhood (SWAN) measured perceptions related to a variety of community environmental features associated with mobility and participation. A total of 24 participants were recruited to each study site for SWAN data collection. The Measure of Environmental Accessibility (MEA) was also used to objectively measure access to exterior and interior environments selected earlier in the project by the participants that could benefit from improvements. RESULTS Funding for this study was obtained from the Social Sciences and Humanities Research Council of Canada. Approval was obtained from the University of British Columbia Research Ethics Board and the Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale Research Ethics Board. Regarding the MEA evaluations, 19 locations (ie, buildings and exterior spaces) where obstacles have been identified by the participants of the PhotoVoice focus groups have been evaluated in Quebec City and 20 locations have been identified in the Vancouver region by the participants of the community forums. Data collection for this project was completed in December 2018. Analysis and writing of manuscripts are underway. CONCLUSIONS The use of a variety of methods to gather data on participation and mobility will allow a more holistic consideration of factors influencing mobility with a MAT device. This study will provide objective information about the mobility of participants and identify barriers and facilitators that impact their mobility and community participation. Through the mixed-methods approach employed in this study, we will gain a subjective evaluation of the participants’ neighborhoods, including personally meaningful information on environmental features that influence participants' everyday mobility and participation. We will also gain an objective evaluation of particular obstacles that community users of MAT identify as significant barriers to their ability to access public environments. We anticipate that these findings will help to identify a broad spectrum of solutions to improve the mobility and community participation of MAT users. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/12089
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.061 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.097 | 0.018 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".