I-PREVENT: Internet-based Stepped Care for Alcohol Use in Denmark

Stepped care is a treatment principle in which the type and intensity of treatment is based on the individual needs of the client. Research on population-based stepped-care approaches in the alcohol field is still very limited. There is also no large-scale study to date comparing the effectiveness of different intensities of internet- and mobile-based interventions among individuals who exhibit the full spectrum of alcohol use.

The main objectives of this study are to compare the short- and long-term effectiveness of internet-based brief intervention programmes, unguided as well as guided cognitive behavioural therapy (iCBT) in reducing alcohol use or alcohol use disorders in 3514 adults as well as in specific socio-demographic subgroups of the Danish population.

Machine learning models will be developed to enable personalised prevention for the development of AUD or progression to severe AUD (Alcohol use disorder). In addition to the direct follow-up interviews of up to two years, the Danish registry data of the participants will be followed over a period of 10 years.

Digital interventions offer great potential for individualising treatments, which is often not exploited. Thanks to the combination of machine learning and stepped care, individualisation is developed both data- and concept-driven. The linkage with Danish registry data offers valuable research opportunities, which would not be so easily feasible in other countries.