Bibliographic record
Abstract
The aim of this work was to study whether fear of movement, and pain catastrophizing predict pain related-disability and depression in sub-acute whiplash patients. Moreover, we wanted to test if fear of movement is a mediator in the relation between catastrophizing and pain-related disability/depression as has been suggested by the fear-avoidance model [Vlaeyen JWS, Kole-Snijders AMJ, Boeren RGB, van Eek H. Fear of movement/(re)injury in chronic low back pain and its relation to behavioral performance. Pain 1995;62:363-72]. The convenience sample used was of 147 sub-acute whiplash patients (pain duration less than 3 months). Two stepwise regression analyses were performed using fear of movement and catastrophizing as the independent variables, and disability and depression as the dependent variables. After controlling for descriptive variables and pain characteristics, catastrophizing and fear of movement were found to be predictors of disability and depression. Pain intensity was a predictor of disability but not of depression. The mediation effect of fear of movement in the relationships between catastrophizing and disability, and between catastrophizing and depression was also supported. The results of this study are in accordance with the fear-avoidance model, and support a biopsychosocial perspective for whiplash disorders.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".