Smoking Behavior Based on Stages of Change Model Among Iranian Male Students in 2009-2010 Academic Year
Bibliographic record
Abstract
Background: According to the stages of change model, individuals are in the different stages of smoking behavior. The aim of current study was to analyze the smoking behavior based on stages of change model among the students of six Iranian universities during 2009-2010 academic year.Materials and Method: This is a descriptive study using convenient sample method (N=578). Data gathering instrument was the short form questionnaire based on stages of change model. Descriptive and inferential statistics were applied using SPSS software.Results: Subjects ages ranged between 18-49 years, with a mean age of 23.2±2.3. Average age for beginning smoking was 18.4±3.2; the duration of smoking was 4.4±3.3 years and the mean number of cigarette smoking per day was 9.09±7.4. 268 cases (46.4%) and 83(14.4%) announced half and more than half of their friends are current smoker, respectively. 321 people (55.5%) were in precontemplation, 109 people (18.9%) in contemplation, 99 people (17.1%) in preparation, 27 people (4.7%) in action and 22 people (3.8%) in maintenance stage. Conclusion: About three quarter of the subjects were in precontemplation and contemplation stage and according to their age situation and known effect of smoking on their health it is necessary to encourage them smoke cessation intervention based on the stages of change model constructs. Meanwhile, 17.8% were in preparation stage and it’s a good opportunity for smoking cessation programs
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".