Evaluation of the fear-avoidance model with health care workers experiencing acute/subacute pain
Bibliographic record
Abstract
Studies in the literature do not show clear evidence supporting the relationship between pain and depressive symptoms in individuals experiencing acute/subacute pain compared to those experiencing chronic pain. However, more information is needed about which variables act as mediators in the pain-depression relationship in people having acute/subacute pain, before pain becomes chronic. Our objectives were to test the suitability of the fear-avoidance model in a sample of 110 health care workers experiencing acute/subacute pain using path analyses, to improve the model as needed, and to examine a model involving both pain catastrophizing and pain self-efficacy with work status as a final outcome. Overall, the results indicated that adjustments to the fear-avoidance model were required for people experiencing acute/subacute pain, in which fear-avoidance beliefs and depressive symptoms were concurrent rather than sequential. The catastrophizing concept was most closely associated with depressive symptoms, while pain self-efficacy was directly associated with fear-avoidance beliefs and indirectly to work outcomes. Assessing and modifying pain self-efficacy in acute/subacute pain patients is important for interventions aiming to decrease fear-avoidance and improve work outcomes.
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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 | 0.018 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".