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Understanding the research on tracking, diagnosing, and intervening in sleep disorders using mHealth apps: Bibliometric analysis and systematic reviews.
Nuo, Mingfu; Fang, Hongjuan; Wang, Tong; Liang, Jun; He, Yunfan; Han, Hongbin; Lei, Jianbo.
Afiliação
  • Nuo M; Institute of Medical Technology, Health Science Center, Peking University, Beijing, China.
  • Fang H; Department of Endocrinology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Wang T; Department of Medical Informatics, School of Public Health, Jilin University, Changchun, China.
  • Liang J; IT Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • He Y; School of Public Health, Zhejiang University, Hangzhou, China.
  • Han H; Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, School of Medicine, Zhejiang University, Hangzhou, China.
  • Lei J; School of Public Health, Zhejiang University, Hangzhou, China.
Digit Health ; 9: 20552076231165967, 2023.
Article em En | MEDLINE | ID: mdl-37051563
ABSTRACT

Objectives:

In solving the global challenge of sleep disorders, Mobile Health app is one of the important means to monitor, diagnose, and intervene in sleep disorders. This study aims to (1) summarize the status and trends of research in this field; (2) assess the production and usage of sleep mHealth apps; (3) calculate the conversion rate of grants that the proportion of newly developed apps from being funded and developed to published on application stores.

Methods:

Using bibliometric and content analysis methods, based on "Research Paper-Product Output-Product Application" chain and considering the "Research Grants" of articles, we conducted a systematic review of eight databases, to identify relevant studies over the last decade.

Results:

Over the past decade, 1399 authors published 313 papers in 182 journals and conferences. The number of publications increased with an average annual growth of 41.6%. The current focus area is research using cognitive behavioral therapy to intervene in sleep. Sleep-staging tracking is a shortcoming of this field. A total 368 sleep mHealth apps (233 newly developed and 135 existing) were examined in 313 papers; 323 grants supported 178 articles (56.9%). Only 12 of the newly developed apps are used in the real world, resulting in a 9% grant conversion rate.

Conclusions:

In the last decade, the field of tracking, diagnosing, and intervening in sleep disorders using mHealth apps has shown a trend of rapid development. However, the conversion rate of products from being funded and developed for use by end-users is low.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article