Remote Patient Monitoring and Incentives to Support Smoking Cessation Among Pregnant and Postpartum Medicaid Members: Three Randomized Controlled Pilot Studies
Bibliographic record
Abstract
BACKGROUND: Smoking rates among low-income individuals, including those eligible for Medicaid, have not shown the same decrease that is observed among high-income individuals. The rate of smoking among pregnant women enrolled in Medicaid is almost twice that among privately insured women, which leads to significant disparities in birth outcomes and a disproportionate cost burden placed on Medicaid. Several states have identified maternal smoking as a key target for improving birth outcomes and reducing health care expenditures; however, efficacious, cost-effective, and feasible cessation programs have been elusive. OBJECTIVE: This study aims to examine the feasibility, acceptability, and effectiveness of a smartwatch-enabled, incentive-based smoking cessation program for Medicaid-eligible pregnant smokers. METHODS: Pilot 1 included a randomized pilot study of smartwatch-enabled remote monitoring versus no remote monitoring for 12 weeks. Those in the intervention group also received the SmokeBeat program. Pilot 2 included a randomized pilot study of pay-to-wear versus pay-to-quit for 4 weeks. Those in a pay-to-wear program could earn daily incentives for wearing the smartwatch, whereas those in pay-to-quit program could earn daily incentives if they wore the smartwatch and abstained from smoking. Pilot 3, similar to pilot 2, had higher incentives and a duration of 3 weeks. RESULTS: For pilot 1 (N=27), self-reported cigarettes per week among the intervention group declined by 15.1 (SD 27) cigarettes over the study; a similar reduction was observed in the control group with a decrease of 17.2 (SD 19) cigarettes. For pilot 2 (N=8), self-reported cigarettes per week among the pay-to-wear group decreased by 43 cigarettes (SD 12.6); a similar reduction was seen in the pay-to-quit group, with an average of 31 (SD 45.6) fewer cigarettes smoked per week. For pilot 3 (N=4), one participant in the pay-to-quit group abstained from smoking for the full study duration and received full incentives. CONCLUSIONS: Decreases in smoking were observed in both the control and intervention groups during all pilots. The use of the SmokeBeat program did not significantly improve cessation. The SmokeBeat program, remote cotinine testing, and remote delivery of financial incentives were considered feasible and acceptable. Implementation challenges remain for providing evidence-based cessation incentives to low-income pregnant smokers. The feasibility and acceptability of the SmokeBeat program were moderately high. Moreover, the feasibility and acceptability of remote cotinine testing and the remotely delivered contingent financial incentives were successful. TRIAL REGISTRATION: ClinicalTrials.gov NCT03209557; https://clinicaltrials.gov/ct2/show/NCT03209557.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".