Smoking cessation interventions for people living in rural and remote areas: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Smoking rates among people living in rural and remote areas are higher and quit rates are lower over the past 10 years compared with people living in suburban and urban areas. Higher smoking rates contribute to greater tobacco-related disease and morbidity in rural and remote areas. Physical and social isolation, greater exposure to pro-tobacco marketing, pro-tobacco social norms, and lower socioeconomic and educational levels are contributing to these higher smoking rates and lower quit rates. Smoking cessation interventions for people in rural and remote areas have been conducted, however little is known about their effectiveness or their mechanisms of action as well as the quality of such research. Behaviour change techniques (BCTs) are mechanisms of action derived from behaviour change theory, such as goal setting and reward. Improved understanding of the contribution of BCTs for smoking cessation in the rural and remote population will support future intervention development. We aim to review the literature on smoking cessation interventions for people living in rural and remote areas to inform evidence about intervention effectiveness and mechanisms of action. METHODS AND ANALYSIS: We will conduct a systematic review using seven scientific databases (EMBASE, MedLine, PsycINFO, CINAHL, Cochrane, Informit Health and Scopus). We will include peer-reviewed journal articles published in English that examine a smoking cessation intervention delivered to people living in rural and remote areas in the USA, Canada and Australia. We will examine outcome data relating to intervention effectiveness (eg, point prevalence abstinence or continuous abstinence), as well as the BCTs used in included interventions and their relationship with intervention outcomes. We will also assess the feasibility, acceptability and quality of research interventions of included articles, and provide graded recommendations based on the review outcomes. Data will be synthesised using narrative approaches and interpreted using content analysis. ETHICS AND DISSEMINATION: Ethics was not required for this systematic review. The results will be disseminated through peer-reviewed publication and at conferences by presentations. PROSPERO REGISTRATION NUMBER: 177398.
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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 | 0.074 | 0.062 |
| Meta-epidemiology (narrow) | 0.007 | 0.008 |
| Meta-epidemiology (broad) | 0.021 | 0.017 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.072 | 0.010 |
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".