ArticleDigital health
Trends in digital mental health interventions: A 20-year bibliometric analysis.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- WeChat in China's mobile health: a bibliometric analysis of trends, hotspots, and academic contributions.JAMIA open · 2026Review
- Mapping research trends in immune cell metabolic reprogramming in breast cancer: a parallel dual-database bibliometric study.Discover oncology · 2026Article
- Association of VDR BsmI polymorphism and vitamin D status with osteoarthritis susceptibility.BMC medical genomics · 2026Article
- From algorithms to clinical execution: A cross-validated knowledge atlas of AI-enabled precision care (2015-2025).Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The rising prevalence of mental health disorders such as depression and anxiety challenges traditional treatments limited by resource shortages, poor accessibility, and low adherence. Digital health technologies-particularly digital mental health interventions-offer innovative, scalable, and personalized solutions. Mobile health applications, online cognitive behavioral therapy (CBT), and AI-driven tools are becoming essential in mental health care. Methods: This study employs bibliometric methods to examine research trends and thematic evolution in digital mental health self-management interventions, using data retrieved from the Web of Science Core Collection (WoSCC). CiteSpace, VOSviewer, and Bibliometrix were applied to quantify research output, collaboration networks, and influential topics. The analysis covered English-language publications from 2006 to 2025, with internal consistency checks and sensitivity analyses within the WoSCC dataset ensuring robustness. Results: A total of 2262 eligible publications were retrieved, showing a clear growth trajectory. The United States led with 932 publications, followed by the United Kingdom and Australia. Citations surged after 2016, peaking in 2023, reflecting increasing academic and clinical relevance. Research has shifted from feasibility studies to AI-enhanced and personalized interventions. Keywords such as "artificial intelligence," "digital CBT," and "personalized care" showed notable growth. International and interdisciplinary collaborations also expanded, underscoring the field's global integration. Conclusion: Digital mental health interventions are evolving from traditional models to intelligent, personalized solutions, providing scalable solutions to global mental health challenges. This study offers insights into future research directions, focusing on technology integration, ethical issues, and clinical validation to drive global application.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.