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A Conversational Model of Reflective Learning for Simulated Debriefing: Collaborative Design and Innovation Processes | BMC Medical Education

Practitioners must possess effective clinical reasoning skills to make appropriate, safe clinical decisions and avoid practice errors. Poorly developed clinical reasoning skills can compromise patient safety and delay care or treatment, especially in intensive care and emergency departments. Simulation-based training uses reflective learning conversations following a simulation as a debriefing method to develop clinical reasoning skills while maintaining patient safety. However, due to the multidimensional nature of clinical reasoning, the potential risk of cognitive overload, and the differential use of analytical (hypothetico-deductive) and non-analytical (intuitive) clinical reasoning processes by advanced and junior simulation participants, it is important to consider experience, abilities, factors related to the flow and volume of information, and case complexity to optimize clinical reasoning by engaging in group reflective learning conversations after the simulation as a debriefing method. Our goal is to describe the development of a model of post-simulation reflective learning dialogue that considers multiple factors that influence the achievement of clinical reasoning optimization.
A co-design working group (N = 18), consisting of physicians, nurses, researchers, educators, and patient representatives, collaborated through successive workshops to co-develop a post-simulation reflective learning dialogue model to debrief the simulation. The co-design working group developed the model through a theoretical and conceptual process and multi-phase peer review. The parallel integration of plus/minus assessment research and Bloom’s taxonomy is believed to optimize simulation participants’ clinical reasoning while participating in simulation activities. Content validity index (CVI) and content validity ratio (CVR) methods were used to establish face validity and content validity of the model.
A post-simulation reflective learning dialogue model was developed and tested. The model is supported by worked examples and scripting guidance. The face and content validity of the model were assessed and confirmed.
The new co-design model was created taking into account the skills and capabilities of the various modeling participants, the flow and volume of information, and the complexity of the modeling cases. These factors are thought to optimize clinical reasoning when participating in group simulation activities.
Clinical reasoning is considered the foundation of clinical practice in health care [ 1 , 2 ] and an important element of clinical competence [ 1 , 3 , 4 ]. It is a reflective process that practitioners use to identify and implement the most appropriate intervention for each clinical situation they encounter [ 5 , 6 ]. Clinical reasoning is described as a complex cognitive process that uses formal and informal thinking strategies to gather and analyze information about a patient, evaluate the importance of that information, and determine the value of alternative courses of action [ 7 , 8 ]. It depends on the ability to gather clues, process information, and understand the patient’s problem in order to take the right action for the right patient at the right time and for the right reason [9, 10].
All healthcare providers are faced with the need to make complex decisions in conditions of high uncertainty [11]. In critical care and emergency care practice, clinical situations and emergencies arise where immediate response and intervention are critical to saving lives and ensuring patient safety [12]. Poor clinical reasoning skills and competence in critical care practice are associated with higher rates of clinical errors, delays in care or treatment [13] and risks to patient safety [14,15,16]. To avoid practical errors, practitioners must be competent and have effective clinical reasoning skills to make safe and appropriate decisions [16, 17, 18]. The non-analytical (intuitive) reasoning process is the fast process favored by professional practitioners. In contrast, analytical (hypothetico-deductive) reasoning processes are inherently slower, more deliberate, and more often used by less experienced practitioners [2, 19, 20]. Given the complexity of the healthcare clinical environment and the potential risk of practice errors [14,15,16], simulation-based education (SBE) is often used to provide practitioners with opportunities to develop competency and clinical reasoning skills. safe environment and exposure to a variety of challenging cases while maintaining patient safety [21, 22, 23, 24].
The Society for Simulation in Health (SSH) defines simulation as “a technology that creates a situation or environment in which people experience representations of real-life events for the purpose of practice, training, evaluation, testing, or gaining understanding of human systems or behavior.” [23] Well-structured simulation sessions provide participants with the opportunity to immerse themselves in scenarios that simulate clinical situations while reducing safety risks [24,25] and practice clinical reasoning through targeted learning opportunities [21,24,26,27,28] SBE enhances field clinical experiences, exposing students to clinical experiences that they may not have experienced in actual patient care settings [24, 29]. This is a non-threatening, blame-free, supervised, safe, low-risk learning environment. It promotes the development of knowledge, clinical skills, abilities, critical thinking and clinical reasoning [22,29,30,31] and can help healthcare professionals overcome the emotional stress of a situation, thereby improving learning ability [22, 27, 28]. , 30, 32].
