珍珠医疗保健述职认知辅助对引导者认知负荷、工作量和述职质量的影响:一项试点研究。

IF 2.8 Q2 HEALTH CARE SCIENCES & SERVICES Advances in simulation (London, England) Pub Date : 2022-12-12 DOI:10.1186/s41077-022-00236-x
Michael Meguerdichian, Komal Bajaj, Rachel Ivanhoe, Yiqun Lin, Audrey Sloma, Ariel de Roche, Brian Altonen, Suzanne Bentley, Adam Cheng, Katie Walker
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引用次数: 2

摘要

背景:在模拟中促进卓越和反思性学习(PEARLS)医疗保健报告工具是一种认知辅助工具,旨在以结构化的方式部署报告。通过分解汇报的复杂性,从而提高新手调解人汇报的质量,该工具有可能增加调解人获得汇报技能的能力。在这项初步研究中,我们旨在评估该工具对引导者认知负荷、工作量和述职质量的影响。方法:来自纽约市卫生+医院模拟奖学金的14名研究人员,是珍珠医疗报告工具的新手,随机分为两组,每组7人。干预组配备认知辅助工具,对照组不使用认知辅助工具。两组都进行了8小时的汇报课程。两组分别对3个视频模拟事件进行了情况介绍,并分别使用Paas-Merriënboer量表和原始的美国国家航空航天局任务负荷指数(NASA-TLX)对他们的经历的认知负荷和工作量进行了评分。然后使用医疗保健模拟汇报评估(DASH)对汇报质量进行评估。认知负荷测量以Paas-Merriënboer量表测量,并使用Wilcoxon秩和检验进行比较。使用混合效应线性回归模型分析工作量和汇报质量的度量。结果:使用工具的患者在3次述评中有2次的认知负荷中位数得分显著降低(使用工具与不使用工具的中位数得分:情景A 6 vs 6, p=0.1331;情景B: 5 vs 6, p=0.043;情境C: 5 vs 7, p=0.031)。工具在降低工作量需求综合评分(NASA-TLX平均差值为-4.5,95%CI为-16.5至7.0,p=0.456)或提高汇报质量综合评分(DASH平均差值为2.4,95%CI为-3.4至8.1,p=0.436)方面的有效性无差异。结论:珍珠保健报告工具可作为报告技能习得的教育辅助工具。使用述职认知辅助工具可能会减少述职的认知负荷,但对新手述职的工作量或质量没有影响。建议进一步研究认知辅助的效果。然而,本研究的设计可以作为未来探索述职报告质量的模型。
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Impact of the PEARLS Healthcare Debriefing cognitive aid on facilitator cognitive load, workload, and debriefing quality: a pilot study.

Background: The Promoting Excellence and Reflective Learning in Simulation (PEARLS) Healthcare Debriefing Tool is a cognitive aid designed to deploy debriefing in a structured way. The tool has the potential to increase the facilitator's ability to acquire debriefing skills, by breaking down the complexity of debriefing and thereby improving the quality of a novice facilitator's debrief. In this pilot study, we aimed to evaluate the impact of the tool on facilitators' cognitive load, workload, and debriefing quality.

Methods: Fourteen fellows from the New York City Health + Hospitals Simulation Fellowship, novice to the PEARLS Healthcare Debriefing Tool, were randomized to two groups of 7. The intervention group was equipped with the cognitive aid while the control group did not use the tool. Both groups had undergone an 8-h debriefing course. The two groups performed debriefings of 3 videoed simulated events and rated the cognitive load and workload of their experience using the Paas-Merriënboer scale and the raw National Aeronautics and Space Administration task load index (NASA-TLX), respectively. The debriefing performances were then rated using the Debriefing Assessment for Simulation in Healthcare (DASH) for debriefing quality. Measures of cognitive load were measured as Paas-Merriënboer scale and compared using Wilcoxon rank-sum tests. Measures of workload and debriefing quality were analyzed using mixed-effect linear regression models.

Results: Those who used the tool had significantly lower median scores in cognitive load in 2 out of the 3 debriefings (median score with tool vs no tool: scenario A 6 vs 6, p=0.1331; scenario B: 5 vs 6, p=0.043; and scenario C: 5 vs 7, p=0.031). No difference was detected in the tool effectiveness in decreasing composite score of workload demands (mean difference in average NASA-TLX -4.5, 95%CI -16.5 to 7.0, p=0.456) or improving composite scores of debriefing qualities (mean difference in DASH 2.4, 95%CI -3.4 to 8.1, p=0.436).

Conclusions: The PEARLS Healthcare Debriefing Tool may serve as an educational adjunct for debriefing skill acquisition. The use of a debriefing cognitive aid may decrease the cognitive load of debriefing but did not suggest an impact on the workload or quality of debriefing in novice debriefers. Further research is recommended to study the efficacy of the cognitive aid beyond this pilot; however, the design of this research may serve as a model for future exploration of the quality of debriefing.

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