Heterogeneity in Symptoms in Depression - A replication study in a Digital Mental Health Intervention using the PHQ-9 Questionnaire (Preprint)
BACKGROUND Past work has shown massive variation in depressive symptoms between patients, challenging the perception of major depressive disorder (MDD) as being uniform. This appears quite relevant also for digital mental health (DMH) interventions. While individualization is one of the key potentials of these approaches, this is regularly not utilized and the same static depression treatment is offered to all patients. OBJECTIVE This paper aims to replicate the approach from Fried & Nesse (2015), analyzing the variation of depressive symptoms within 1757 participants in a DMH intervention for depression and anxiety. METHODS Participants’ answers to the single items of the Patient Health Questionnaire 9-item scale (PHQ-9) were used to identify distinct patterns out of the 9 core symptoms of the DSM-5. RESULTS Overall, the 1757 participants showed 231 different patterns of symptoms. The most regular pattern occurred for 8% of the patients. 85% of the participants had a symptom pattern that was shared with less than 4% of the whole sample. The number of unique symptom patterns per participant decreased with higher symptom severity, but the 342 patients with overall severe depression symptoms still exhibited 34 different constellations of single symptoms. CONCLUSIONS The large variation in symptoms challenges the assignment of static depression interventions in DMH and calls for more individualized treatment procedures. Luckily, such procedures can be implemented particularly easily in an app-based context, for example by modular program structures.