Continuing Professional Development in Response to COVID-19: Knowledge Mobilization for Occupational Therapy and Physiotherapy via a Curated Web Site
Bibliographic record
Abstract
Purpose: Once the COVID-19 pandemic was declared, clinicians were redeployed to prepare for increased hospitalizations. This disruption necessitated rapid continuing professional development (CPD) resources for health care providers. This mixed-method study explored the experiences of occupational therapists and physiotherapists who accessed a CPD Web site that provided educational resources related to the pandemic to refresh their clinical knowledge and skills. Methods: Faculty from the Michener Institute of Education at the University Health Network and University of Toronto along with 60 collaborators created a Web site to support the need for rapid CPD. An occupational therapist and physiotherapist advisory group informed the evolving design of the occupational therapy and physiotherapy content. Results: In the occupational therapy profession 535 users created an account between April and November 2020 (236 practicing, 283 students, and 16 did not specify) and in the physiotherapy profession 829 created an account (532 practicing, 278 students and 19 did not specify). Each user viewed an average of 53 Web pages. Three themes emerged: (1)To prepare for practice changes, clinicians value a single repository of information; (2) Web site features can either facilitate or hinder access to the needed information; and (3) Participants described diverse learning needs. Conclusions: The Web site design features assisted participants in preparing for redeployment and patient care. Features to encourage self-directed learning, such as the grouping of relevant topics and self-check quizzes, can enhance the user experience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".