Larisa Dinu: Do engagement and behavioural mechanisms underpin the effectiveness of the Drink Less app?
Digital interventions, such as websites and smartphone applications (‘apps’), potentially have a broad reach and low incremental costs for delivering alcohol interventions at scale2. Apps are a particularly promising mode of intervention delivery because smartphones have become increasingly affordable to end users, with approximately 84% of the UK population having access to a smartphone3. Meta-analyses have shown there is evidence for the effectiveness of digital interventions at reducing alcohol consumption4,5. Nonetheless, most of the interventions included in these meta-analyses were websites rather than apps. Furthermore, despite many alcohol reduction apps being available on app stores in the United Kingdom (UK), none have been evaluated in a randomised controlled trial (RCT) among the adult general population. To address this gap, we conducted an RCT (the iDEAS trial; iOS Drink Less, evaluating the Effectiveness of an Alcohol Smartphone app) to evaluate the effectiveness of recommending the evidence- and theory-informed app, Drink Less, in reducing alcohol consumption among increasing and higher risk drinkers in the UK, compared with usual digital care6,7. After accounting for missing data using multiple imputation, we found a two-unit reduction (95% CI = −3.76 to −0.24) in weekly alcohol consumption among the Drink Less group after 6 months compared with usual digital care, though the effect without imputation (where non-responders were assumed to be drinking at baseline levels) was weaker (−0.98 units, 95% CI = −2.67 to 0.70)7.
In addition to establishing whether an alcohol reduction app is effective, it is critical to understand its mechanisms of action, or, in other words, why it is effective. Understanding the underlying processes through which an intervention has its effects can help design more effective interventions8. To this end, process evaluations can help test hypothesised causal pathways using quantitative data9. In the current study, the overarching theoretical framework underpinning the Drink Less app is the COM-B model of behaviour10, and the proposed mechanisms of action were engagement with the interventional components of the Drink Less app (see ‘Methods’ section)11,12, which, in turn, influences participants’ behavioural characteristics, including urges to drink, motivation to drink less and self-regulatory behaviour (see Fig. 1 for the logic model).
This study used data from the iDEAS trial comparing the effectiveness of the Drink Less app with usual digital care in reducing alcohol consumption in increasing and higher risk drinkers, focusing on participants’ behavioural characteristics and engagement with the intervention as part of the embedded mixed-methods process evaluation. The qualitative component evaluating the acceptability of the digital tools is reported elsewhere13 and found that Drink Less was perceived as being ethical, easy, user-friendly and effective. The following research questions were addressed:
(1)
To what extent do participants self-report adhering to their recommended digital tool and how does this differ by group?
(2)
Among participants in the intervention group, to what extent do participants engage with the Drink Less app in terms of (i) downloading the app; (ii) depth; (iii) frequency; (iv) duration; and (v) amount of use over the 6-month period from the date of recommendation?
(3)
Does motivation to drink less at baseline moderate the effect of the intervention on alcohol reduction in increasing and higher risk drinkers at 6-month follow-up?
(4)
Do (i) urges to drink, self-regulatory and self-monitoring behaviour at 6-month follow-up, and (ii) self-reported adherence at 1- or 6-month follow-up to the recommended digital tool mediate the effect of the intervention on alcohol reduction in increasing and higher risk drinkers at 6-month follow-up?
(5)
Among participants in the intervention group, does extent of behavioural engagement with the Drink Less app mediate the effect of self-reported adherence on intervention effectiveness on alcohol reduction in increasing and higher risk drinkers at 6-month follow-up?