The Impact of Using DASH First Element as a Pre-Briefing Tool on Nurse Competency and Learning during Code Blue Simulation: A Mixed-Methods Study

The Impact of Using DASH First Element as a Pre-Briefing Tool on Nurse Competency and Learning during Code Blue Simulation: A Mixed-Methods Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Using DASH First Element as a Pre-Briefing Tool on Nurse Competency and Learning during Code Blue Simulation: A Mixed-Methods Study Ralph C. Villar, Abdulqadir J. Nashwan, John Paul Silang, Ebtsam Abou Hashish, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2481528/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Simulation in healthcare is a growing teaching modality that allows undergraduate and graduate nurses to improve their clinical practice, communication skills, critical thinking, and team performance in a real-world clinical setting. Aim: The aim of the study was to determine if significant associations exist in the groups (control and experimental), the impact on competency performance during a code blue simulation (cardiac arrests in adults), and the learning experiences of nurses when using the 1st element of Debriefing Assessment for Simulation in Healthcare (DASH) as the pre-briefing guide. Design: This study employed a mixed-methods design for collecting quantitative and qualitative data. The quantitative portion was guided by a quasi-experimental design with a convenient sample of 120 nurses, while to uncover the meaning of the individual’s experience, a qualitative, phenomenological research design was used with a purposeful sample of 15 nurses. We utilized descriptive and inferential statistics for the quantitative data and phenomenological analysis for the qualitative data. Results : A total of N=120 nurses participated in the study, and 15 nurses from the experimental group were interviewed. There were 60 participants randomly selected for each of the control and experimental groups. The majority of participants in both the control group and the experimental group are males (90.83%). Most of the participants (98.33%) have more than 3 years of nursing experience. Regarding the specialty of nurses in the control group, an equal number were drawn from each of the five nursing specialties. Among the specialties of the nurses in the experimental groups are ED, OPD, CCU, MED-SURG, and PERI-OP. There was a statistically significant difference between the control and experimental groups in competency performance during the Code Blue simulation, p=0.00001. Aside from the age, the years of experience also have a significant effect on the CCEI scores, with p-values of 0.0232 and 0.0239, respectively, in the experimental group. No association was found between gender and specialization to competency performance. Five (5) themes were drawn from this study: (1) setting the tone; (2) reducing stress levels and improving confidence; (3) establishing a safe learning environment; (4) a positive impact on overall perceptions of pre-briefing; and (5) Expectation vs Reality. Conclusions: Utilizing the 1 st element of DASH improves competency performance and learning experience among experienced nurses in code blue simulation. Regardless of experience and specialization, nurses who participated in pre-briefing have better CCEI scores. Furthermore, the impact on the overall perception about pre-briefing promotes learning and engagement among experienced nurses. Despite establishing fiction contract and a safe learning environment, experienced nurses will still have anxiety, stress, and dissatisfaction in the realism of simulation. Pre-briefing Code Blue Cardiac Arrest Simulation Competency Performance Nurse Simulation Debriefing Assessment for Simulation in Healthcare (DASH) Figures Figure 1 Figure 2 Introduction Simulation in healthcare is an expanding teaching modality that enables both undergraduate and graduate nurses to improve their practice, communication skills, critical thinking, and team performance in a real clinical setting (Morse, Fey, Kardong-Edgren, Mullen, Barlow, and Barwick, 2019; Hughes and Hughes, 2019). Simulation is defined as an activity that mimics the reality of a clinical scenario and is designed to demonstrate procedures, decision-making, and critical thinking through different educational strategies (Jeffries, 2005). Simulation has been a tool used by most clinical instructors to assess the healthcare provider's and the hospital’s readiness to respond to emergency situations. Simulation is far beyond role-playing or dramatization that follows a script. It involves foundational concepts, some of which are pre-briefing, debriefing, and safety in simulation. However, there are a lot of research studies that support a high level of stress and anxiety during simulation, which can impair learning and competency performance. Most of these studies were done among nursing students (Labrague et al., 2019; Al-Ghareeb et al., 2019; Yockey & Henry, 2019). Conceptual Framework This study was be guided by the National League for Nursing (Jeffries, Rodgers, &Adamson, 2015) (Figure 2). According to Jeffries (2005), there is a need for a consistent guide for the design and implementation of simulations in order to assess positive learning outcomes. Initially, Jeffries (2005) introduced a proposal framework for simulation that was divided into five major components, however, when the National League for Nursing (2015) adopted and recognized the framework as the National League for Nursing (NLN) Jeffries Simulation Theory, a few minor changes were made within the conceptual illustration and the major concepts were divided into six: context, background, design, simulation experience, facilitator and educational strategies, participant, and outcomes. The context is an important starting point for the simulation. The design and implementation should include factors such as the place (bedside or lab) and overarching purpose (whether the simulation is for evaluation or instructional purposes). Within the context lies the background, where the goal(s) of the simulation, expectations, and resources are synced. The specific learning objectives and physical and conceptual fidelity are established as part of the design. The simulation experience is an experiential, interactive, and learner-centered environment. This requires the establishment of trust, which is dependent on both the facilitator and the learner. This aids in promoting engagement and psychological fidelity and safety within the simulation experience (Jeffries et al., 2015). The outcomes of the simulation may be separated into three areas: participant, patient, and system outcomes. To the participant (which is the focus of the study), results are associated with knowledge, skill performance, learner satisfaction, critical thinking, and self-confidence (Jeffries, 2005; Jeffries et al., 2015). In line with this framework, pre-briefing, considered one of the foundational concepts of simulation (Morse, Fey, Kardong-Edgren, Mullen, Barlow, and Barwick, 2019; Hughes & Hughes, 2019), creates an atmosphere for the learner’s psychological safety that hopes to optimize experience and reduce stress and anxiety (Hughes and Hughes, 2019). Psychological safety in simulation is defined as one where the participants feel comfortable undergoing simulation activities without fear of negative consequences (Kostovich et al., 2020). Psychological safety improves learning behaviors and outcomes in simulation (Daniels et al., 2021; Hughes & Hughes, 2019). Creating a psychologically safe environment moves towards working with learners through a set of discrete and concrete activities (Rudolph et al., 2014). The instructor attempts to establish expectations and remove fear from the learners during pre-briefing in order for them to perform at their best. Upon the development of this research, there was no single format, framework, or specific time allotment for pre-briefing (McDermott et al., 2020; Morse et al., 2019). According to Rudolph et al. (2014), the first element of Debriefing Assessment for Simulation in Healthcare (DASH) contains the necessary practices to create a psychologically safe environment in simulation. The first element of DASH was used to assess the instructor and includes essential behaviors in pre-briefings. Focusing on establishing an engaging learning environment, it requires trainers or simulators to: (1) clarify the course objectives, environment, roles, and expectations; (2) establish a "fiction contract" with the participants; (3) attend to logistical details; and (4) convey a commitment to respecting learners and understanding their perspective. Researchers and educators continue to explore many aspects of DASH as an integral part of simulation, and while it is mostly used to aid faculty in developing debriefing skills, each dimension can serve as a reference for future research studies (Rudolph et al., 2016). Significance of the study For the last four decades, clinical training and simulation in nursing have been gaining power. Their role in increasing nursing competence has been extensively researched (Abou Hashish & Bajbeir, 2022). One of the most important competencies for nurses is the ability to successfully process code blue when faced with cardiac resuscitation. Nurse educators and managers aim to ensure that the nursing staff can respond to cardiac arrests confidently and efficiently. Despite quality improvements in response to cardiac arrests, survival rates are lower in adults compared to children (Brady et al., 2019; Corazza et al., 2022). Simulation-based medical education is a safe, structured, and effective strategy to train nurses for code blue situations (Shrestha et al., 2020; McGaghie et al., 2014). In fact, the Joint Commission International Accreditation (JCIA), one of the most recognized accrediting bodies in healthcare, requires periodic resuscitation training among hospital staff to improve patients' survival rates (R3, 2021). Simulation-based training in response to Code Blue aims to evaluate the system, the process flow, and the readiness of staff during cardiac arrests. Code-blue simulations are being done to meet this, and a pre-briefing tool was introduced to bring about a meaningful learning experience. Furthermore, there is a lack of research on the impact of pre-briefing on code blue simulations among experienced nurses. This study aims to describe the impact of using the first element of the Debriefing Assessment for Simulation in Healthcare (DASH) as a pre-briefing guide on the nurses’ competency performance and learning experience during a code blue simulation. Objectives This study aims to determine if significant associations exist between the groups (control and experimental) and performance during a code blue simulation (cardiac arrests in adults) and the learning experiences of nurses. Specifically, the study aims to provide answers to the following research questions: Are there significant associations between groups (nurses who participated in the standardized pre-briefing and those who participated in the traditional pre-briefing activities) and competency performance during the Code Blue simulation and its categories? What are the experiences, feelings, and thought processes of nurses who participated in a standardized pre-briefing activity? Methods Design, setting, and sample: This study employed a mixed methods design for collecting quantitative and qualitative data to achieve the research objectives. The quantitative portion was guided by a quasi-experimental design, while to uncover the meaning of the individual’s experience, a qualitative, phenomenological research design was used to collect qualitative data. The study was conducted at a single tertiary hospital in Qatar. The participants were selected by any of the research team members through purposive and snowball sampling. A total of 120 nurses participated in the study, and 15 nurses from the experimental group were interviewed for the qualitative part. The subjects' inclusion criteria included being a graduate registered nurse with prior experience in code blue simulation and being willing to participate in the study. To maintain confidentiality, all participants were coded N1, N2, and so forth. Study procedure Quantitative part For the purpose of this study, a