Evidence map›Paper›PMID 41961898›Full record

ArticlePLOS digital health2026

Reducing alcohol consumption in UK armed forces veterans: Feasibility of using personalized push notifications with AI.

Daniel Leightley, Charlotte Williamson, Iain J Marshall, Vasa Curcin, Roberto J Rona, Dominic Murphy, Nicola T Fear, Laura Goodwin

Abstract read
In one paragraph

Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Daniel LeightleyDepartment of Population Health Sciences, School of Population Health Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-9512-752X
Charlotte WilliamsonDepartment of Population Health Sciences, School of Population Health Sciences, King's College London, London, United Kingdom.
Iain J MarshallDepartment of Population Health Sciences, School of Population Health Sciences, King's College London, London, United Kingdom.
Vasa CurcinDepartment of Population Health Sciences, School of Population Health Sciences, King's College London, London, United Kingdom.
Roberto J RonaKing's Centre for Military Health Research, King's College London, London, United Kingdom.
Dominic MurphyKing's Centre for Military Health Research, King's College London, London, United Kingdom.
Nicola T FearKing's Centre for Military Health Research, King's College London, London, United Kingdom.
Laura GoodwinFaculty of Health and Medicine, Lancaster University, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study assessed the feasibility of deploying RationAI, a personalized AI-supported messaging framework, to reduce alcohol consumption among UK Armed Forces veterans. Participants were given DrinksRation, a mobile phone app, and allocated to receive either personalized or generic behavior change messages over 12 weeks. A total of 2,871 participants registered for an account during the study period. Feasibility was evaluated through recruitment (n = 2,871), retention (25.4% met engagement criteria), app usage and message delivery. Of those eligible, 343 participants were allocated to the personalized messaging group and 385 to the generic message group. The personalized group had higher early engagement, with app usage peaking at 212.4 (95% CI: 207.32 to 217.45) seconds in Week 2 compared to 183.7 seconds in the control group (95% CI: 178.90 to 188.46; p < 0.001) and received more notifications on average, reflecting additional personalized and event-triggered messages delivered as part of the intervention (47.7 [SD = 18.8] vs 16.3 [SD = 5.3]). Alcohol consumption declined in both groups over the 12-week period, with the personalized group showing a greater reduction from 31.08 to 13.20 units per week, compared to 31.24 to 15.17 units in the control group. Statistically significant between-group differences were observed at Week 2 (p = 0.027), Week 3 (p = 0.041), Week 4 (p = 0.008), and Week 10 (p = 0.049), favoring the personalized group, although between-group differences attenuated towards Week 12. Despite high attrition, the app engaged participants from an important population. These findings suggest the feasibility of personalized digital interventions for alcohol reduction, but there is a need for improved strategies to enhance long-term engagement.

Identifiers

PMID41961898
PMCPMC13068231

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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.