November 2, 2023By Teresa Gore

Clinical Simulation Research Focus: Debriefing Methodology

Healthcare Simulation Debriefing Research

Debriefing in healthcare simulation is considered essential for all simulation experiences to assist the learners to translate knowledge gained in the simulation into clinical practice. The Healthcare Simulation Dictionary defines debriefing as “an activity that follows a simulation experience and led by a facilitator to encourage participants’ reflective thinking and provide feedback about their performance, while various aspects of the completed simulation are discussed.” As a verb, debriefing is to “conduct a session after a simulation event shere educators/instructors/facilitators and learners re-examine the simulation experience for the purpose of moving towards assimilation and accommodation of learning to future situations.” This HealthySimulation.com series by INACSL Past-President Dr. Teresa Gore, PhD, DNP, APRN, FNP-BC, CHSE-A, FSSH, FAAN, will explore the published research in simulation literature in 2023 on debriefing methodologies.

Baliga et al. (2023). The Debriefing Assessment in Real Time (DART) tool for simulation-based medical education : Debriefing is crucial for enhancing learning following healthcare simulation. Various validated tools have been shown to have contextual value for assessing debriefers. The Debriefing Assessment in Real Time (DART) tool may offer an alternative or additional assessment of conversational dynamics during debriefings. This is a multi-method international study investigating reliability and validity. Enrolled raters (n = 12) were active simulation educators. Following tool training, the raters were asked to score a mixed sample of debriefings. Descriptive statistics are recorded, with coefficient of variation (CV%) and Cronbach’s α used to estimate reliability. Raters returned a detailed reflective survey following their contribution. Kane’s framework was used to construct validity arguments. The 8 debriefings (μ = 15.4 min (SD 2.7)) included 45 interdisciplinary learners at various levels of training. Reliability (mean CV%) for key components was as follows: instructor questions μ = 14.7%, instructor statements μ = 34.1%, and trainee responses μ = 29.0%. Cronbach α ranged from 0.852 to 0.978 across the debriefings. Post-experience responses suggested that DARTs can highlight suboptimal practices including unqualified lecturing by debriefers. The DART demonstrated acceptable reliability and may have a limited role in assessment of healthcare simulation debriefing. Inherent complexity and emergent properties of debriefing practice should be accounted for when using this tool.

Benchadlia et al. (2023). Debriefing in Computer Simulation: Real Activity and Perspective : Digital simulation has reached a place of importance in nursing education. Debriefing is a crucial step in this experience. However, the practices of teachers remain little explored. This research aimed to explore and describe virtual simulation debriefing practices by faculty in the basic education of undergraduate nursing students. This was a qualitative study with exploratory and descriptive objectives. A mixed-methods approach was used, incorporating audio-visual recordings and self-confrontation interviews. Three teachers participated in the study. Concerning the pedagogical approach to the debriefing process in digital simulation, we highlighted the place of teachers in managing the debriefing environment, structuring the debriefing and managing the group dynamic interactions. Other attributes of digital debriefing have been derived from this study: performance evaluation support, ensuring learners are all protagonists, group dynamics and learning traceability. Some teacher activities fit the requirements of digital debriefing. However, other attributes of this type of debriefing need to be adopted. This calls for further engagement of trainers and more investigation of these innovative activities.

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Bradley et al. (2023). The Impact of Single-Dose Debriefing for Meaningful Learning Training on Debriefer Quality, Time, and Outcomes: Early Evidence to Inform Debriefing Training and Frequency : This study evaluated the impact of a single dose of training in Debriefing for Meaningful Learning (DML) on learner knowledge outcomes and time spent in debriefing. Regulatory bodies recommend that faculty who debrief receive training and competence assessment to ensure positive student learning outcomes, yet there is little literature describing the training needed. There is also little understanding of the impact of a single training on the length of debriefing, debriefer skill, and learner outcomes. Following training, debriefers submitted a recorded debriefing for assessment by experts; their learners completed knowledge assessment tests at three time points. Longer debriefing time led to higher DML Evaluation Scale scores. Learner knowledge scores improved and later decayed. The results of this study contribute to the evidence about the importance of training to debrief well, the impact of training on the length of debriefing time, and subsequent learner outcomes.

