Exploring the Experiences of Individuals Allocated to a Control Setting: Findings From a Mobile Health Smoking Cessation Trial
Bibliographic record
Abstract
BACKGROUND: Tobacco smoking is the primary cause of preventable premature disease and death worldwide. Evidence of the efficacy of text messaging interventions to reduce smoking behavior is well established, but there is still a need for studies targeting young people, especially because young adult smokers are less likely to seek treatment than older adults. A mobile health intervention, Nicotine Exit (NEXit), targeting smoking among university students was developed to support university students to quit smoking. Short-term effectiveness was measured through a randomized controlled trial, which found that immediately after the 12-week intervention, 26% of smokers in the intervention group had prolonged abstinence compared with 15% in the control group. OBJECTIVE: The objective of this study was to explore the experience of being allocated to the control group in the NEXit smoking cessation intervention. METHODS: We asked students who were allocated to the control group in the main NEXit randomized controlled trial to report their experiences. An email was sent to the participants with an electronic link to a short questionnaire. We assessed the distribution of the responses to the questionnaire by descriptive analysis. We analyzed free-text comments to 4 questions. RESULTS: The response rate for the questionnaire was 33.8% (258/763), and we collected 143 free-text comments. Of the responders, 60.9% (157/258) experienced frustration, disappointment, and irritation about being allocated to the control group; they felt they were being denied support by having to wait for the intervention. Monthly text messages during the waiting period thanking them for taking part in the trial were perceived as negative by 72.3% (189/258), but for some the messages served as a reminder about the decision to quit smoking. Of the responders, 61.2% (158/258) chose to wait to quit smoking until they had access to the intervention, and 29.8% (77/258) decided to try to quit smoking without support. Of the respondents, 77.5% (200/258) claimed they were still smoking and had signed up or were thinking about signing up for the smoking cessation program at the time of the questionnaire. CONCLUSIONS: Most of the respondents reported negative feelings about having to wait for the support of the intervention and that they had decided to continue smoking. A similar number decided to wait to quit smoking until they had access to the intervention, and these respondents reported a high interest in the intervention. Free-text comments indicated that some control group participants believed that they had been excluded from the trial, while others were confused when asked to sign up for the intervention again. TRIAL REGISTRATION: ISRCTN Registry ISRCTN75766527; http://www.isrctn.com/ISRCTN75766527 (Archived by WebCite at http://www.webcitation.org/7678sUKbR).
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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 | 0.017 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 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".