Exploring the Intersection Between Sex- and Gender-based Considerations and Exercise-based Telerehabilitation in Individuals with Stroke
Bibliographic record
Abstract
Sex- and gender-based factors disproportionally impact stroke recovery in women, and thus there is an urgent need for rehabilitation scientists to consider innovative forms of delivering stroke rehabilitation to optimize their participation, physical and psychosocial outcomes. Telerehabilitation which involves minimal travel requirements and costs may help overcome barriers related to accessing rehabilitation services. This PhD thesis is comprised of three studies that had an overarching aim of examining the intersection between sex- and gender-based considerations and exercise-based telerehabilitation among individuals with stroke. The first study was a scoping review of 38 primary research studies exploring facilitators and barriers to participation in exercise-based telerehabilitation in men and women with stroke. We reported many facilitators related to environmental factors including variety of games or exercises, convenience/flexibility of the training schedule, accessibility, strong communication skills possessed by therapists, and self-reported improvements in physical function. Challenges with internet connectivity and wearing and/or adjusting the technological device(s) used were the most commonly reported barriers. Both men and women reported being satisfied with the intervention components and possessed knowledge to participate. The second study aimed to explore participants’ experiences with a synchronously-delivered 4-week lower extremity-focused telerehabilitation program. Participants corroborated many of the facilitators identified in our scoping review, in addition to telerehabilitation providing opportunities to extend the continuum of stroke recovery. The third study included multiple case studies of 6 participants involved with the 4-week exercise-based telerehabilitation, whereby we explored sex- and gender-based factors that could potentially explain the responses in performance-based strength and health-related quality of life. We reported that factors such as stroke type and marital status of female participants could have helped explain their more favourable responses in contrast to males. Overall, this thesis provided preliminary evidence of the use of telerehabilitation as a viable means of delivering stroke rehabilitation to women.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".