To support the effective development of clinical reasoning and decision-making skills through SBE, attention must be paid to the design, template, and structure of the post-simulation debriefing process [24, 33, 34, 35]. Post-simulation reflective learning conversations (RLC) were used as a debriefing technique to help participants reflect, explain actions, and harness the power of peer support and groupthink in the context of teamwork [ 32 , 33 , 36 ]. The use of group RLCs carries the potential risk of underdeveloped clinical reasoning, particularly in relation to the varying abilities and seniority levels of participants. The dual process model describes the multidimensional nature of clinical reasoning and differences in the propensity of senior practitioners to use analytical (hypothetico-deductive) reasoning processes and junior practitioners to use non-analytical (intuitive) reasoning processes [34, 37]. ]. These dual reasoning processes involve the challenge of adapting optimal reasoning processes to different situations, and it is unclear and controversial how to effectively use analytic and non-analytic methods when there are senior and junior participants in the same modeling group. High school and junior high school students of varying abilities and experience levels participate in simulation scenarios of varying complexity [34, 37]. The multidimensional nature of clinical reasoning is associated with a potential risk of underdeveloped clinical reasoning and cognitive overload, particularly when practitioners participate in group SBEs with varying case complexity and levels of seniority [38]. It is important to note that although there are a number of debriefing models using RLC, none of these models have been designed with a specific focus on the development of clinical reasoning skills, taking into account experience, competence, flow and volume of information, and modeling complexity factors [38]. ]. , 39]. All of this requires the development of a structured model that considers various contributions and influencing factors to optimize clinical reasoning, while incorporating post-simulation RLC as a reporting method. We describe a theoretically and conceptually driven process for the collaborative design and development of a post-simulation RLC. A model was developed to optimize clinical reasoning skills during participation in SBE, considering a wide range of facilitating and influencing factors to achieve optimized clinical reasoning development.
The RLC post-simulation model was developed collaboratively based on existing models and theories of clinical reasoning, reflective learning, education, and simulation. To jointly develop the model, a collaborative working group (N = 18) was formed, consisting of 10 intensive care nurses, one intensivist, and three representatives of previously hospitalized patients of varying levels, experience, and gender. One intensive care unit, 2 research assistants and 2 senior nurse educators. This co-design innovation is designed and developed through peer collaboration between stakeholders with real-world experience in healthcare, either healthcare professionals involved in the development of the proposed model or other stakeholders such as patients [40,41,42]. Including patient representatives in the co-design process can further add value to the process, as the ultimate goal of the program is to improve patient care and safety [43].
The working group conducted six 2-4 hour workshops to develop the structure, processes and content of the model. The workshop includes discussion, practice and simulation. Elements of the model are based on a range of evidence-based resources, models, theories and frameworks. These include: constructivist learning theory [44], the dual loop concept [37], the clinical reasoning loop [10], the appreciative inquiry (AI) method [45], and the reporting plus/delta method [46]. The model was collaboratively developed based on the International Nurses Association’s INACSL debriefing process standards for clinical and simulation education [36] and was combined with worked examples to create a self-explanatory model. The model was developed in four stages: preparation for reflective learning dialogue after the simulation, initiation of reflective learning dialogue, analysis/reflection and debriefing (Figure 1). The details of each stage are discussed below.
The preparatory stage of the model is designed to psychologically prepare participants for the next stage and increase their active participation and investment while ensuring psychological safety [36, 47]. This stage includes an introduction to the purpose and objectives; expected duration of RLC; expectations of the facilitator and participants during the RLC; site orientation and simulation setup; ensuring confidentiality in the learning environment, and increasing and enhancing psychological safety. The following representative responses from the co-design working group were considered during the pre-development phase of the RLC model. Participant 7: “As a primary care nurse practitioner, if I were participating in a simulation without the context of a scenario and older adults were present, I would likely avoid participating in the post-simulation conversation unless I felt that my psychological safety was being respected. and that I would avoid participating in conversations after the simulation. “Be protected and there will be no consequences.” Participant 4: “I believe that being focused and establishing ground rules early on will help learners after the simulation. Active participation in reflective learning conversations.”
