Efficacy of stand-alone digital mental health applications for anxiety and depression: A meta-analysis of randomized controlled trials

Paige L Seegan; Michael J Miller; Jennifer L Heliste; Lily Fathi; Joseph F McGuire

doi:10.1016/j.jpsychires.2023.06.019

Efficacy of stand-alone digital mental health applications for anxiety and depression: A meta-analysis of randomized controlled trials

J Psychiatr Res. 2023 Aug:164:171-183. doi: 10.1016/j.jpsychires.2023.06.019. Epub 2023 Jun 16.

Authors

Paige L Seegan¹, Michael J Miller², Jennifer L Heliste², Lily Fathi², Joseph F McGuire³

Affiliations

¹ Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
² Mid-Atlantic Permanente Research Institute, Kaiser Permanente Mid-Atlantic States, Rockville, MD, USA; Mid-Atlantic Permanente Medical Group, Rockville, MD, USA.
³ Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: jfmcguire@jhmi.edu.

PMID: 37352813
PMCID: PMC10527200 (available on 2024-08-01)
DOI: 10.1016/j.jpsychires.2023.06.019

Abstract

Background: Anxiety and depressive disorders affect 20% of the population, cause functional impairment, and represent a leading cause of disability. Although evidence-based treatments exist, the shortage of trained clinicians and high demand for mental health services have resulted in limited access to evidence-based care. Digital mental health applications (DMHA) present innovative, scalable, and sustainable solutions to address disparities in mental health care.

Methods: The present study used meta-analytic techniques to evaluate the therapeutic effect of DMHAs in randomized controlled trials (RCTs) for individuals experiencing anxiety and/or depressive symptoms. Search terms were selected based on concepts related to digital mental health applications, mental health/wellness, intervention type, trial design, and anxiety and/or depression symptoms/diagnosis outcomes to capture all potentially eligible results. Potential demographic, DMHA, and trial design characteristics were examined as moderators of therapeutic effects.

Results: Random effects meta-analyses found that stand-alone DMHAs produced a modest reduction in anxiety (g = 0.31) and depressive (g = 0.35) symptom severity. Several moderators influenced the therapeutic effects of DMHAs for anxiety and/or depressive symptoms including treatment duration, participant inclusion criteria, and outcome measures.

Limitations: Minimal information was available on DMHA usability and participant engagement with DMHAs within RCTs.

Conclusions: While DMHAs have the potential to be scalable and sustainable solutions to improve access and availability of evidence-based mental healthcare, moderator analyses highlight the considerations for implementation of DMHAs in practice. Further research is needed to understand factors that influence therapeutic effects of DMHAs and investigate strategies to optimize its implementation and overcome the extant research-to-practice gap.

Keywords: Anxiety; Depression; Digital mental health applications; mHealth; meta-Analysis.

Publication types

Meta-Analysis
Review
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Anxiety / etiology
Anxiety / therapy
Anxiety Disorders / therapy
Depression* / etiology
Depression* / therapy
Humans
Mental Health*
Randomized Controlled Trials as Topic

Grants and funding

UL1 TR003098/TR/NCATS NIH HHS/United States