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D-Arianna Eng


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Digital - Alcohol RIsk Alertness Notifying Network for Adolescents

Giuseppe Carrà, Cristina Crocamo, Francesco Bartoli, Giulia Brambilla, Daniele Carretta, Alessandro Schivalocchi, Stefano Reato, Caterina Clerici, Massimo Clerici

Department of Surgery and Translational Medicine, Psychiatry section, University of Milano-Bicocca.

An innovative eHealth app estimating current risk for binge drinking in young people
University of Milano-Bicocca
Supported by a Cariplo Foundation grant

HINTS
The risk percentage provided by D-ARIANNA is only an estimate of the probability of binge drinking. It does not imply the ability to predict that it will happen.
Please remember that binge drinking is the consumption of five or more alcoholic drinks for men and four or more for women. and indeed adolescents and young adults who engage in binge drinking are more likely to report health risk behaviors. People who have previously engaged in binge drinking face increased risk of further episodes. If your risk for binge drinking is high you may wish to discuss it and its consequences with your family doctor.

WHAT’S D-ARIANNA FOR?
D-ARIANNA provides an evidence based current risk estimate for binge drinking. Binge drinking is common among young people but often relevant risk is not recognized. D-ARIANNA, as an attractive eHealth app for young people, may be useful to enhance awareness of this problem.

HOW DOES D-ARIANNA WORK? A specific questionnaire investigates domains derived from identified risk/protective factors. User’s answers are implemented in an algorithm, estimating user’s percentage risk for binge drinking, and providing classification of different risk levels (from low to high), with user-friendly screens. Risk factors that mostly contribute to the overall score are shown in a closing summary message

HOW MANY D-ARIANNA VERSIONS ARE AVAILABLE?
Risk prediction model implementation has been based on a systematic review of the scientific literature. This has not been experimentally tested yet. Though most of risk factors can be generalizable across different populations, accounting for variability due to local drinking cultures, prevalence data for age groups and gender of young binge drinkers need to be collected at a National level. Thus the model can be easily adapted if relevant national data can be retrieved. If other investigators wish to explore modification of binge drinking risk by demographic factors, our model, along with the eHealth app, is available upon request.