group of nurse educators who have lengthy experience in conducting code blue simulation reviewed the first element of DASH as the pre-briefing guide, including the code blue simulation scenario, roles for the participants, and the equipment to be used in the simulation. A quasi-experimental study was conducted to assess the competency performance of the participants. There were two groups in the study. The first group (experimental) received the pre-briefing guided by the 1 st element of DASH, while the second group (control) received the traditional pre-briefing being done in the study setting. The principal investigator assigned the groups before each simulation. A Resusci Anne manikin was used in the simulation. A standardized clinical scenario for chest pain management progressing to cardiac arrest was presented to the participants. To minimize internal threats to the study and to maintain consistency, the same scenario, roles, and equipment were provided to all participants. A pilot study was done with the first 10 participants, and the results were not included in the study. To assess the nurse's competency performance during the simulation, the Creighton Competency Evaluation Instrument (CCEI) (Hayden et al., 2014) was used. The CCEI was developed to be used as an evaluation instrument for both simulation and traditional clinical experiences in associate and baccalaureate nursing programs, with content validity ranging from 3.78 to 3.89 on a four-point Likert-like scale and Cronbach's alpha greater than 0.90 when used to score three levels of simulation performance (Hayden, Keegan, Kardong-Edgren, & Smiley, 2014). The CCEI is a 23-item assessment instrument divided into four categories: assessment, communication, clinical judgment, and patient safety. All participants were given the same scenario for the simulation. At least two members of the research team were present during the simulation. One dictated the scenario, and the other evaluated the participant using the CCEI. Analysis of quantitative data Independent t-test or unpaired t-test were used to test if there is a significant difference between the control group and intervention group in terms of assessment, communication, clinical judgment, and patient safety. The critical value for the independent t-test is determined by the level of significance of 0.05 with 60 respondents. If the observed independent T-test is greater than the critical value, then the null hypothesis can be rejected, and it can be determined which group had a better result or the hypothesis was rejected. When the research team tests the hypothesis at alpha 0.05, we do not reject the hypothesis if and only if the p-value is greater than 0.05; otherwise, we reject the null hypothesis with a 99% confidence interval. The unpaired t-test was used to test the significant differences between the overall scores of control group and intervention group with a level of significance of 0.05 with 60 respondents. The team will not reject the hypothesis if and only if the p-value is greater than 0.05 otherwise we reject the null hypothesis. Multivariate linear regression analysis using all the demographic variables as independent variables (i.e. gender, age, years of experience and specialization) and CCE scores as outcome variable. This test identified the factors associated with CCE scores with the level of significance 0.05 with 60 respondents. We do not reject the hypothesis if and only if the p-value is greater than 0.05 otherwise we reject the null hypothesis. We test the null the hypothesis that there is no significant effect to those participated in the traditional pre-briefing activities otherwise we reject the null hypothesis. Qualitative part To be able to uncover the meaning of the individual’s experience, a qualitative, phenomenological research design was used. Phenomenology is both a research method and a philosophical movement that is interested in the world as it is experienced by human beings; it is concerned with the phenomena that appear in our consciousness as we engage with the world (Willig, 2013). The purpose of phenomenological research is to focus on the experiences of the participants. It emphasizes the importance of personal perspective and interpretation. Any of the members of the research team who approached the participant from the experimental group after the simulation were asked privately if they were willing to be interviewed. To make sure that there was no duplication, the researcher asked the participant prior to the interview if he or she had been interviewed before for the same study. A semi-structured interview guide was used. Probing questions (Figure 1) were also formulated to get a deeper understanding of the participant’s experiences, guided by their initial responses. The durations of the interviews ranged between 30-45 minutes. Data gathering was facilitated by audio recording to aid in the accurate transcription of the responses, which was deleted after the end of the study. The transcriptions of the responses were done within 24 hours of the interview and were reviewed by two researchers for this study. Academic rigor and trustworthiness are maintained. Analysis of qualitative data In this study, Collaizzi’s seven-step procedure analysis for the phenomenological method (Jauregui and Xu, 2010) was followed: Time devoted to reading and rereading the transcript The goal is to get a "feel" for what is there. Return to each transcript and extract statements that express something significant about the nurses’ experience in the code blue simulation. Work to discern the "meaning" from the significant statements. Attempt to thematically organize the clusters of "meaning." Reread all the transcripts through the frame of the clusters to make sure they stay close to the raw data. Work to ensure that no data is rejected because it does not fit. The description is focused on embracing all the varied meanings as essences of experience. Finally, develop a coherent and integrated description of the nurses’ experience in the Code Blue simulation. Ethical consideration The Medical Research Center (MRC) of Hamad Medical Corporation's IRB reviewed and approved this research project (MRC-01-20-042), and the study was carried out in strict accordance with the "Declaration of Helsinki" for good clinical practice (GCP). All ethical considerations regarding human rights were maintained by the research team. Results A total of 120 experienced nurses participated in the study. Table 1 shows the demographic profile of nurse participants. It could be seen that there are 60 (100%) participants for each of the control and experimental groups. In terms of age, the majority of the participants in the control group are males (n = 53), while the remaining seven (11.67%) are females. The same is true for the experimental group since males (n = 56) occupy more than 90% of the participants and only 4 females (6.67%) are in this group. In terms of age, the majority of the participants in the control group have ages belonging in the "31–40 years" bracket (n = 51), while the remaining 15.00% (n = 9) have ages ranging from 21–30 years. No participant in the control group was aged 41 or older. The majority of participants in the experimental group (n = 54) are between the ages of 31 and 40, while 8.33% (n = 5) are between the ages of 21 and 30. Only 1 (1.67%) participant in the experimental group has an age between 41 and 50. In terms of years of experience, it could be noticed that for both the control and experimental groups, only 1 (1.67%) has 1 to 3 years of experience while the remaining 59 (98.33%) comprise the majority of the respondents. In terms of the specialization of nurses in the control group, it could be noticed that an equal number (n = 12, 20%) were taken from each of the 5 specializations. In terms of specialization of nurses in the experimental group, 25% (n = 15) and 15% (n = 9) specialize in ED and OPD, respectively, and the rest have 20.00% (n = 12) each. Table 1 . Demographic Profile of the Participants Category Control Experimental n % n % A. Entire Group 60 100.00 60 100.00 B. Sex Male 53 88.33 56 93.33 Female 7 11.67 4 6.67 C. Age 21-30 years 9 15.00 5 8.33 31-40 years 51 85.00 54 90.00 41-50 years 0 0.00 1 1.67 D. Years of Experience 1 – 3 1 1.67 1 1.67 Greater than 3 59 98.33 59 98.33 E. Specialization CCU 12 20.00 12 20.00 ED 12 20.00 15 25.00 MED-SURG 12 20.00 12 20.00 OPD 12 20.00 9 15.00 PERI-OP 12 20.00 12 20.00 The result in Table 2 shows that all the p-values are less than 0.01; hence, there is a significant difference between the control and experimental groups in terms of assessment, communication, clinical judgment, and patient safety. Based on the standard errors of the control and intervention groups, the result shows that the assessment of the control group has a better result and a smaller standard error of 0.0628 than that of the intervention group, which has a standard error of 0.085. The control group has a better result, which makes the hypothesis rejected with a standard error of 0.109 compared to a standard error of 0.136 for the intervention group. However, in clinical judgment, the intervention group has a better result with a standard error of 0.1418 than the control group with a standard error of 0.1432. Lastly, the patient safety of the intervention group has also shown a better result, with a standard error of 0.1147, than the control group, with a standard error of 0.122. Table 2. Comparison of the CCEI scores according to the four subscales between control and intervention group. Independent T-test Results Control Group n = 60 Experimental Group n = 60 p-value Mean Std. Dev. Std. Err Mean Std. Dev. Std. Err CCEI-Assessment 1 0.487 0.0628 1.35 0.659 0.085 0.0012** CCEI- Communication 1.7 0.849 0.109 2.73 1.055 0.136 0.0001** CCEI - Clinical Judgement 1.3 1.109 0.1432 2.75 1.098 0.1418 0.0001** CCEI - Patient Safety 1.18 0.947 0.122 2.58 0.888 0.1147 0.0001** Significant p-value < 0.05* and p-value < 0.01* Moreover, with the p-value of 0.0001, it can be concluded that there is a significant difference between the overall scores of control group and intervention group with 99% confidence interval (See Table3). Based on these findings, the utilization of standardized pre-briefing produces better overall competency performance on nurses during code blue simulation. Table 3. Comparison of the overall CCE scores between control and intervention group. Independent T-test Results Control Group n = 60 Experimental Group n = 60 p-value Mean Std. Dev. (95% CI-L, CI- U) Mean Std. Dev. (95% CI-L, CI – U) Overall Result 5.13 3.18 (4.58,5.68) 9.45 2.547 (8.79, 10.1) 0.00001 Significant p-value < 0.05* and p-value < 0.01* Table 4 showed the factors affecting the CCEI scores for those who were guided by the first dimension of DASH during pre-briefing (the experimental group). Aside from the age, the years of experience also have a significant effect on the CCEI scores, with p-values of 0.0232 and 0.0239, respectively. Using all demographic profiles as independent variables, the age range of 40 to 50 years old and years of experience greater than 3 years produce the most significant results in CCEI scores during the code blue simulation among those who attended the pre-briefing. Both gender and area of specialization were not found to be significantly associated with the CCEI scores in the experimental group. Table 4. Regression analysis with the factors affecting the CCEI scores in the experimental group. Instrument/Subscales Estimate Std. Error T-value P-value Gender -0.07827 0.1962 -0.399 0.6917 Age 0.82861 0.35315 2.346 0.0232* Years of Experience 0.83493 0.35756 2.335 0.0239* Specialization -0.10882 0.12221 -0.89 0.3777 Significant p-value < 0.05* and p-value < 0.01* Qualitative results. A total of 15 nurses participated in the qualitative part of the study. Five themes were drawn from the analysis: (1) setting the tone; (2) reducing stress levels and improving confidence; (3) establishing a safe learning environment; (4) a positive impact on overall perceptions of pre-briefing; and (5) Expectation vs Reality. See table 5 for the emerged themes and examples of participants quotations. Table 5. Themes emerged from the Qualitative data analysis Themes Transcripts quota’s examples Theme 1: Setting the tone “With