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      Efficacy of adaptive e-learning for health professionals and students: a systematic review and meta-analysis

      systematic-review

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          Abstract

          Objective

          Although adaptive e-learning environments (AEEs) can provide personalised instruction to health professional and students, their efficacy remains unclear. Therefore, this review aimed to identify, appraise and synthesise the evidence regarding the efficacy of AEEs in improving knowledge, skills and clinical behaviour in health professionals and students.

          Design

          Systematic review and meta-analysis.

          Data sources

          CINAHL, EMBASE, ERIC, PsycINFO, PubMed and Web of Science from the first year of records to February 2019.

          Eligibility criteria

          Controlled studies that evaluated the effect of an AEE on knowledge, skills or clinical behaviour in health professionals or students.

          Screening, data extraction and synthesis

          Two authors screened studies, extracted data, assessed risk of bias and coded quality of evidence independently. AEEs were reviewed with regard to their topic, theoretical framework and adaptivity process. Studies were included in the meta-analysis if they had a non-adaptive e-learning environment control group and had no missing data. Effect sizes (ES) were pooled using a random effects model.

          Results

          From a pool of 10 569 articles, we included 21 eligible studies enrolling 3684 health professionals and students. Clinical topics were mostly related to diagnostic testing, theoretical frameworks were varied and the adaptivity process was characterised by five subdomains: method, goals, timing, factors and types. The pooled ES was 0.70 for knowledge (95% CI −0.08 to 1.49; p.08) and 1.19 for skills (95% CI 0.59 to 1.79; p<0.00001). Risk of bias was generally high. Heterogeneity was large in all analyses.

          Conclusions

          AEEs appear particularly effective in improving skills in health professionals and students. The adaptivity process within AEEs may be more beneficial for learning skills rather than factual knowledge, which generates less cognitive load. Future research should report more clearly on the design and adaptivity process of AEEs, and target higher-level outcomes, such as clinical behaviour.

          PROSPERO registration number

          CRD42017065585

          Related collections

          Most cited references35

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          Technology-enhanced simulation for health professions education: a systematic review and meta-analysis.

          Although technology-enhanced simulation has widespread appeal, its effectiveness remains uncertain. A comprehensive synthesis of evidence may inform the use of simulation in health professions education. To summarize the outcomes of technology-enhanced simulation training for health professions learners in comparison with no intervention. Systematic search of MEDLINE, EMBASE, CINAHL, ERIC, PsychINFO, Scopus, key journals, and previous review bibliographies through May 2011. Original research in any language evaluating simulation compared with no intervention for training practicing and student physicians, nurses, dentists, and other health care professionals. Reviewers working in duplicate evaluated quality and abstracted information on learners, instructional design (curricular integration, distributing training over multiple days, feedback, mastery learning, and repetitive practice), and outcomes. We coded skills (performance in a test setting) separately for time, process, and product measures, and similarly classified patient care behaviors. From a pool of 10,903 articles, we identified 609 eligible studies enrolling 35,226 trainees. Of these, 137 were randomized studies, 67 were nonrandomized studies with 2 or more groups, and 405 used a single-group pretest-posttest design. We pooled effect sizes using random effects. Heterogeneity was large (I(2)>50%) in all main analyses. In comparison with no intervention, pooled effect sizes were 1.20 (95% CI, 1.04-1.35) for knowledge outcomes (n = 118 studies), 1.14 (95% CI, 1.03-1.25) for time skills (n = 210), 1.09 (95% CI, 1.03-1.16) for process skills (n = 426), 1.18 (95% CI, 0.98-1.37) for product skills (n = 54), 0.79 (95% CI, 0.47-1.10) for time behaviors (n = 20), 0.81 (95% CI, 0.66-0.96) for other behaviors (n = 50), and 0.50 (95% CI, 0.34-0.66) for direct effects on patients (n = 32). Subgroup analyses revealed no consistent statistically significant interactions between simulation training and instructional design features or study quality. In comparison with no intervention, technology-enhanced simulation training in health professions education is consistently associated with large effects for outcomes of knowledge, skills, and behaviors and moderate effects for patient-related outcomes.
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            Cognitive Load Theory and Instructional Design: Recent Developments

