A Gender-Informed Smoking Cessation App for Women: Protocol for an Acceptability and Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Tobacco smoking remains the leading preventable cause of death and disease among women. Quitting smoking offers numerous health benefits; however, women tend to have less success than men when attempting to quit. This discrepancy is partly due to sex- and gender-related factors, including the lower effectiveness of smoking cessation medication and the presence of unique motives for smoking and barriers to quitting among women. Despite the gendered nature of smoking, most smoking cessation apps are gender-neutral and fail to address women's specific needs. OBJECTIVE: This study aims to test the acceptability and feasibility of a smartphone app that delivers gender-informed content to support women in quitting smoking. METHODS: We co-developed a smoking cessation app specifically tailored for women, named My Change Plan-Women (MCP-W). This app builds upon our previous gender-neutral app, MCP, by retaining its content grounded in behavioral change techniques aimed at supporting tobacco reduction and cessation. This includes goal setting for quitting, identifying triggers to smoking, creating coping strategies, tracking cigarettes and cravings, and assessing financial savings from quitting smoking. The MCP-W app contains additional gender-informed content that acknowledges barriers to quitting, such as coping with stress, having smokers in one's social circle, and managing unpleasant emotions. This content is delivered through testimonials and animated videos. This study is a prospective, single-group, mixed methods investigation in which 30 women smokers will trial the app for a period of 28 days. Once participants provide informed consent, they will complete a baseline survey and download the app on their smartphones. After 28 days, participants will complete follow-up surveys. Acceptability will be assessed using the Theoretical Framework of Acceptability, which evaluates whether participants perceive the app as helpful in changing their smoking. The app will be deemed acceptable if the majority of participants rate it as such, and feasible if the majority of the participants use it for at least 7 days. Furthermore, after the 28-day trial period, participants will complete a semistructured interview regarding their experience with the app and suggestions for improvement. RESULTS: Development of the MCP-W app was completed in September 2023. Participant recruitment for testing of the app commenced in February 2024 and was completed in July 2024. We will analyze the data upon completion of data collection from all 30 participants. We expect to share the results of this acceptability trial in the middle of 2025. CONCLUSIONS: Offering smoking cessation support tailored specifically to address the unique needs of women through a smartphone app represents a novel approach. This study will test whether women who smoke perceive this approach to be acceptable and feasible in their journey toward smoking cessation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/60677.
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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 | 0.033 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.096 | 0.018 |
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".