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      What Are We Looking for in Computer-Based Learning Interventions in Medical Education? A Systematic Review

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          Abstract

          Background

          Computer-based learning (CBL) has been widely used in medical education, and reports regarding its usage and effectiveness have ranged broadly. Most work has been done on the effectiveness of CBL approaches versus traditional methods, and little has been done on the comparative effects of CBL versus CBL methodologies. These findings urged other authors to recommend such studies in hopes of improving knowledge about which CBL methods work best in which settings.

          Objective

          In this systematic review, we aimed to characterize recent studies of the development of software platforms and interventions in medical education, search for common points among studies, and assess whether recommendations for CBL research are being taken into consideration.

          Methods

          We conducted a systematic review of the literature published from 2003 through 2013. We included studies written in English, specifically in medical education, regarding either the development of instructional software or interventions using instructional software, during training or practice, that reported learner attitudes, satisfaction, knowledge, skills, or software usage. We conducted 2 latent class analyses to group articles according to platform features and intervention characteristics. In addition, we analyzed references and citations for abstracted articles.

          Results

          We analyzed 251 articles. The number of publications rose over time, and they encompassed most medical disciplines, learning settings, and training levels, totaling 25 different platforms specifically for medical education. We uncovered 4 latent classes for educational software, characteristically making use of multimedia (115/251, 45.8%), text (64/251, 25.5%), Web conferencing (54/251, 21.5%), and instructional design principles (18/251, 7.2%). We found 3 classes for intervention outcomes: knowledge and attitudes (175/212, 82.6%), knowledge, attitudes, and skills (11.8%), and online activity (12/212, 5.7%). About a quarter of the articles (58/227, 25.6%) did not hold references or citations in common with other articles. The number of common references and citations increased in articles reporting instructional design principles ( P=.03), articles measuring online activities ( P=.01), and articles citing a review by Cook and colleagues on CBL ( P=.04). There was an association between number of citations and studies comparing CBL versus CBL, independent of publication date ( P=.02).

          Conclusions

          Studies in this field vary highly, and a high number of software systems are being developed. It seems that past recommendations regarding CBL interventions are being taken into consideration. A move into a more student-centered model, a focus on implementing reusable software platforms for specific learning contexts, and the analysis of online activity to track and predict outcomes are relevant areas for future research in this field.

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          Most cited references130

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          The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration

          Systematic reviews and meta-analyses are essential to summarise evidence relating to efficacy and safety of healthcare interventions accurately and reliably. The clarity and transparency of these reports, however, are not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (quality of reporting of meta-analysis) statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realising these issues, an international group that included experienced authors and methodologists developed PRISMA (preferred reporting items for systematic reviews and meta-analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this explanation and elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA statement, this document, and the associated website (www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.
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            The NumPy array: a structure for efficient numerical computation

            In the Python world, NumPy arrays are the standard representation for numerical data. Here, we show how these arrays enable efficient implementation of numerical computations in a high-level language. Overall, three techniques are applied to improve performance: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts. We first present the NumPy array structure, then show how to use it for efficient computation, and finally how to share array data with other libraries.
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              Knowledge transfer for the management of dementia: a cluster-randomised trial of blended learning in general practice

              Background The implementation of new medical knowledge into general practice is a complex process. Blended learning may offer an effective and efficient educational intervention to reduce the knowledge-to-practice gap. The aim of this study was to compare knowledge acquisition about dementia management between a blended learning approach using online modules in addition to quality circles (QCs) and QCs alone. Methods In this cluster-randomised trial with QCs as clusters and general practitioners (GPs) as participants, 389 GPs from 26 QCs in the western part of Germany were invited to participate. Data on the GPs' knowledge were obtained at three points in time by means of a questionnaire survey. Primary outcome was the knowledge gain before and after the interventions. A subgroup analysis of the users of the online modules was performed. Results 166 GPs were available for analysis and filled out a knowledge test at least two times. A significant increase of knowledge was found in both groups that indicated positive learning effects of both approaches. However, there was no significant difference between the groups. A subgroup analysis of the GPs who self-reported that they had actually used the online modules showed that they had a significant increase in their knowledge scores. Conclusion A blended learning approach was not superior to a QCs approach for improving knowledge about dementia management. However, a subgroup of GPs who were motivated to actually use the online modules had a gain in knowledge. Trial registration Current Controlled Trials ISRCTN36550981.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                August 2016
                01 August 2016
                : 18
                : 8
                : e204
                Affiliations
                [1] 1Department of Medical Education and Simulation Faculty of Medicine University of Porto PortoPortugal
                [2] 2Department of Clinical Neurosciences and Mental Health, Medical Psychology Unit Faculty of Medicine University of Porto PortoPortugal
                [3] 3Department of Clinical Epidemiology, Predictive Medicine and Public Health Faculty of Medicine University of Porto PortoPortugal
                Author notes
                Corresponding Author: Tiago Taveira-Gomes tiago.taveira@ 123456me.com
                Author information
                http://orcid.org/0000-0002-0998-6000
                http://orcid.org/0000-0001-5054-4936
                http://orcid.org/0000-0003-2164-7690
                http://orcid.org/0000-0002-5787-4871
                http://orcid.org/0000-0001-6789-3796
                Article
                v18i8e204
                10.2196/jmir.5461
                4985611
                27480053
                63f9a017-b28c-4ebd-803e-19562267bdcb
                ©Tiago Taveira-Gomes, Patrícia Ferreira, Isabel Taveira-Gomes, Milton Severo, Maria Amélia Ferreira. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 01.08.2016.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 19 December 2015
                : 3 April 2016
                : 1 June 2016
                : 21 June 2016
                Categories
                Original Paper
                Original Paper

                Medicine
                medical education,internet-based learning,computer-based learning,e-learning,b-learning,systematic review

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