Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2026-03-26 @ 3:19 PM
Ignite Modification Date:
2026-03-26 @ 3:19 PM
NCT ID:
NCT07373405
Brief Summary:
Background: Internet-based interventions can improve access to non-treatment-seeking populations, preventing the onset or progression of alcohol use disorder (AUD). Stepped-care guidelines for face-to-face AUD interventions recommend internet-based Brief Intervention (iBI) or unguided Cognitive Behavioural Therapy (iCBT) for no or mild AUD, and guided iCBT for moderate to severe AUD. However, no large-scale superiority trial has compared the effectiveness of these interventions among non-treatment-seeking individuals across the full spectrum of problematic alcohol use.
Aims: 1) Compare the effectiveness of iBI, unguided, and guided iCBT in reducing alcohol consumption in non-treatment-seeking individuals with sub-threshold or full AUD; 2) develop models via machine learning for personalized AUD prevention and progression management.
Methods: A nationwide sample of 3519 individuals will be stratified by sub-threshold/mild AUD and moderate/severe AUD and randomized to: 1) online assessment (OA)+ iBI; 2) OA+ unguided iCBT; or 3) OA+ guided iCBT. The iCBT sessions will address problematic alcohol use and co-occuring externalizing and internalizing psychiatric symptoms. Data will be collected from OA, interventions, and Danish registries at baseline and 3-, 6-, 12-, and 24-month follow-ups, with registry follow-up over 10 years.
Perspectives: Findings will compare stepped-care and machine learning-driven personalized approaches to inform guidelines for non-treatment-seeking populations. Internet-based assessment and interventions support continuous data collection, enabling ongoing improvements and personalized prevention. This large-scale dissemination targeting non-treatment-seeking populations across the full spectrum of problematic alcohol use will pave the way for future initiatives and may refine prevention strategies if the stepped-care model proves insufficient for this group.
Key words: Alcohol Use Disorder, Internet-Based Interventions, Machine Learning, Non-treatment Seekers, Stepped-Care
Study:
NCT07373405
Study Brief:
Protocol Section:
NCT07373405