Determinants of chronic disability related to low back pain: Towards an integrative biopsychosocial model
Bibliographic record
Abstract
PURPOSE: Since the early 1990s, numerous prospective studies have been published on the determinants of chronic disability related to low back pain (LBP) of non-specific origin whose human and financial costs are enormous. The significant contribution of psychosocial factors is being increasingly recognized. However, additional efforts are needed to clarify their role and to improve the interventions. The purpose of this theoretical paper is to propose a coherent organization of the medical and psychosocial determinants identified in prospective studies into a conceptual framework. METHOD: Several models available in the field of pain and disability as well as in health psychology were reviewed. RESULTS: A recent version of the stress coping model was chosen and adapted to the problem. The adapted model suggests that stress, particularly that caused by the pain associated with LBP, could have a negative impact on the outcome either: (1) indirectly through the negative emotional responses that it produces, which can cause biological or behavioural changes; or (2) directly through the biological or behavioural changes, which can in turn negatively affect the emotional response. CONCLUSIONS: The proposed biopsychosocial model assumes that LBP-related chronic disability is possibly, in some cases, a stress-related disorder. Its empirical verification in LBP could particularly improve the understanding of the interrelationships between certain variables.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".