Shirley Quach, Wade Michaelchuk, Adam Benoit, Ana Oliveira, Tara L Packham, Roger Goldstein, Dina Brooks
{"title":"移动健康在慢性肺病自我管理中的应用:一项系统综述。","authors":"Shirley Quach, Wade Michaelchuk, Adam Benoit, Ana Oliveira, Tara L Packham, Roger Goldstein, Dina Brooks","doi":"10.1007/s13721-023-00419-0","DOIUrl":null,"url":null,"abstract":"<p><p>Integration of mobile health (mHealth) applications (apps) into chronic lung disease management is becoming increasingly popular. MHealth apps may support adoption of self-management behaviors to assist people in symptoms control and quality of life enhancement. However, mHealth apps' designs, features, and content are inconsistently reported, making it difficult to determine which were the effective components. Therefore, this review aims to summarize the characteristics and features of published mHealth apps for chronic lung diseases. A structured search strategy across five databases (CINAHL, Medline, Embase, Scopus and Cochrane) was performed. Randomized controlled trials investigating interactive mHealth apps in adults with chronic lung disease were included. Screening and full-text reviews were completed by three reviewers using Research Screener and Covidence. Data extraction followed the mHealth Index and Navigation Database (MIND) Evaluation Framework (https://mindapps.org/), a tool designed to help clinicians determine the best mHealth apps to address patients' needs. Over 90,000 articles were screened, with 16 papers included. Fifteen distinct apps were identified, 8 for chronic obstructive pulmonary disease (53%) and 7 for asthma (46%) self-management. Different resources informed app design approaches, accompanied with varying qualities and features across studies. Common reported features included symptom tracking, medication reminders, education, and clinical support. There was insufficient information to answer MIND questions regarding security and privacy, and only five apps had additional publications to support their clinical foundation. Current studies reported designs and features of self-management apps differently. These app design variations create challenges in determining their effectiveness and suitability for chronic lung disease self-management. <i>Registration</i>: PROSPERO (CRD42021260205).</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s13721-023-00419-0.</p>","PeriodicalId":44876,"journal":{"name":"Network Modeling and Analysis in Health Informatics and Bioinformatics","volume":"12 1","pages":"25"},"PeriodicalIF":2.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10242585/pdf/","citationCount":"0","resultStr":"{\"title\":\"Mobile heath applications for self-management in chronic lung disease: a systematic review.\",\"authors\":\"Shirley Quach, Wade Michaelchuk, Adam Benoit, Ana Oliveira, Tara L Packham, Roger Goldstein, Dina Brooks\",\"doi\":\"10.1007/s13721-023-00419-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Integration of mobile health (mHealth) applications (apps) into chronic lung disease management is becoming increasingly popular. 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Mobile heath applications for self-management in chronic lung disease: a systematic review.
Integration of mobile health (mHealth) applications (apps) into chronic lung disease management is becoming increasingly popular. MHealth apps may support adoption of self-management behaviors to assist people in symptoms control and quality of life enhancement. However, mHealth apps' designs, features, and content are inconsistently reported, making it difficult to determine which were the effective components. Therefore, this review aims to summarize the characteristics and features of published mHealth apps for chronic lung diseases. A structured search strategy across five databases (CINAHL, Medline, Embase, Scopus and Cochrane) was performed. Randomized controlled trials investigating interactive mHealth apps in adults with chronic lung disease were included. Screening and full-text reviews were completed by three reviewers using Research Screener and Covidence. Data extraction followed the mHealth Index and Navigation Database (MIND) Evaluation Framework (https://mindapps.org/), a tool designed to help clinicians determine the best mHealth apps to address patients' needs. Over 90,000 articles were screened, with 16 papers included. Fifteen distinct apps were identified, 8 for chronic obstructive pulmonary disease (53%) and 7 for asthma (46%) self-management. Different resources informed app design approaches, accompanied with varying qualities and features across studies. Common reported features included symptom tracking, medication reminders, education, and clinical support. There was insufficient information to answer MIND questions regarding security and privacy, and only five apps had additional publications to support their clinical foundation. Current studies reported designs and features of self-management apps differently. These app design variations create challenges in determining their effectiveness and suitability for chronic lung disease self-management. Registration: PROSPERO (CRD42021260205).
Supplementary information: The online version contains supplementary material available at 10.1007/s13721-023-00419-0.
期刊介绍:
NetMAHIB publishes original research articles and reviews reporting how graph theory, statistics, linear algebra and machine learning techniques can be effectively used for modelling and analysis in health informatics and bioinformatics. It aims at creating a synergy between these disciplines by providing a forum for disseminating the latest developments and research findings; hence, results can be shared with readers across institutions, governments, researchers, students, and the industry. The journal emphasizes fundamental contributions on new methodologies, discoveries and techniques that have general applicability and which form the basis for network based modelling, knowledge discovery, knowledge sharing and decision support to the benefit of patients, healthcare professionals and society in traditional and advanced emerging settings, including eHealth and mHealth .