Clinical ethics consultants are required to provide specialized guidance, care, and support on ethics issues in healthcare settings. They need to develop a varied set of competencies ranging from clinical and ethics knowledge, critical thinking and decision-making, difficult conversation and conflict management skills, cultural competence, professionalism, adaptability, educational skills, and the ability to respectfully handle conflicting priorities in high-stakes situations. How to teach and learn ethics consultation skills is a nuanced and evolving process. It is often unexpectedly hindered not just by external pressures but by educators’ blind spots. These blind spots prevent them from detecting subtle but important inconsistencies between the care and curiosity they bring to their interactions with clients versus the way they treat their learners. These mismatches, though common and documented, can unintentionally weaken or threaten the quality and consistency of learning environments, limiting learners’ opportunities for deep, experiential growth. Drawing on the literature of behavior change, development, and simulation-based medical education, we identify three challenges to developing ethics consulting skills and the implications of these challenges for educational settings. The intention-versus-impact challenge highlights the mismatch between a consultant’s intentions—such as fostering dialogue or reducing moral distress—and the actual effects of their interventions, which may inhibit dialogue and exacerbate learners’ distress as they seek to learn new skills. The feedback challenge captures the common difficulty of giving and receiving feedback that is meaningful, honest, and timely yet does not harm; instead, it strengthens the relationship between ethics instructor and ethics consultation learner. Ethics consults often occur in emotionally charged contexts, and when these are replicated in training, ethics consultants-in-training may be reluctant or unable to take in critiques or reflect critically on their performance. In parallel, ethics instructors may struggle to “tell it like it is” with their learners in the same way they must with their ethics consult clients. Learners’ struggles to tolerate feedback and instructors’ struggles to lead conversations that are neither harsh nor judgment-hiding can limit opportunities for professional growth and quality assurance. Third, the walk-your-talk challenge highlights the mismatch between the ethics ideals consultants espouse and promote and how they enact these espoused values when they interact with ethics consultants-in-training. Institutional and interpersonal constraints ethics instructors face often make upholding the transparency, respect, and moral courage they espouse difficult to carry out in their teaching practice. We propose the use of reflective practice—the systematic examination of one’s actions, assumptions, and impacts—as a lens for exploring these challenges and identifying a pathway for faculty development. Applying the Learning Pathway Grid—a reflective practice tool—to illuminate how educators can surface and realign the invisible frames that shape their education behaviors. This approach strengthens educational integrity by helping ethics educators more consistently embody the values they teach, thereby fostering safer, more authentic, and more effective learning environments. The particular challenges for developing ethics consulting skills provide guidance for targeting reflective practice and faculty development efforts.

Introduction:Despite widespread investment in teamwork training, coordination failures persist in acute healthcare environments. Traditional team-based education tends to focus on large teams or isolated technical skills, often overlooking the smallest and arguably most critical unit of collaboration: the healthcare dyad. This study explored how expert healthcare dyads; two individuals working closely in high-stakes clinical settings developed and sustained collaborative expertise. Furthermore, we considered how their practices might have an impact on health professions education. Methods:We conducted a limited realist-perspective study comprising 10 semi-structured dyadic interviews (20 participants) of expert healthcare dyads in acute care settings. Participants were purposively sampled. Using template analysis, we began with a preliminary coding template based on relational coordination and distributed cognition, then iteratively revised it. We undertook deductive indexing using the template, followed by open coding of uncaptured data. Codes were charted, and our analytical framework constructed by clustering themes, and refining relationships. Interpretation was theory driven. Results:Using template analysis, we identified four core collaborative strategies: connectedness, situation awareness, physical communication, and reflective practice, all embedded in a foundation of trust. From these findings, we developed the Expert Dyad Framework (EDF), which characterizes relational and cognitive behaviors, comprising of collaborative micro-practices, essential to high-functioning clinical partnerships. Discussion:The expert dyad framework contributes a practice-informed conceptual tool for educators, highlighting dyadic collaboration as a developmental target for those conducting health professions' education. This study extends existing models of teamwork by focusing on the micro-interactions that underpin team performance.

