Design and Development of Smoking Cessation Apps Based on Smokers’ and Providers’ Perspectives in China: Survey Study
Bibliographic record
Abstract
BACKGROUND: Although there are more than 60 smartphone apps for smoking cessation in China, many of them do not include the content and features that health care professionals and smokers prefer-which may make them impractical, unengaging, and ineffective. Therefore, we investigated both health care providers' and smokers' preferences for features of future smoking cessation apps. OBJECTIVE: This study aimed to investigate Chinese health care providers' and smokers' desired features of a smoking cessation app, with the goal of providing design recommendations for app designers and researchers. METHODS: Both Chinese smokers who own smartphones (n=357) and Chinese health care providers (n=224) responded to a survey collecting data on their sociodemographic characteristics and opinions on the importance of 20 smoking cessation app design features studied in previous US research. RESULTS: Chinese health care providers expressed strong support of smoking cessation apps on a number of attitude indicators (range 153/224, 68.3% to 204/224, 91.1%). They rated nearly all (18/20) features as very or extremely important (range 52.2%-83.4%) and rated nearly all features (17/20) as more important than the smokers did. More than 60% of smokers rated the following 4 features as very or extremely important: allow sharing the process of smoking cessation with family members and friends (216/319, 67.7%), helping smokers track their progress (such as the amount of smoking per day; 213/319, 66.8%), helping with the side effects of medications and nicotine withdrawal symptoms (201/319, 63.0%), and adapting to ongoing needs and interests of smokers (194/319, 60.8%). Contrary to a similar study of US smokers and health care providers, Chinese smokers and providers rated reputation and ability to communicate with family members and friends as important features, whereas Chinese smokers rated privacy and security as less important. CONCLUSIONS: The design of future smoking cessation and health behavior change apps should consider perspectives of both providers and smokers as well as the role of culture.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".