Changes to Rehabilitation Service Delivery and the Associated Physician Perspectives During the COVID-19 Pandemic
Bibliographic record
Abstract
This project aimed to determine the impact of and needs from physician members of the Canadian Association of Physical Medicine & Rehabilitation during the early response to the COVID-19 global pandemic. The purpose of this project was to develop a framework for addressing the pandemic tailored to the needs of Canadian physiatrists. A convergent mixed-methods design was used for this needs assessment quality project. A total of 136 responses were obtained with an overall response rate of 34%. Three major themes were identified relating to the impact of COVID-19 on physicians: (1) changes to direct patient care, (2) changes to nonclinical aspects of physician's practices, and (3) impacts on personal and family well-being. Three requests for Canadian Association of Physical Medicine & Rehabilitation support during the pandemic were as follows: (1) collaborative sharing of information and resources, (2) advocacy for both patients and providers, and (3) avenues for social connection and wellness. This project provided insight into the impact of COVID-19 and current needs of Canadian Association of Physical Medicine & Rehabilitation physicians. The results were used to develop a solutions framework including guidance on use of virtual care and holding education webinars on high-yield topics. Next steps include a follow-up survey on change in preparedness and member satisfaction with the Canadian Association of Physical Medicine & Rehabilitation response.
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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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".