SynthesisJMIR mental health2024
Digital Mental Health Interventions for Alleviating Depression and Anxiety During Psychotherapy Waiting Lists: Systematic Review.
Synthesis in JMIR mental health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Evaluation of Two Web-Based Interventions (REMOTION and Res-Up!) for Clients From Psychotherapy Waitlists in Routine Outpatient Psychotherapy (Therapy Online Plus-TOP): Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Conversational AI should fill the white space in mental health care, not replace humans.NPJ digital medicine · 2026Review
- Patients' attitudes and expectations toward a digital inpatient-like psychotherapy concept: a qualitative interview study.BMC psychiatry · 2026Article
- Smartphone-based digital phenotyping for detection of high-risk depression and anxiety in Korean community settings.Internet interventions · 2026Article
- Addressing the Psychological Needs of Adolescents During the Wait Time for Mental Health Treatment: Service Design Study.JMIR formative research · 2026Article
- The present and future of blended care: current research and introduction to the B-FIT framework.NPJ digital medicine · 2026Review
- Myofascial pain in older adults: a geroscience-informed framework integrating precision geriatrics and digital therapeutics.Frontiers in aging neuroscience · 2026Review
- Digital health and consumer health informatics: past and future.Medical research archives · 2026Article
- Computational network models for forecasting and control of mental health trajectories in digital applications.NPJ digital medicine · 2025Article
- Predictors of Perceived Need for and Prescribing of Digital Health Applications for Mental Disorders Among Psychotherapists in Germany: Cross-Sectional Survey Study.Journal of medical Internet research · 2025Article
- Key questions to ask before implementing a Digital Mental Health Service (DMHS): A primer for policy makers.Internet interventions · 2025Review
- Digital Health Applications (DiGA) for Treating Depression and Generalized Anxiety Disorder: Protocol for a Systematic Health App Review and Systematic Review of Published Evidence.JMIR research protocols · 2025Article
- Article
- Enhancing Access to Mental Health Services for Antepartum and Postpartum Women Through Telemental Health Services at Wellbeing Centers in Selected Health Facilities in Bangladesh: Implementation Research.JMIR pediatrics and parenting · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDepression and anxiety have become increasingly prevalent across the globe. The rising need for treatment and the lack of clinicians has resulted in prolonged waiting times for patients to receive their first session. Responding to this gap, digital mental health interventions (DMHIs) have been found effective in treating depression and anxiety and are potentially promising pretreatments for patients who are awaiting face-to-face psychotherapy. Nevertheless, whether digital interventions effectively alleviate symptoms for patients on waiting lists for face-to-face psychotherapy remains unclear.
objectiveThis review aimed to synthesize the effectiveness of DMHIs for relieving depression and anxiety symptoms of patients on waiting lists for face-to-face therapy. This review also investigated the features, perceived credibility, and usability of DMHIs during waiting times.
methodsIn this systematic review, we searched PubMed, PsycINFO, Cochrane, and Web of Science for research studies investigating the effectiveness of DMHIs in reducing either depression or anxiety symptoms among individuals waiting for face-to-face psychotherapy. The search was conducted in June 2024, and we have included the studies that met the inclusion criteria and were published before June 6, 2024.
resultsOf the 9267 unique records identified, 8 studies met the eligibility criteria and were included in the systematic review. Five studies were randomized controlled trials (RCTs), and 3 studies were not. Among the RCTs, we found that digital interventions reduced depression and anxiety symptoms, but the majority of interventions were not more effective compared to the control groups where participants simply waited or received a self-help book. For the non-RCTs, the interventions also reduced symptoms, but without control groups, the interpretation of the findings is limited. Finally, participants in the included studies perceived the digital interventions to be credible and useful, but high dropout rates raised concerns about treatment adherence.
conclusionsDue to the lack of effective interventions among the reviewed studies, especially among the RCTs, our results suggest that waiting list DMHIs are not more effective compared to simply waiting or using a self-help book. However, more high-quality RCTs with larger sample sizes are warranted in order to draw a more robust conclusion. Additionally, as this review revealed concerns regarding the high dropout rate in digital interventions, future studies could perhaps adopt more personalized and human-centered functions in interventions to increase user engagement, with the potential to increase treatment adherence and effectiveness.
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