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Abstract Background Meta-analyses indicate a high prevalence of burnout among medical students. Although studies have investigated different coping strategies and health interventions to prevent burnout, professional experience’s influence on burnout resilience as seldom been explored. Therefore, in our study we aimed to examine the self-efficacy’s mediating role in the relationship between past vocational training and burnout resilience. In the process, we also analysed the associations between study-related variables and burnout resilience. Methods In our cross-sectional study, we analysed the data of 2217 medical students at different stages of their university education (i.e. 1st, 3rd, 6th, 10th semester, and final year) at five medical faculties in Germany. The questionnaire included items addressing variables related to medical school, previous professional and academic qualifications, and validated instruments for measuring burnout and self-efficacy. Results The overall prevalence of burnout was 19.7%, as defined by high scores for emotional exhaustion and notable values in at least one of the other two dimensions (cynicism or academic efficacy). Higher levels for self-efficacy (p

BackgroundAlthough history taking is fundamental for diagnosing medical conditions, teaching and providing feedback on the skill can be challenging due to resource constraints. Virtual simulated patients and web-based chatbots have thus emerged as educational tools, with recent advancements in artificial intelligence (AI) such as large language models (LLMs) enhancing their realism and potential to provide feedback. ObjectiveIn our study, we aimed to evaluate the effectiveness of a Generative Pretrained Transformer (GPT) 4 model to provide structured feedback on medical students’ performance in history taking with a simulated patient. MethodsWe conducted a prospective study involving medical students performing history taking with a GPT-powered chatbot. To that end, we designed a chatbot to simulate patients’ responses and provide immediate feedback on the comprehensiveness of the students’ history taking. Students’ interactions with the chatbot were analyzed, and feedback from the chatbot was compared with feedback from a human rater. We measured interrater reliability and performed a descriptive analysis to assess the quality of feedback. ResultsMost of the study’s participants were in their third year of medical school. A total of 1894 question-answer pairs from 106 conversations were included in our analysis. GPT-4’s role-play and responses were medically plausible in more than 99% of cases. Interrater reliability between GPT-4 and the human rater showed “almost perfect” agreement (Cohen κ=0.832). Less agreement (κ

Abstract Introduction The global trend of legalizing medical cannabis (MC) is on the rise. In Germany, physicians have prescribed MC at the expense of health insurers since 2017. However, the teaching on MC has been scant in medical training. This study investigates medical students’ attitudes and perceived competence regarding MC and evaluates how varying materials (videos/articles) impact their opinions. Methods Fourth-year medical students were invited to participate in the cross-sectional study. During an online session, students viewed a video featuring a patient with somatoform pain discussing her medical history, plus one of four randomly assigned MC-related materials (each an article and a video depicting a positive or negative perspective on MC). Students’ opinions were measured at the beginning [T0] and the end of the course [T1] using a standardized questionnaire with a five-point Likert scale. We assessed the influence of the material on the students’ opinions using paired-sample t-tests. One-way analysis of variance and Tukey post-hoc tests were conducted to compare the four groups. Pearson correlations assessed correlations. Results 150 students participated in the course, the response rate being 75.3% [T0] and 72.7% [T1]. At T0, students felt a little competent regarding MC therapy (M = 1.80 ± 0.82). At T1, students in groups 1 (positive video) and 3 (positive article) rated themselves as more capable in managing MC therapy $$ (\text{t}\left(28\right)=-3.816,\text{p}

