Faculty of Nursing, Université de Montréal, Montréal, Québec, Canada
Research Center, Montreal Heart Institute, Montréal, Québec, Canada.
BMJ Open. 2019 Aug 28;9(8):e025252. doi: 10.1136/bmjopen-2018-025252.
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.
Systematic review and meta-analysis.
CINAHL, EMBASE, ERIC, PsycINFO, PubMed and Web of Science from the first year of records to February 2019.
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.
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.
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.
CRD42017065585.
尽管自适应电子学习环境(AEE)可以为医疗保健专业人员和学生提供个性化教学,但它们的疗效仍不清楚。因此,本综述旨在确定、评估和综合有关 AEE 提高医疗保健专业人员和学生知识、技能和临床行为的疗效的证据。
系统评价和荟萃分析。
从记录的第一年到 2019 年 2 月,CINAHL、EMBASE、ERIC、PsycINFO、PubMed 和 Web of Science。
评估 AEE 对医疗保健专业人员或学生的知识、技能或临床行为影响的对照研究。
筛选、数据提取和综合:两名作者独立筛选研究、提取数据、评估偏倚风险和编码证据质量。如果具有非自适应电子学习环境对照组且无缺失数据,则将研究纳入荟萃分析。使用随机效应模型汇总效应大小(ES)。
从 10569 篇文章中,我们纳入了 21 项符合条件的研究,共纳入了 3684 名医疗保健专业人员和学生。临床主题主要与诊断测试有关,理论框架多种多样,适应过程的特点是五个子领域:方法、目标、时间、因素和类型。知识的汇总 ES 为 0.70(95%CI-0.08 至 1.49;p.08),技能的汇总 ES 为 1.19(95%CI0.59 至 1.79;p<0.00001)。偏倚风险普遍较高。所有分析的异质性均较大。
AEE 似乎特别有助于提高医疗保健专业人员和学生的技能。AEE 中的适应过程可能更有利于学习技能而不是事实知识,因为后者产生的认知负荷较小。未来的研究应更清楚地报告 AEE 的设计和适应过程,并针对更高水平的结果,如临床行为。
PROSPERO 注册号:CRD42017065585。