Effective debriefings in simulation-based education require accurate observation of team interactions, yet facilitators face challenges due to cognitive load, observer bias, and the complexity of team dynamics. Generative artificial intelligence (AI) tools offer a potential means to support this process by analyzing verbal communication and providing structured feedback. This study explored how AI tools can contribute to teamwork observation and debriefing in immersive medical simulations. We conducted a qualitative, exploratory study using thematic analysis of simulation participants’ and debriefers’ experiences with AI-generated teamwork reports. Forty-one participants (anesthesia nurses, residents, and attendings) participated in immersive scenarios at the University Hospital Zurich simulation center. Verbal interactions were transcribed with AI-assisted speech recognition and analyzed using two large language model–based systems (Isaac and ChatGPT-4o) guided by a prompt based on the Team-FIRST framework. Structured reports were generated for each scenario and reviewed by four simulation experts. Semi-structured interviews captured learners’ perspectives on being observed by AI tools. A total of 26 AI-generated reports and 27 learner interviews were analyzed. Experts valued the detailed transcripts and illustrative quotes, which supported structured feedback and captured observations that might otherwise be missed. Limitations included inaccuracies in categorization, misattribution of speakers, overly generalized interpretations, and the absence of contextual or nonverbal information. Learners expressed openness and optimism about AI’s potential benefits: efficiency, objectivity, and enhanced perception, while also raising concerns about transparency, data protection, interpretation errors, and risks of overreliance. Both groups emphasized the necessity of human oversight. Generative AI tools can complement simulation debriefings by structuring communication data and highlighting teamwork patterns, supporting reflective practice. Current limitations highlight the need for multimodal approaches, refined prompting strategies, and integration with expert facilitation to ensure AI functions as a support tool rather than a replacement in simulation-based education. BASEC ID: Req-2024-01642.

Modern armed conflicts reveal increasingly complex injury patterns that challenge both civilian and military healthcare systems. In Switzerland, exposure to such injuries is limited. For a planned multicenter, high-fidelity, in-situ simulation-based study assessing trauma care performance across both military and civilian prehospital and clinical teams, a standardized and validated evaluation tool is required. The current study was designed to develop a consensus-based performance assessment tool/framework for evaluating the management of complex combat trauma, integrating civilian and military standards of care. A structured consensus process was conducted, combining an initial nominal group technique with a multi-round Delphi process. Fourteen experts from military medicine, emergency medicine, anesthesiology, and trauma surgery participated. Assessment items were iteratively refined until predefined consensus criteria were achieved. Consensus was reached after five Delphi rounds. The evaluation tool includes 35 items covering key domains such as prioritization of interventions, procedural quality, adherence to trauma principles, and time to critical actions. Initial differences between civilian and military perspectives—particularly regarding cervical spine immobilization, neurological assessment, coagulation management, and fluid resuscitation—were identified and resolved through the consensus process. The results of this Delphi-based evaluation framework highlight both areas of consensus and ongoing controversy in modern combat trauma care. Differences between civilian and military perspectives are largely driven by divergent injury patterns, resources, and operational constraints. By explicitly incorporating these differences into a standardized evaluation tool, this study provides a robust framework for comparing performance across different levels of trauma care.

Teamwork is critical for patient safety. Simulation provides a well-established environment for training and studying teamwork. Yet, studying teamwork can be as challenging as teamwork as such, risking stagnation of teamwork simulation research and knowledge gain. This paper presents a methodological approach for investigating the impact of relevant, external team factors (e.g., sound, temperature) on team interaction, performance, and patient outcomes in healthcare settings. Using the example of the “Mozart Effect” [i.e., listening to Mozart's sonata in D Major (KV 448) enhances spatial-temporal reasoning in humans] we introduce a team theory-based, methodological approach for guiding research on external-level impact on team interaction, performance, and patient outcomes. By providing this methodological framework, particularly for novice team researchers, we aim to stimulate future team research in simulation in healthcare to advance science, training, and patient care.