the pre-briefing, it gives you a clear picture and a calming effect and know I will do it one by one and I will be corrected only when necessary. There is also confidentiality. In normal code drill, there are corrections immediately and you will be lost. These things in pre-briefing are effective”. Theme 2: Reducing stress levels and improving confidence “The pre-briefing helped me reduced my stress level. It paved the way for better performance in code blue simulations”. Theme 3: Establishing a safe environment “I felt comfortable because of the pre-briefing. I was a little bit nervous, but the pre-briefing helped. I did not feel being judged during the simulation and I was acceptant of any corrections because I know there’s always a room for improvement”. Theme 4: Positive impact on overall perceptions on pre-briefing “I will be happy to attend simulations with pre-briefing. We are human and we make mistakes. Without establishing that in pre-briefing, we’ll be ashamed of our performance and excuse ourselves from future drills. For me, it was a good experience”. Theme 4: Expectation vs Reality “In a real patient you will be able to see outcomes of your intervention, either good or bad, and you will be able to react to it spontaneously. However, in a simulation you won’t see the outcomes because it is just a dummy”. Five themes were exposed after the examination of open codes. The first theme is " Setting the Tone ." The participants mentioned the improvement of the simulation process as a result of pre-briefing. Most of the nurses described that with pre-briefing, expectations were clearer, and rapport was seamlessly established. These improvements in the process are essential to both the nurses and the simulation team in establishing connection and communication, as they were coming from different departments. The intervention group also appreciated the discussion of the scenario which was well-explained which improved their focus towards the simulation process. Notable quotes from the interview discussed that without pre-briefing there will be many obstacles, uncertainties, and lack of simulation orientation. In relation to stress levels, a theme emerged from the interview that showed that code blue simulation will be better with pre-briefing, as the intervention group explained that it reduced their stress levels, they gained better understanding, and pre-briefing leads to better nurse performance. The nurses in the study admit that they still feel some amount of stress and anxiety, but the increased awareness during the pre-briefing helps them think more critically as they formulate strategies for handling the scenario. The nurses became more prepared, cautious, and confident. They gained better recall of the steps and other details when performing their expected tasks. In comparison to simulation without pre-briefing, nurses encounter difficulties, recognize weaknesses, fail to recall, and lose focus. Another theme that has emerged is that pre-briefing establishes a safe environment among nurses, and it pertains to how learning experiences are improved with pre-briefing. With pre-briefing, the simulation team was more approachable to the intervention group. The nurses felt valued and were encouraged to openly discuss their feelings and thoughts. They were able to raise concerns and seek clarifications, which improved their understanding. The simulation team also shared reminders and were reinforcing the nurses. The overall experience with pre-briefing created a comfortable environment for learning, which is attractive to the nurses. Unlike with no pre-briefing, nurses were anxious and nervous, and encounters fear of being corrected or receiving failing scores especially for experienced nurses. The fourth theme, Impact on Overall Perceptions of Pre-briefing , explains the thoughts of the nurses towards pre-briefing as a beneficial adjunct to simulation in enhancing competency. The nurses viewed the pre-briefing as an opportunity to learn. Hence, nurses suggested having more time for practice and taking breaks during pre-briefing. In doing so, nurses can gain mastery over the procedures even during the pre-briefing period. Adding more time will encourage more opportunities to fix concerns about the simulation before engaging. The intervention group discussed that code blue situation is not often encountered and described as rare but an essential competency for nurses. In fact, because code blue is viewed as not being an everyday experience, they may forget what they’ve learned in the simulation. It will become usual and simple for the nurses to perform the intervention using simulation on a regular basis, especially during outbreaks like the COVID-19 pandemic, which demands nurses be ready and efficient to engage in such emergency circumstances. The intervention group recommended that nurses should join frequent simulation with pre-briefing to reduce hesitancies in performing the tasks in real situations. The last theme that emerged ( expectation vs. reality ) is that results in simulation are not the same as in real life. Despite establishing a fiction contract in pre-briefing, nurses view the entire process of pre-briefing and simulation as distinct from real situations. The responses to this theme by the respondents are varied but meaningful, as the intervention can improve the experience of nurses in code blue simulations both in fiction and in real-life situations. The materials used and the time to accomplish tasks like reviving the patient are not similar in real code blue situations. Thus, nurses will likely perform better during simulation than in real code-blue situations. The code blue simulation remains fictional to others, as nobody will be supporting or evaluating nurses by scoring their performance. Others were able to perform the procedures well in real-life code blue situations despite the fact that the situation was fictional due to the pre-briefing. Discussion Pre-briefing has been a vital step in arriving at better outcomes in different fields; it sets the tone for an upcoming learning experience (Hughes & Hughes, 2022). Strategies are being developed and tested as organizations try to arrive at productive outcomes and significant results in various process dynamics, such as training and simulation exercises. Researchers and educators continue to explore many aspects of DASH as an integral part of simulation, and while it is mostly used to aid faculty in developing debriefing skills, the findings of this study can serve as a reference for future research (Rudolph et al., 2016 ). In implementing a pre-briefing approach in simulation activities, a qualified and properly trained instructor should ensure that the tools to be implemented are reliable and appropriate. He is the one responsible for formulating the pre-briefing tool that will fit the needs of the participants, or else desired outcomes will not be met, and the experience gained in the simulation will negate quality outcomes and engagement. This study is similar to that of Page-Cutrara (2016). While the former designed their pre-briefing to encourage reflection before action among nursing students, this study was based on the first element of DASH, in which instructors assist participants in clarifying expectations, becoming familiar with the simulation setting, and creating a safe learning environment among experienced nurses. There is a lack of literature on the impact of pre-briefing on the competence and learning experience of experienced nurses. The study was able to evaluate the first element of DASH as a pre-briefing guide and its impact on the experienced nurse’s competence and learning experience in a code blue simulation. A total of 120 nurses participated in the quasi-experimental part of the study, and 15 nurses from the experimental group were interviewed for the phenomenological part of the study. Interestingly, the majority of the participants are male nurses (90.83%). Despite the fact that nursing has been dominated by the female gender, there has been a slow rise in the number of male nurses in the past 10 years (Younas et al., 2019 ). Nursing in Qatar and other Middle East countries faces challenges because of the negative conception of nursing and cultural roles of women (Alsadaan et al., 2021 ; Levers, 2019 ; Tieleman & Cable, 2021 ). While this warrants further investigation, the relationship between gender and competency performance cannot be established due to the huge disparity between male and female nurses in this study. This study shows that utilizing the first element of DASH as a pre-briefing guide before a code blue simulation improves competency performance and the learning experience among experienced nurses. Experienced nurses are trained on how to respond to code blue situations; it has been a part of their continuing education and they are expected to have completed Basic Life Support (BLS) and Advanced Cardiopulmonary Life Support (ACLS) training. Despite that, a significant difference is found in all aspects of the nurses’ competency performance (assessment, communication, clinical judgment, and patient safety). This study shows that nurses who participated in the pre-briefing utilizing the first element of DASH performed far better than those who did not. Nurses assigned to the ER and ICU are more exposed to code blue situations than nurses assigned to the outpatient setting, medical unit, or OR, giving them an advantage in code blue simulation. However, the findings of this study show that competency performance and learning experience improve regardless of exposure to real-life Code Blue situations. Pre-briefing creates a safe environment but does not completely eliminate anxiety; participants will still experience anxiety in relation to the degree of work that needs to be performed. Being oriented from the start is an advantage; the idea of having a picture of what lies ahead permeates an avenue of security as it draws the line of expectations. Yet this is not an assurance that participants will render a smooth transition in the said activity; the setting and nature of the task will always play a significant role in the simulation and outcome measures. Being oriented from the beginning is an advantage; the idea of having a picture of what lies ahead permeates an avenue of security as it draws the line of expectations. Yet, this is not an assurance that participants will render a smooth transition in the said activity; the setting and nature of the task will always play a significant role in the simulation and outcome measures. Despite the fictional contract in pre-briefing, experienced nurses find it difficult to see reality or find satisfaction in simulation. In any simulation, coherent truths have priority over correspondences (Oatley, 1999 ). The feel and quality of the simulation can cast a veil of inauthenticity that may deter participants from achieving quality experiences and outcomes. Nurses with clinical experience will still find a lack of realism in simulation. People tend to develop preconceptions and biases toward certain situations that they deem untrue. Utilization of virtual reality or high-fidelity simulation improves satisfaction among nursing students or novice nurses (Basak et al., 2016 ; Alconero-Camarero et al., 2021 ; Kang et al., 2020 ). Instructors should try to devise methods to improve the quality of simulation programs where participants can experience a diverse simulation that can somewhat make it feel like a real-life scenario, especially for experienced nurses. Pre-briefing positively impacts trainings and simulation activities; the use of initial orientation through the use of handouts, face-to-face orientation, etc. facilitates better interaction and develops preparedness to promise positive outcomes (Lioce et al., 2020). The outcomes that we have gathered in the study based on the application of the first element of DASH as a pre-briefing method are positive and significant in improving learner engagement, experience, and competence. Applying it in hospital institutions whenever they conduct simulation activities would provide a great benefit to their staff and the team as a whole. Additionally, this pre-briefing tool can also be further developed in certain variations that can cater to identified needs and areas of