Breaking the cycle of smoking and pain: do pain-related anxiety and pain reduction expectancies sabotage attempts to quit smoking and can smoking cessation improve pain and pain-related disability outcomes?
Bibliographic record
Abstract
Contemporary models of smoking and pain suggest a reciprocal and self-perpetuating cycle, wherein smoking reduces pain in the short term but indirectly exacerbates pain in the long term. In a sample of participants engaged in an active smoking-cessation attempt, this investigation assessed a) whether specific smoking risk factors (i.e., smoking expectancies for pain reduction, pain-related anxiety) acted as barriers to cessation, and b) whether breaking the smoking-pain cycle through successful smoking abstinence impacted pain and pain-related disability outcomes for participants with pain. Participants comprised 168 smokers (44.4% with pain) who engaged in an online smoking-cessation program. Pain-related anxiety, but not smoking expectancies, accounted for a significant proportion of variance of smoking dependence from pre- to post-intervention. Results suggest that pain-related anxiety is a risk factor for maintained smoking dependence for all smokers regardless of pain status. Participants with pain who successfully quit smoking experienced statistically and clinically meaningful decreases in pain and pain-related disability from pre- to post-intervention. Exploratory post hoc analyses indicated that individuals who signed-up for the smoking cessation program but failed to begin a quit-attempt had significantly higher pain disability, depression, and anxiety scores than participants who commenced a quit-attempt. Theoretical and practical implications are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".