Impact of Nicotine Withdrawal and Postcessation Self-Efficacy on Short-Term Abstinence from Smoking
Bibliographic record
Abstract
Nicotine withdrawal is cited by smokers as a principal reason for relapse and a significant barrier to sustained abstinence.Postcessation self-efficacy has been established as a predictor of smoking cessation success but may be influenced by the impact of nicotine withdrawal symptoms.The objective of the current study was to determine if the relationship between nicotine withdrawal and relapse to smoking was mediated by diminished postcessation self-efficacy.Smokers (N = 266) ready to make a quit attempt completed measures of nicotine withdrawal, depressed mood and selfefficacy at Week 1 post-target quit date (TQD); smoking status was collected at Week 3 post-TQD.Both nicotine withdrawal (OR = 0.56, CI = 0.36-0.85,p <.01) and self-efficacy (OR = 1.50, CI = 1.09-2.05,p <.05) predicted continuous abstinence at Week 3; depressed mood did not.Mediational analysis did not support the contention that selfefficacy mediated the role of nicotine withdrawal on abstinence.iii Acknowledgments My deepest thanks to Dr. Andrew Pipe and Dr. Joanna Pozzulo for providing me with this opportunity to further my studies; I am so grateful for your
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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 | 0.009 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".