Smartphone-Delivered Cognitive Bias Modification for Reducing Harmful Drinking amongst middle – older age adults

Background:

Australia, like most high-income countries is facing a rapidly aging population, where established heavy alcohol use patterns are carried into older-adulthood, a period when risk of alcohol-related harms is increased. Novel, scalable, low-cost, digital interventions are needed to reduce harmful drinking amongst this age-group. Among treatment seekers, Cognitive Bias modification (CBM) is proving to be a promising new form of cognitive training for preventing/reducing alcohol use, that can be delivered via smartphone. This study explored the acceptability and preliminary effectiveness of the world's first personalised alcohol CBM app (SWiPE), in a sample of Australians >55 years. 

Methods

In an open-label trial of non-treatment seekers wanting to reduce their alcohol use, 289 middle-to-older aged adults (mean age 60.4 years) were asked to complete two personalised CBM sessions a week, for 4 weeks and report weekly consumption of alcohol (drinking days and standard drinks) and alcohol craving. Participants were trained to automatically avoid (swipe away) self-selected images of alcohol, and to approach self-selected positive/healthy images reflecting their personal goals, hobbies or values. We explored the apps acceptability (adherence, user mobile acceptability ratings, free text responses) and preliminary effectiveness (changes in standard drinks, craving, dependence, and proportion drinking within government recommended guidelines (i.e. <4 standard drinks) and weekly (i.e. <10 standard drinks), in week 4 of training, relative to baseline (week prior to training). 

Results 

The intervention was deemed acceptable amongst survey completers, with 72.3% demonstrating training adherence. Relative to baseline, there was a significant increase in the proportion drinking within recommended single-session (no more than 4) and weekly alcohol consumption guidelines (no more than 10) post-training (from 25 to 41% and 6 to 28%, respectively, p<.001), with past-week standard drinks significantly decreasing by 18.2% (p<.001), a 15.5% reduction in drinking frequency (p<.001), and significant reductions in mean craving and dependence scores (p<.001). 

Conclusions

Findings suggest smartphone-delivered CBM is acceptable amongst middle-to-older aged Australians and may support this ‘at risk’ cohort to remain within government-recommended alcohol consumption guidelines to optimise healthy aging. These soon-to-be published findings add to growing evidence for smartphone interventions with older adults and for CBM as a low-cost, wide-reaching intervention to reduce alcohol use. Recognising that the single-arm design necessitates cautious interpretation of these preliminary findings, we discuss a later iteration of the app incorporating user-informed adaptations being tested in a double-blind RCT, to elucidate the impact of personalised CBM over and above routine alcohol monitoring.