opportunity, especially when trying to improve performance and competence in dealing with code blue situations. Limitations This study poses many limitations in terms of applicability and generalizability. The findings of the study may only be true for the research locale where the participants were taken from and may not be true for other settings. Since nurse-participants were selected via non-probability sampling techniques, it should be emphasized that the results should not be generalized for all nurses. Ratings derived were given by raters based on their perceived judgment. Such bias may not be totally avoided, even though the researcher tried to be as objective as possible. Since only nominal-level data were collected, analysis was limited to the use of nonparametric statistics. The demographic profile of respondents was collected but not utilized to interpret the results of the study. The researcher tried to control aspects of the study, but it may have been possible that extraneous variables (internal or external), such as personal factors from participants and raters, affected the results of the study. Furthermore, theme analysis was used for qualitative data analyses for nurses who only received the standardized pre-briefing. Nurses who received the traditional pre-briefing were excluded from the qualitative data analysis. The researcher and author acknowledge that interpretation is based only on information gathered from transcripts. Due to these limitations, the author/researcher suggests conducting future similar studies, especially on areas or other factors not explored in this study. Conclusion And Implications In code blue simulation, using the first element of DASH improves competency performance and learning experiences among experienced nurses. Regardless of experience and specialization, nurses who participated in pre-briefing had better CCEI scores. Furthermore, the impact on the overall perception of pre-briefing promotes learning and engagement among experienced nurses. Despite establishing a fictional contract and a safe learning environment, experienced nurses will still have anxiety, stress, and dissatisfaction with the realism of simulation. Pre-briefing positively impacts trainings and simulation activities; the use of initial orientation using handouts, face-to-face orientation, etc. facilitates better interaction and develops preparedness to promise positive outcomes (Lioce et al., 2020). The outcomes that we have gathered in the study based on the application of the first element of DASH as a pre-briefing method are positive and significant in improving learner engagement, experience, and competence. Applying it in hospital institutions whenever they conduct simulation activities would provide a great benefit to their staff and the team. Additionally, this pre-briefing tool can also be further developed in certain variations that can cater to identified needs and areas of opportunity, especially when trying to improve performance and competence in dealing with code blue situations. Multidisciplinary simulation activities could be suggested to encourage healthcare team collaboration, problem solving, comprehension, and confidence. Declarations Ethics approval and consent to participate: The local Institutional Review Board at the Medical Research Center in Hamad Medical Corporation (Doha, Qatar) (IRB-MRC) approved the study (MRC-01-20-042). Informed consent was obtained from all participants. All methods were carried out in accordance with relevant guidelines and regulations or Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials All data generated or analyzed during this study are included in this published article. Competing interests The authors have no conflicts of interest to disclose. Funding This study was funded by the Medical Research Center at Hamad Medical Corporation (MRC-01-20-042). Authors’ contributions RCV: Conceptualization. RCV, AJN, JPS, EAH, KCP, RGM, SAM, NFA, JPA, JPZ, AZK, JCP, AAA: Research design, Data collection, Analysis, Literature search, Manuscript preparation. All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Acknowledgments The authors would like to acknowledge the nurses and midwifes who participated in the study. The publication of this article was funded by the Qatar National Library. References Abou Hashish, E. A., & Bajbeir, E. F. (2022). The Effect of Managerial and Leadership Training and Simulation on Senior Nursing Students’ Career Planning and Self-Efficacy. 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Using Duchscher’s theory of transition shock to inform the experience of newly graduated nurses in Qatar: A qualitative case study. MedEdPublish , 10 (156), 1–15. Więch, P., Sałacińska, I., Muster, M., Bazaliński, D., Kucaba, G., Fąfara, A., … Januszewicz, P. (2019). Use of Selected Telemedicine Tools in Monitoring Quality of In-Hospital Cardiopulmonary Resuscitation: A Prospective Observational Pilot Simulation Study. Medical science monitor: international medical journal of experimental and clinical research , 25 , 2520–2526. doi:10.12659/MSM.913191 Willhaus J, Averette M, Gates M, Jackson J, Windnagel S. Proactive policy planning for unexpected student distress during simulation. Nurse Educ. 2014 Sep-Oct;39(5):232-5. [PubMed] Vandyk, A. D., Lalonde, M., Merali, S., Wright, E., Bajnok, I. and Davies, B. (2018), The use of psychiatry‐focused simulation in undergraduate nursing education: A systematic search and review.Int J Mental Health Nurs, 27: 514-535. doi:10.1111/inm.12419 Yockey, J., & Henry, M. (2019). Simulation anxiety across the curriculum. Clinical Simulation in Nursing , 29 , 29-37. Younas, A., Sundus, A., Zeb, H., & Sommer, J. (2019). A mixed methods review of male nursing students' challenges during nursing education and strategies to tackle these challenges. Journal of Professional Nursing , 35 (4), 260-276. Yu, J., Chung, Y., Lee, J. E., Suh, D. H., Wie, J. H., Ko, H. S., … Shin, J. C. (2019). The Educational Effects of a Pregnancy Simulation in Medical/Nursing Students and Professionals. BMC medical education , 19 (1), 168. doi:10.1186/s12909-019-1589-8 Additional Declarations No competing interests reported. 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Simulation is defined as an activity that mimics the reality of a clinical scenario and is designed to demonstrate procedures, decision-making, and critical thinking through different educational strategies (Jeffries, 2005). Simulation has been a tool used by most clinical instructors to assess the healthcare provider\u0026apos;s and the hospital\u0026rsquo;s readiness to respond to emergency situations. Simulation is far beyond role-playing or dramatization that follows a script. It involves foundational concepts, some of which are pre-briefing, debriefing, and safety in simulation. However, there are a lot of research studies that support a high level of stress and anxiety during simulation, which can impair learning and competency performance. Most of these studies were done among nursing students (Labrague et al., 2019; Al-Ghareeb et al., 2019; Yockey \u0026amp; Henry, 2019). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptual Framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was be guided by the National League for Nursing (Jeffries, Rodgers, \u0026amp;Adamson, 2015) (Figure 2). According to Jeffries (2005), there is a need for a consistent guide for the design and implementation of simulations in order to assess positive learning outcomes. Initially, Jeffries (2005) introduced a proposal framework for simulation that was divided into five major components, however, when the National League for Nursing (2015) adopted and recognized the framework as the National League for Nursing (NLN) Jeffries Simulation Theory, a few minor changes were made within the conceptual illustration and the major concepts were divided into six: context, background, design, simulation experience, facilitator and educational strategies, participant, and outcomes. The context is an important starting point for the simulation. The design and implementation should include factors such as the place (bedside or lab) and overarching purpose (whether the simulation is for evaluation or instructional purposes). Within the context lies the background, where the goal(s) of the simulation, expectations, and resources are synced. The specific learning objectives and physical and conceptual fidelity are established as part of the design. The simulation experience is an experiential, interactive, and learner-centered environment. This requires the establishment of trust, which is dependent on both the facilitator and the learner. This aids in promoting engagement and psychological fidelity and safety within the simulation experience (Jeffries et al., 2015). The outcomes of the simulation may be separated into three areas: participant, patient, and system outcomes. To the participant (which is the focus of the study), results are associated with knowledge, skill performance, learner satisfaction, critical thinking, and self-confidence (Jeffries, 2005; Jeffries et al., 2015).\u003c/p\u003e\n\u003cp\u003eIn line with this framework, pre-briefing, considered one of the foundational concepts of simulation (Morse, Fey, Kardong-Edgren, Mullen, Barlow, and Barwick, 2019; Hughes \u0026amp; Hughes, 2019), creates an atmosphere for the learner\u0026rsquo;s psychological safety that hopes to optimize experience and reduce stress and anxiety (Hughes and Hughes, 2019). Psychological safety in simulation is defined as one where the participants feel comfortable undergoing simulation activities without fear of negative consequences (Kostovich et al., 2020). Psychological safety improves learning behaviors and outcomes in simulation (Daniels et al., 2021; Hughes \u0026amp; Hughes, 2019). Creating a psychologically safe environment moves towards working with learners through a set of discrete and concrete activities (Rudolph et al., 2014). The instructor attempts to establish expectations and remove fear from the learners during pre-briefing in order for them to perform at their best. Upon the development of this research, there was no single format, framework, or specific time allotment for pre-briefing (McDermott et al., 2020; Morse et al., 2019).\u003c/p\u003e\n\u003cp\u003eAccording to Rudolph et al. (2014), the first element of Debriefing Assessment for Simulation in Healthcare (DASH) contains the necessary practices to create a psychologically safe environment in simulation. The first element of DASH was used to assess the instructor and includes essential behaviors in pre-briefings. Focusing on establishing an engaging learning environment, it requires trainers or simulators to: (1) clarify the course objectives, environment, roles, and expectations; (2) establish a \u0026quot;fiction contract\u0026quot; with the participants; (3) attend to logistical details; and (4) convey a commitment to respecting learners and understanding their perspective. Researchers and educators continue to explore many aspects of DASH as an integral part of simulation, and while it is mostly used to aid faculty in developing debriefing skills, each dimension can serve as a reference for future research studies (Rudolph et al., 2016).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSignificance of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the last four decades, clinical training and simulation in nursing have been gaining power. Their role in increasing nursing competence has been extensively researched (Abou Hashish \u0026amp; Bajbeir, 2022). One of the most important competencies for nurses is the ability to successfully process code blue when faced with cardiac resuscitation. Nurse educators and managers aim to ensure that the nursing staff can respond to cardiac arrests confidently and efficiently. Despite quality improvements in response to cardiac arrests, survival rates are lower in adults compared to children (Brady et al., 2019; Corazza et al., 2022). Simulation-based medical education is a safe, structured, and effective strategy to train nurses for code blue situations (Shrestha et al., 2020; McGaghie et al., 2014). In fact, the Joint Commission International Accreditation (JCIA), one of the most recognized accrediting bodies in healthcare, requires periodic resuscitation training among hospital staff to improve patients\u0026apos; survival rates (R3, 2021). Simulation-based training in response to Code Blue aims to evaluate the system, the process flow, and the readiness of staff during cardiac arrests. Code-blue simulations are being done to meet this, and a pre-briefing tool was introduced to bring about a meaningful learning experience. Furthermore, there is a lack of research on the impact of pre-briefing on code blue simulations among experienced nurses. This study aims to describe the impact of using the first element of the Debriefing Assessment for Simulation in Healthcare (DASH) as a pre-briefing guide on the nurses\u0026rsquo; competency performance and learning experience during a code blue simulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aims to determine if significant associations exist between the groups (control and experimental) and performance during a code blue simulation (cardiac arrests in adults) and the learning experiences of nurses.