INTRODUCTION:Collaborative behaviours in acute care remain inconsistent despite substantial educational investment. Teamwork training often focuses on larger groups, overlooking dyads; the smallest collaborative unit. This study examines high-performing tennis doubles teams and expert medical dyads to identify collaborative behaviours that may inform medical education. METHODS:Using a limited realist perspective approach, we conducted 15 semi-structured interviews with 30 participants: 20 clinicians working in acute care dyads and 10 elite tennis doubles players. Participants were purposively sampled. Template analysis, guided by relational coordination and distributed cognition frameworks, was applied to explore how dyads coordinate and collaborate. RESULTS:Six collaborative dimensions were identified across both domains: trust, connectedness, shared goals, situation awareness, physical communication, and reflective practice with varying enactment strategies. Tennis dyads developed connectedness through repeated practice, psychological safety, co-regulation, error normalisation, and emotional trust. Medical dyads emphasised technical trust and task coordination, with limited opportunities for rehearsal, informal feedback, or relational engagement, often due to workload pressures and shifting schedules. DISCUSSION:While collaborative dimensions are shared, tennis dyads draw on a broader behavioural repertoire. These findings highlight opportunities to enhance medical education by integrating dyad-focused training that explicitly develops relational competence in simulation, debriefing, and workplace learning.

BACKGROUND:Routine clinical debriefings (RCDs) have been shown to improve communication, team reflexivity, and safety in clinical settings. When combined with incident reports (IRs), RCDs offer a potential tool for enhancing quality improvement frameworks. This study aimed to identify and compare healthcare safety-related information captured through RCDs and IRs in a Belgian emergency department operating across two distinct facilities. METHODS:This study employed a quasi-mixed-method design with a monostrand conversion approach. Information was collected from 90 RCDs and 263 IRs. Data were analyzed using two frameworks: the World Health Organization's Incident Report Classification Grid and the Debriefing and Organizational Lessons Learned Grid. RESULTS:The findings revealed significant differences in the types of information captured by RCDs and IRs. RCDs predominantly highlighted teamwork, internal organization, and procedural issues, while IRs focused more on care processes, patient concerns, and patient flow. These complementary insights demonstrate the value of integrating RCDs and IRs to create a comprehensive understanding of patient and clinician safety. CONCLUSIONS:This study highlights the complementary nature of RCDs and IRs in addressing healthcare safety. RCDs foster team reflexivity and promote open discussions about systemic challenges, directly improving team cohesion, resilience, and learning. Combining RCDs and IRs provides actionable insights for enhancing safety and driving organizational improvements.

BackgroundIn response to the coronavirus pandemic, hospitals worldwide implemented simulation-based training to help healthcare providers (HCPs) adapt to revised protocols for airway management in patients with infectious coronavirus disease 2019 (COVID-19). We conducted a systematic review of simulation-based studies on airway management in COVID-19 patients, with the aim of analyzing the findings of these studies and consolidating evidence-based recommendations to optimize responses to possible future pandemics.MethodsWe performed a systematic literature search of PubMed, Embase, Medline, and the Cochrane Library on 25 August 2022. As different studies measured different outcomes (e.g., only confidence, only knowledge, or both) in different ways, a random-effects model was used for meta-analysis and change scores were calculated.ResultsThe systematic review included 20 studies after screening 141 articles. The meta-analysis revealed significant improvements in participants' confidence and knowledge after simulation training, as evidenced by negative standardized mean differences (SMDs, Cohen's d). Sensitivity analysis confirmed that the results were robust across various correlation estimates. However, there was a high risk of publication bias, as funnel plots showed asymmetry and studies fell outside the 95% confidence interval.ConclusionThis systematic review highlights the effectiveness of simulation training in improving healthcare providers' confidence and knowledge regarding airway management during pandemics. The findings underscore the positive impact of simulation-based education, as demonstrated by significant improvements from pre-training to post-training assessments. However, the observed publication bias suggests that additional high-quality, unbiased studies are necessary to strengthen the evidence base and inform future training programs for pandemic preparedness.Systematic review registrationPROSPERO, CRD42022293708.

The evidence base supporting the adoption of simulation in health care has not kept pace with the rapid growth of the field. Although there is a growing body of research in health care simulation, many published studies describe small-scaled, underpowered projects with insufficient methodological rigor to inform our understanding of simulation. This problem is indicative of a larger challenge: the lack of focused, cohesive programs of research designed to advance the science of simulation. The METRICS framework is a model of scholarship that categorizes scholarship into 7 intersecting domains: Metascholarship, Evaluation, Translation, Research, Innovation, Conceptual, and Synthesis. In this article, we aim to explore how the METRICS framework can serve as a roadmap for researchers to develop cohesive simulation research programs. We also describe how the METRICS framework applies to existing institutional and network-based programs of health care simulation research and discuss future implications for the global health care simulation community.

