A Pilot Test of Self-Affirmations to Promote Smoking Cessation in a National Smoking Cessation Text Messaging Program
Bibliographic record
Abstract
BACKGROUND: Although effective smoking cessation treatments, including mHealth interventions, have been empirically validated and are widely available, smoking relapse is likely. Self-affirmation, a process through which individuals focus on their strengths and behaviors, has been shown to reduce negative effects of self-threats and to promote engagement in healthier behavior. OBJECTIVE: To assess the feasibility of incorporating self-affirmations into an existing text messaging-based smoking cessation program (Smokefree TXT) and to determine whether self-affirmation led to greater engagement and higher cessation rates than the standard intervention. METHODS: Data were collected from smokers (n=1261) who subscribed to a free smoking cessation program and met eligibility criteria. The intervention lasted 42 days. The original design was a 2 (Baseline affirmation: 5-item questionnaire present vs absent) × 2 (Integrated affirmation: texts present vs absent) factorial design. Only 17 eligible users completed all baseline affirmation questions and these conditions did not influence any outcomes, so we collapsed across baseline affirmation conditions in analysis. In the integrated affirmation conditions, affirmations replaced approximately 20% of texts delivering motivational content. RESULTS: In all, 687 users remained enrolled throughout the 42-day intervention and 81 reported smoking status at day 42. Among initiators (n=1261), self-affirmation did not significantly improve (1) intervention completion, (2) days enrolled, (3) 1-week smoking status, or (4) 6-week smoking status (all Ps>.10); and among the 687 completers, there were no significant effects of affirmation on cessation (Ps>.25). However, among the 81 responders, those who received affirmations were more likely to report cessation at 6 weeks (97.5%; 39 of 40) than those not given affirmations (78.1%; 32 of 41; χ(2)(1)=7.08, P=.008). CONCLUSION: This proof-of-concept study provides preliminary evidence that self-affirmation can be integrated into existing text-based cessation programs, as the affirmations did not lead to any adverse effects (ie, less engagement or lower rates of cessation). Among those who reported smoking status at the end of the intervention period (6.4% of eligible respondents), affirmations facilitated cessation. This study provides a "proof-of-concept" that brief, low-touch interventions may be integrated into a text messaging program with potential benefits, minimal disruption to the program or users, and little cost. Many questions remain regarding how self-affirmation and similar approaches can promote engagement in population interventions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".