Facilitators and Barriers to Participation in Exercise-Based Telerehabilitation in Individuals with Stroke: A Scoping Review of Quantitative and Qualitative Studies
Bibliographic record
Abstract
BACKGROUND: Barriers to stroke rehabilitation, including travel and other costs, impact women more, but may be mitigated with telerehabilitation. This scoping review aimed to identify and describe facilitators and barriers to participation in exercise-based telerehabilitation after stroke. Our secondary aim was to explore whether gender-related facilitators or barriers exist to participation. METHODS: Six electronic databases were searched for studies exploring facilitators and barriers to participation in exercise-based telerehabilitation in community-dwelling adults with stroke. A list of key constructs was developed and provided a definition, and mapped onto one or more domains of the Theoretical Domains Framework (TDF). RESULTS: = 882 participants). The most commonly reported facilitators were mapped onto the TDF domain "environmental context and resources," and included the following: acceptable audio and video features, accessibility, convenience/flexibility of the training schedule and variety of games, and therapist communication skills. Other facilitators included ease of use (TDF "skills" domain), comfort with technology ("knowledge," "skills"), self-perceived improvements in physical function ("reinforcement"), enjoyment ("emotion," "reinforcement"), positive feedback/encouragement from family/friends ("social influences"), and the usefulness of telerehabilitation ("intentions," "reinforcement"). Barriers included challenges with internet speed and connectivity and adjusting and/or wearing the device(s) ("environmental"). Men and women reported facilitators related to "skills" and "knowledge" to participate in telerehabilitation, but few studies described gender-related factors. DISCUSSION: We found that many facilitators and few barriers exist to participation in exercise-based telerehabilitation for men and women with stroke, whereby the environmental and resources domain of the TDF was represented by most constructs.
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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 | 0.060 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".