Background Effective debriefings in simulation-based education require accurate observation of team interactions, yet facilitators face challenges due to cognitive load, observer bias, and the complexity of team dynamics. Generative artificial intelligence (AI) offers a potential means to support this process by analyzing verbal communication and providing structured feedback. This study explored how AI can contribute to teamwork observation and debriefing in high-fidelity medical simulations. Methods We conducted a qualitative, exploratory study using thematic analysis of simulation participants’ and debriefers’ experiences with AI-generated teamwork reports. Forty-one participants (anesthesia nurses, residents, and attendings) participated in high-fidelity scenarios at the University Hospital Zurich simulation center. Verbal interactions were transcribed with AI-assisted speech recognition and analyzed using two large language model–based systems (Isaac and ChatGPT-4o) guided by a prompt based on the Team-FIRST framework. Structured reports were generated for each scenario and reviewed by four experienced debriefers. Semi-structured interviews captured learners’ perspectives on being observed by AI. Results A total of 26 AI-generated reports and 27 learner interviews were analyzed. Debriefers valued the detailed transcripts and illustrative quotes, which supported structured feedback and captured observations that might otherwise be missed. Limitations included inaccuracies in categorization, misattribution of speakers, overly generalized interpretations, and the absence of contextual or nonverbal information. Learners expressed openness and optimism about AI’s potential benefits: efficiency, objectivity, and enhanced perception, while also raising concerns about transparency, data protection, interpretation errors, and risks of overreliance. Both groups emphasized the necessity of human oversight. Conclusion Generative AI can complement simulation debriefings by structuring communication data and highlighting teamwork patterns, thereby supporting reflective practice. Current limitations highlight the need for multimodal approaches, refined prompting strategies, and integration with expert facilitation to ensure AI functions as a support tool rather than a replacement in simulation-based education. Trial Registration BASEC ID: Req-2024-01642.

Objectives Little is known about medical students’ speak-up barriers upon recognizing or becoming aware of risky or deficient actions of others. Improving our knowledge on these helps in preparing student to function in actual health care organizations. The aim was to examine medical students' perceived reasons for silence in respect to different speak-up situations (i.e., vignette content) and to test if vignette difficulty had an effect on reasons indicated. Methods This study was a randomized, controlled, single-blind trial, with text-based vignettes to investigate speak-up barriers. Vignette contents described speak-up situations that varied systematically with respect to speak up barrier (i.e., environmental norm, uncertainty, hierarchy) and difficulty (i.e., easy, difficult). For each vignette, participants indicated which speak-up barriers they regarded as important. Descriptive analysis was performed for the study population, the numbers of barriers perceived and rating of vignette difficulty. Logistic regression analysis was used to examine the association between barriers perceived and vignette contents, designed vignette difficulty and subjectively rated vignette difficulty. Results A total of 265 students were included. The response rate was 100%. Different barriers were relevant for the different vignettes and varied in a consistent way with the theme of the vignette. Significantly more speak-up barriers were indicated for participants with the difficult version for vignette 1 (not an environmental norm) and vignette 3 (hierarchy) with odds ratio (OR) = 1.52 and 95% confidence interval (95% CI: 1.33–1.73) and OR = 1.25 (95% CI: 1.09–1.44). For (OR) estimates, confidence intervals were rather large. Conclusions Perceived barriers for speak-up vary consistently with the characteristics of the situation and more barriers preventing speak up were related to the difficult versions of the vignettes.

BackgroundSimulation has become a staple in the training of healthcare professionals with accumulating evidence on its effectiveness. However, guidelines for optimal methods of simulation training do not currently exist.MethodsSystematic reviews of the literature on 16 identified key questions were conducted and expert panel consensus recommendations determined using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology.ObjectiveThese evidence-based guidelines from the Society for Simulation in Healthcare intend to support healthcare professionals in decisions on the most effective methods for simulation training in healthcareResultsTwenty recommendations on 16 questions were determined using GRADE. Four expert recommendations were also provided.ConclusionsThe first evidence-based guidelines for simulation training are provided to guide instructors and learners on the most effective use of simulation in healthcare.

