Health Professions’ Digital Education: Review of Learning Theories in Randomized Controlled Trials by the Digital Health Education Collaboration
| Autor: | Andy Hau Yan Ho, Josip Car, Shweta Bajpai, Monika Semwal, Ram Bajpai |
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| Přispěvatelé: | School of Social Sciences, Lee Kong Chian School of Medicine (LKCMedicine), Ageing Research Institute for Society and Education, Centre for Population Health Sciences |
| Rok vydání: | 2019 |
| Předmět: |
020205 medical informatics
BEHAVIOR-CHANGE Health Professions Health Informatics Review 02 engineering and technology PsycINFO Cochrane Library Education Distance MEDICAL-EDUCATION digital education 0202 electrical engineering electronic engineering information engineering Learning theory Humans Medicine [Science] TECHNOLOGY Health Education Curriculum Social learning theory 11 Medical and Health Sciences Randomized Controlled Trials as Topic Medical education Science & Technology digital health education R735 SCIENCE L1 R1 Digital health 17 Psychology and Cognitive Sciences Health Care Sciences & Services learning theory digital education interventions 08 Information and Computing Sciences health professions Thematic analysis Psychology Life Sciences & Biomedicine Medical Informatics Learning Theory Medical literature |
| Zdroj: | Journal of Medical Internet Research |
| ISSN: | 1438-8871 |
| Popis: | Background: Learning theory is an essential component for designing an effective educational curriculum. Reviews of existing literature consistently lack sufficient evidence to support the effectiveness of digital interventions for health professions’ education, which may reflect disconnections among learning theories, curriculum design, use of technology, and outcome evaluation. Objective: The aim of this review was to identify, map, and evaluate the use of learning theories in designing and implementing intervention trials of health professions’ digital education, as well as highlight areas for future research on technology-enhanced education via the establishment of a development framework for practice and research. Methods: We performed a systematic search of Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, Cochrane Central Register of Controlled Trials (Cochrane Library), PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Education Resources Information Center, and Web of Science for randomized controlled trials (RCTs) published between 2007 and 2016. Results: A total of 874 RCTs on digital health education were identified and categorized into online-offline, mobile digital education, and simulation-based modalities for pre and postregistration health professions’ education. Of these, 242 studies were randomly selected for methodological review and thematic analysis. Data were extracted by one author using a standardized form, with a (48/242, 20%) random sample extracted by a second author, in duplicate. One-third (81/242, 33.4%) of the studies reported single or multiple learning theories in design, assessment, conceptualization, or interpretation of outcomes of the digital education interventions. Commonly reported learning theories were problem-based learning (16/81, 20%), social learning theory (11/81, 14%), and cognitive theory of multimedia learning (10/81, 12%). Most of these studies assessed knowledge (118/242, 48.8%), skills (62/242, 25.6%), and performance (59/242, 24.3%) as primary outcomes with nonvalidated assessment tools (151/242, 62.4%). Studies with reported learning theories (χ21=8.2; P=.002) and validated instruments (χ21=12.6; P=.006) have shown effective acquisition of learning outcomes. Conclusions: We proposed a Theory-Technology Alignment Framework to safeguard the robustness and integrity of the design and implementation of future digital education programs for the training of health professionals. Published version |
| Databáze: | OpenAIRE |
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