The persistence of pain behaviors in patients with chronic back pain is independent of pain and psychological factors
Bibliographic record
Abstract
The primary purpose of the present study was to examine the temporal stability of communicative and protective pain behaviors in patients with chronic back pain. The study also examined whether the stability of pain behaviors could be accounted for by patients' levels of pain severity, catastrophizing, or fear of movement. Patients (n=70) were filmed on two separate occasions (i.e., baseline, follow-up) while performing a standardized lifting task designed to elicit pain behaviors. Consistent with previous studies, the results provided evidence for the stability of pain behaviors in patients with chronic pain. The analyses indicated that communicative and protective pain behavior scores did not change significantly from baseline to follow-up. In addition, significant test-retest correlations were found between baseline and follow-up pain behavior scores. The results of hierarchical multiple regression analyses further showed that pain behaviors remained stable over time even when accounting for patients' levels of pain severity. Regression analyses also showed that pain behaviors remained stable when accounting for patients' levels of catastrophizing and fear of movement. Discussion addresses the potential contribution of central neural mechanisms and social environmental reinforcement contingencies to the stability of pain behaviors. The discussion also addresses how treatment interventions specifically aimed at targeting pain behaviors might help to augment the overall impact of pain and disability management programs.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".