BackgroundDebriefing enhances team learning, performance, and patient safety. Despite its benefits, it’s underused. To address this, we developed an evidence-based debriefing app.MethodsThis pilot study, conducted at a Swiss hospital, evaluated team performance during two anesthesia inductions using the Team Performance Scale (TPS). Following the first induction, teams engaged with the Zurich Debriefing App, with debriefing sessions meticulously recorded for subsequent evaluation. To mitigate bias, raters underwent comprehensive TPS training. The debriefings were analyzed through the DE-CODE framework. We utilized paired t-tests to examine performance improvements and linear regressions to assess the impact of reflective statements on performance, moderated by psychological safety.ResultsTeam performance significantly improved from the first to the second induction (t (9) = −2.512, p = 0.033). Senior physicians’ (n = 8) reflective statements predicted post-assessment TPS scores (R2 = 0.732, p = 0.061), while consultants (n = 7) and nurse anesthetists (n = 10) did not. Interaction analysis revealed no moderation effects, but a main effect indicated the significance of senior physicians’ reflective statements.ConclusionThis pilot study confirms the efficacy of the evidence-based debriefing app in enhancing anesthesia team performance. Senior physicians’ reflective statements positively influenced performance; however, no moderation effects were observed. The study highlights the potential of debriefing apps to streamline and enhance team debriefing processes, with significant implications for improving clinical practice and patient safety. Further research is needed to validate these findings on a larger scale and optimize the integration of debriefing into routine clinical practice.

Background: : Training schoolchildren in basic life support ('Kids-Save-Lives' training) is widely believed to improve outcomes from out-of-hospital cardiac arrest. Numerous programmes have been launched, but to our knowledge, neither children nor schoolteachers have been directly involved in designing these courses. This is unfortunate, as it is well-known that children (as the target goup of training) learn differently from adults. We therefore sought to explore the view of schoolchildren and their teachers on the design of a 'Kids-Save-Lives' course. Methods: : We designed a state-of-the-art, 90-min BLS training and delivered it to all 13 classes of a secondary community school (children aged 12- 16). Directly after each training, we performed Video-Stimulated Recall (VSR) with 2 children and 2 schoolteachers. For VSR, we presented video sequences from defined sections of the training and related semi-structured questions to these sections. The interviews were audio-recorded, transcribed, and analysed using qualitative content analysis. Results: : Twenty-four children and 24 teachers participated in the VSR. The overall satisfaction with the training was very high. Participants especially appreciated the brief theoretical introduction using a video, the high practical involvement, and the final scenario. Children suggested the program could be improved by better linking the video to the children's world, increasing excitement and action, and limiting the group size in the final scenario. Teachers suggested incorporating more theoretical background, using terms and language more consistently, and better integrating the program into the school curriculum. Conclusions: : Although very satisfied with a state-of-the-art 'Kids-Save-Lives' training, children and teachers made important suggestions for improvement.

Healthcare debriefing is a cognitively demanding conversation after a simulation or clinical experience that promotes reflection, underpinned by psychological safety and attention to learner needs. The process of debriefing requires mental processing that engages both “fast” or unconscious thinking and “slow” intentional thinking to be able to navigate the conversation. “Fast” thinking has the potential to surface cognitive biases that impact reflection and may negatively influence debriefer behaviors, debriefing strategies, and debriefing foundations. As a result, negative cognitive biases risk undermining learning outcomes from debriefing conversations. As the use of healthcare simulation is expanding, the need for faculty development specific to the roles bias plays is imperative. In this article, we hope to build awareness about common cognitive biases that may present in debriefing conversations so debriefers have the chance to begin the hard work of identifying and attending to their potential detrimental impacts.

BackgroundDebriefings are central to effective learning in simulation-based medical education. However, educators often face challenges when conducting debriefings, which are further compounded by the lack of empirically derived knowledge on optimal debriefing processes. The goal of this study was to explore the technical feasibility of audio-based speaker diarization for automatically, objectively, and reliably measuring debriefing interaction patterns among debriefers and participants. Additionally, it aimed to investigate the ability to automatically create statistical analyses and visualizations, such as sociograms, solely from the audio recordings of debriefings among debriefers and participants.MethodsWe used a microphone to record the audio of debriefings conducted during simulation-based team training with third-year medical students. The debriefings were led by two healthcare simulation instructors. We processed the recorded audio file using speaker diarization machine learning algorithms and validated the results manually to showcase its accuracy. We selected two debriefings to compare the speaker diarization results between different sessions, aiming to demonstrate similarities and differences in interaction patterns.ResultsTen debriefings were analyzed, each lasting about 30 min. After data processing, the recorded data enabled speaker diarization, which in turn facilitated the automatic creation of visualized interaction patterns, such as sociograms. The findings and data visualizations demonstrated the technical feasibility of implementing audio-based visualizations of interaction patterns, with an average accuracy of 97.78%.We further analyzed two different debriefing cases to uncover similarities and differences between the sessions. By quantifying the response rate from participants, we were able to determine and quantify the level of interaction patterns triggered by instructors in each debriefing session. In one session, the debriefers triggered 28% of the feedback from students, while in the other session, this percentage increased to 36%.ConclusionOur results indicate that speaker diarization technology can be applied accurately and automatically to provide visualizations of debriefing interactions. This application can be beneficial for the development of simulation educator faculty. These visualizations can support instructors in facilitating and assessing debriefing sessions, ultimately enhancing learning outcomes in simulation-based healthcare education.