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              Online eLearning for undergraduates in health professions: A systematic review of the impact on knowledge, skills, attitudes and satisfaction

              Background Health systems worldwide are facing shortages in health professional workforce. Several studies have demonstrated the direct correlation between the availability of health workers, coverage of health services, and population health outcomes. To address this shortage, online eLearning is increasingly being adopted in health professionals’ education. To inform policy–making, in online eLearning, we need to determine its effectiveness. Methods We performed a systematic review of the effectiveness of online eLearning through a comprehensive search of the major databases for randomised controlled trials that compared online eLearning to traditional learning or alternative learning methods. The search period was from January 2000 to August 2013. We included articles which primarily focused on students' knowledge, skills, satisfaction and attitudes toward eLearning and cost-effectiveness and adverse effects as secondary outcomes. Two reviewers independently extracted data from the included studies. Due to significant heterogeneity among the included studies, we presented our results as a narrative synthesis. Findings Fifty–nine studies, including 6750 students enrolled in medicine, dentistry, nursing, physical therapy and pharmacy studies, met the inclusion criteria. Twelve of the 50 studies testing knowledge gains found significantly higher gains in the online eLearning intervention groups compared to traditional learning, whereas 27 did not detect significant differences or found mixed results. Eleven studies did not test for differences. Six studies detected significantly higher skill gains in the online eLearning intervention groups, whilst 3 other studies testing skill gains did not detect differences between groups and 1 study showed mixed results. Twelve studies tested students' attitudes, of which 8 studies showed no differences in attitudes or preferences for online eLearning. Students' satisfaction was measured in 29 studies, 4 studies showed higher satisfaction for online eLearning and 20 studies showed no difference in satisfaction between online eLearning and traditional learning. Risk of bias was high for several of the included studies. Conclusion The current evidence base suggests that online eLearning is equivalent, possibly superior to traditional learning. These findings present a potential incentive for policy makers to cautiously encourage its adoption, while respecting the heterogeneity among the studies.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2019
                28 August 2019
                : 9
                : 8
                : e025252
                Affiliations
                [1 ] departmentFaculty of Nursing , Université de Montréal , Montréal, Québec, Canada
                [2 ] departmentResearch Center , Montreal Heart Institute , Montréal, Québec, Canada
                [3 ] departmentBouve College of Health Sciences , Northeastern University , Boston, Massachusetts, USA
                [4 ] departmentSchool of Librarianship and Information Science , Université de Montréal , Montréal, Québec, Canada
                [5 ] departmentResearch Center , University of Montreal Hospital Centre , Montréal, Québec, Canada
                [6 ] departmentFaculty of Nursing , Université Laval , Québec City, Québec, Canada
                [7 ] departmentResearch Center , CHU de Québec-Université Laval , Québec City, Québec, Canada
                Author notes
                [Correspondence to ] Guillaume Fontaine; guillaume.fontaine@ 123456umontreal.ca
                Author information
                http://orcid.org/0000-0002-7806-814X
                http://orcid.org/0000-0001-5840-9122
                http://orcid.org/0000-0003-3190-0901
                http://orcid.org/0000-0002-3156-4955
                http://orcid.org/0000-0002-7949-4466
                http://orcid.org/0000-0002-4574-7672
                http://orcid.org/0000-0002-0617-2861
                http://orcid.org/0000-0002-0782-5457
                http://orcid.org/0000-0002-0602-0390
                Article
                bmjopen-2018-025252
                10.1136/bmjopen-2018-025252
                6719835
                31467045
                37646178-1ff8-4ae8-93e5-f2894d2ee747
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 06 July 2018
                : 10 June 2019
                : 30 July 2019
                Categories
                Medical Education and Training
                Research
                1506
                1709
                Custom metadata
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                Medicine
                computer-assisted instruction,medical education,nursing education,e-learning,meta-analysis

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