Constructing the program impact theory for an evidence-based work rehabilitation program for workers with low back pain
Bibliographic record
Abstract
PURPOSE: Several low back pain work rehabilitation programs have been developed and evaluated for their outcomes. Unfortunately, the program impact theory for these programs is not described, and consequently, the exact mechanisms of action by which these programs intend to increase the probability of return to work remain unknown. This lack of knowledge jeopardizes the implementation of effective programs by health professionals and managers. The objective of this paper is to present the results of an exploratory study aimed at building the program impact theory for the PREVICAP work rehabilitation program. METHODS: The program impact theory was develop by conducting: unpublished documents and scientific literature analyses, individual and group discussions with multiple stakeholders and observation of program reality by reviewing the files of workers who completed the program. RESULTS: The PREVICAP program's impact theory was elaborated based on an ecological approach to work rehabilitation. Program goals and objectives were defined for the three dimensions of the model: the worker, the work environment and the interaction between the worker and his work environment. Two program action mechanisms were defined and describe how the program was intended to achieve its expected outcomes. CONCLUSIONS: This study made explicit the PREVICAP program impact theory and can help rehabilitation practitioners to address work disability according to an ecological model.
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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 | 0.029 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".