Mobile heath applications for self-management in chronic lung disease: a systematic review.

IF 2 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Network Modeling and Analysis in Health Informatics and Bioinformatics Pub Date : 2023-01-01 Epub Date: 2023-06-06 DOI:10.1007/s13721-023-00419-0

Shirley Quach, Wade Michaelchuk, Adam Benoit, Ana Oliveira, Tara L Packham, Roger Goldstein, Dina Brooks

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引用次数: 0

Abstract

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.

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移动健康在慢性肺病自我管理中的应用：一项系统综述。

将移动健康（mHealth）应用程序集成到慢性肺病管理中越来越受欢迎。MHealth应用程序可能支持采用自我管理行为，以帮助人们控制症状和提高生活质量。然而，mHealth应用程序的设计、功能和内容报告不一致，很难确定哪些是有效的组件。因此，本综述旨在总结已发表的用于慢性肺部疾病的mHealth应用程序的特点和特点。在五个数据库（CINAHL、Medline、Embase、Scopus和Cochrane）中执行结构化搜索策略。包括在患有慢性肺病的成年人中调查交互式mHealth应用程序的随机对照试验。筛选和全文综述由三名评审员使用Research Screener和Covidence完成。数据提取遵循mHealth指数和导航数据库（MIND）评估框架(https://mindapps.org/)，一个旨在帮助临床医生确定最佳mHealth应用程序以满足患者需求的工具。放映了90000多篇文章，其中包括16篇论文。确定了15种不同的应用程序，其中8种用于慢性阻塞性肺病（53%），7种用于哮喘（46%）自我管理。不同的资源为应用程序设计方法提供了依据，同时研究中也存在不同的质量和功能。常见的报告特征包括症状跟踪、药物提醒、教育和临床支持。没有足够的信息来回答MIND关于安全和隐私的问题，只有五款应用程序有额外的出版物来支持其临床基础。目前的研究报告了不同的自我管理应用程序的设计和功能。这些应用程序设计的变化在确定其对慢性肺病自我管理的有效性和适用性方面带来了挑战。注册：PROSPERO（CRD42021260205）。补充信息：在线版本包含补充材料，可访问10.1007/s13721-023-00419-0。

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来源期刊

Network Modeling and Analysis in Health Informatics and Bioinformatics MATHEMATICAL & COMPUTATIONAL BIOLOGY-

CiteScore

5.40

自引率

4.30%

发文量

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 .