Digital Education in Health Professions: The Need for Overarching Evidence Synthesis (Preprint)

系统回顾 数字健康 过程(计算) 预印本 分类 包裹体(矿物) 计算机科学 医学教育 数字图书馆 数据科学 知识管理 心理学 工程伦理学 梅德林 医疗保健 医学 政治学 万维网 工程类 人工智能 艺术 操作系统 诗歌 法学 文学类 社会心理学
作者
Josip Car,Jan Carlstedt‐Duke,Lorainne Tudor Car,Paul Posadzki,Penny Whiting,Nabil Zary,Rifat Atun,Azeem Majeed,James Campbell
标识
DOI:10.2196/preprints.12913
摘要

UNSTRUCTURED Synthesizing evidence from randomized controlled trials of digital health education poses some challenges. These include a lack of clear categorization of digital health education in the literature; constantly evolving concepts, pedagogies, or theories; and a multitude of methods, features, technologies, or delivery settings. The Digital Health Education Collaboration was established to evaluate the evidence on digital education in health professions; inform policymakers, educators, and students; and ultimately, change the way in which these professionals learn and are taught. The aim of this paper is to present the overarching methodology that we use to synthesize evidence across our digital health education reviews and to discuss challenges related to the process. For our research, we followed Cochrane recommendations for the conduct of systematic reviews; all reviews are reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidance. This included assembling experts in various digital health education fields; identifying gaps in the evidence base; formulating focused research questions, aims, and outcome measures; choosing appropriate search terms and databases; defining inclusion and exclusion criteria; running the searches jointly with librarians and information specialists; managing abstracts; retrieving full-text versions of papers; extracting and storing large datasets, critically appraising the quality of studies; analyzing data; discussing findings; drawing meaningful conclusions; and drafting research papers. The approach used for synthesizing evidence from digital health education trials is commonly regarded as the most rigorous benchmark for conducting systematic reviews. Although we acknowledge the presence of certain biases ingrained in the process, we have clearly highlighted and minimized those biases by strictly adhering to scientific rigor, methodological integrity, and standard operating procedures. This paper will be a valuable asset for researchers and methodologists undertaking systematic reviews in digital health education.

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