Abstract BackgroundThe increasing importance of artificial intelligence (AI) in health care has generated a growing need for health care professionals to possess a comprehensive understanding of AI technologies, requiring an adaptation in medical education. ObjectiveThis paper explores stakeholder perceptions and expectations regarding AI in medicine and examines their potential impact on the medical curriculum. This study project aims to assess the AI experiences and awareness of different stakeholders and identify essential AI-related topics in medical education to define necessary competencies for students. MethodsThe empirical data were collected as part of the TüKITZMed project between August 2022 and March 2023, using a semistructured qualitative interview. These interviews were administered to a diverse group of stakeholders to explore their experiences and perspectives of AI in medicine. A qualitative content analysis of the collected data was conducted using MAXQDA software. ResultsSemistructured interviews were conducted with 38 participants (6 lecturers, 9 clinicians, 10 students, 6 AI experts, and 7 institutional stakeholders). The qualitative content analysis revealed 6 primary categories with a total of 24 subcategories to answer the research questions. The evaluation of the stakeholders’ statements revealed several commonalities and differences regarding their understanding of AI. Crucial identified AI themes based on the main categories were as follows: possible curriculum contents, skills, and competencies; programming skills; curriculum scope; and curriculum structure. ConclusionsThe analysis emphasizes integrating AI into medical curricula to ensure students’ proficiency in clinical applications. Standardized AI comprehension is crucial for defining and teaching relevant content. Considering diverse perspectives in implementation is essential to comprehensively define AI in the medical context, addressing gaps and facilitating effective solutions for future AI use in medical studies. The results provide insights into potential curriculum content and structure, including aspects of AI in medicine.

IntroductionInternational evidence strongly suggests that medical students are at high risk of mental health problems. This distress, which can be mediated by a variety of individual, interpersonal and contextual factors within the curriculum, can be mitigated by effective coping strategies and interventions. Central to this discourse is the recognition that the challenges of professional identity formation can contribute significantly to medical students' distress. The focus of our study is therefore to examine discrepancies in professional identities and role models in undergraduate medical education in relation to affective burden.MethodsMedical students at different stages of university education and high school graduates intending to study medicine were surveyed in a cross-sectional study. The study employed Osgood and Hofstätter's polarity profile to evaluate the self-image of participants, the image of an ideal and real physician, and their correlation with depression (PHQ-9) and anxiety (GAD-7).ResultsOut of the 1535 students recruited, 1169 (76.2%) participated in the study. Students rated their self-image as somewhere between a more critical real image of physicians and a more positive ideal image. Medical students at all training levels consistently rated the ideal image as remaining constant. Significant correlations were found between the professional role models of medical students and affective symptoms, particularly for the discrepancy between the ideal image of a physician and their self-image. Furthermore, 17% and nearly 15% reported significant symptoms of depression and anxiety, respectively.DiscussionOur study adds to the growing body of knowledge on professional identity formation in medicine and socialisation in the medical environment. The study highlights the importance of discrepancies between self-image and ideal image in the experience of depressive and anxiety symptoms. Primary prevention-oriented approaches should incorporate these findings to promote reflective competence in relation to professional role models and strengthen the resilience of upcoming physicians in medical training.

Abstract Background Surgical ward rounds are key element to point-of-care interprofessional postoperative treatment and technical and communicational aspects are relevant for the patient’s safety and satisfaction. Due to COVID-19 restrictions, the training opportunity of experiencing a face-to-face surgical ward round was massively hampered and thus, we developed a digital concept. This study aims to investigate the feasibility of video-transmitted ward rounds integrating surgical and communicational aspects with live streaming from wards. Further, medical students were asked for their satisfaction and their subjective learning success. Methods The proof-of-concept study consisted of self-reported subjective evaluation of competences in ward round skills. Qualitative feedback was collected to gain deeper insight and students’ empathy was rated by using the student version of the Jefferson Empathy Scale (JES). Results One hundred three medical students participated. The students were satisfied with the video-transmitted ward round (M = 3.54; SD = 1.22). In the subjective evaluation students’ ward round competencies rose significantly (p

BackgroundLarge language models such as GPT-4 (Generative Pre-trained Transformer 4) are being increasingly used in medicine and medical education. However, these models are prone to “hallucinations” (ie, outputs that seem convincing while being factually incorrect). It is currently unknown how these errors by large language models relate to the different cognitive levels defined in Bloom’s taxonomy. ObjectiveThis study aims to explore how GPT-4 performs in terms of Bloom’s taxonomy using psychosomatic medicine exam questions. MethodsWe used a large data set of psychosomatic medicine multiple-choice questions (N=307) with real-world results derived from medical school exams. GPT-4 answered the multiple-choice questions using 2 distinct prompt versions: detailed and short. The answers were analyzed using a quantitative approach and a qualitative approach. Focusing on incorrectly answered questions, we categorized reasoning errors according to the hierarchical framework of Bloom’s taxonomy. ResultsGPT-4’s performance in answering exam questions yielded a high success rate: 93% (284/307) for the detailed prompt and 91% (278/307) for the short prompt. Questions answered correctly by GPT-4 had a statistically significant higher difficulty than questions answered incorrectly (P=.002 for the detailed prompt and P

