The efficacy of mobile applications for reducing depression in adolescents and young adults: A meta-analysis of randomized control trials
BackgroundMobile applications for mental health have the potential to aid people with mental health disorders, especially depression, by providing them with tools and coping mechanisms. Adolescents and young adults, being at risk of depressive symptoms and leading mobile users, are among the main targets of using mobile applications to alleviate symptoms.ObjectiveThis study aimed to evaluate the impact of mobile application-based psychological interventions in reducing depression symptoms in adolescents and young adults compared to those not exposed to the intervention.MethodsWe conducted a meta-analysis focusing on mobile applications for reducing depressive symptoms. We searched two databases: MEDLINE and EMBASE and included randomized controlled trials conducted in English among participants aged 18-35 years old who were assessed for depressive symptoms using a validated screening measure and used mobile applications-based psychological interventions. Two of six independent reviewers conducted study selection, data extraction, and bias assessment. A pooled mean standardized difference (Cohen's <i>d</i>) and 95% CI were calculated using random-effects meta-analysis. Risk of bias was assessed using <i>I</i>2 statistics and forest plot. Egger's test was used for assessing publication bias.ResultsAfter screening 740 references, we identified 12 trials with 1869 participants, with a mean age of participants ranging from 14.70 to 25.1 years. The interventions ranged from cognitive behavioral therapy (CBT)-based mobile apps to interactive story-telling apps and apps delivering a mix of CBT, interpersonal psychotherapy for adolescents, and dialectical behavior therapy elements. Control groups included information-only, waitlist, no intervention, and treatment as usual. Seven studies used Patient Health Questionnaire-9 (PHQ-9) to assess the severity of depressive symptoms, while the other five used different scales. There was no evidence of publication bias (<i>p</i> = 0.325). The mobile applications reduced depression score by 0.08 units of standardized difference more than the control, with a 95% CI of -0.19 to 0.03 (<i>p</i> = 0.294, <i>I</i><sup>2 </sup>= 15.4%) using standardized mean difference (SMD) as the effect estimate. In a sensitivity analysis including only studies that used PHQ-9, we found a similar trend, SMD -0.72 (95%CI -1.48 to 0.03). However, both findings were not significant.ConclusionsCurrent evidence is insufficient to support mobile applications to relieve depression symptoms in adolescents and young adults. Further trials with larger sample size are needed to confirm our findings of a positive trend. With emerging technologies and the high exposure of apps in this population, mobile applications for depression hold promise for the future of treatment and awareness of mental health disorders in this population.
Authors
- Takuto Yoshida (ORCID: https://orcid.org/0000-0003-3311-5579)
- Watsamon Jantarabenjakul (ORCID: https://orcid.org/0000-0003-4251-3499)
- Jolene Si Min Wong (ORCID: https://orcid.org/0000-0002-9750-5755)
- Stefania Papatheodorou (ORCID: https://orcid.org/0000-0002-9451-9094)
- C. Lee (ORCID: https://orcid.org/0000-0002-1121-8991)
- Sheng‐Yi Lin (ORCID: https://orcid.org/0000-0002-9008-3000)
- Maria Bazan (ORCID: https://orcid.org/0000-0002-9818-7699)
Institutions
- Rutgers, The State University of New Jersey (US)
- Beth Israel Deaconess Medical Center (US)
- University Health Network (CA)
- Harvard University (US)
- National Yang Ming Chiao Tung University (TW)
- Chulalongkorn University (TH)
- Chang Gung University (TW)
- Singapore General Hospital (SG)
- Universidad Científica del Sur (PE)
- Linkou Chang Gung Memorial Hospital (TW)
- Ministry of Health and Welfare (TW)
- National Cancer Centre Singapore (SG)
- Artificial Intelligence in Medicine (Canada) (CA)
Publication Details
- Journal
- Journal of Telemedicine and Telecare
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1177/1357633x241273032
- Citations
- 3
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 1.23