Author: Maria J Serrano-Ripoll#1,2,3, Rocío Zamanillo-Campos#1,2, Maria A Fiol-DeRoque1,2, Adoración Castro1,4, Ignacio Ricci-Cabello1,2,5
Affiliation: <sup>1</sup> Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain.
<sup>2</sup> Balearic Islands Health Services, Primary Care Research Unit of Mallorca, Palma de Mallorca, Spain.
<sup>3</sup> Primary Care Prevention and Health Promotion Network, RedIAPP, Barcelona, Spain.
<sup>4</sup> Research Institute of Health Sciences (IUNICS), University of the Balearic Islands, Palma de Mallorca, Spain.
<sup>5</sup> Centro de Investigación Biomedica en Red (CIBERESP), Madrid, Spain.
Conference/Journal: JMIR Mhealth Uhealth
Date published: 2022 Jan 27
Other:
Volume ID: 10 , Issue ID: 1 , Pages: e29621 , Special Notes: doi: 10.2196/29621. , Word Count: 445
Background:
Depression is a serious, disabling mental disorder that severely affects quality of life. Patients with depression often do not receive adequate treatment. App-based psychotherapy is considered to have great potential to treat depression owing to its reach and easy accessibility.
Objective:
We aim to analyze the impact of app-based psychological interventions for reducing depressive symptoms in people with depression.
Methods:
We conducted a systematic literature review and meta-analysis. We searched Medline, Embase, PsycINFO, Web of Science, and Cochrane Central Register of Controlled Trials from inception to December 23, 2020. We selected randomized controlled trials to examine the impact of app-based psychological interventions for reducing depressive symptoms in people with depression. Study selection, data extraction, and critical appraisal (using the Cochrane Risk of Bias tool for randomized studies and the ROBINS-I tool for nonrandomized studies) were conducted independently by 2 reviewers. Where possible, we pooled data using random effects meta-analyses to obtain estimates of the effect size of the intervention. We conducted post hoc meta-regression analyses to explore the factors associated with intervention success.
Results:
After screening 3468 unique references retrieved from bibliographic searches and assessing the eligibility of 79 full texts, we identified 12 trials (2859 participants) evaluating 14 different interventions. Of 14 trials, 7 (58%) were conducted in the United States; 3 (25%) trials, in Asia (Japan, South Korea, and China); 1 (8%) trial, in Australia; and 1 (8%) trial, in Germany. Of the 12 trials, 5 (42%) trials presented a low risk of bias. The mean duration of the interventions was 6.6 (SD 2.8) weeks. Two-thirds of the interventions were based on cognitive behavioral therapy alone or included it in combination with cognitive control therapy, positive psychology, brief behavioral activation, or mindfulness- and acceptance-based therapy. With no evidence of publication bias, a pooled analysis of 83% (10/12) of the trials and 86% (12/14) of the interventions showed that app-based interventions, compared with a control group receiving usual care or minimal intervention, produced a moderate reduction in depressive symptoms (standardized mean difference [SMD] -0.51, 95% CI -0.69 to -0.33; 2018/2859, 70.58% of the participants; I2=70%). Our meta-regression analyses indicated that there was a greater reduction in symptoms of depression (P=.04) in trials that included participants with moderate to severe depression (SMD -0.67, 95% CI -0.79 to -0.55), compared with trials with participants exhibiting mild to moderate depression (SMD -0.15, 95% CI -0.43 to -0.12).
Conclusions:
App-based interventions targeted at people with depression produce moderate reductions in the symptoms of depression. More methodologically robust trials are needed to confirm our findings, determine which intervention features are associated with greater improvements, and identify those populations most likely to benefit from this type of intervention.
Trial registration:
PROSPERO CRD42019145689; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=145689.
Keywords: apps; depression; eHealth; mHealth; mental health interventions; meta-analysis; mobile phone; smartphone technology; systematic review.
PMID: 35084346 DOI: 10.2196/29621