BackgroundCommunication is a core competency of medical professionals and of utmost importance for patient safety. Although medical curricula emphasize communication training, traditional formats, such as real or simulated patient interactions, can present psychological stress and are limited in repetition. The recent emergence of large language models (LLMs), such as generative pretrained transformer (GPT), offers an opportunity to overcome these restrictions ObjectiveThe aim of this study was to explore the feasibility of a GPT-driven chatbot to practice history taking, one of the core competencies of communication. MethodsWe developed an interactive chatbot interface using GPT-3.5 and a specific prompt including a chatbot-optimized illness script and a behavioral component. Following a mixed methods approach, we invited medical students to voluntarily practice history taking. To determine whether GPT provides suitable answers as a simulated patient, the conversations were recorded and analyzed using quantitative and qualitative approaches. We analyzed the extent to which the questions and answers aligned with the provided script, as well as the medical plausibility of the answers. Finally, the students filled out the Chatbot Usability Questionnaire (CUQ). ResultsA total of 28 students practiced with our chatbot (mean age 23.4, SD 2.9 years). We recorded a total of 826 question-answer pairs (QAPs), with a median of 27.5 QAPs per conversation and 94.7% (n=782) pertaining to history taking. When questions were explicitly covered by the script (n=502, 60.3%), the GPT-provided answers were mostly based on explicit script information (n=471, 94.4%). For questions not covered by the script (n=195, 23.4%), the GPT answers used 56.4% (n=110) fictitious information. Regarding plausibility, 842 (97.9%) of 860 QAPs were rated as plausible. Of the 14 (2.1%) implausible answers, GPT provided answers rated as socially desirable, leaving role identity, ignoring script information, illogical reasoning, and calculation error. Despite these results, the CUQ revealed an overall positive user experience (77/100 points). ConclusionsOur data showed that LLMs, such as GPT, can provide a simulated patient experience and yield a good user experience and a majority of plausible answers. Our analysis revealed that GPT-provided answers use either explicit script information or are based on available information, which can be understood as abductive reasoning. Although rare, the GPT-based chatbot provides implausible information in some instances, with the major tendency being socially desirable instead of medically plausible information.

Objectives Artificial intelligence (AI) is used in a variety of contexts in medicine. This involves the use of algorithms and software that analyze digital information to make diagnoses and suggest adapted therapies. It is unclear, however, what medical students know about AI in medicine, how they evaluate its application, and what they expect from their medical training accordingly. In the study presented here, we aimed at providing answers to these questions. Methods In this survey study, we asked medical students about their assessment of AI in medicine and recorded their ideas and suggestions for considering this topic in medical education. Fifty-eight medical students completed the survey. Results Almost all participants were aware of the use of AI in medicine and had an adequate understanding of it. They perceived AI in medicine to be reliable, trustworthy, and technically competent, but did not have much faith in it. They considered AI in medicine to be rather intelligent but not anthropomorphic. Participants were interested in the opportunities of AI in the medical context and wanted to learn more about it. They indicated that basic AI knowledge should be taught in medical studies, in particular, knowledge about modes of operation, ethics, areas of application, reliability, and possible risks. Conclusions We discuss the implications of these findings for the curricular development in medical education. Medical students need to be equipped with the knowledge and skills to use AI effectively and ethically in their future practice. This includes understanding the limitations and potential biases of AI algorithms by teaching the sensible use of human oversight and continuous monitoring to catch errors in AI algorithms and ensure that final decisions are made by human clinicians.

