User characteristics of a smartphone app to reduce alcohol consumption

Transl Behav Med. 2017 Dec;7(4):845-853. doi: 10.1007/s13142-017-0477-1.

Abstract

Digital interventions are available to help people reduce their alcohol consumption, but it is not known who uses these interventions and how this treatment-seeking group compares with the general population of drinkers. The study objective was to compare the socio-demographic and drinking characteristics of users of the 'Drinks Meter' smartphone app with the general population of drinkers in England and website users of the same intervention. Data were used from the Drinks Meter app and website, and a nationally representative cross-sectional survey in England (Alcohol Toolkit Study). Participants were drinkers aged 16+ in England. Data were collected on participants' age, gender, region, sexual orientation, social grade and AUDIT score. Regression analyses were conducted to assess differences in socio-demographic and drinking characteristics between samples. Drinks Meter app users, compared with drinkers of the general population, were younger, more likely to be from the South, not heterosexual, less likely to be of a lower social grade and had a higher mean AUDIT score. Drinks Meter app users were younger than website users and reported greater alcohol consumption and related harms. Drinkers using the Drinks Meter app are more likely to be younger and report greater alcohol consumption and related harms compared with the general population of drinkers in England and website users of the same intervention. Apps that provide feedback on drinking appear to be reaching those who report greater alcohol consumption and related harms.

Keywords: Alcohol; Digital; Intervention; Smartphone app; User.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Alcohol Drinking*
  • Alcohol-Related Disorders / prevention & control*
  • Cross-Sectional Studies
  • England
  • Female
  • Health Promotion* / methods
  • Humans
  • Internet
  • Male
  • Middle Aged
  • Mobile Applications*
  • Regression Analysis
  • Smartphone*
  • Socioeconomic Factors