\u003c/p\u003e\n\u003cp\u003eSpecifically, the study aims to provide answers to the following research questions:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n\u003cli\u003eAre there significant associations between groups (nurses who participated in the standardized pre-briefing and those who participated in the traditional pre-briefing activities) and competency performance during the Code Blue simulation and its categories?\u003c/li\u003e\n\u003cli\u003eWhat are the experiences, feelings, and thought processes of nurses who participated in a standardized pre-briefing activity?\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Methods","content":"\u003cp\u003eDesign, setting, and sample: This study employed a mixed methods design for collecting quantitative and qualitative data to achieve the research objectives. The quantitative portion was guided by a quasi-experimental design, while to uncover the meaning of the individual\u0026rsquo;s experience, a qualitative, phenomenological research design was used to collect qualitative data. The study was conducted at a single tertiary hospital in Qatar. The participants were selected by any of the research team members through purposive and snowball sampling. A total of 120 nurses participated in the study, and 15 nurses from the experimental group were interviewed for the qualitative part. The subjects\u0026apos; inclusion criteria included being a graduate registered nurse with prior experience in code blue simulation and being willing to participate in the study. To maintain confidentiality, all participants were coded N1, N2, and so forth.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy procedure\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative part\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the purpose of this study, a group of nurse educators who have lengthy experience in conducting code blue simulation reviewed the first\u0026nbsp;element of DASH as the pre-briefing guide, including the code blue simulation scenario, roles for the participants, and the equipment to be used in the simulation. A quasi-experimental study was conducted to assess the competency performance of the participants. There were two groups in the study. The first group (experimental) received the pre-briefing guided by the 1\u003csup\u003est\u003c/sup\u003e element of DASH, while the second group (control) received the traditional pre-briefing being done in the study setting. The principal investigator assigned the groups before each simulation.\u003c/p\u003e\n\u003cp\u003eA \u003cstrong\u003e\u003cem\u003eResusci Anne manikin\u003c/em\u003e\u003c/strong\u003e was used in the simulation. A standardized clinical scenario for chest pain management progressing to cardiac arrest was presented to the participants. To minimize internal threats to the study and to maintain consistency, the same scenario, roles, and equipment were provided to all participants. A pilot study was done with the first 10 participants, and the results were not included in the study.\u003c/p\u003e\n\u003cp\u003eTo assess the nurse\u0026apos;s competency performance during the simulation, the Creighton Competency Evaluation Instrument (CCEI) (Hayden et al., 2014) was used. The CCEI was developed to be used as an evaluation instrument for both simulation and traditional clinical experiences in associate and baccalaureate nursing programs, with content validity ranging from 3.78 to 3.89 on a four-point Likert-like scale and Cronbach\u0026apos;s alpha greater than 0.90 when used to score three levels of simulation performance (Hayden, Keegan, Kardong-Edgren, \u0026amp; Smiley, 2014). The CCEI is a 23-item assessment instrument divided into four categories: assessment, communication, clinical judgment, and patient safety. All participants were given the same scenario for the simulation. At least two members of the research team were present during the simulation. One dictated the scenario, and the other evaluated the participant using the CCEI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAnalysis of quantitative data\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndependent t-test or unpaired t-test were used to test if there is a significant difference between the control group and intervention group in terms of assessment, communication, clinical judgment, and patient safety. The critical value for the independent t-test is determined by the level of significance of 0.05 with 60 respondents. If the observed independent T-test is greater than the critical value, then the null hypothesis can be rejected, and it can be determined which group had a better result or the hypothesis was rejected. When the research team tests the hypothesis at alpha 0.05, we do not reject the hypothesis if and only if the p-value is greater than 0.05; otherwise, we reject the null hypothesis with a 99% confidence interval. The unpaired t-test was used to test the significant differences between the overall scores of control group and intervention group with a level of significance of 0.05 with 60 respondents. The team will not reject the hypothesis if and only if the p-value is greater than 0.05 otherwise we reject the null hypothesis. Multivariate linear regression analysis using all the demographic variables as independent variables (i.e. gender, age, years of experience and specialization) and CCE scores as outcome variable. This test identified the factors associated with CCE scores with the level of significance 0.05 with 60 respondents. We do not reject the hypothesis if and only if the p-value is greater than 0.05 otherwise we reject the null hypothesis. We test the null the hypothesis that there is no significant effect to those participated in the traditional pre-briefing activities otherwise we reject the null hypothesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQualitative part\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo be able to uncover the meaning of the individual\u0026rsquo;s experience, a qualitative, phenomenological research design was used. Phenomenology is both a research method and a philosophical movement that is interested in the world as it is experienced by human beings; it is concerned with the phenomena that appear in our consciousness as we engage with the world (Willig, 2013). The purpose of phenomenological research is to focus on the experiences of the participants. It emphasizes the importance of personal perspective and interpretation. Any of the members of the research team who approached the participant from the experimental group after the simulation were asked privately if they were willing to be interviewed. To make sure that there was no duplication, the researcher asked the participant prior to the interview if he or she had been interviewed before for the same study. A semi-structured interview guide was used. Probing questions (Figure 1) were also formulated to get a deeper understanding of the participant\u0026rsquo;s experiences, guided by their initial responses. The durations of the interviews ranged between 30-45 minutes. Data gathering was facilitated by audio recording to aid in the accurate transcription of the responses, which was deleted after the end of the study. The transcriptions of the responses were done within 24 hours of the interview and were reviewed by two researchers for this study. Academic rigor and trustworthiness are maintained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAnalysis of qualitative data\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, Collaizzi\u0026rsquo;s seven-step procedure analysis for the phenomenological method (Jauregui and Xu, 2010) was followed:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eTime devoted to reading and rereading the transcript The goal is to get a \u0026quot;feel\u0026quot; for what is there.\u003c/li\u003e\n \u003cli\u003eReturn to each transcript and extract statements that express something significant about the nurses\u0026rsquo; experience in the code blue simulation.\u003c/li\u003e\n \u003cli\u003eWork to discern the \u0026quot;meaning\u0026quot; from the significant statements.\u003c/li\u003e\n \u003cli\u003eAttempt to thematically organize the clusters of \u0026quot;meaning.\u0026quot;\u003c/li\u003e\n \u003cli\u003eReread all the transcripts through the frame of the clusters to make sure they stay close to the raw data.\u003c/li\u003e\n \u003cli\u003eWork to ensure that no data is rejected because it does not fit. The description is focused on embracing all the varied meanings as essences of experience.\u003c/li\u003e\n \u003cli\u003eFinally, develop a coherent and integrated description of the nurses\u0026rsquo; experience in the Code Blue simulation.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical consideration\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Medical Research Center (MRC) of Hamad Medical Corporation\u0026apos;s IRB reviewed and approved this research project (MRC-01-20-042), and the study was carried out in strict accordance with the \u0026quot;Declaration of Helsinki\u0026quot; for good clinical practice (GCP). All ethical considerations regarding human rights were maintained by the research team.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 120 experienced nurses participated in the study. Table 1 shows the demographic profile of nurse participants. It could be seen that there are 60 (100%) participants for each of the control and experimental groups. In terms of age, the majority of the participants in the control group are males (n = 53), while the remaining seven (11.67%) are females. The same is true for the experimental group since males (n = 56) occupy more than 90% of the participants and only 4 females (6.67%) are in this group. In terms of age, the majority of the participants in the control group have ages belonging in the \u0026quot;31\u0026ndash;40 years\u0026quot; bracket (n = 51), while the remaining 15.00% (n = 9) have ages ranging from 21\u0026ndash;30 years. No participant in the control group was aged 41 or older. The majority of participants in the experimental group (n = 54) are between the ages of 31 and 40, while 8.33% (n = 5) are between the ages of 21 and 30. Only 1 (1.67%) participant in the experimental group has an age between 41 and 50. In terms of years of experience, it could be noticed that for both the control and experimental groups, only 1 (1.67%) has 1 to 3 years of experience while the remaining 59 (98.33%) comprise the majority of the respondents. In terms of the specialization of nurses in the control group, it could be noticed that an equal number (n = 12, 20%) were taken from each of the 5 specializations. In terms of specialization of nurses in the experimental group, 25% (n = 15) and 15% (n = 9) specialize in ED and OPD, respectively, and the rest have 20.00% (n = 12) each.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e. Demographic Profile of the Participants\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"609\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.916256157635466%\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"31.03448275862069%\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"30.049261083743843%\"\u003e\n \u003cp\u003eExperimental\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003eA. Entire Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003eB. Sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e88.