Tobacco smoking among nursing students in Saudi Arabia: A descriptive correlational study
Bibliographic record
Abstract
Background and objectives: Tobacco smoking is a global epidemic and health threat that continues to increase. Nursing students primarily develop their professional roles toward smoking cessation during their academic nursing education. We assessed prevalence and behavioral patterns of tobacco smoking among nursing students. Along with nature of education received on tobacco smoking cessation, we sought to explore their knowledge, attitudes and beliefs toward tobacco smoking.Methods: Using convenience sampling, a descriptive correlational research design was used. Subjects were undergraduate students from a public university located in Alriyadh, the capital of Saudi Arabia. A standardized self-administered questionnaire, the Global Health Professional Student Survey, was utilized.Results: Eighty-four percent reported not smoking tobacco throughout their lifetime (i.e., never smokers), while the remaining were former smokers. Although 11.7% indicated that they had received formal training on tobacco-smoking cessation, more former smokers reported receiving such formal training than never smokers (25% vs. 9.3%, χ2 = 4.04, df = 1, p = .04). Students who were in third year of program, who thought that a smoker who quits smoking tobacco products would avoid/decrease serious health problems, and who stated that tobacco smoking never been allowed inside their living homes while children were present were more likely be never smokers.Conclusions: Adding training modules on smoking cessation to undergraduate nursing program curricula is highly suggested. Considering our unique findings on the effect of smoking status on the attitudes and beliefs toward smoking among nursing students when planning and implementing training modules seems beneficial. Future research is recommended to explore the lived experiences and consequences of smoking behavior among former smokers group.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".