ABSTRACT
BACKGROUND: Digital self-help interventions for reducing the use of alcohol tobacco and other drugs (ATOD) have generally shown positive but small effects in controlling substance use and improving the quality of life of participants. Nonetheless, low adherence rates remain a major drawback of these digital interventions, with mixed results in (prolonged) participation and outcome. To prevent non-adherence, we developed models to predict success in the early stages of an ATOD digital self-help intervention and explore the predictors associated with participant's goal achievement. METHODS: We included previous and current participants from a widely used, evidence-based ATOD intervention from the Netherlands (Jellinek Digital Self-help). Participants were considered successful if they completed all intervention modules and reached their substance use goals (i.e., stop/reduce). Early dropout was defined as finishing only the first module. During model development, participants were split per substance (alcohol, tobacco, cannabis) and features were computed based on the log data of the first 3 days of intervention participation. Machine learning models were trained, validated and tested using a nested k-fold cross-validation strategy. RESULTS: From the 32,398 participants enrolled in the study, 80% of participants did not complete the first module of the intervention and were excluded from further analysis. From the remaining participants, the percentage of success for each substance was 30% for alcohol, 22% for cannabis and 24% for tobacco. The area under the Receiver Operating Characteristic curve was the highest for the Random Forest model trained on data from the alcohol and tobacco programs (0.71 95%CI 0.69-0.73) and (0.71 95%CI 0.67-0.76), respectively, followed by cannabis (0.67 95%CI 0.59-0.75). Quitting substance use instead of moderation as an intervention goal, initial daily consumption, no substance use on the weekends as a target goal and intervention engagement were strong predictors of success. DISCUSSION: Using log data from the first 3 days of intervention use, machine learning models showed positive results in identifying successful participants. Our results suggest the models were especially able to identify participants at risk of early dropout. Multiple variables were found to have high predictive value, which can be used to further improve the intervention.
ABSTRACT
BACKGROUND: Depressive disorders and problematic drinking often co-occur, also among young adults. These co-occurring conditions are associated with various negative health outcomes compared to both conditions alone. Early intervention by addressing alcohol use and depressive symptoms simultaneously in the same treatment might improve both conditions. However, evidence on the (cost-) effectiveness of digital combined depression and alcohol interventions for young adults is currently insufficient. We therefore developed an add-on digital alcohol moderation adherence-focussed guided intervention to complement treatment as usual (TAU) for depressive disorders. The digital intervention is a web-app, including 6 modules based on motivational interviewing and cognitive behavioural therapy. This study aims to evaluate the (cost-)effectiveness of a digital alcohol moderation intervention + TAU compared to TAU on alcohol and depression outcomes among young adults with co-occurring depressive disorders and problematic alcohol use. METHODS: One hundred fifty-six participants, aged 18-35 years, with problematic alcohol use and a diagnosed depressive disorder will participate in a pragmatic multicentre two-arm randomized controlled trial. Problematic alcohol use is operationalised as scoring ≥5 for women and ≥ 8 for men on the Alcohol Use Disorder Identification Test (AUDIT). Participants will be randomized to either the experimental group (digital alcohol intervention + TAU) or control group (TAU only). Participants will be recruited at three Dutch mental health care centres and through social media. Assessments take place at baseline and after 3, 6 and 12 months post-randomization. The primary outcome is treatment response at 6-month follow-up, operationalized as a composite score that combines alcohol use and depression measures and indicates whether treatment has been successful or not. Secondary outcomes are depressive symptoms and alcohol use (i.e. number of weekly standard drinks and AUDIT score). An economic evaluation will be conducted alongside the trial. DISCUSSION: This study evaluates the (cost-) effectiveness of an add-on digital alcohol moderation intervention for young adults who are in treatment for depressive disorders. If proven effective, the digital intervention could be implemented in mental health care and improve treatment for people with co-occurring depressive disorders and problematic alcohol use. TRIAL REGISTRATION: Pre-registered on October 29, 2019 in The Netherlands Trial Register ( NL8122 ).