BackgroundViscoelastic hemostatic assays, such as rotational thromboelastometry (ROTEM) or thromboelastography, enable prompt diagnosis and accelerate targeted treatment. However, the complex interpretation of the results remains challenging. Visual Clot—a situation awareness-based visualization technology—was developed to assist clinicians in interpreting viscoelastic tests. ObjectiveFollowing a previous high-fidelity simulation study, we analyzed users’ perceptions of the technology, to identify its strengths and limitations from clinicians’ perspectives. MethodsThis is a mixed qualitative-quantitative study consisting of interviews and a survey. After solving coagulation scenarios using Visual Clot in high-fidelity simulations, we interviewed anesthesia personnel about the perceived advantages and disadvantages of the new tool. We used a template approach to identify dominant themes in interview responses. From these themes, we defined 5 statements, which were then rated on Likert scales in a questionnaire. ResultsWe interviewed 77 participants and 23 completed the survey. We identified 9 frequently mentioned topics by analyzing the interview responses. The most common themes were “positive design features,” “intuitive and easy to learn,” and “lack of a quantitative component.” In the survey, 21 respondents agreed that Visual Clot is easy to learn and 16 respondents stated that a combination of Visual Clot and ROTEM would help them manage complex hemostatic situations. ConclusionsA group of anesthesia care providers found Visual Clot well-designed, intuitive, and easy to learn. Participants highlighted its usefulness in emergencies, especially for clinicians inexperienced in coagulation management. However, the lack of quantitative information is an area for improvement.

Debriefings are an important part of healthcare, especially for acute care teams. They can increase the effectiveness of teams and promote open communication. At the same time, debriefings provide an opportunity for learning within teams. Both exceptional clinical events and challenging procedures, as well as new algorithms or operations in new vehicles or with new material, can provide a reason for a debriefing. It is useful to debrief clinical events without exceptional occurrences so that team members learn how debriefing works. Effective and outstanding points should always be discussed and a focus on errors should be placed in the background. Structure and setting of specific topics play a special role in debriefings. Informal and unstructured discussions should be avoided, as should digressing into topics that are less relevant to the situation at hand. At an organizational level, debriefings should be incorporated into the structures of acute teams and encouraged. Relevance should be created through content whereas reference to the assessment of individual employees should be avoided.

ABSTRACT:Debriefing is a critical component in most simulation experiences. With the growing number of debriefing concepts, approaches, and tools, we need to understand how to debrief most effectively because there is little empiric evidence to guide us in their use. This systematic review explores the current literature on debriefing in healthcare simulation education to understand the evidence behind practice and clarify gaps in the literature. The PICO question for this review was defined as "In healthcare providers [P], does the use of one debriefing or feedback intervention [I], compared to a different debriefing or feedback intervention [C], improve educational and clinical outcomes [O] in simulation-based education?" We included 70 studies in our final review and found that our current debriefing strategies, frameworks, and techniques are not based on robust empirical evidence. Based on this, we highlight future research needs.

In vielen Situationen im Rettungsdienst, sei es nach kritischen Einsätzen, bei der Anwendung neuer Techniken oder als Routine, kommt das Bedürfnis nach einer strukturierten Nachbesprechung (Debriefing) bei den beteiligten Personen auf. Dennoch wird dies verhältnismäßig wenig durchgeführt. Der folgende Beitrag zeigt Stärken und Schwächen und gibt auf Basis der bestehenden Evidenz zum Thema Hinweise zu Inhalt, Setting und der Durchführung.