The initial stages of the RLC model include exploring the participant’s feelings, describing the underlying processes and diagnosing the scenario, and listing the participant’s positive and negative experiences, but not analysis. The model at this stage is created in order to encourage candidates to be self- and task-oriented, as well as mentally prepare for in-depth analysis and in-depth reflection [24, 36]. The goal is to reduce the potential risk of cognitive overload [48], especially for those who are new to the topic of modeling and have no previous clinical experience with the skill/topic [49]. Asking participants to briefly describe the simulated case and make diagnostic recommendations will help the facilitator ensure that students in the group have a basic and general understanding of the case before moving on to the extended analysis/reflection phase. Additionally, inviting participants at this stage to share their feelings in simulated scenarios will help them overcome the emotional stress of the situation, thereby enhancing learning [24, 36]. Addressing emotional issues will also help the RLC facilitator understand how participants’ feelings affect individual and group performance, and this can be critically discussed during the reflection/analysis phase. The Plus/Delta method is built into this phase of the model as a preparatory and decisive step for the reflection/analysis phase [46]. Using the Plus/Delta approach, both participants and students can process/list their observations, feelings and experiences of the simulation, which can then be discussed point by point during the reflection/analysis phase of the model [46]. This will help participants achieve a metacognitive state through targeted and prioritized learning opportunities to optimize clinical reasoning [24, 48, 49]. The following representative responses from the co-design working group were considered during the initial development of the RLC model. Participant 2: “I think that as a patient who has previously been admitted to the ICU, we need to consider the feelings and emotions of the simulated students. I raise this issue because during my admission I observed high levels of stress and anxiety, especially among critical care practitioners. and emergency situations. This model must take into account the stress and emotions associated with simulating the experience.” Participant 16: “For me as a teacher, I find it very important to use the Plus/Delta approach so that students are encouraged to actively participate by mentioning the good things and needs they encountered during the simulation scenario. Areas for improvement.”
Although the previous stages of the model are critical, the analysis/reflection stage is the most important for achieving optimization of clinical reasoning. It is designed to provide advanced analysis/synthesis and in-depth analysis based on clinical experience, competencies, and impact of the topics modeled; RLC process and structure; the amount of information provided to avoid cognitive overload; effective use of reflective questions. methods for achieving learner-centered and active learning. At this point, clinical experience and familiarity with simulation topics are divided into three parts to accommodate different levels of experience and ability: first: no previous clinical professional experience/no previous exposure to simulation topics, second: clinical professional experience, knowledge and skills/none. previous exposure to modeling topics. Third: Clinical professional experience, knowledge and skills. Professional/previous exposure to modeling topics. The classification is done to accommodate the needs of people with different experiences and ability levels within the same group, thereby balancing the tendency of less experienced practitioners to use analytical reasoning with the tendency of more experienced practitioners to use non-analytic reasoning skills [19, 20, 34]. , 37]. The RLC process was structured around the clinical reasoning cycle [10], the reflective modeling framework [47], and experiential learning theory [50]. This is achieved through a number of processes: interpretation, differentiation, communication, inference and synthesis.
To avoid cognitive overload, promoting a learner-centered and reflective speaking process with sufficient time and opportunities for participants to reflect, analyze, and synthesize to achieve self-confidence was considered. Cognitive processes during RLC are addressed through consolidation, confirmation, shaping, and consolidation processes based on the double-loop framework [37] and cognitive load theory [48]. Having a structured dialogue process and allowing sufficient time for reflection, taking into account both experienced and inexperienced participants, will reduce the potential risk of cognitive load, especially in complex simulations with varying prior experiences, exposures and ability levels of participants. After the scene. The model’s reflective questioning technique is based on Bloom’s taxonomic model [51] and appreciative inquiry (AI) methods [45], in which the modeled facilitator approaches the subject in a step-by-step, Socratic, and reflective manner. Ask questions, starting with knowledge-based questions. and addressing skills and issues related to reasoning. This questioning technique will improve the optimization of clinical reasoning by encouraging active participant participation and progressive thinking with less risk of cognitive overload. The following representative responses from the co-design working group were considered during the analysis/reflection phase of RLC model development. Participant 13: “To avoid cognitive overload, we need to consider the amount and flow of information when engaging in post-simulation learning conversations, and to do this, I think it is critical to give students enough time to reflect and start with the basics. Knowledge. initiates conversations and skills, then moves to higher levels of knowledge and skills to achieve metacognition.” Participant 9: “I strongly believe that questioning methods using Appreciative Inquiry (AI) techniques and reflective questioning using Bloom’s Taxonomy model will promote active learning and learner-centeredness while reducing the potential for risk of cognitive overload.” The debriefing phase of the model aims to summarize the learning points raised during the RLC and ensure that the learning objectives are realized. Participant 8: “It is very important that both the learner and facilitator agree on the most important key ideas and key aspects to consider when moving into practice.”
