A Personalized Approach Bias Modification Smartphone App (“SWiPE”) to Reduce Alcohol Use: Open-Label Feasibility, Acceptability, and Preliminary Effectiveness Study

Abstract

Background Approach bias modification (ApBM), a computerized cognitive intervention that trains people to “avoid” alcohol-related images and “approach” nonalcohol images, reduces the likelihood of relapse when administered during residential alcohol treatment. However, most individuals experiencing alcohol problems do not require, do not seek, or have difficulty accessing residential treatment. Smartphone-delivered ApBM could offer an easily accessible intervention to reduce alcohol consumption that can be personalized (eg, allowing selection of personally relevant alcohol and positive nonalcohol training images) and gamified to optimize engagement. Objective We examined the feasibility, acceptability, and preliminary effectiveness of “SWiPE,” a gamified, personalized alcohol ApBM smartphone app, and explored alcohol consumption and craving outcomes in people drinking at hazardous levels or above (Alcohol Use Disorders Identification Test [AUDIT] score ≥8) who wanted to reduce their alcohol use. Methods In this open-label trial, frequency and quantity of alcohol consumption, alcohol dependence severity, and craving were measured prior to participants downloading SWiPE. Participants (n=1309) were instructed to complete at least 2 sessions per week for 4 weeks. Recruitment and completion rates were indicators of feasibility. Functionality, aesthetics, and quality ratings were indicators of acceptability. Participants were prompted to report frequency and quantity of alcohol consumption weekly during training and 1 month after training. They completed measures of craving and dependence after 4 weeks of training. Results We recruited 1309 participants (mean age 47.0, SD 10.0 years; 758/1309, 57.9% female; mean AUDIT score 21.8, SD 6.5) over 6 months. Participants completed a median of 5 sessions (IQR 2-9); 31.2% (409/1309) completed ≥8 sessions; and 34.8% (455/1309) completed the posttraining survey. Mean Mobile Application Rating Scale scores indicated good acceptability for functionality and aesthetics and fair acceptability for subjective quality. Among those who completed the posttraining assessment, mean past-week drinking days reduced from 5.1 (SD 2.0) pre-training to 4.2 (SD 2.3) in week 4 (t454=7.87; P<.001), and mean past-week standard drinks reduced from 32.8 (SD 22.1) to 24.7 (SD 20.1; t454=8.58; P<.001). Mean Craving Experience Questionnaire frequency scores reduced from 4.5 (SD 2.0) to 2.8 (SD 1.8; t435=19.39; P<.001). Severity of Dependence scores reduced from 7.7 (SD 3.0) to 6.0 (SD 3.2; t435=12.44; P<.001). For the 19.4% (254/1309) of participants who completed a 1-month follow-up, mean past-week drinking days and standard drinks were 3.9 (SD 2.5) and 23.9 (SD 20.7), respectively, both significantly lower than at baseline (P<.001). Conclusions The findings suggest SWiPE is feasible and acceptable and may be effective at reducing alcohol consumption and craving in a predominantly nontreatment-seeking sample of adult Australians drinking at hazardous levels. SWiPE’s efficacy, relative to a control condition, now needs establishing in a randomized controlled trial. Smartphone-delivered personalized ApBM could be a highly scalable, widely accessible support tool for reducing alcohol use. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12620000638932; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12620000638932p International Registered Report Identifier (IRRID) RR2-10.2196/21278

Leveraging mHealth and Wearable Sensors to Manage Alcohol Use Disorders: A Systematic Literature Review

“…Of the 25 studies, 14/25 (56%) used an mHealth app, 4/25 (16%) used telephone or interactive voice response, 3/25 (12%) used mHealth serious games or cognitive training delivered on mobile devices, and four studies used either mHealth SMS or mHealth + telephone (2/26 each, 8%). Of the 25 studies analyzed over a 10-year period, 2 were from 2012 [ 17 , 18 ], 1 was from 2013 [ 19 ], 2 were from 2014 [ 20 , 21 ], 1 was from 2015 [ 22 ], 3 were from 2016 [ 23 , 24 , 25 ], 4 were from 2017 [ 26 , 27 , 28 , 29 ], 2 were from 2019 [ 30 , 31 ], and 2020 [ 32 , 33 ], 4 were from 2021 [ 34 , 35 , 36 , 37 ], and 2022 [ 38 , 39 , 40 , 41 ]. Zero studies were from 2018.…”

“…Five themes and three individual observations were identified by the reviewers for a total of 68 occurrences in the literature. Reduction in consumption was identified in 15/31 (48%) of the occurrences [ 18 , 23 , 26 , 27 , 30 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. In 10/31 (32%) of the occurrences, the reduction was statistically significant, but in 5/31 (15%) of the occurrences, it was not statistically significant [ 21 , 22 , 29 , 31 , 33 ].…”

“…Almost every intervention would require additional teaching of users and provider teams to work with it. This theme occurred 22/34 (65%) occurrences [ 17 , 18 , 20 , 23 , 24 , 25 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. In 4/34 (12%) occurrences, it was highlighted that the intervention was equally as effective at managing AUD as the traditional treatment methods, so change may not be necessary [ 21 , 22 , 29 , 31 ].…”

“…Overall, mHealth apps mostly resulted in a reduction in alcohol consumption or a reduction in cravings [ 17 , 18 , 19 , 20 , 24 , 26 , 28 , 30 , 33 , 36 , 37 , 38 , 39 , 41 ]. The mHealth + telephone interventions had the same effect [ 35 , 40 ].…”

The current evidence for substance use disorder apps

“…A total of 1309 Australian participants drinking at hazardous levels (i.e. AUDIT scores ≥8) who wanted to reduce or quit drinking were recruited from the community, where 59% scored ≥20 on the AUDIT (indicating likely dependence) despite only 8.9% currently accessing treatment [16 ▪ ]. Participants completed at least two sessions of ApBM per week for 4-weeks.…”