Risk Estimation Modeling and Feasibility Testing for a Mobile eHealth Intervention for Binge Drinking among Young People: The D-ARIANNA (Digital-Alcohol RIsk Alertness Notifying Network for Adolescents and young adults) Project

Binge drinking is common among young people but often relevant risk factors are not recognized. eHealth apps, attractive for young people, may be useful to enhance awareness of this problem. We aimed at developing a current risk estimation model for binge drinking, incorporated into an eHealth app-D-ARIANNA (Digital-Alcohol RIsk Alertness Notifying Network for Adolescents and young adults)-for young people. Methods: A longitudinal approach with phase 1 (risk estimation), phase 2 (design), and phase 3 (feasibility) was followed. Risk/protective factors identified from the literature were used to develop a current risk estimation model for binge drinking. Relevant odds ratios were subsequently pooled through meta-analytic techniques with a random-effects model, deriving weighted estimates to be introduced in a final model. A set of questions, matching identified risk factors, were nested in a questionnaire and assessed for wording, content, and acceptability in focus groups involving 110 adolescents and young adults. Results: Ten risk factors (5 modifiable) and 2 protective factors showed significant associations with binge drinking and were included in the model. Their weighted coefficients ranged between-0.71 (school proficiency) and 1.90 (cannabis use). The model, nested in an eHealth app questionnaire, provides in percent an overall current risk score, accompanied by appropriate images. Factors that mostly contribute are shown in summary messages. Minor changes have been realized after focus groups review. Most of the subjects (74%) regarded the eHealth app as helpful to assess binge drinking risk. Conclusions: We could produce an evidence-based eHealth app for young people, evaluating current risk for binge drinking. Its effectiveness will be tested in a large trial.