디지털 치료기기의 글로벌 연구 동향에 대한 계량서지학적 분석|RISS 상세보기

다국어 초록 (Multilingual 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 analy- sis 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”, “health- care”, “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 re- main 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.

번역하기

참고문헌 (Reference)

1 Lehne M, "Why digital medicine depends on interoperability" 2 (2): 79-, 2019

2 Garrido S, "What works and what doesn’t work? A systematic review of digital mental health interventions for depression and anxiety in young people" 10 : 759-, 2019

3 Goldsack JC, "Verification, analytical validation, and clinical validation(V3) : the foundation of determining fit-for-purpose for Biometric Monitoring Technologies(BioMeTs)" 3 (3): 55-, 2020

4 Yardley L, "Understanding and promoting effective engagement with digital behavior change interventions" 51 (51): 833-842, 2016

5 Alkhaldi G, "The effectiveness of prompts to promote engagement with digital interventions : a systematic review" 18 (18): e6-, 2016

6 Dorsey ER, "Telemedicine 2020 and the next decade" 395 (395): 859-, 2020

7 Kaner EF, "Personalised digital interventions for reducing hazardous and harmful alcohol consumption in community-dwelling populations" 9 (9): CD011479-, 2017

8 Kim M, "Multidimensional Cognitive Behavioral Therapy for Obesity Applied by Psychologists Using a Digital Platform : Open-Label Randomized Controlled Trial" 8 (8): e14817-, 2020

9 Hong JS, "Introduction of digital therapeutics" 209 : 106319-, 2021

10 National Institute of Food and Drug Safety Evaluation, "Guidelines for approval and review of digital therapeutics"