A Mobile Social Network–Based Smoking Cessation Intervention for Chinese Male Smokers: Protocol for a Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Approximately 2 million Chinese people die annually from tobacco-related diseases, mostly men; yet, fewer than 8% of Chinese smokers ever receive any smoking cessation advice or support. A social network-based gamified smoking cessation intervention (SCAMPI: Smoking Cessation App for Chinese Male: Pilot Intervention) is designed to help Chinese male smokers to quit smoking. OBJECTIVE: This paper aims to present the protocol of a study examining the preliminary effectiveness of SCAMPI by comparing the prolonged abstinence rate of a group of users with a comparator group during a 6-week follow-up period. METHODS: A two-arm pilot randomized controlled trial was conducted to assess the preliminary effectiveness and acceptability of the SCAMPI program as a smoking cessation intervention. After initial web-based screening, the first 80 eligible individuals who had gone through the required registration process were registered as participants of the trial. Participants were randomly allocated to the intervention group (n=40) and the control group (n=40). Participants in the intervention group used the full version of the SCAMPI program, which is a Chinese smoking cessation program developed based on the Behavior Change Wheel framework and relevant smoking cessation and design guidelines with involvement of target users. The program delivers a range of smoking cessation approaches, including helping users to make quitting plans, calculator to record quitting benefits, calendar to record progress, gamification to facilitate quitting, providing information about smoking harms, motivational messages to help users overcome urges, providing standardized tests to users for assessing their levels of nicotine dependence and lung health, and providing a platform to encourage social support between users. Participants in the control group used the restricted version of the SCAMPI program (placebo app). RESULTS: Recruitment for this project commenced in January 2019 and proceeded until March 2019. Follow-up data collection was commenced and completed by June 2019. The primary outcome measure of the study was the 30-day bio-verified smoking abstinence at the 6-week follow-up (self-reported data verified by the Nicotine Cotinine Saliva Test). The secondary outcome measures of the study included participants' cigarette consumption reduction (compared baseline daily cigarette consumption with end-of-trial daily cigarette consumption), participants' 7-day smoking abstinence at 4-week and 6-week follow-up (self-reported), participants' 30-day smoking abstinence at 6-week follow-up (self-reported data only), and participants' acceptability and satisfaction levels of using the SCAMPI program (measured by the Mobile App Rating Scale questionnaire). CONCLUSIONS: If the SCAMPI program is shown to be preliminary effective, the study will be rolled out to be a future trial with a larger sample size and longer follow-up (6 months) to identify if it is an effective social network-based tool to support Chinese male smokers to quit smoking. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12618001089224; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375381. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/18071.
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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 | 0.028 | 0.021 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.100 | 0.012 |
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".