Attrition and Retention of Rehabilitation Professionals: A Scoping Review
Bibliographic record
Abstract
INTRODUCTION: Attrition is defined as a permanent departure from one's profession or the workforce. Existing literature on retention strategies, contributing factors to the attrition of rehabilitation professionals and how different environments influence professionals' decision-making to stay in/leave their profession, is limited in scope and specificity. The objective of our review was to map the depth and breadth of the literature on attrition and retention of rehabilitation professionals. METHODS: We used Arksey and O'Malley's methodological framework. A search was conducted on MEDLINE (Ovid), Embase (Ovid), AMED, CINAHL, Scopus, and ProQuest Dissertations and Theses from 2010 to April 2021 for concepts of attrition and retention in occupational therapy, physical therapy, and speech-language pathology. RESULTS: Of the 6031 retrieved records, 59 papers were selected for data extraction. Data were organized into three themes: (1) descriptions of attrition and retention, (2) experiences of being a professional, and (3) experiences in institutions where rehabilitation professionals work. Seven factors across three levels (individual, work, and environment) were found to influence attrition. DISCUSSION: Our review showcases a vast, yet superficial array of literature on attrition and retention of rehabilitation professionals. Differences exist between occupational therapy, physical therapy, and speech-language pathology with respect to the focus of the literature. Push , pull , and stay factors would benefit from further empirical investigation to develop targeted retention strategies. These findings may help to inform health care institutions, professional regulatory bodies, and associations, as well as professional education programs, to develop resources to support retention of rehabilitation professionals.
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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 | 0.025 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.026 | 0.030 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".