Adapting Primary Care Occupational, Physical, and Respiratory Therapy Practice to Meet Pandemic Demands: A Longitudinal Study
Bibliographic record
Abstract
<h3>Context:</h3> In Canada, physical, occupational, and respiratory therapists (PORTs) have joined primary care teams to improve the comprehensiveness of primary care, especially for chronic condition management. We have little research on the roles of PORTs in primary care, and minimal guidance on possible adapted roles for PORTs in disasters, such as pandemics. <h3>Objective:</h3> Explore clinical adaptations made, and micro/meso/macro challenges primary care PORTs experienced, in the first year of the COVID-19 pandemic. <h3>Study design/instruments and analysis:</h3> A longitudinal semi-structured diary-interview study, involving 12 weeks of audiodiaries (Apr-Oct 2020), and two interviews (Dec 2020/Jan 2021; Apr/May 2021). Analysis focused on change over time within each case, and cross-case comparisons. <h3>Setting:</h3> Primary care clinics in Ontario and Manitoba <h3>Population studied:</h3> PORTs <h3>Instrument:</h3> Semi-structured diary prompts; semi-structured interview guide. <h3>Outcome measures:</h3> N/A <h3>Results:</h3> Initial weeks were marked by confusion, including about how to adapt care, with much emotional strain and uncertainty. At a micro level, each profession suffered a disorienting loss of central role early in the pandemic. Over time, they created new methods to meet patients’ needs, including strengthening education and support for health behavior change and chronic condition management. The move to virtual care was mostly unplanned, with limited or untimely supports. Over time, they perceived benefits of virtual care, and hope to continue offering this option for some patients. At the meso level, team functioning was much like it was pre-pandemic; those with strong teams found new ways to maintain relationships, while others remained isolated. Participants described multiple disconnects with the macro-level decision-makers, and redeployment assignments made it evident that health administrators did not understand their role, and the important work that they were leaving behind. <h3>Conclusions:</h3> Despite challenges and barriers, the participants showed creativity and adaptability in the pandemic. In the face of negative impacts on some aspects of practice, therapists tested and embraced practices, some of which may continue post-pandemic, including a broader use of technologies and a broadened scope of practice that can positively contribute to patient outcomes in primary care. Moving forward, better understanding of PORTs’ contributions, and involvement in pandemic could improve future response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".