Identification of recruitment and retention strategies for rehabilitation professionals in Ontario, Canada: results from expert panels
Bibliographic record
Abstract
BACKGROUND: Demand for rehabilitation services is expected to increase due to factors such as an aging population, workforce pressures, rise in chronic and complex multi-system disorders, advances in technology, and changes in interprofessional health service delivery models. However, health human resource (HHR) strategies for Canadian rehabilitation professionals are lagging behind other professional groups such as physicians and nurses. The objectives of this study were: 1) to identify recruitment and retention strategies of rehabilitation professionals including occupational therapists, physical therapists and speech language pathologists from the literature; and 2) to investigate both the importance and feasibility of the identified strategies using expert panels amongst HHR and education experts. METHODS: A review of the literature was conducted to identify recruitment and retention strategies for rehabilitation professionals. Two expert panels, one on Recruitment and Retention and the other on Education were convened to determine the importance and feasibility of the identified strategies. A modified-delphi process was used to gain consensus and to rate the identified strategies along these two dimensions. RESULTS: A total of 34 strategies were identified by the Recruitment and Retention and Education expert panels as being important and feasible for the development of a HHR plan for recruitment and retention of rehabilitation professionals. Seven were categorized under the Quality of Worklife and Work Environment theme, another seven in Financial Incentives and Marketing, two in Workload and Skill Mix, thirteen in Professional Development and five in Education and Training. CONCLUSION: Based on the results from the expert panels, the three major areas of focus for HHR planning in the rehabilitation sector should include strategies addressing Quality of Worklife and Work Environment, Financial Incentives and Marketing and Professional Development.
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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 | 0.008 | 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 | 0.001 |
| 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".