Return-to-work success despite conflicts: an exploration of decision-making during a work rehabilitation program
Bibliographic record
Abstract
PURPOSE: Collective decision-making by stakeholders appears important to return-to-work success, yet few studies have explored the processes involved. This study aims to explore the influence of decision-making on return-to-work for workers with musculoskeletal or common mental disorders. METHOD: This study is a secondary analysis using data from three earlier multiple-case studies that documented decision-making during similar and comparable work rehabilitation programs. Individual interviews were conducted at the end of the program with stakeholders, namely, the disabled workers and representatives of health care professionals, employers, unions and insurers. Verbatims were analysed inductively. RESULTS: The 28 decision-making processes (cases) led to 115 different decisions-making instances and included the following components: subjects of the decisions, stakeholders' concerns and powers, and types of decision-making. No differences were found in decision-making processes relative to the workers' diagnoses or return-to-work status. However, overall analysis of decision-making revealed that stakeholder agreement on a return-to-work goal and acceptance of an intervention plan in which the task demands aligned with the worker's capacities were essential for return-to-work success. CONCLUSION: These results support the possibility of return-to-work success despite conflictual decision-making processes. In addition to facilitating consensual decisions, future studies should be aimed at facilitating negotiated decisions. Implications for rehabilitation Facilitating decision-making, with the aim of obtaining agreement from all stakeholders on a return-to-work goal and their acceptance of an intervention plan that respects the worker's capacities, is important for return-to-work success. Rehabilitation professionals should constantly be on the lookout for potential conflicts, which may either complicate the reach of an agreement between the stakeholders or constrain return-to-work possibilities. Rehabilitation professionals should also be constantly watching for workers' and employers' return-to-work concerns, as they may change during work rehabilitation, potentially challenging a reached agreement.
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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 | 0.026 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".