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Related Concept Videos

Randomized Experiments01:13

Randomized Experiments

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
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Testing a Machine Learning-Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers

Ariana Kamberi1, Benjamin Weitz1, Julie Flahive2

  • 1Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, MA, United States.

JMIR Research Protocols
|April 16, 2025
PubMed
Summary
This summary is machine-generated.

This study tested the Adapt2Quit recommender system to increase smoking cessation in socioeconomically disadvantaged individuals. The system uses machine learning to tailor messages, aiming to improve quit rates in this high-risk population.

Keywords:
mHealthmachine learningsmoking cessationsocioeconomically disadvantaged, biochemical verification

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Area of Science:

  • Public Health
  • Digital Health
  • Behavioral Science

Background:

  • Socioeconomically disadvantaged individuals exhibit high smoking rates and face barriers to cessation interventions.
  • Computer-tailored health communication shows potential for promoting behavior change.
  • The Adapt2Quit recommender system, a machine learning approach, was developed to enhance message relevance and smoking cessation effectiveness.

Purpose of the Study:

  • To evaluate the efficacy of the Adapt2Quit recommender system in increasing smoking cessation among socioeconomically disadvantaged smokers through a randomized controlled trial.

Main Methods:

  • Recruitment of socioeconomically disadvantaged smokers from low-income insurance groups and community health centers.
  • Intervention group received tailored text messages via the Adapt2Quit system for 6 months, including facilitation and status assessment messages.
  • Control group received only facilitation and status assessment messages; primary outcome measured by 7-day point-prevalence smoking cessation at 6 months, verified by carbon monoxide testing.

Main Results:

  • Recruitment of 757 participants, with a diverse sample including 64% female, 35% Black or African American, and 51.1% White individuals.
  • Participant characteristics include 52.6% with a high school education, 70% smoking within 30 minutes of waking, and 50% having abstained from smoking for at least one day in the past year.
  • The study is ongoing, with recruitment and 6-month follow-up completed; main analysis is pending.

Conclusions:

  • A diverse sample of socioeconomically disadvantaged smokers was recruited for the Adapt2Quit study.
  • A rigorous protocol was established to evaluate the Adapt2Quit recommender system's effectiveness.
  • Future publications will present the primary analysis of the randomized controlled trial data.