Clinicians’ Experiences of Implementing a Telerehabilitation Toolkit During the COVID-19 Pandemic: Qualitative Descriptive Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Although the COVID-19 pandemic resulted in a rapid implementation and scale-up of telehealth for patients in need of rehabilitation, an overall slower scaling up to telerehabilitation has been documented. OBJECTIVE The purpose of this study was to understand experiences of implementing telerehabilitation during the COVID-19 pandemic as well as using the Toronto Rehab Telerehab Toolkit from the perspective of rehabilitation professionals across Canada and internationally. METHODS The study adopted a qualitative descriptive approach that consisted of telephone- or videoconference-supported interviews and focus groups. Participants included rehabilitation providers as well as health care leaders who had used the Toronto Rehab Telerehab Toolkit. Each participant took part in a semi-structured interview or focus group, lasting approximately 30-40 minutes. Thematic analysis was used to understand the barriers and enablers of providing telerehabilitation and implementing the Toronto Rehab Telerehab Toolkit. Three members of the research team independently analyzed a set of the same transcripts and met after each set to discuss their analysis. RESULTS A total of 22 participants participated, and 7 interviews and 4 focus groups were included. The data of participants were collected from both Canadian (Alberta, New Brunswick, and Ontario) and international sites (Australia, Greece, and South Korea). A total of 11 sites were represented, 5 of which focused on neurological rehabilitation. Participants included health care providers (ie, physicians, occupational therapists, physical therapists, speech language pathologists, and social workers), managers and system leaders, as well as research and education professionals. Overall, 4 themes were identified including (1) implementation considerations for telerehabilitation, encompassing 2 subthemes of “infrastructure, equipment, and space” and “leadership and organizational support”; (2) innovations developed as a result of telerehabilitation; (3) the toolkit as a catalyst for implementing telerehabilitation; and (4) recommendations for improving the toolkit. CONCLUSIONS Findings from this qualitative study confirm some of the previously identified experiences with implementing telerehabilitation, but from the perspective of Canadian and international rehabilitation providers and leaders. These findings include the importance of adequate infrastructure, equipment, and space; the key role of organizational or leadership support in adopting telerehabilitation; and availing resources to implement it. Importantly, participants in our study described the toolkit as an important resource to broker networking opportunities and highlighted the need to pivot to telerehabilitation, especially early in the pandemic. Findings from this study will be used to improve the next iteration of the toolkit (Toolkit 2.0) to promote safe, accessible, and effective telerehabilitation to those patients in need in the future.
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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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| 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".