Self-efficacy as a moderator in the relationship between peer pressure and family smoking, and adolescent cigarette smoking behavior
Bibliographic record
Abstract
This paper examines the relationship between the environmental factors of peer pressure and family smoking (parents’ smoking and siblings’ smoking), and adolescent cigarette smoking habits in Kerman (as a big province in Iran). In addition, in terms of the afore-mentioned behavior, the moderating role of self-efficacy on the link of peer pressure and family smoking is studied. A quantitative research method was used for this purpose. The sample included 300 adolescents between the ages of 15 and 18 as current smokers. Self-administered questionnaires were used to collect the data which were then analyzed using AMOS Software and running Structural Equation Modeling (SEM). The results showed positive significant relationship between peer pressure plus family smoking (parents’ smoking and siblings’ smoking), and adolescent cigarette smoking. The relevant findings and results revealed that self-efficacy has a considerable moderating effect on the relationship between cigarette smoking behavior, and peer pressure and family smoking. The results of the present study can contribute to the literature and have significant implications for practitioners and policy makers to prevent adolescents in Iran from developing smoking habits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".