Cheng et al. (2023). Data-informed debriefing for cardiopulmonary arrest: A randomized controlled trial : To determine if data-informed debriefing, compared to a traditional debriefing, improves the process of care provided by healthcare teams during a simulated pediatric cardiac arrest. We conducted a prospective, randomized trial. Participants were randomized to a traditional debriefing or a data-informed debriefing supported by a debriefing tool. Participant teams managed a 10-minute cardiac arrest simulation case, followed by a debriefing (i.e. traditional or data-informed), and then a second cardiac arrest case. The primary outcome was the percentage of overall excellent CPR. The secondary outcomes were compliance with AHA guidelines for depth and rate, chest compression (CC) fraction, peri-shock pause duration, and time to critical interventions. A total of 21 teams (84 participants) were enrolled, with data from 20 teams (80 participants) analyzed. The data-informed debriefing group was significantly better in percentage of overall excellent CPR (control vs intervention: 53.8% vs 78.7%; MD 24.9%, 95%CI: 5.4 to 44.4%, p = 0.02), guideline-compliant depth (control vs. intervention: 60.4% vs 85.8%, MD 25.4%, 95%CI: 5.5 to 45.3%, p = 0.02), CC fraction (control vs intervention: 88.6% vs 92.6, MD 4.0%, 95%CI: 0.5 to 7.4%, p = 0.03), and peri-shock pause duration (control vs intervention: 5.8 s vs 3.7 s, MD −2.1 s, 95%CI: −3.5 to −0.8 s, p = 0.004) compared to the control group. There was no significant difference in time to critical interventions between groups. When compared with traditional debriefing, data-informed debriefing improves CPR quality and reduces pauses in CPR during simulated cardiac arrest, with no improvement in time to critical interventions.

Floridis (2023). Debriefing after critical incidents in rural and remote healthcare settings-a remote clinical perspective : Debriefing following a critical incident allows teams to reflect on the experience and to work together to improve future performance. Hot, warm and cold debriefs occur at various stages following the incident – each with its own structure and objectives. Effective debriefing requires training and practice, with a variety of tools available for this purpose. Healthcare professionals working in rural and remote areas face a variety of unique barriers, not encountered by colleagues in urban settings, that may make debriefing challenging. A hypothetical case example illustrates the complexities of a critical incident in a remote service. Evidence-based strategies are outlined to support team members in rural and remote areas to debrief effectively, including the use of technology, formal teaching in university curriculums and regular practice by simulation.

View the HealthySimulation.com LEARN CE/CME Platform Webinar Debriefing Psychologically Stressful Simulations: A Different Perspective to learn more!

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Høegh-Larsen et al. (2023). PEARLS debriefing compared to standard debriefing effects on nursing students’ professional competence and clinical judgment: a quasi-experimental study : Debriefing is an important learning component of simulation-based education (SBE) for nursing students. The evidence-based, scripted, and structured debriefing model—Promoting Excellence and Reflective Learning in Simulation (PEARLS) is meeting the standard of best practice by using a blended approach in the debriefing process with appropriate integration of feedback, debriefing, and/or guided reflection. Evidence demonstrating that PEARLS promotes better outcomes than other debriefing strategies is lacking. Our study compared PEARLS to a standard debriefing on nursing students’ professional competence and clinical judgment abilities. A quasi-experimental design was applied to compare differences in the effects of PEARLS (intervention group) and standard debriefing (control group) on nursing students’ self-reported professional competence and clinical judgment in SBE and clinical placement. No significant differences in nursing students’ self-reported professional competence or clinical judgment were found between the two groups. Professional competence and clinical judgment increased significantly within the intervention group, but not the control group. The results provide some support for implementation of PEARLS debriefing in nursing education. Faculty should receive the training and resources necessary for implementation.

Newton (2023). High-fidelity simulation in healthcare education: Considerations for design, delivery and debriefing : High-Fidelity Simulation (HFS) is a recognised teaching and learning tool and capable of facilitating skill retention and knowledge retrieval. Attitudes, values and behaviors may also be shaped by HFS, fostering a deeper appreciation of the experiential learning cycle as a lifelong learning strategy. Successfully achieving these outcomes relies on effective design, delivery and debriefing. A 3-step debriefing strategy was devised (Trinity Technique) and pilot-tested over a 17-month period. This incorporated a Hot Debrief, a ‘Question and Answer’ session and finally a Cold Debrief (using a newly fashioned tool called STOCK TAKE). The strategy was introduced into the learning of 208 students attached to paramedic science, physician associate, adult nursing and forensic science programmes. Participant feedback was captured in the form of Microsoft Teams transcribes and handwritten notes. Data was evaluated by faculty personnel to instigate refinements to teaching and learning practices. High levels of student and staff engagement were observed. Valuable insight into learner experience was gained and the novel strategy possessed a unique ability to debrief institutions as well as learners – enabling strategic improvements to future HFS design, delivery and debriefing. The Trinity Technique demonstrates promise and was effective when applied to interprofessional HFS.

To remain current in best healthcare simulation practices, simulationists must read and evaluate the literature and research published. This clinical simulation review on debriefing methodology research is part of a series to focus on published research in healthcare simulation for 2023.

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clinical simulation in nursing, debrief, debriefing, Debriefing Research, research