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1.
BMJ Open ; 9(8): e025252, 2019 08 28.
Artículo en Inglés | MEDLINE | ID: mdl-31467045

RESUMEN

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.


Asunto(s)
Instrucción por Computador , Educación Médica/métodos , Instrucción por Computador/métodos , Personal de Salud/educación , Humanos , Aprendizaje
2.
BMJ Open ; 8(3): e019871, 2018 03 16.
Artículo en Inglés | MEDLINE | ID: mdl-29549206

RESUMEN

INTRODUCTION: Serious games (SGs) are interactive and entertaining digital software with an educational purpose. They engage the learner by proposing challenges and through various design elements (DEs; eg, points, difficulty adaptation, story). Recent reviews suggest the effectiveness of SGs in healthcare professionals' and students' education is mixed. This could be explained by the variability in their DEs, which has been shown to be highly variable across studies. The aim of this systematic review is to identify, appraise and synthesise the best available evidence regarding the effectiveness of SGs and the impact of DEs on engagement and educational outcomes of healthcare professionals and students. METHODS AND ANALYSIS: A systematic search of the literature will be conducted using a combination of medical subject headings terms and keywords in Cumulative Index of Nursing and Allied Health, Embase, Education Resources Information Center, PsycInFO, PubMed and Web of Science. Studies assessing SGs on engagement and educational outcomes will be included. Two independent reviewers will conduct the screening as well as the data extraction process. The risk of bias of included studies will also be assessed by two reviewers using the Effective Practice and Organisation of Care criteria. Data regarding DEs in SGs will first be synthesised qualitatively. A meta-analysis will then be performed, if the data allow it. Finally, the quality of the evidence regarding the effectiveness of SGs on each outcome will be assessed using the Grading of Recommendations Assessment, Development and Evaluation approach. ETHICS AND DISSEMINATION: As this systematic review only uses already collected data, no Institutional Review Board approval is required. Its results will be submitted in a peer-reviewed journal by the end of 2018. PROSPERO REGISTRATION NUMBER: CRD42017077424.


Asunto(s)
Instrucción por Computador/métodos , Educación Médica/métodos , Personal de Salud/educación , Aprendizaje , Juegos de Video , Competencia Clínica , Escolaridad , Humanos , Revisiones Sistemáticas como Asunto
3.
JMIR Res Protoc ; 6(7): e128, 2017 Jul 05.
Artículo en Inglés | MEDLINE | ID: mdl-28679491

RESUMEN

BACKGROUND: Adaptive e-learning environments (AEEs) can provide tailored instruction by adapting content, navigation, presentation, multimedia, and tools to each user's navigation behavior, individual objectives, knowledge, and preferences. AEEs can have various levels of complexity, ranging from systems using a simple adaptive functionality to systems using artificial intelligence. While AEEs are promising, their effectiveness for the education of health professionals and health professions students remains unclear. OBJECTIVE: The purpose of this systematic review is to assess the effectiveness of AEEs in improving knowledge, competence, and behavior in health professionals and students. METHODS: We will follow the Cochrane Collaboration and the Effective Practice and Organisation of Care (EPOC) Group guidelines on systematic review methodology. A systematic search of the literature will be conducted in 6 bibliographic databases (CINAHL, EMBASE, ERIC, PsycINFO, PubMed, and Web of Science) using the concepts "adaptive e-learning environments," "health professionals/students," and "effects on knowledge/skills/behavior." We will include randomized and nonrandomized controlled trials, in addition to controlled before-after, interrupted time series, and repeated measures studies published between 2005 and 2017. The title and the abstract of each study followed by a full-text assessment of potentially eligible studies will be independently screened by 2 review authors. Using the EPOC extraction form, 1 review author will conduct data extraction and a second author will validate the data extraction. The methodological quality of included studies will be independently assessed by 2 review authors using the EPOC risk of bias criteria. Included studies will be synthesized by a descriptive analysis. Where appropriate, data will be pooled using meta-analysis by applying the RevMan software version 5.1, considering the heterogeneity of studies. RESULTS: The review is in progress. We plan to submit the results in the beginning of 2018. CONCLUSION: Providing tailored instruction to health professionals and students is a priority in order to optimize learning and clinical outcomes. This systematic review will synthesize the best available evidence regarding the effectiveness of AEEs in improving knowledge, competence, and behavior in health professionals and students. It will provide guidance to policy makers, hospital managers, and researchers in terms of AEE development, implementation, and evaluation in health care.

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