Cigarette smokers’ perceptions of smoking cessation and associated factors in Karachi, Pakistan
Bibliographic record
Abstract
OBJECTIVES: The study explored the perceptions of adult smokers with cardiovascular and respiratory diseases regarding cigarette smoking cessation. We also explored factors that may hinder or facilitate smoking cessation process. DESIGN: Qualitative descriptive exploratory design SAMPLE: Purposive sample of 13 adult smokers with cardiovascular or respiratory diseases visiting outpatient cardiac and respiratory clinics at a private tertiary care hospital MEASUREMENTS: In-depth, face-to-face, and semi-structured interviews were conducted. The interviews were digitally recorded and transcribed verbatim followed by a six steps process of manual thematic analysis of data. RESULTS: Meaningful statements were assigned codes and grouped into categories. Categories were clustered under three themes representing individual factors, socio-cultural factors, and institutional factors. CONCLUSIONS: Smoking cessation is influenced by personal, cultural, as well as social aspects. Institutionally, there is a need to recognize that smoking is a learned behavior; hence, prohibiting public smoking will potentially contribute to non-smoking behaviors. Although the nature of misconceptions varies, this is imperative to ensure consistency in messaging, programming, and supports led by healthcare professionals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".