โก Quick Summary
This bibliometric analysis explores the rapid growth and innovation in CBT-based mobile interventions for depression, identifying key trends and future directions in research. The study highlights a significant increase in publications, with a focus on integrating AI and wearable technologies to enhance treatment accessibility and effectiveness.
๐ Key Details
- ๐ Dataset: 350 articles from Web of Science, 72 clinical trials from PubMed, and 20 articles from PsycINFO.
- ๐งฉ Key Themes: Smartphone interventions, blended treatments, CBT for insomnia, adolescent depression.
- โ๏ธ Analysis Tools: CiteSpace 6.4 R1, Microsoft Excel 2019, Python.
- ๐ Citation Bursts: Indicated shifts towards prevention, technology integration, and standardized outcome measures.
๐ Key Takeaways
- ๐ Growth: Research on CBT-based mobile applications is rapidly increasing, with a notable rise in publications since 2013.
- ๐ Global Contributions: The United States leads in research output, with significant contributions from major academic centers.
- ๐ก Interdisciplinary Approaches: There’s a growing interest in integrating interpersonal therapy and mindfulness into mobile interventions.
- ๐ค Future Innovations: Anticipated integration of AI and large language models into mobile CBT platforms.
- ๐ฑ Emerging Technologies: Convergence of app-based interventions with sensor-based digital phenotyping and wearable devices.
- ๐ Cultural Adaptation: Research emphasizes culturally adapted applications for diverse populations, including Chinese cultural groups.
- ๐ Focus on Comorbidities: Digital interventions targeting comorbid social anxiety are gaining attention.
- ๐ Future Directions: Key research streams will likely focus on personalized, adaptive, and preventive digital interventions.
๐ Background
Depression remains a significant global health challenge, exacerbated by a shortage of therapists and economic barriers to traditional cognitive behavioral therapy (CBT). The emergence of CBT-based mobile applications presents a promising solution, offering scalable and accessible alternatives for individuals seeking mental health support. However, a comprehensive overview of the research landscape surrounding these interventions has been lacking.
๐๏ธ Study
This study systematically retrieved relevant articles from the Web of Science Core Collection, PubMed, and PsycINFO, covering the period from inception to June 25, 2025. Utilizing bibliometric methods, the researchers aimed to map global research trends, clinical progress, and emerging frontiers in CBT-based mobile applications for depression.
๐ Results
The analysis revealed a total of 350 articles published between 2013 and 2025, indicating a marked growth trajectory in research output. The PubMed analysis highlighted 72 clinical trial articles, with randomized controlled trials being the predominant design. Notable themes included smartphone interventions and blended treatments, while citation bursts indicated a shift towards prevention and technology integration.
๐ Impact and Implications
The findings of this study underscore the potential for CBT-based mobile applications to transform mental health care by making interventions more personalized and accessible. The integration of innovative technologies, such as AI and wearable devices, could enhance real-time monitoring and user engagement, ultimately narrowing treatment gaps across diverse populations. This research paves the way for future developments in digital mental health interventions.
๐ฎ Conclusion
The rapid advancement of research on CBT-based mobile applications for depression highlights the importance of interdisciplinary collaboration and technological innovation. As we look to the future, the integration of AI and immersive technologies into these platforms promises to enhance their effectiveness and accessibility. Continued exploration in this field is essential for developing scalable mental health solutions that meet the needs of diverse populations.
๐ฌ Your comments
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Bibliometric analysis of trends, innovations, and the future of CBT-based mobile interventions for depression.
Abstract
BACKGROUND: Depression is a major global health challenge, and traditional cognitive behavioral therapy (CBT) is constrained by therapist shortages and economic barriers. CBT-based mobile applications offer a scalable and accessible alternative, yet a comprehensive overview of their global research landscape remains limited.
OBJECTIVE: To map global research trends, clinical progress, and emerging frontiers in CBT-based mobile applications for depression using bibliometric methods.
METHODS: Relevant studies were systematically retrieved from the Web of Science Core Collection, PubMed, and PsycINFO from inception to June 25, 2025. CiteSpace 6.4 R1, Microsoft Excel 2019, and Python were used for visualization and data analysis, including temporal publication trends, co-authorship, co-citation, keyword analyses, and citation burst detection.
RESULTS: The WoSCC analysis identified 350 articles published between 2013 and 2025, showing a marked growth trajectory with leading contributions from the United States and major academic centers. Dominant themes included smartphone interventions, blended treatments, CBT for insomnia, and adolescent depression, while citation bursts indicated recent shifts toward prevention, technology integration, and standardized outcome measures. The PubMed analysis included 72 clinical trial articles, highlighting randomized controlled trials as the predominant design and revealing growing interest in integrating interpersonal therapy and mindfulness within broader, interdisciplinary treatment frameworks. The PsycINFO analysis comprised 20 articles and provided a complementary behavioral science perspective, emphasizing mobile phone-delivered CBT for major depression, digital interventions targeting comorbid social anxiety, culturally adapted applications for Chinese cultural groups, and emerging work linking mobile health and virtual reality.
CONCLUSIONS: Research on CBT-based mobile applications for depression is rapidly advancing toward more personalized, adaptive, and preventive digital interventions grounded in robust clinical and behavioral evidence. Strengthening global, interdisciplinary collaboration and leveraging innovative technologies will be critical for translating these tools into effective, scalable services. Over the next 5-10 years, key research streams are likely to include the integration of Artificial Intelligence (AI) and large language models (LLMs) into mobile CBT platforms and the convergence of app-based interventions with sensor-based digital phenotyping, wearable devices, and immersive technologies to enhance real-time monitoring, user engagement, and long-term outcomes, with the potential to narrow treatment gaps across diverse populations.
SYSTEMATIC REVIEW REGISTRATION: https://osf.io/, Identifier: https://doi.org/10.17605/OSF.IO/YCSR8.
Author: [‘Gao Z’, ‘Zhao T’, ‘Li Y’, ‘Huang W’, ‘Tang J’, ‘Yu X’, ‘Li Y’, ‘Peng T’]
Journal: Front Med (Lausanne)
Citation: Gao Z, et al. Bibliometric analysis of trends, innovations, and the future of CBT-based mobile interventions for depression. Bibliometric analysis of trends, innovations, and the future of CBT-based mobile interventions for depression. 2025; 12:1710291. doi: 10.3389/fmed.2025.1710291