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e93.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e11.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e6.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003eC. Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;21-30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e15.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;31-40 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e85.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e90.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;41-50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003eD. Years of Experience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Greater than 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e98.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e98.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003eE. Specialization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;CCU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;ED\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e25.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;MED-SURG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;OPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e15.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.85245901639344%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;PERI-OP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.40983606557377%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.573770491803279%\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.918032786885245%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.245901639344263%\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe result in Table 2 shows that all the p-values are less than 0.01; hence, there is a significant difference between the control and experimental groups in terms of assessment, communication, clinical judgment, and patient safety. Based on the standard errors of the control and intervention groups, the result shows that the assessment of the control group has a better result and a smaller standard error of 0.0628 than that of the intervention group, which has a standard error of 0.085. The control group has a better result, which makes the hypothesis rejected with a standard error of 0.109 compared to a standard error of 0.136 for the intervention group. However, in clinical judgment, the intervention group has a better result with a standard error of 0.1418 than the control group with a standard error of 0.1432. Lastly, the patient safety of the intervention group has also shown a better result, with a standard error of 0.1147, than the control group, with a standard error of 0.122.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eComparison of the CCEI scores according to the four subscales between control and intervention group.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"32.396694214876035%\"\u003e\n \u003cp\u003eIndependent\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eT-test Results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"27.768595041322314%\"\u003e\n \u003cp\u003eControl Group\u003c/p\u003e\n \u003cp\u003en = 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"29.58677685950413%\"\u003e\n \u003cp\u003eExperimental Group\u003c/p\u003e\n \u003cp\u003en = 60\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.24793388429752%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.691931540342297%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.71393643031785%\"\u003e\n \u003cp\u003eStd. Dev.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.669926650366747%\"\u003e\n \u003cp\u003eStd. Err\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.91442542787286%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.425427872860636%\"\u003e\n \u003cp\u003eStd. Dev.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.425427872860636%\"\u003e\n \u003cp\u003eStd. Err\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.158924205378973%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.396694214876035%\"\u003e\n \u003cp\u003eCCEI-Assessment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.256198347107437%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.59504132231405%\"\u003e\n \u003cp\u003e0.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.917355371900827%\"\u003e\n \u003cp\u003e0.0628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.082644628099173%\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.75206611570248%\"\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.75206611570248%\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.24793388429752%\"\u003e\n \u003cp\u003e0.0012**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.396694214876035%\"\u003e\n \u003cp\u003eCCEI- Communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.256198347107437%\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.59504132231405%\"\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.917355371900827%\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.082644628099173%\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.75206611570248%\"\u003e\n \u003cp\u003e1.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.75206611570248%\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.24793388429752%\"\u003e\n \u003cp\u003e0.0001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.396694214876035%\"\u003e\n \u003cp\u003eCCEI - Clinical Judgement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.256198347107437%\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.59504132231405%\"\u003e\n \u003cp\u003e1.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.917355371900827%\"\u003e\n \u003cp\u003e0.1432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.082644628099173%\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.75206611570248%\"\u003e\n \u003cp\u003e1.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.75206611570248%\"\u003e\n \u003cp\u003e0.1418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.24793388429752%\"\u003e\n \u003cp\u003e0.0001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.396694214876035%\"\u003e\n \u003cp\u003eCCEI - Patient Safety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.256198347107437%\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.59504132231405%\"\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.917355371900827%\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.082644628099173%\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.75206611570248%\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.75206611570248%\"\u003e\n \u003cp\u003e0.1147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.24793388429752%\"\u003e\n \u003cp\u003e0.0001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eSignificant p-value \u0026lt; 0.05* and p-value \u0026lt; 0.01*\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMoreover, with the p-value of 0.0001, it can be concluded that there is a significant difference between the overall scores of control group and intervention group with 99% confidence interval (See Table3). Based on these findings, the utilization of standardized pre-briefing produces better overall competency performance on nurses during code blue simulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eComparison of the overall CCE scores between control and intervention group.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"19.74317817014446%\"\u003e\n \u003cp\u003eIndependent\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eT-test Results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"32.58426966292135%\"\u003e\n \u003cp\u003eControl Group\u003c/p\u003e\n \u003cp\u003en = 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"36.91813804173355%\"\u003e\n \u003cp\u003eExperimental Group\u003c/p\u003e\n \u003cp\u003en = 60\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.754414125200642%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"14.087759815242494%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.163972286374134%\"\u003e\n \u003cp\u003eStd. Dev.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.630484988452658%\"\u003e\n \u003cp\u003e(95% CI-L, CI- U)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.549653579676674%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.087759815242494%\"\u003e\n \u003cp\u003eStd. Dev.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.480369515011546%\"\u003e\n \u003cp\u003e(95% CI-L, CI \u0026ndash; U)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.74317817014446%\"\u003e\n \u003cp\u003eOverall Result\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.791332263242376%\"\u003e\n \u003cp\u003e5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.149277688603531%\"\u003e\n \u003cp\u003e3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.643659711075442%\"\u003e\n \u003cp\u003e(4.58,5.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.112359550561798%\"\u003e\n \u003cp\u003e9.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.791332263242376%\"\u003e\n \u003cp\u003e2.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.014446227929373%\"\u003e\n \u003cp\u003e(8.79, 10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.754414125200642%\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eSignificant p-value \u0026lt; 0.05* and p-value \u0026lt; 0.01*\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 showed the factors affecting the CCEI scores for those who were guided by the first\u0026nbsp;dimension of DASH during pre-briefing (the experimental group). Aside from the age, the years of experience also have a significant effect on the CCEI scores, with p-values of 0.0232 and 0.0239, respectively. Using all demographic profiles as independent variables, the age range of 40 to 50 years old and years of experience greater than 3 years produce the most significant results in CCEI scores during the code blue simulation among those who attended the pre-briefing. Both gender and area of specialization were not found to be significantly associated with the CCEI scores in the experimental group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eRegression analysis with the factors affecting the CCEI scores in the experimental group.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"601\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"27.69485903814262%\"\u003e\n \u003cp\u003eInstrument/Subscales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003eEstimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.5787728026534%\"\u003e\n \u003cp\u003eT-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"27.69485903814262%\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e-0.07827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.1962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.5787728026534%\"\u003e\n \u003cp\u003e-0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.6917\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"27.69485903814262%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.82861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.35315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.5787728026534%\"\u003e\n \u003cp\u003e2.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.0232*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"27.69485903814262%\"\u003e\n \u003cp\u003eYears of Experience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.83493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.35756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.5787728026534%\"\u003e\n \u003cp\u003e2.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.0239*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"27.69485903814262%\"\u003e\n \u003cp\u003eSpecialization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e-0.10882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.12221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.5787728026534%\"\u003e\n \u003cp\u003e-0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.24212271973466%\"\u003e\n \u003cp\u003e0.3777\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eSignificant p-value \u0026lt; 0.05* and p-value \u0026lt; 0.01*\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQualitative results.