Cognitive Coping Style and the Effectiveness of Distraction or Sensation-Focused Instructions in Chronic Pain Patients
Bibliographic record
Abstract
AIM: This study set out to investigate whether cognitive coping strategies that match participants' preferred coping style effectively reduce pain intensity and situational anxiety in a population of people with chronic pain. METHOD: Chronic pain patients (N = 43) completed questionnaires on coping style, pain intensity, self-efficacy, and situational/trait anxiety. Participants were classified as Monitors (n = 16) or Blunters (n = 19) based on their Miller Behavioural Style Scale score. Participants were then provided with an audiotaped intervention in which they were instructed to focus on pain sensations or to engage in a distraction task and then to rate the pain intensity and their anxiety during and after the attentional focus and distraction conditions. The two interventions were each completed by all participants, having been presented in counterbalanced order. RESULTS: Findings revealed that Monitors' level of anxiety decreased following a congruent (i.e., sensation-focused) intervention. No effects were obtained in terms of perceived pain. For blunters, however, their perceived levels of anxiety and pain did not attenuate following a congruent, distraction-focused intervention. CONCLUSION: Among persons experiencing chronic pain, tailoring coping strategies to match an individual's preferred coping style--in particular, those with a high level of monitoring--may enhance the benefit of psychological approaches to management of anxiety.
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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 | 0.000 | 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 | 0.000 |
| 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".