Impact of the PEARLS Healthcare Debriefing cognitive aid on facilitator cognitive load, workload, and debriefing quality: a pilot study

Abstract

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.

Data-informed debriefing for cardiopulmonary arrest: A randomized controlled trial

“…Use of a debriefing tool has been shown to decrease the cognitive load of facilitators and improve learner knowledge acquisition and performance. [22] , [43] With the support of objective performance data, use of a debriefing tool ensures that facilitators will systematically review the performance of all key clinical tasks relative to targets and provide actionable solutions to improve the performance of each team. The teaching points provided in the debriefing tool are supported by existing evidence – for example, we teach the team leader to share their mental model prior to defibrillation as this behavior is associated with reduced peri-shock pause duration during cardiac arrest.…”

Debriefer cognitive load during Traditional Reflective Debriefing vs. Rapid Cycle Deliberate Practice interdisciplinary team training

“…The primary outcome included cognitive load of debriefers leading SbTT sessions. Cognitive load and perceived workload were measured by self-reporting using the National Aeronautics and Space Administration Task Load Index (NASA TLX) [ 10 ] (Appendix 1 in Table 3). Cognitive load of the debriefers were measured after the baseline simulation at the start of the workshop and after debriefing intervention with RCDP or TRD, and the learners completed on final simulation without interruption (Fig.…”

“…Three types of cognitive load that are involved in debriefing have been described: intrinsic cognitive load (recalling simulation events and listening to learner responses), extraneous load (performing tasks outside the debriefing, such as mannequin management), and germane load (learning from experience, such as processing successful or unsuccessful approaches during debriefing and adjusting to the learners’ responses). In addition to the cognitive load described above, there is a significant workload in the execution of debriefing skills and processing [ 10 ]. This unique combination of cognitive load and workload from execution of tasks involved with effective debriefing is taxing and is becoming an active area of study.…”

Debriefing experiential learning in counselor education

“…In support of faculty development in debriefing, the PEARLS framework has been adapted into a cognitive aid info, which offers more specific scripted language for educators to facilitate debriefing conversations (Bajaj et al., 2018). Recent research demonstrated that using the PEARLS Healthcare Debriefing Cognitive Aid helped novice debriefers decrease their cognitive load while facilitating debriefings, suggesting that the tool benefits faculty development as they learn to be more effective debriefers (Meguerdichian et al., 2022). The physical, cognitive aid serves as a guide to help educators develop their skills as they move through the stages of debriefing skill development (discovery, growth, and maturity; Cheng et al., 2020).…”

“…Debriefing can be cognitively overwhelming for educators to navigate as they attend to various tasks, including learning objectives, timing, structure, number of learners, and complexities of process and content (Meguerdichian et al., 2022). Importantly, facilitator/debriefer competency and style are highlighted as positive contributing factors to effective debriefing, suggesting faculty development is needed to enhance meaningful learning and quality of facilitation (Dreifuerst, 2012; Høegh‐Larsen et al., 2023; Krogh et al., 2016; Mariani et al., 2013; Moldjord & Hybertsen, 2015).…”