\u003c/strong\u003e A total of 15 nurses participated in the qualitative part of the study. Five themes were drawn from the analysis: (1) setting the tone; (2) reducing stress levels and improving confidence; (3) establishing a safe learning environment; (4) a positive impact on overall perceptions of pre-briefing; and (5) Expectation vs Reality. See table 5 for the emerged themes and examples of participants quotations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eThemes emerged from the Qualitative data analysis\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"599\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.42809364548495%\"\u003e\n \u003cp\u003eThemes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"71.57190635451505%\"\u003e\n \u003cp\u003eTranscripts quota\u0026rsquo;s examples\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.42809364548495%\"\u003e\n \u003cp\u003eTheme 1:\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSetting the tone\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"71.57190635451505%\"\u003e\n \u003cp\u003e\u0026ldquo;With the pre-briefing, it gives you a clear picture and a calming effect and know I will do it one by one and I will be corrected only when necessary. There is also confidentiality. In normal code drill, there are corrections immediately and you will be lost. These things in pre-briefing are effective\u0026rdquo;.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.42809364548495%\"\u003e\n \u003cp\u003eTheme 2:\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReducing stress levels and improving confidence\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"71.57190635451505%\"\u003e\n \u003cp\u003e\u0026ldquo;The pre-briefing helped me reduced my stress level. It paved the way for better performance in code blue simulations\u0026rdquo;.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.42809364548495%\"\u003e\n \u003cp\u003eTheme 3:\u003c/p\u003e\n \u003cp\u003eEstablishing a safe environment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"71.57190635451505%\"\u003e\n \u003cp\u003e\u0026ldquo;I felt comfortable because of the pre-briefing. I was a little bit nervous, but the pre-briefing helped. I did not feel being judged during the simulation and I was acceptant of any corrections because I know there\u0026rsquo;s always a room for improvement\u0026rdquo;.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.42809364548495%\"\u003e\n \u003cp\u003eTheme 4:\u003c/p\u003e\n \u003cp\u003ePositive impact on overall perceptions on pre-briefing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"71.57190635451505%\"\u003e\n \u003cp\u003e\u0026ldquo;I will be happy to attend simulations with pre-briefing. We are human and we make mistakes. Without establishing that in pre-briefing, we\u0026rsquo;ll be ashamed of our performance and excuse ourselves from future drills. For me, it was a good experience\u0026rdquo;.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.42809364548495%\"\u003e\n \u003cp\u003eTheme 4:\u003c/p\u003e\n \u003cp\u003eExpectation vs Reality \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"71.57190635451505%\"\u003e\n \u003cp\u003e\u0026ldquo;In a real patient you will be able to see outcomes of your intervention, either good or bad, and you will be able to react to it spontaneously. However, in a simulation you won\u0026rsquo;t see the outcomes because it is just a dummy\u0026rdquo;.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFive themes were exposed after the examination of open codes. The first theme is \u0026quot;\u003cem\u003eSetting the Tone\u003c/em\u003e.\u0026quot; The participants mentioned the improvement of the simulation process as a result of pre-briefing. Most of the nurses described that with pre-briefing, expectations were clearer, and rapport was seamlessly established. These improvements in the process are essential to both the nurses and the simulation team in establishing connection and communication, as they were coming from different departments. The intervention group also appreciated the discussion of the scenario which was well-explained which improved their focus towards the simulation process. Notable quotes from the interview discussed that without pre-briefing there will be many obstacles, uncertainties, and lack of simulation orientation.\u003c/p\u003e\n\u003cp\u003eIn relation to stress levels, a theme emerged from the interview that showed that code blue simulation will be better with pre-briefing, as the intervention group explained that it reduced their stress levels, they gained better understanding, and pre-briefing leads to better nurse performance. The nurses in the study admit that they still feel some amount of stress and anxiety, but the increased awareness during the pre-briefing helps them think more critically as they formulate strategies for handling the scenario. The nurses became more prepared, cautious, and confident. They gained better recall of the steps and other details when performing their expected tasks. In comparison to simulation without pre-briefing, nurses encounter difficulties, recognize weaknesses, fail to recall, and lose focus.\u003c/p\u003e\n\u003cp\u003eAnother theme that has emerged is that \u003cem\u003epre-briefing establishes a safe environment\u003c/em\u003e among nurses, and it pertains to how learning experiences are improved with pre-briefing. With pre-briefing, the simulation team was more approachable to the intervention group. The nurses felt valued and were encouraged to openly discuss their feelings and thoughts. They were able to raise concerns and seek clarifications, which improved their understanding. The simulation team also shared reminders and were reinforcing the nurses. The overall experience with pre-briefing created a comfortable environment for learning, which is attractive to the nurses. Unlike with no pre-briefing, nurses were anxious and nervous, and encounters fear of being corrected or receiving failing scores especially for experienced nurses.\u003c/p\u003e\n\u003cp\u003eThe fourth theme, \u003cem\u003eImpact on Overall Perceptions of Pre-briefing\u003c/em\u003e, explains the thoughts of the nurses towards pre-briefing as a beneficial adjunct to simulation in enhancing competency. The nurses viewed the pre-briefing as an opportunity to learn. Hence, nurses suggested having more time for practice and taking breaks during pre-briefing. In doing so, nurses can gain mastery over the procedures even during the pre-briefing period. Adding more time will encourage more opportunities to fix concerns about the simulation before engaging. The intervention group discussed that code blue situation is not often encountered and described as rare but an essential competency for nurses. In fact, because code blue is viewed as not being an everyday experience, they may forget what they\u0026rsquo;ve learned in the simulation. It will become usual and simple for the nurses to perform the intervention using simulation on a regular basis, especially during outbreaks like the COVID-19 pandemic, which demands nurses be ready and efficient to engage in such emergency circumstances. The intervention group recommended that nurses should join frequent simulation with pre-briefing to reduce hesitancies in performing the tasks in real situations.\u003c/p\u003e\n\u003cp\u003eThe last theme that emerged (\u003cem\u003eexpectation vs. reality\u003c/em\u003e) is that results in simulation are not the same as in real life. Despite establishing a fiction contract in pre-briefing, nurses view the entire process of pre-briefing and simulation as distinct from real situations. The responses to this theme by the respondents are varied but meaningful, as the intervention can improve the experience of nurses in code blue simulations both in fiction and in real-life situations. The materials used and the time to accomplish tasks like reviving the patient are not similar in real code blue situations. Thus, nurses will likely perform better during simulation than in real code-blue situations. The code blue simulation remains fictional to others, as nobody will be supporting or evaluating nurses by scoring their performance. Others were able to perform the procedures well in real-life code blue situations despite the fact that the situation was fictional due to the pre-briefing.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePre-briefing has been a vital step in arriving at better outcomes in different fields; it sets the tone for an upcoming learning experience (Hughes \u0026amp; Hughes, 2022). Strategies are being developed and tested as organizations try to arrive at productive outcomes and significant results in various process dynamics, such as training and simulation exercises. Researchers and educators continue to explore many aspects of DASH as an integral part of simulation, and while it is mostly used to aid faculty in developing debriefing skills, the findings of this study can serve as a reference for future research (Rudolph et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In implementing a pre-briefing approach in simulation activities, a qualified and properly trained instructor should ensure that the tools to be implemented are reliable and appropriate. He is the one responsible for formulating the pre-briefing tool that will fit the needs of the participants, or else desired outcomes will not be met, and the experience gained in the simulation will negate quality outcomes and engagement. This study is similar to that of Page-Cutrara (2016). While the former designed their pre-briefing to encourage reflection before action among nursing students, this study was based on the first element of DASH, in which instructors assist participants in clarifying expectations, becoming familiar with the simulation setting, and creating a safe learning environment among experienced nurses. There is a lack of literature on the impact of pre-briefing on the competence and learning experience of experienced nurses. The study was able to evaluate the first element of DASH as a pre-briefing guide and its impact on the experienced nurse\u0026rsquo;s competence and learning experience in a code blue simulation.\u003c/p\u003e \u003cp\u003eA total of 120 nurses participated in the quasi-experimental part of the study, and 15 nurses from the experimental group were interviewed for the phenomenological part of the study. Interestingly, the majority of the participants are male nurses (90.83%). Despite the fact that nursing has been dominated by the female gender, there has been a slow rise in the number of male nurses in the past 10 years (Younas et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Nursing in Qatar and other Middle East countries faces challenges because of the negative conception of nursing and cultural roles of women (Alsadaan et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Levers, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tieleman \u0026amp; Cable, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While this warrants further investigation, the relationship between gender and competency performance cannot be established due to the huge disparity between male and female nurses in this study.\u003c/p\u003e \u003cp\u003eThis study shows that utilizing the first element of DASH as a pre-briefing guide before a code blue simulation improves competency performance and the learning experience among experienced nurses. Experienced nurses are trained on how to respond to code blue situations; it has been a part of their continuing education and they are expected to have completed Basic Life Support (BLS) and Advanced Cardiopulmonary Life Support (ACLS) training. Despite that, a significant difference is found in all aspects of the nurses\u0026rsquo; competency performance (assessment, communication, clinical judgment, and patient safety). This study shows that nurses who participated in the pre-briefing utilizing the first element of DASH performed far better than those who did not. Nurses assigned to the ER and ICU are more exposed to code blue situations than nurses assigned to the outpatient setting, medical unit, or OR, giving them an advantage in code blue simulation. However, the findings of this study show that competency performance and learning experience improve regardless of exposure to real-life Code Blue situations.