Individual, Social and Psychological Characteristics of Smoking Cessation Behaviors: A Systematic Review
Bibliographic record
Abstract
About two thirds of active smokers want to quit smoking, yet not many people finally succeed in smoking cessation. Smoking cessation involve complex behaviors associated with individual, social and psychological characteristics as the key factors. Our objective is to review the studies about smoking cessation behavior correlated issues in order to find effective interventions of smoking cessation program. Terms and keywords pertinent to individual, social and psychological characteristics of smoking cessation behavior were used in a search of the electronic databases. Searches were limited to English language, included papers were: a) had clearly report the predictor variables related to smoking cessation behaviors, b) exclusively represent nation/s of study population, c) the time frame for the analysis was limited from 1998 to 2018. A result of 116 individual studies were retrieved at first and reviewed. After further inspection of references from the collected studies, 9 studies were approximately selected that met all inclusion criteria. The final studies consisted of five cross-sectional study and four cohort studies, conducted from different countries. There were several characteristics related to smoking cessation behavior including on levels of nicotine dependence, self-efficacy, smoking restriction and involve other smokers environment, motivation and educational background. Adjusted interventions due to those specific behaviors are needed in order to make more effective smoking cessation programs. Therefore, this study may provide new perspective for encouraged to decrease the amount of smokers worldwide through smoking cessation program.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".