The Efficacy of Automated Feedback After Internet-based Depression Screening

Major depressive disorder (MDD) is a highly prevalent condition associated with substantial disease burden and economic costs. Still, it often remains undetected and untreated, which in turn increases the likelihood of a chronic course, treatment resistance and rising healthcare costs. One solution to address early detection and disease burden could be widely accessible depression screening. Our previous trial in cardiac patients provides first evidence that depression screening combined with written individual-targeted feedback on the screening results improves depression severity and encourages greater patient participation and engagement in mental health. To amplify these effects in a broader setting, the internet-based DISCOVER randomized controlled trial (RCT) now aims at addressing affected but yet undetected individuals on the internet. In order to evaluate the effect of feedback in this setting, a total of 1076 individuals reporting elevated levels of depression (PHQ-9 score ≥ 10) will be randomized into three groups. They either receive a) no feedback (control group), b) standardised or c) tailored feedback on their depression screening results. The primary hypothesis is that feedback reduces depression severity six months after screening compared to no feedback. The secondary hypothesis is that tailored feedback is more efficacious as compared to standard feedback. Futher outcomes are guideline-based depression care, depression-related help-seeking behaviour, a health economic evaluation, clinical outcomes (somatic symptom severity and anxiety), health-related quality of life, illness beliefs, intervention acceptance, depression diagnosis and adverse events.