\u003c/p\u003e \u003cp\u003ePre-briefing creates a safe environment but does not completely eliminate anxiety; participants will still experience anxiety in relation to the degree of work that needs to be performed. Being oriented from the start is an advantage; the idea of having a picture of what lies ahead permeates an avenue of security as it draws the line of expectations. Yet this is not an assurance that participants will render a smooth transition in the said activity; the setting and nature of the task will always play a significant role in the simulation and outcome measures. Being oriented from the beginning is an advantage; the idea of having a picture of what lies ahead permeates an avenue of security as it draws the line of expectations. Yet, this is not an assurance that participants will render a smooth transition in the said activity; the setting and nature of the task will always play a significant role in the simulation and outcome measures.\u003c/p\u003e \u003cp\u003eDespite the fictional contract in pre-briefing, experienced nurses find it difficult to see reality or find satisfaction in simulation. In any simulation, coherent truths have priority over correspondences (Oatley, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). The feel and quality of the simulation can cast a veil of inauthenticity that may deter participants from achieving quality experiences and outcomes. Nurses with clinical experience will still find a lack of realism in simulation. People tend to develop preconceptions and biases toward certain situations that they deem untrue. Utilization of virtual reality or high-fidelity simulation improves satisfaction among nursing students or novice nurses (Basak et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Alconero-Camarero et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kang et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Instructors should try to devise methods to improve the quality of simulation programs where participants can experience a diverse simulation that can somewhat make it feel like a real-life scenario, especially for experienced nurses.\u003c/p\u003e \u003cp\u003ePre-briefing positively impacts trainings and simulation activities; the use of initial orientation through the use of handouts, face-to-face orientation, etc. facilitates better interaction and develops preparedness to promise positive outcomes (Lioce et al., 2020). The outcomes that we have gathered in the study based on the application of the first element of DASH as a pre-briefing method are positive and significant in improving learner engagement, experience, and competence. Applying it in hospital institutions whenever they conduct simulation activities would provide a great benefit to their staff and the team as a whole. Additionally, this pre-briefing tool can also be further developed in certain variations that can cater to identified needs and areas of opportunity, especially when trying to improve performance and competence in dealing with code blue situations.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eThis study poses many limitations in terms of applicability and generalizability. The findings of the study may only be true for the research locale where the participants were taken from and may not be true for other settings. Since nurse-participants were selected via non-probability sampling techniques, it should be emphasized that the results should not be generalized for all nurses. Ratings derived were given by raters based on their perceived judgment. Such bias may not be totally avoided, even though the researcher tried to be as objective as possible. Since only nominal-level data were collected, analysis was limited to the use of nonparametric statistics. The demographic profile of respondents was collected but not utilized to interpret the results of the study. The researcher tried to control aspects of the study, but it may have been possible that extraneous variables (internal or external), such as personal factors from participants and raters, affected the results of the study. Furthermore, theme analysis was used for qualitative data analyses for nurses who only received the standardized pre-briefing. Nurses who received the traditional pre-briefing were excluded from the qualitative data analysis. The researcher and author acknowledge that interpretation is based only on information gathered from transcripts. Due to these limitations, the author/researcher suggests conducting future similar studies, especially on areas or other factors not explored in this study.\u003c/p\u003e"},{"header":"Conclusion And Implications","content":"\u003cp\u003eIn code blue simulation, using the first element of DASH improves competency performance and learning experiences among experienced nurses. Regardless of experience and specialization, nurses who participated in pre-briefing had better CCEI scores. Furthermore, the impact on the overall perception of pre-briefing promotes learning and engagement among experienced nurses. Despite establishing a fictional contract and a safe learning environment, experienced nurses will still have anxiety, stress, and dissatisfaction with the realism of simulation. Pre-briefing positively impacts trainings and simulation activities; the use of initial orientation using handouts, face-to-face orientation, etc. facilitates better interaction and develops preparedness to promise positive outcomes (Lioce et al., 2020). The outcomes that we have gathered in the study based on the application of the first element of DASH as a pre-briefing method are positive and significant in improving learner engagement, experience, and competence. Applying it in hospital institutions whenever they conduct simulation activities would provide a great benefit to their staff and the team. Additionally, this pre-briefing tool can also be further developed in certain variations that can cater to identified needs and areas of opportunity, especially when trying to improve performance and competence in dealing with code blue situations. Multidisciplinary simulation activities could be suggested to encourage healthcare team collaboration, problem solving, comprehension, and confidence.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe local Institutional Review Board at the Medical Research Center in Hamad Medical Corporation (Doha, Qatar) (IRB-MRC) approved the study (MRC-01-20-042). Informed consent was obtained from all participants. All methods were carried out in accordance with relevant guidelines and regulations or Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Medical Research Center at Hamad Medical Corporation (MRC-01-20-042).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRCV: Conceptualization. RCV, AJN, JPS, EAH, KCP, RGM, SAM, NFA, JPA, JPZ, AZK, JCP, AAA: Research design, Data collection, Analysis, Literature search, Manuscript preparation. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the nurses and midwifes who participated in the study. The publication of this article was funded by the Qatar National Library.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbou Hashish, E. A., \u0026amp; Bajbeir, E. F. (2022). The Effect of Managerial and Leadership Training and Simulation on Senior Nursing Students\u0026rsquo; Career Planning and Self-Efficacy. \u003cem\u003eSAGE Open Nursing\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e, 23779608221127952. \u003c/li\u003e\n\u003cli\u003eAlconero-Camarero, A. R., Sarabia-Cobo, C. 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The Educational Effects of a Pregnancy Simulation in Medical/Nursing Students and Professionals. \u003cem\u003eBMC medical education\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(1), 168. doi:10.1186/s12909-019-1589-8\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pre-briefing, Code Blue, Cardiac Arrest, Simulation, Competency Performance, Nurse Simulation, Debriefing Assessment for Simulation in Healthcare (DASH)","lastPublishedDoi":"10.21203/rs.3.rs-2481528/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2481528/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Simulation in healthcare is a growing teaching modality that allows undergraduate and graduate nurses to improve their clinical practice, communication skills, critical thinking, and team performance in a real-world clinical setting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim:\u0026nbsp;\u003c/strong\u003eThe aim of the study was to determine if significant associations exist in the groups (control and experimental), the impact on competency performance during a code blue simulation (cardiac arrests in adults), and the learning experiences of nurses when using the 1st element of Debriefing Assessment for Simulation in Healthcare (DASH) as the pre-briefing guide.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign:\u0026nbsp;\u003c/strong\u003eThis study employed a mixed-methods design for collecting quantitative and qualitative data. The quantitative portion was guided by a quasi-experimental design with a convenient sample of 120 nurses, while to uncover the meaning of the individual’s experience, a qualitative, phenomenological research design was used with a purposeful sample of 15 nurses. We utilized descriptive and inferential statistics for the quantitative data and phenomenological analysis for the qualitative data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e:\u0026nbsp;A total of N=120 nurses participated in the study, and 15 nurses from the experimental group were interviewed. There were 60 participants randomly selected for each of the control and experimental groups. The majority of participants in both the control group and the experimental group are males (90.83%). Most of the participants (98.33%) have more than 3 years of nursing experience. Regarding the specialty of nurses in the control group, an equal number were drawn from each of the five nursing specialties. Among the specialties of the nurses in the experimental groups are ED, OPD, CCU, MED-SURG, and PERI-OP. There was a statistically significant difference between the control and experimental groups in competency performance during the Code Blue simulation, p=0.00001. Aside from the age, the years of experience also have a significant effect on the CCEI scores, with p-values of 0.0232 and 0.0239, respectively, in the experimental group. No association was found between gender and specialization to competency performance. Five (5) themes were drawn from this study: (1) setting the tone; (2) reducing stress levels and improving confidence; (3) establishing a safe learning environment; (4) a positive impact on overall perceptions of pre-briefing; and (5) Expectation vs Reality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u0026nbsp;\u003c/strong\u003eUtilizing the 1\u003csup\u003est\u003c/sup\u003e element of DASH improves competency performance and learning experience among experienced nurses in code blue simulation. Regardless of experience and specialization, nurses who participated in pre-briefing have better CCEI scores. Furthermore, the impact on the overall perception about pre-briefing promotes learning and engagement among experienced nurses. Despite establishing fiction contract and a safe learning environment, experienced nurses will still have anxiety, stress, and dissatisfaction in the realism of simulation.\u003c/p\u003e","manuscriptTitle":"The Impact of Using DASH First Element as a Pre-Briefing Tool on Nurse Competency and Learning during Code Blue Simulation: A Mixed-Methods Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-23 23:07:29","doi":"10.21203/rs.3.rs-2481528/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"723d6c6f-59df-4d4b-b8bd-ec86d80f3027","owner":[],"postedDate":"January 23rd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-07-20T12:44:25+00:00","versionOfRecord":[],"versionCreatedAt":"2023-01-23 23:07:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2481528","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2481528","identity":"rs-2481528","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}