Automated Telephone Follow-up for Smoking Cessation in Smokers With Coronary Heart Disease: A Randomized Controlled Trial
Bibliographic record
Abstract
INTRODUCTION: Smokers with coronary heart disease (CHD) benefit from in-hospital cessation treatment, but relapse is common without ongoing support postdischarge. The purpose of this study was to determine if smoking abstinence would be higher after hospital discharge in smokers who received automated telephone follow-up (ATF) and nurse-counseling, compared with a standard care (SC) control group. METHODS: A total of 440 smokers hospitalized with CHD were randomly assigned to the ATF group (n = 216) or to the SC group (n = 224). Participants in the ATF group received automated phone calls 3, 14, 30, 60, 90, 120, 150, and 180 days after hospital discharge. The ATF system posed questions concerning smoking status, confidence in staying smoke-free, and need for assistance. If flagged by the ATF system, a nurse-counselor provided additional counseling by phone. Self-reported continuous smoking abstinence was assessed 26 and 52 weeks postdischarge using intention-to-treat analysis. The main outcome measure was continuous abstinence for weeks 1-26 postdischarge. RESULTS: Participants in the ATF group achieved higher abstinence rates for weeks 1-26 than those in the SC group (odds ratio [OR] = 1.53, 95% confidence interval [CI] = 1.01 to 2.33). There was no significant difference between groups in abstinence rates for weeks 27-52 (OR = 1.37; 95% CI = 0.89 to 2.09). CONCLUSIONS: ATF-mediated follow-up helped smokers with CHD achieve abstinence during the intervention period. There was a trend toward clinically important improvements for weeks 27-52; but between-group differences for this time point did not achieve statistical significance. CLINICAL TRIAL NUMBER: NCT00449852. IMPLICATIONS: Automated telephone follow-up exerts its effect by reinforcing participants' efforts to be smoke-free and by proactively linking people requiring assistance to individualized support (eg, telephone counseling). This study shows that automated telephone follow-up can assist smokers with CHD in remaining smoke-free; however, the success of automated telephone follow-up is limited to the treatment period and abstinence rates after the treatment period were not statistically different from among those receiving standard care. Extended treatment via automated telephone follow-up may provide a solution to extend cessation assistance beyond hospital discharge.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".