Development of preventive behavior at work: Description of occupational therapists’ practice
Bibliographic record
Abstract
BACKGROUND: Integrating more prevention interventions into different workplace settings as a component of the role of occupational therapists has a significant relevance recognized by the occupational therapy professional community. Even if some studies suggested that occupational therapists already provide prevention interventions, and that other studies showed the efficacy of such interventions, the literature does not offer a comprehensive understanding of the specific practice of occupational therapists engaging in prevention in workplace settings. OBJECTIVE: The aim of the study was to describe the practice of occupational therapists toward the development of preventive behaviour at work among their clients. METHOD: Semi-structured interviews were conducted with 13 occupational therapists. Phenomenological analysis was used to examine the content of the interviews. RESULTS: Results suggest that occupational therapists form representations of preventive behavior that are consistent with theory, but those are limited and do not take into account the complexity of the concept. Results of the interviews found eight different interventions provided by occupational therapists toward the development of their clients' preventive behavior at work. CONCLUSION: Occupational therapists recognize their role in supporting their clients' development of preventive behavior at work. However, they appear to lack a conceptual understanding and resources to help them in their practice toward prevention.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".