JMIR Form Res. 2026 Sep 10;10:e89635. doi: 10.2196/89635.
ABSTRACT
BACKGROUND: Targeting automatic approach tendencies toward alcohol-related stimuli has been shown to significantly reduce relapse rates in patients with alcohol use disorder (AUD) when used as an add-on to inpatient treatment. Traditional approach-avoidance task (AAT) training requires a clinical setting and a stationary device.
OBJECTIVE: A mobile app was tested that allowed the training to be conducted outside a clinical environment while capturing actual motion parameters, such as acceleration.
METHODS: Three proof-of-concept studies assessed the reliability and validity of the mobile app version of the AAT. Study 1 tested technical stability and measurement reliability in 26 university students across 6 home-based sessions. Study 2 examined approach-avoidance tendencies in 15 inpatients with AUD. Study 3 tested 28 soccer fans to determine the modifiability of alcohol-related biases after 3 or 6 training sessions.
RESULTS: The app demonstrated high technical stability and measurement reliability in study 1. In study 2, patients showed faster reaction times (RTs) when pushing away alcohol-related images (avoidance tendency) and greater acceleration when pulling them toward themselves (approach tendency). In study 3, participants also exhibited an RT-based alcohol avoidance bias and a small acceleration-based alcohol approach bias. Training effects were observed for RTs after the test, indicating an increase in alcohol avoidance. An increase in acceleration-based alcohol avoidance was only found in participants with risky alcohol consumption.
CONCLUSIONS: The mobile app version of the AAT appears to produce reliable measures and might have the potential to effectively modify alcohol-related automatic tendencies. The current study serves as a proof of concept, so all results should be treated as exploratory. Future randomized controlled trials are needed to evaluate the app’s potential to change actual alcohol behavior in nonclinical populations.
PMID:42721312 | DOI:10.2196/89635
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