Stakeholder Perspectives on Retention Strategies for Rehabilitation Professionals: A Qualitative Study
Bibliographic record
Abstract
There is a scarcity of health human resources worldwide. In occupational therapy (OT), physical therapy (PT), and speech-language pathology (S-LP), attrition and retention issues amplify this situation and contribute to the precarity of health systems. Therefore, we aimed to investigate retention strategies for rehabilitation professionals in Quebec. We present an analysis from individual interviews with rehabilitation professionals and focus groups with stakeholders. We used purposeful sampling (maximum variation approach) to recruit participants from Quebec, Canada. We conducted interviews with 51 OTs, PTs, and S-LPs (2019-2020) and four focus groups with managers, professional education programs, professional associations, and regulatory bodies (2022). Cultural-historical activity theory provided the theoretical scaffolding for these interpretive description studies. Inductive and deductive approaches and constant comparative techniques were used for data analysis. Five sets of retention strategies were developed: (1) ensuring that work aligns with values; (2) improving alignment of work parameters with needs and interests of rehabilitation professionals; (3) modifying physical, social, cultural, and structural aspects of a workplace; (4) addressing how the profession is governed; and (5) offering informal and formal benefits. Multi-systemic retention strategies with intersectoral partnerships were deemed essential to effectively change rehabilitation professionals' work and work environments and to increase public awareness of the added value of rehabilitation professionals. Our findings emphasize a critical need to design targeted, multi-systemic retention strategies to influence the work experiences of rehabilitation professionals and to ensure the availability of OTs, PTs, and S-LPs for present and future rehabilitation needs.
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 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 | 0.093 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".