Ethical approval was obtained under protocol numbers (MRC-01-22-117) and (HSK/PGR/UH/04728). The model was tested in three professional intensive care simulation courses to evaluate the usability and practicality of the model. The face validity of the model was assessed by a co-design working group (N = 18) and educational experts serving as educational directors (N = 6) to correct issues related to appearance, grammar, and process. After face validity, content validity was determined by senior nurse educators (N = 6) who were certified by the American Nurses Credentialing Center (ANCC) and served as educational planners, and (N = 6) who had more than 10 years of education and teaching experience. Work Experience The assessment was conducted by educational directors (N = 6). Modeling experience. Content validity was determined using the Content Validity Ratio (CVR) and the Content Validity Index (CVI). The Lawshe method [52] was used to estimate CVI, and the method of Waltz and Bausell [53] was used to estimate CVR. CVR projects are necessary, useful, but not necessary or optional. The CVI is scored on a four-point scale based on relevance, simplicity, and clarity, with 1 = not relevant, 2 = somewhat relevant, 3 = relevant, and 4 = very relevant. After verifying the face and content validity, in addition to the practical workshops, orientation and orientation sessions were conducted for teachers who will use the model.
The work group was able to develop and test a post-simulation RLC model to optimize clinical reasoning skills during participation in SBE in intensive care units (Figures 1, 2, and 3). CVR = 1.00, CVI = 1.00, reflecting appropriate face and content validity [52, 53].
The model was created for group SBE, where exciting and challenging scenarios are used for participants with the same or different levels of experience, knowledge and seniority. The RLC conceptual model was developed according to INACSL flight simulation analysis standards [36] and is learner-centered and self-explanatory, including worked examples (Figures 1, 2 and 3). The model was purposefully developed and divided into four stages to meet modeling standards: starting with briefing, followed by reflective analysis/synthesis, and ending with information and summary. To avoid the potential risk of cognitive overload, each stage of the model is purposefully designed as a prerequisite for the next stage [34].
The influence of seniority and group harmony factors on participation in RLC has not been previously studied [38]. Taking into account the practical concepts of double loop and cognitive overload theory in simulation practice [34, 37], it is important to consider that participating in group SBE with different experiences and ability levels of participants in the same simulation group is a challenge. Neglect of information volume, flow and structure of learning, as well as the simultaneous use of fast and slow cognitive processes by both high school and junior high school students pose a potential risk of cognitive overload [18, 38, 46]. These factors were taken into account when developing the RLC model to avoid underdeveloped and/or suboptimal clinical reasoning [18, 38]. It is important to take into account that conducting RLC with different levels of seniority and competence causes a dominance effect among senior participants. This occurs because advanced participants tend to avoid learning basic concepts, which is critical for younger participants to achieve metacognition and enter higher-level thinking and reasoning processes [38, 47]. The RLC model is designed to engage senior and junior nurses through appreciative inquiry and the delta approach [45, 46, 51]. Using these methods, the views of senior and junior participants with varying abilities and levels of experience will be presented item by item and discussed reflectively by the debriefing moderator and co-moderators [45, 51]. In addition to the input of the simulation participants, the debriefing facilitator adds their input to ensure that all collective observations comprehensively cover each learning moment, thereby enhancing metacognition to optimize clinical reasoning [10].
Information flow and learning structure using the RLC model are addressed through a systematic and multi-step process. This is to assist debriefing facilitators and ensure that each participant speaks clearly and confidently at each stage before moving on to the next stage. The moderator will be able to initiate reflective discussions in which all participants participate, and reach a point where participants of varying seniority and ability levels agree on best practices for each discussion point before moving on to the next [38]. Using this approach will help experienced and competent participants share their contributions/observations, while the contributions/observations of less experienced and competent participants will be assessed and discussed [38]. However, to achieve this goal, facilitators will have to face the challenge of balancing discussions and providing equal opportunities for senior and junior participants. To this end, the model survey methodology was purposefully developed using Bloom’s taxonomic model, which combines evaluative survey and additive/delta method [45, 46, 51]. Using these techniques and starting with knowledge and understanding of the focal questions/reflective discussions will encourage less experienced participants to participate and actively participate in the discussion, after which the facilitator will gradually move to a higher level of evaluation and synthesis of the questions/discussions in which both parties have to give Seniors and Juniors participants have an equal opportunity to participate based on their previous experience and experience with clinical skills or simulated scenarios. This approach will help less experienced participants actively participate and benefit from the experiences shared by more experienced participants as well as the input of the debriefing facilitator. On the other hand, the model is designed not only for SBEs with different participant abilities and experience levels, but also for SBE group participants with similar experience and ability levels. The model was designed to facilitate a smooth and systematic movement of the group from a focus on knowledge and understanding to a focus on synthesis and evaluation to achieve learning goals. The model structure and processes are designed to suit modeling groups of different and equal abilities and experience levels.
