Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
권호 표지
DOI QR코드

DOI QR Code

A Bibliometric Analysis of Global Research Trends in Digital Therapeutics

디지털 치료기기의 글로벌 연구 동향에 대한 계량서지학적 분석

  • Dae Jin Kim (Korea Institute of Oriental Medicine) ;
  • Hyeon Su Kim (Korea Research Institute of Bioscience and Biotechnology) ;
  • Byung Gwan Kim (Ministry of Food and Drug Safety) ;
  • Ki Chang Nam (Dongguk University College of Medicine)
  • 김대진 (한국한의학연구원) ;
  • 김현수 (한국생명공학연구원) ;
  • 김병관 (식품의약품안전처) ;
  • 남기창 (동국대학교 의과대학)
  • Received : 2024.07.29
  • Accepted : 2024.08.12
  • Published : 2024.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

To analyse the overall research trends in digital therapeutics, this study conducted a quantitative bibliometric analysis of articles published in the last 10 years from 2014 to 2023. We extracted bibliographic information of studies related to digital therapeutics from the Web of Science (WOS) database and performed publication status, citation analysis and keyword analysis using R (version 4.3.1) and VOSviewer (version 1.6.18) software. A total of 1,114 articles were included in the study, and the annual publication growth rate for digital therapeutics was 66.1%, a very rapid increase. "health" is the most used keyword based on Keyword Plus, and "cognitive-behavioral therapy", "depression", "healthcare", "mental-health", "meta-analysis" and "randomized controlled-trial" are the research keywords that have driven the development and impact of digital therapeutic devices over the long term. A total of five clusters were observed in the co-occurrence network analysis, with new research keywords such as "artificial intelligence", "machine learning" and "regulation" being observed in recent years. In our analysis of research trends in digital therapeutics, keywords related to mental health, such as depression, anxiety, and disorder, were the top keywords by occurrences and total link strength. While many studies have shown the positive effects of digital therapeutics, low engagement and high dropout rates remain a concern, and much research is being done to evaluate and improve them. Future studies should expand the search terms to ensure the representativeness of the results.

Keywords

Acknowledgement

이 논문은 한국한의학연구원 「한의 정책 기반연구사업(KSN1831422)」의 연구비 지원을 받아 수행된 결과로 이에 감사드립니다.

References

  1. Ronquillo Y, Meyers A, Korvek SJ. Digital health. https:// www.ncbi.nlm.nih.gov. Accessed on 28 June 2024.
  2. O'Reilly-Jacob M, Mohr P, Ellen M. Digital health & low-value care. In Healthcare. 2021;9(2):100533
  3. Park S, Garcia-Palacios J, Cohen A. From Treatment to Prevention: The Evolution of Digital Healthcare. Nature. 2019. https://www.nature.com. Accessed on 28 June 2024.
  4. Chung JY. Digital Therapeutics and Clinical Pharmacology. Transl Clin Pharmacol. 2019;27(1):6-11.
  5. National Institute of Food and Drug Safety Evaluation. Guidelines for approval and review of digital therapeutics. 2020. https://www.mfds.go.kr. Accessed on 3 July 2024.
  6. Burrone, V, Graham, L, Bevan A. Digital therapeutics past trends and future prospects. Digit. Technol. 2020;32:1-64.
  7. Yardley L, Spring BJ, Riper H. Understanding and promoting effective engagement with digital behavior change interventions. Am J Prev Med. 2016;51(5):833-842.
  8. Briganti G, Le Moine O. Artificial intelligence in medicine: today and tomorrow. Front Med (Lausanne). 2020;7:27.
  9. Kaner EF, Beyer FR, Garnett C. Personalised digital interventions for reducing hazardous and harmful alcohol consumption in community-dwelling populations. Cochrane Database Syst Rev. 2017;9(9):CD011479.
  10. Goldsack JC, Coravos A, Bakker JP. Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs). NPJ Digit Med. 2020;3(1):55.
  11. Fogel AL, Kvedar JC. Artificial intelligence powers digital medicine. NPJ Digit Med. 2018;1(1):5.
  12. Topooco N, Riper H, Araya R. Attitudes towards digital treatment for depression: a European stakeholder survey. Internet interv. 2017;8:1-9.
  13. Garrido S, Millington C, Cheers D. What works and what doesn't work? A systematic review of digital mental health interventions for depression and anxiety in young people. Front Psychiatry. 2019;10:759.
  14. Lehne M, Sass J, Essenwanger A. Why digital medicine depends on interoperability. NPJ Digit Med. 2019;2(1):79.
  15. Alkhaldi G, Hamilton FL, Lau R. The effectiveness of prompts to promote engagement with digital interventions: a systematic review. J Med Internet Res. 2016;18(1):e6.
  16. Dorsey ER, Topol EJ. Telemedicine 2020 and the next decade. The Lancet, 2020;395(10227):859.
  17. Nwosu A, Boardman S, Husain M. Digital therapeutics for mental health: is attrition the Achilles heel?. Front Psychiatry. 2022;13:900615.
  18. Torous J, Lipschitz J, Ng M. Dropout rates in clinical trials of smartphone apps for depressive symptoms: a systematic review and meta-analysis. J Affect Disord. 2020;263:413-419.
  19. Boardman S. Creating wellness apps with high patient engagement to close the intention-action gap. Int PsychGeriatr. 2021;33:551-552.
  20. Hong JS, Wasden C, Han DH. Introduction of digital therapeutics. Comput Methods Programs Biomed. 2021;209:106319.
  21. Ponzo S, Morelli D, Kawadler J. Efficacy of the digital therapeutic mobile app BioBase to reduce stress and improve mental well-being among university students: randomized controlled trial. JMIR mHealth uHealth. 2020;8(4):e17767.
  22. Frias J, Virdi N, Raja P. Effectiveness of digital medicines to improve clinical outcomes in patients with uncontrolled hypertension and type 2 diabetes: prospective, open-label, cluster-randomized pilot clinical trial. J Med Internet Res. 2017;19(7):e246.
  23. Zhang X, Luo Z, Yang M. Efficacy and safety of digital therapeutics-based cardiac rehabilitation in heart failure patients: a systematic review. ESC Heart Fail. 2020;9(6):3751-3760.
  24. Kumbhare SV, Francis-Lyon PA, Kachru D. Digital therapeutics care utilizing genetic and gut microbiome signals for the management of functional gastrointestinal disorders: Results from a preliminary retrospective study. Front Microbiol. 2022;13:826916.
  25. Kim M, Kim Y, Go Y. Multidimensional Cognitive Behavioral Therapy for Obesity Applied by Psychologists Using a Digital Platform: Open-Label Randomized Controlled Trial. JMIR Mhealth Uhealth. 2020;8(4):e14817.