ABSTRACTArtificial intelligence (AI) in medicine and digital assistance systems such as chatbots will play an increasingly important role in future doctor – patient communication. To benefit from the potential of this technical innovation and ensure optimal patient care, future physicians should be equipped with the appropriate skills. Accordingly, a suitable place for the management and adaptation of digital assistance systems must be found in the medical education curriculum. To determine the existing levels of knowledge of medical students about AI chatbots in particular in the healthcare setting, this study surveyed medical students of the University of Luebeck and the University Hospital of Tuebingen. Using standardized quantitative questionnaires and qualitative analysis of group discussions, the attitudes of medical students toward AI and chatbots in medicine were investigated. From this, relevant requirements for the future integration of AI into the medical curriculum could be identified. The aim was to establish a basic understanding of the opportunities, limitations, and risks, as well as potential areas of application of the technology. The participants (N = 12) were able to develop an understanding of how AI and chatbots will affect their future daily work. Although basic attitudes toward the use of AI were positive, the students also expressed concerns. There were high levels of agreement regarding the use of AI in administrative settings (83.3%) and research with health-related data (91.7%). However, participants expressed concerns that data protection may be insufficiently guaranteed (33.3%) and that they might be increasingly monitored at work in the future (58.3%). The evaluations indicated that future physicians want to engage more intensively with AI in medicine. In view of future developments, AI and data competencies should be taught in a structured way during the medical curriculum and integrated into curricular teaching.

Abstract Background Peer-assisted learning represents a favoured method of teaching in universities. The COVID-19 pandemic has necessitated transferring medical education to digital formats, and subsequently, the question has arisen of whether online tutorials might be effective. This study, thus, investigated the efficacy of online tutorials in a communication course by assessing the interaction, verbal communication, and nonverbal communication of tutors and students. Methods Second-year medical students were invited to participate in this longitudinal quantitative study. Validated and self-developed questionnaires (e.g., Jefferson Empathy Scale) including 39 questions (rated on a 7- or 5-point Likert scale) were used to assess the different variables including interaction, verbal and nonverbal communication and students’ learning success. Results Out of 165 medical students, 128 took part in the study. The students as well as tutors reported that they found each other likeable (Mstudents = 4.60±0.71; Mtutors = 4.38±0.53; p > .05). Learning success increased throughout the communication course (Cohen’s d = 0.36–0.74). The nonverbal and verbal communication in the simulated patient (SP) encounter was also rated as high by all three groups (Mnonverbal = 3.90±0.83; Mverbal = 4.88±0.35). Conclusions Interaction as well as nonverbal and verbal communication occurred in the online format, indicating that online tutorials can be effective. The implementation of SPs increases the efficiency of synchronous online learning as it enhances the simulation of a real patient–physician encounter. Thus, online tutorials are a valuable amendment to medical education.

BackgroundDifficulties in implementing behavior change in patients with chronic diseases are common in clinical practice. Motivational interviewing (MI) helps clinicians to support patients in overcoming ambivalence while maintaining self-determination. The inclusion of MI in German medical training curricula is still rare. Furthermore, the effects of systematic teaching of MI, especially via blended learning, have hardly been investigated.MethodsMedical students participated in three curricular events related to MI, consisting of instructional videos and theoretical and practical components in a blended learning format. The aim of the study was to investigate the effect of teaching MI in students’ medical education. A controlled, non-randomized study was conducted with an intervention group and a control group. Both groups completed questionnaires on their experience and knowledge related to MI, completed a knowledge test and rated their satisfaction with the course. MI was taught in the 6th semester of medical coursework as part of a psychosomatic course, in the 8th semester during a psychiatry course and in the 9th semester during a weekly psychiatry clerkship.ResultsData from the intervention group (n = 35) and control group (n = 14) were analyzed, with 65.7% of students participating in all three parts of the curriculum. Overall interest in learning MI was high, with M = 2.92 (SD = 1.00). The results indicate a greater increase in knowledge over time in the intervention group. The majority (62.86%) stated that the curriculum was relevant to their future career. Free-form text responses indicated a high level of satisfaction with practical relevance.ConclusionThis study demonstrates the usefulness of an MI curriculum for medical students. The integration of MI into medical curricula is a promising curricular addition to improve doctor-patient communication. Future research should address patient perceptions of MI competencies and the persistence of acquired competencies.