In addition, although SBE in healthcare in combination with RLC is used to develop clinical reasoning and competence in practitioners [22,30,38], however, relevant factors must be taken into account related to case complexity and potential risks of cognitive overload, especially when Participants involved SBE scenarios simulated highly complex, critically ill patients requiring immediate intervention and critical decision-making [2,18,37,38,47,48]. To this end, it is important to take into account the tendency of both experienced and less experienced participants to simultaneously switch between analytical and non-analytic reasoning systems when participating in SBE, and to establish an evidence-based approach that allows both older and younger students to actively participate in the learning process. Thus, the model was designed in such a way that, regardless of the complexity of the simulated case presented, the facilitator must ensure that aspects of the knowledge and background understanding of both senior and junior participants are first covered and then gradually and reflexively developed to facilitate analysis. synthesis and understanding. evaluative aspect. This will help younger students build and consolidate what they have learned, and help older students synthesize and develop new knowledge. This will meet the requirements for the reasoning process, taking into account the prior experience and abilities of each participant, and have a general format that addresses the tendency of high school and junior high school students to simultaneously move between analytical and nonanalytic reasoning systems, thereby ensuring optimization of clinical reasoning.
Additionally, simulation facilitators/debriefers may have difficulty mastering simulation debriefing skills. The use of cognitive debriefing scripts is believed to be effective in improving knowledge acquisition and behavioral skills of facilitators compared to those who do not use scripts [54]. Scenarios are a cognitive tool that can facilitate teachers’ modeling work and improve debriefing skills, especially for teachers who are still consolidating their debriefing experience [55]. achieve greater usability and develop user-friendly models. (Figure 2 and Figure 3).
The parallel integration of plus/delta, appreciative survey, and Bloom’s Taxonomy survey methods has not yet been addressed in currently available simulation analysis and guided reflection models. The integration of these methods highlights the innovation of the RLC model, in which these methods are integrated in a single format to achieve optimization of clinical reasoning and learner-centeredness. Medical educators may benefit from modeling group SBE using the RLC model to improve and optimize participants’ clinical reasoning abilities. The model’s scenarios can help educators master the process of reflective debriefing and strengthen their skills to become confident and competent debriefing facilitators.
SBE can include many different modalities and techniques, including but not limited to mannequin-based SBE, task simulators, patient simulators, standardized patients, virtual and augmented reality. Considering that reporting is one of the important modeling criteria, the simulated RLC model can be used as a reporting model when using these modes. Moreover, although the model was developed for the nursing discipline, it has potential for use in interprofessional healthcare SBE, highlighting the need for future research initiatives to test the RLC model for interprofessional education.
Development and evaluation of a post-simulation RLC model for nursing care in SBE intensive care units. Future evaluation/validation of the model is recommended to increase the generalizability of the model for use in other health care disciplines and interprofessional SBE.
The model was developed by a joint working group based on theory and concept. To improve the validity and generalizability of the model, the use of enhanced reliability measures for comparative studies may be considered in the future.
To minimize practice errors, practitioners must possess effective clinical reasoning skills to ensure safe and appropriate clinical decision making. Using SBE RLC as a debriefing technique promotes the development of knowledge and practical skills necessary to develop clinical reasoning. However, the multidimensional nature of clinical reasoning, related to prior experience and exposure, changes in ability, volume and flow of information, and the complexity of simulation scenarios, highlights the importance of developing post-simulation RLC models through which clinical reasoning can be actively and effectively implemented. skills. Ignoring these factors may result in underdeveloped and suboptimal clinical reasoning. The RLC model was developed to address these factors to optimize clinical reasoning when participating in group simulation activities. To achieve this goal, the model simultaneously integrates plus/minus evaluative inquiry and the use of Bloom’s taxonomy.
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Post time: Jan-08-2024