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Meta-Analysis
. 2019 Mar 12;21(3):e12912.
doi: 10.2196/12912.

Health Professions' Digital Education: Review of Learning Theories in Randomized Controlled Trials by the Digital Health Education Collaboration

Shweta Bajpai  1   2 , Monika Semwal  1   2 , Ram Bajpai  1 , Josip Car  1   3 , Andy Hau Yan Ho #  1   4   5
Affiliations
Meta-Analysis

Health Professions' Digital Education: Review of Learning Theories in Randomized Controlled Trials by the Digital Health Education Collaboration

Shweta Bajpai et al. J Med Internet Res. .

Abstract

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.

Keywords: digital education; digital education interventions; digital health education; health professions; learning theory.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Frequency distribution of reported primary outcomes in digital health professions’ education intervention studies.
Figure 2
Figure 2
Theory-Technology Alignment Framework for health professions’ digital education.
See this image and copyright information in PMC

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