Tobacco cessation interventions in high-income countries with Chinese, Vietnamese and Arab people who smoke: a scoping review of outcomes and cultural considerations
Bibliographic record
Abstract
Objectives: There are large and growing communities of Chinese, Vietnamese and Arab populations within many high-income countries, including Australia. These populations experience disproportionately higher rates of tobacco smoking. Cessation strategies are required that acknowledge the cultural factors shaping smoking behaviours. This review aimed to synthesise the evidence for smoking cessation interventions among Chinese, Vietnamese and Arab people, including outcomes and cultural considerations. Design: Scoping review. Data sources: We searched five electronic databases for peer-reviewed literature (CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cochrane Library, PsycINFO, PubMed and Scopus). Relevant grey literature was sourced from research and health organisations, and community cultural organisations. Eligibility criteria: English-language studies of tobacco cessation interventions with Chinese-speaking, Vietnamese-speaking or Arabic-speaking participants conducted in Australia, the USA, Canada, the UK or New Zealand between 2013 and 2025. Data extraction and synthesis: Two reviewers independently screened for eligible studies and, if included, assessed risk of bias using Joanna Briggs Institute critical appraisal tools. Results: We identified 23 studies describing 15 intervention types, with written resources most highly featured. Promising category evidence was found for nine intervention types with Chinese people (written information, education sessions, visual information, counselling, involving others, providing nicotine replacement therapy, intervention branded merchandise, mobile messaging and telephone follow-up), as well as counselling with Arab people, and telephone follow-up with Vietnamese people. A variety of cultural considerations were addressed in the interventions, most commonly language barriers as well as the use of co-design and community participation. Conclusions: Smoking cessation interventions with Chinese people were strongly supported, with less evidence for interventions with Vietnamese and Arabic people. Education-focused interventions were particularly effective, addressing low baseline knowledge underpinning smoking. Language barriers to smoking cessation were addressed through primary language supports. Further research is needed on effective smoking cessation intervention types with Arab and Vietnamese people.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".