Do illness beliefs predict uptake of depression treatment after web-based depression screening? A secondary analysis of the DISCOVER RCT.

Abstract

BACKGROUND Only a minority of those with depressive disorder receive treatment. Besides system-level factors, individual factors could account for the gap between detection and treatment of depression in so far unreached but affected populations. OBJECTIVE This study tests the predictive value of illness beliefs (IB) for the uptake of depression treatment 6 months after web-based depression screening. METHODS This is a secondary analysis of the randomised controlled Germany-wide DISCOVER trial that investigated the effects of automated results feedback following web-based depression screening in untreated participants with at least moderate depression severity (Patient Health Questionnaire ≥10 points). IB were examined as predictors of depression treatment uptake. Eligible participants were at least 18 years old, reported proficiency in German language, and provided informed consent. IB were assessed at the time of screening (baseline) with an adapted version of the Brief Illness Perception Questionnaire. Uptake of depression treatment was operationalised as self-reported initialisation of psychotherapy and/or antidepressant medication 6 months after baseline. Analyses were adjusted for study arm. FINDINGS Data from N=871 participants of the DISCOVER trial providing follow-up data were analysed. IB denoting more consequences (OR (95% CI) 1.12 (1.00 to 1.26)), higher treatment control (OR (95% CI) 1.19 (1.11 to 1.29)) and a depression-conforming illness identity (OR (95% CI) 1.65 (1.15 to 2.36)) were associated with up to 56.8% relative increase in predicted probability of depression treatment uptake 6 months after baseline. CONCLUSIONS Results suggest considerable effects of IB for depression treatment uptake in untreated populations. CLINICAL IMPLICATIONS IB could reflect relevant barriers in access to depression care and, concurrently, intervention targets to foster health service utilisation in untreated populations.