Trial reportJournal of substance abuse treatment2014
Predictive modeling of addiction lapses in a mobile health application.
Trial report in Journal of substance abuse treatment, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 citing papers in PubMed, 2 syntheses or guidelines pooled it, 98 citations in OpenAlex.
- Measures of Effectiveness, Efficiency, and Quality of Telemedicine in the Management of Alcohol Abuse, Addiction, and Rehabilitation: Systematic Review.Journal of medical Internet research · 2020Pooled it
- Feasibility and Effects of Digital Interventions to Support People in Recovery From Substance Use Disorders: Systematic Review.Journal of medical Internet research · 2018Pooled it
- Developing and Testing a Smartphone Application to Enhance Adherence to Voice Therapy: A Pilot Study.International journal of environmental research and public health · 2023Trial
- Using ecological momentary assessments to predict relapse after adult substance use treatment.Addictive behaviors · 2018Trial
- Trial
- Exploring the use patterns of a mobile health application for alcohol addiction before the initial lapse after detoxification.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Trial
- Observational
- Digital relapse prevention plan for substance use disorders: study protocol for a multicentre randomised controlled trial.BMJ health & care informatics · 2025Article
- Maximizing Engagement, Trust, and Clinical Benefit of AI-Generated Recovery Support Messages for Alcohol Use Disorder: Protocol for an Optimization Study.JMIR research protocols · 2025Article
- A Brief Cognitive Behavioral Therapy-Based Digital Intervention for Reducing Hazardous Alcohol Use in South Korea: Development and Prospective Pilot Study.JMIR formative research · 2025Article
- Machine learning models for temporally precise lapse prediction in alcohol use disorder.Journal of psychopathology and clinical science · 2024Article
- Delivering MOUD to the Underserved: How Can Pharmacies Really Help?Journal of studies on alcohol and drugs · 2024Article
- Predicting high-risk periods for weight regain following initial weight loss.Obesity (Silver Spring, Md.) · 2024Article
- Acceptability of Personal Sensing Among People With Alcohol Use Disorder: Observational Study.JMIR mHealth and uHealth · 2023Observational
- Using Machine Learning of Online Expression to Explain Recovery Trajectories: Content Analytic Approach to Studying a Substance Use Disorder Forum.Journal of medical Internet research · 2023Article
- Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study.JMIR formative research · 2023Article
- Leveraging mHealth and Wearable Sensors to Manage Alcohol Use Disorders: A Systematic Literature Review.Healthcare (Basel, Switzerland) · 2022Review
- Intensive Longitudinal Data Collection Using Microinteraction Ecological Momentary Assessment: Pilot and Preliminary Results.JMIR formative research · 2022Article
- Processing incomplete questionnaire data into continuous digital biomarkers for addiction monitoring.PloS one · 2022Article
- Digital Public Health Surveillance Tools for Alcohol Use and HIV Risk Behaviors.AIDS and behavior · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
The chronically relapsing nature of alcoholism leads to substantial personal, family, and societal costs. Addiction-comprehensive health enhancement support system (A-CHESS) is a smartphone application that aims to reduce relapse. To offer targeted support to patients who are at risk of lapses within the coming week, a Bayesian network model to predict such events was constructed using responses on 2,934 weekly surveys (called the Weekly Check-in) from 152 alcohol-dependent individuals who recently completed residential treatment. The Weekly Check-in is a self-monitoring service, provided in A-CHESS, to track patients' recovery progress. The model showed good predictability, with the area under receiver operating characteristic curve of 0.829 in the 10-fold cross-validation and 0.912 in the external validation. The sensitivity/specificity table assists the tradeoff decisions necessary to apply the model in practice. This study moves us closer to the goal of providing lapse prediction so that patients might receive more targeted and timely support.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.