Evidence map›Paper›PMID 41634908›Full record

ArticleThe American journal of psychiatry2026

Mobile Health for Alcohol Use Assessment: Longitudinal Effects of Breathalyzer Self-Monitoring in Everyday Contexts.

Yang Lu, Catharine E Fairbairn, Jiaxu Han, Nigel Bosch

Abstract read
In one paragraph

Article in The American journal of psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yang LuDepartment of Psychology, University of Illinois at Urbana-Champaign, Champaign-Urbana.ORCID 0000-0003-1968-9285
Catharine E FairbairnDepartment of Psychology, University of Illinois at Urbana-Champaign, Champaign-Urbana.
Jiaxu HanDepartment of Psychology, University of Illinois at Urbana-Champaign, Champaign-Urbana.
Nigel BoschSchool of Information Sciences, University of Illinois at Urbana-Champaign.

Funding

Examining the Impact of Stress on the Emotionally Reinforcing Properties of Alcohol in Heavy Social Drinkers: A Multimodal Investigation Integrating Laboratory and Ambulatory MethodsR01AA025969 · NIAAA · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Catharine Fairbairn · 2017 to 2026
$3.5M
Towards a Wearable Alcohol Biosensor: Examining the Accuracy of BAC Estimates from New-Generation Transdermal Technology using Large-Scale Human Testing and Machine Learning AlgorithmsR01AA028488 · NIAAA · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Catharine Fairbairn · 2021 to 2026
$2.8M
NIAAA NIH HHS R01 AA025969NIAAA NIH HHS R01 AA028488
6 · The paper itself

Abstract

objectiveAlthough mobile health-tracking technologies have burgeoned, offering objective health information to consumers on an unprecedented scale, opportunities to directly test effects of such monitoring have been limited. Low-cost mobile breathalyzers are one tool commonly employed for blood alcohol concentration (BAC) assessment. The authors explored outcomes linked with BAC-tracking technologies, examining effects on alcohol use and self-estimation of BAC levels in a large U.S. sample.

methodsParticipants (N=32,179) were individuals who voluntarily purchased a mobile breathalyzer and provided at least three ad-lib readings between 2016 and 2022. A paired smartphone application prompted users to enter a BAC self-estimate (a guess) before the measured BAC level was displayed. Analyses included observations collected during active consumption (BAC >0.00%) from breathalyzer users who opted to share anonymized data. Breathalyzer users who displayed inattentive patterns of guessing were excluded from self-estimation analyses. The final dataset comprised 787,393 BAC readings and 387,643 self-estimates.

resultsThe accuracy of BAC guesses increased by 2.38% over the course of breathalyzer use. Associations between breathalyzer use and BAC levels varied significantly according to participants' initial drinking levels (b=-0.0062, 95% CI=-0.0065, -0.0059). Among heavy-drinking participants, BAC levels decreased on average from 0.106% to 0.096%, whereas the reverse trend was observed for lighter-drinking participants, whose levels increased from 0.058% to 0.067%. A similar interaction emerged for BAC underestimation (b=-0.0058, 95% CI=-0.0066, -0.0049), with odds of underestimation decreasing among heavy-drinking and increasing among light-drinking participants.

conclusionsThe results indicate promise for mobile BAC-tracking technologies as a low-impact intervention with the potential to decrease drinking among individuals who drink heavily-a population particularly susceptible to alcohol-related problems. In contrast, inverted trends emerged for light-drinking individuals, highlighting the need for empirical research in the fast-moving landscape of digital health.

Indexed as

Alcohol DrinkingBlood Alcohol ContentMobile ApplicationsAdultBreath TestsDigital HealthFemaleHumansLongitudinal StudiesMaleMiddle AgedTelemedicineYoung AdultBlood Alcohol ContentAddiction PsychiatryHarm ReductionMobile Health (mHealth) ToolPublic Health PsychiatrySubstance-Related and Addictive Disorders

Identifiers

PMID41634908
PMCPMC12875647

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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.