Pain Coping but Not Readiness to Change Is Associated With Pretreatment Pain-related Functioning
Bibliographic record
Abstract
OBJECTIVE: The purpose of the present study was to determine if readiness to use adaptive and avoid maladaptive pain-coping skills before initiation of psychosocial treatment for chronic pain was related to reports of present coping, and whether those variables, together or separately, explained variance in pain, pain interference, and symptoms of depression. METHODS: A total of 132 patients with chronic low back pain completed measures of readiness, coping, and pain-related functioning before participation in a clinical trial of cognitive-behavioral therapy for pain. RESULTS: Pearson correlations indicated that the content-matched subscales of readiness and coping were moderately correlated (rs between 0.30 and 0.60), and "mismatched" subscales were generally more weakly related or unrelated. None of the readiness subscales were significantly associated with variance in any of the functioning variables. However, several aspects of coping were significantly associated with functioning. Task persistence was associated with lower pain interference and symptoms of depression; asking for assistance was associated with higher pain interference; and pain-contingent rest was associated with higher pain interference. DISCUSSION: Overall, the results indicate that adaptive coping is associated with better pain-related functioning and maladaptive coping is associated with poorer functioning, whereas readiness appears to not play a significant role in patient functioning before psychosocial pain treatment. The findings support the discriminant validity of the coping and readiness measures and inform treatment conceptualization.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".