JMIR Publications

ABSTRACT

Background:

Smartwatch-based ecological momentary assessment (EMA) methods have previously been developed to minimise participant burden and maximise engagement and compliance. In this study we explore the feasibility of using these smartwatch-based EMA methods to capture longitudinal, high temporal density self-report data about alcohol consumption in a non-clinical population selected to represent high and low Social-Economic Position (SEP) groups.

Objective:

To assess the feasibililty of using smartwatch-based ecological momentary assessment methods to capture self-report data about alcohol consumption.

Methods:

Thirty-two participants from the Avon Longitudinal Study of Parents and Children (13 high, 19 low SEP) wore a smartwatch running a custom-developed EMA app for 3 months between Oct 2019 and June 2020. Every day over a 12 week period, participants were asked five times a day about any alcoholic drinks they had consumed in the previous two hours, and the context in which they were consumed. They were also asked if they had missed recording any alcoholic drinks the day before. As a comparison, participants also completed fortnightly online diaries of alcohol consumed using the Timeline Followback (TLFB) method. At the end of the study participants completed a semi-structured interview about their experiences.

Results:

The compliance rate for all participants who started the study for the smartwatch EMA method decreased from around 70% in week 1 to 45% in week 12, compared with the online TLFB method which was flatter at around 50% over the 12 weeks. The compliance for all participants still active for the smartwatch EMA method was much flatter, around 70% for the whole 12 weeks, while for the online TLFB method it varied between 50% and 80% over the same period. The completion rate for the smartwatch EMA method varied around 80% across the twelve weeks. Within high and low SEP groups there was considerable variation in compliance and completion at each week of the study. However, almost all point estimates for both smartwatch EMA and online TLFB indicated lower levels of engagement for low SEP participants. All participants scored ‘experiences of using’ the two methods equally highly, with ‘willingness to use again’ slightly higher for smartwatch EMA.

Conclusions:

Our findings demonstrate the feasibility and acceptability of using smartwatch EMA methods for capturing alcohol consumption. These methods have the benefits of capturing higher temporal density, longitudinal data on alcohol consumption, with greater participant engagement and less missing data, and with the potential to be less susceptible to the recall errors than established methods such as TLFB. Future studies should explore the factors impacting participant attrition (the biggest reason for reduced engagement), and the validity of alcohol data captured with these methods. The consistent pattern of lower engagement in low SEP than high SEP participants indicates further work is also warranted to explore the impact and causes of these differences.