Predictive value of the transtheoretical model to smoking cessation in hospitalized patients with cardiovascular disease
Bibliographic record
Abstract
BACKGROUND: Several authors have questioned the transtheoretical model. Determining the predictive value of each cognitive-behavioural element within this model could explain the multiple successes reported in smoking cessation programmes. The purpose of this study was to predict point-prevalent smoking abstinence at 2 and 6 months, using the constructs of the transtheoretical model, when applied to a pooled sample of individuals who were hospitalized for a cardiovascular event. DESIGN: The study follows a predictive correlation design. METHODS: Recently hospitalized patients (n=168) with cardiovascular disease were pooled from a randomized, controlled trial. Independent variables of the predictive transtheoretical model comprise stages and processes of change, pros and cons to quit smoking (decisional balance), self-efficacy, and social support. These were evaluated at baseline, 2 and 6 months. RESULTS: Compared to smokers, individuals who abstained from smoking at 2 and 6 months were more confident at baseline to remain non-smokers, perceived less pros and cons to continue smoking, utilized less consciousness raising and self-re-evaluation experiential processes of change, and received more positive reinforcement from their social network with regard to their smoke-free behaviour. Self-efficacy and stages of change at baseline were predictive of smoking abstinence after 6 months. Other variables found to be predictive of smoking abstinence at 6 months were an increase in self-efficacy; an increase in positive social support behaviour and a decrease of the pros within the decisional balance. CONCLUSIONS: The results partially support the predictive value of the transtheoretical model constructs in smoking cessation for cardiovascular disease patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".