A Systematic Review of Qualitative Studies on Factors Associated With Smoking Cessation Among Adolescents and Young Adults
Bibliographic record
Abstract
OBJECTIVE: To summarize findings from qualitative studies on factors associated with smoking cessation among adolescents and young adults. DATA SOURCES: We searched Pubmed, Psychinfo, CINAHL, Embase, Web of Science, and SCOPUS databases, as well as reference lists, for peer-reviewed articles published in English or French between January 1, 2000, and November 18, 2020. We used keywords such as adolescents, determinants, cessation, smoking, and qualitative methods. STUDY SELECTION: Of 1724 records identified, we included 39 articles that used qualitative or mixed methods, targeted adolescents and young adults aged 10-24, and aimed to identify factors associated with smoking cessation or smoking reduction. DATA EXTRACTION: Two authors independently extracted the data using a standardized form. We assessed study quality using the National Institute for Health and Care Excellence checklist for qualitative studies. DATA SYNTHESIS: We used an aggregative meta-synthesis approach and identified 39 conceptually distinct factors associated with smoking cessation. We grouped them into two categories: (1) environmental factors [tobacco control policies, pro-smoking norms, smoking cessation services and interventions, influence of friends and family], and (2) individual attributes (psychological characteristics, attitudes, pre-quitting smoking behavior, nicotine dependence symptoms, and other substances use). We developed a synthetic framework that captured the factors identified, the links that connect them, and their associations with smoking cessation. CONCLUSIONS: This qualitative synthesis offers new insights on factors related to smoking cessation services, interventions, and attitudes about cessation (embarrassment when using cessation services) not reported in quantitative reviews, supplementing limited evidence for developing cessation programs for young persons who smoke. IMPLICATIONS: Using an aggregative meta-synthesis approach, this study identified 39 conceptually distinct factors grouped into two categories: Environmental factors and individual attributes. These findings highlight the importance of considering both environmental and individual factors when developing smoking cessation programs for young persons who smoke. The study also sheds light on self-conscious emotions towards cessation, such as embarrassment when using cessation services, which are often overlooked in quantitative reviews. Overall, this study has important implications for developing effective smoking cessation interventions and policies that address the complex factors influencing smoking behavior among young persons.
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 | 0.097 | 0.235 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".