Evidence map›Paper›PMID 40905156›Full record

Trial reportAddiction (Abingdon, England)2026

Efficacy of a personalised alcohol approach bias modification smartphone app in people accessing outpatient alcohol use disorder treatment: A randomised controlled trial.

Joshua B B Garfield, Bosco Rowland, Samuel K Liu, Hugh Piercy, Yvonne Bonomo, Danielle Whelan, Victoria Manning

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Addiction (Abingdon, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
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

7 authors.

Joshua B B GarfieldMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, Melbourne, Australia.ORCID 0000-0002-5076-6499
Bosco RowlandMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, Melbourne, Australia.
Samuel K LiuTurning Point, Eastern Health, Richmond, Victoria, Australia.
Hugh PiercyMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, Melbourne, Australia.
Yvonne BonomoDepartment of Addiction Medicine, St Vincent's Hospital Melbourne, Melbourne, Australia.
Danielle WhelanMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, Melbourne, Australia.
Victoria ManningMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, Melbourne, Australia.

Funding

National Health and Medical Research Council 2009851Victorian Alcohol and Drug Association's (VAADA) Alcohol and Drug Research Innovation Agenda (ADRIA)
6 · The paper itself

Abstract

BACKGROUND AND

aimsSeveral randomised controlled trials (RCTs) have demonstrated that delivering approach bias modification (ApBM) during residential alcohol use disorder (AUD) treatment helps prevent post-treatment relapse. However, few studies have examined ApBM's efficacy for AUD in outpatients. We trialled a personalised ApBM smartphone app in individuals receiving outpatient AUD treatment.

designThis double-blind RCT randomised participants to receive ApBM or sham training, adjunctive to treatment as usual.

settingParticipants were recruited from alcohol and other drug treatment services in Melbourne, Australia.

participants79 participants (mean age 46.6 years; 45 male, 34 female) installed the app between May 2022 and January 2024. INTERVENTION AND COMPARATOR: In the ApBM condition, the app delivered personalised, gamified ApBM. Notifications prompted participants (n = 39) to complete 2 ApBM sessions weekly for 4 weeks. The control version prompted participants (n = 40) to complete a weekly sham-training task for 4 weeks. MEASUREMENTS: The primary outcome was number of standard drinks (10 g pure alcohol) consumed in week 4 of the intervention period, self-reported in the app. Secondary outcomes included past-week standard drinks at 8-week and 16-week follow-ups, past-week drinking days, past-week heavy drinking days (HDDs; days when ≥5 standard drinks were consumed) and questionnaire measures of AUD severity, quality of life and alcohol craving. Primary analyses followed an intention-to-treat (ITT) approach, with secondary complete-case sensitivity analyses also conducted for all outcomes.

findingsGroups did not statistically significantly differ in the primary outcome [values from ITT negative binomial model: ApBM = 75.49 standard drinks, control = 71.34 standard drinks, difference = 4.16, 95% confidence interval (CI) = -42.37 to 50.69, P = 0.859]. Most analyses of secondary outcomes showed statistically non-significant effects, with the only exception being past-week standard drinks at the 16-week follow-up, where ApBM participants showed statistically significantly larger decreases than controls in past-week standard drinks (reduction of 14.6, relative to baseline, versus 2.1 in controls; interaction β = -12.53, 95% CI = -23.85 to -1.22; P = 0.030). Time x group interaction effects were statistically non-significant for all other secondary outcomes (Ps > 0.069).

conclusionsA smartphone app using approach bias modification showed no evidence for reducing alcohol use among alcohol use disorder outpatients after 4 weeks, or evidence for effects on most secondary outcomes, although 16-week follow-up results suggested that approach bias modification may have facilitated delayed/longer-term reductions in alcohol use.

Indexed as

AlcoholismMobile ApplicationsAdultAustraliaDouble-Blind MethodFemaleHumansMaleMiddle AgedOutpatientsSmartphoneTreatment Outcomeaddictionalcohol use disorderapproach bias modificationcognitive bias modificationoutpatient treatmentrandomised controlled trialsmartphone app

Identifiers

PMID40905156
PMCPMC12710684

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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.