An evaluation of the efficacy of two add-on ecological momentary intervention modules for depression in a pragmatic randomized controlled trial (ZELF-i)

Psychol Med. 2020 Dec 14;52(13):1-10. doi: 10.1017/S0033291720004845. Online ahead of print.

Abstract

Background: Depression treatment might be enhanced by ecological momentary interventions (EMI) based on self-monitoring and person-specific feedback. This study is the first to examine the efficacy of two different EMI modules for depression in routine clinical practice.

Methods: Outpatients starting depression treatment at secondary mental health services (N = 161; MIDS-DEPRESSION = 35.9, s.d. = 10.7; MAGE = 32.8, s.d. = 12.1; 46% male) participated in a pragmatic randomized controlled trial with three arms. Two experimental groups engaged in 28 days of systematic self-monitoring (5 times per day), and received weekly feedback on either positive affect and activities (Do-module) or negative affect and thinking patterns (Think-module). The control group received no additional intervention. Participants completed questionnaires on depressive symptoms (primary outcome), social functioning, and empowerment before and after the intervention period, and at four measurements during a 6-month follow-up period.

Results: Of the 90 (out of 110) participants who completed the intervention, 86% would recommend it. However, the experimental groups did not show significantly more or faster changes over time than the control group in terms of depressive symptoms, social functioning, and empowerment. Furthermore, the trajectories of the two EMI modules were very similar.

Conclusions: We did not find statistical evidence that this type of EMI augments the efficacy of regular depression treatment, regardless of module content. We cannot rule out that EMIs have a positive impact on other domains or provide a more efficient way of delivering care. Nonetheless, EMI's promise of effectiveness has not materialized yet.

Keywords: Depression; ecological momentary assessment; experience sampling; intervention; mHealth; personalized medicine.