Transforming the meaning of pain: An important step for the return to work
Bibliographic record
Abstract
UNLABELLED: Previous studies have found illness representations to be associated with the degree to which patients adopt health behaviours. Surprisingly, pain representations, especially those in a work rehabilitation context, have rarely been explored. OBJECTIVE: To conduct a thorough investigation of the pain representations held by workers who were on sick leave due to persistent musculoskeletal pain during the process of an intensive work rehabilitation program. METHODS: Qualitative semi-structured interviews were conducted with 16 participants (male, female), three times during the program and one month after discharge. Data analysis was based on a narrative approach. RESULTS: Throughout the process, pain representation was an indicator of the type of action the participants were ready to take to control the immediate or possible consequences of their pain. Using the context of a work rehabilitation trajectory we identified the differential impact of reconstruction or status quo in pain representations that eventually led to a return to work, or not. DISCUSSION: This study highlights the importance of identifying and acknowledging workers' pain representations in facilitating their return to work.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".