IntroductionThe patient-physician encounter is the core element in the treatment of patients and the diagnosis of disease. In these times of digitalization, patient-physician communication is increasingly taking place online: patients embrace new possibilities offered digitally, and physicians are encouraged to adapt accordingly. Since a huge part of online communication is written, this study aims to investigate how medical students communicate with patients online by focusing on their written competencies and whether an intervention might improve their competencies.MethodsThis study was performed in an explanatory cross-sectional manner with a cross-over design. Second-year medical students participated. An intervention was developed on how to formulate an appropriate written response to a patient’s request and integrated a longitudinal communication class. The intervention consists of education on general set-up (e.g., greetings), syntax, spelling, content and kind of communication (e.g., appreciative attitude). After meeting a patient in a simulated role play medical students received the patient’s request via a digital platform. The control group had the same simulated role play and the same task but they received the intervention on communication afterwards. Intervention and control group were statistically compared based on a checklist.ResultsTwenty-nine medical students took part in the study. The results showed that the medical students had basic competencies in dealing with written communication independent if they received the intervention (CG: M = 3.86 ± 1.23 vs. IG: M = 4.07 ± 1.03; p = 0.625). Similar results were also for the emotional competency ratings (MCG = 3.36 ± 1.08; MIG = 3.67 ± 0.98; p = 0.425).The intervention was able to lead to a more appreciative response toward patient.DiscussionIntervention on basic competencies such as simple language and clear presentation might not be needed as an integral part in medical education. However, medical students should learn how to present empathic and authentic behavior in written online communication.

BackgroundVirtual reality (VR)–based simulation is being increasingly used to train medical students in emergency medicine. However, because the usefulness of VR may depend on various factors, the best practices for implementing this technology in the medical school curriculum are yet to be determined. ObjectiveThe overall objective of our study was to assess the perceptions of a large cohort of students toward VR-based training and to identify the associations between these attitudes and individual factors, such as gender and age. MethodsThe authors implemented a voluntary, VR-based teaching session in the emergency medicine course at the Medical Faculty in Tübingen, Germany. Fourth-year medical students were invited to participate on a voluntary basis. Afterward, we asked the students about their perceptions, collected data on individual factors, and assessed the test scores achieved by them in the VR-based assessment scenarios. We used ordinal regression analysis and linear mixed-effects analysis to detect the impact of individual factors on the questionnaire answers. ResultsA total of 129 students participated in our study (mean age 24.7, SD 2.9 years; n=51, 39.8% male; n=77, 60.2% female). No student had previously used VR for learning, and only 4.7% (n=6) of the students had prior experience with VR. Most of the students agreed that VR can convey complex issues quickly (n=117, 91%), that VR is a useful addition to mannequin-based courses (n=114, 88%) or could even replace them (n=93, 72%), and that VR simulations should also be used for examinations (n=103, 80%). However, female students showed significantly less agreement with these statements. Most students perceived the VR scenario as realistic (n=69, 53%) and intuitive (n=62, 48%), with a relatively lower agreement for the latter among female respondents. We found high agreement among all participants (n=88, 69%) for immersion but strong disagreement (n=69, 54%) for empathy with the virtual patient. Only 3% (n=4) of the students felt confident regarding the medical content. Responses for the linguistic aspects of the scenario were largely mixed; however, most of the students were confident with the English language (not native) scenarios and disagreed that the scenario should be offered in their native language (female students agreed more strongly than male students). Most of the students would not have felt confident with the scenarios in a real-world context (n=69, 53%). Although physical symptoms during VR sessions were reported by 16% (n=21) of the respondents, this did not lead to the termination of the simulation. The regression analysis revealed that the final test scores were not influenced by gender, age, or prior experience in emergency medicine or with virtual reality. ConclusionsIn this study, we observed a strong positive attitude in medical students toward VR-based teaching and assessment. However, this positivity was comparatively lower among female students, potentially indicating that gender differences need to be addressed when VR is implemented in the curriculum. Interestingly, gender, age, or prior experience did not influence the final test scores. Furthermore, confidence regarding the medical content was low, which suggests that the students may need further training in emergency medicine.

BackgroundChronic pain (CP), a complex biopsychosocial disorder with a global prevalence of up to 33%, can be treated by following multidisciplinary approaches that may include cannabis-based medicine (CBM). However, because CBM continues to be a new treatment, questions remain regarding the ideal duration for CBM and its psychosocial determinants, including mental comorbidities.MethodsIn a retrospective cross-sectional study involving 46 patients with CP (ICD-10 code F45.4-), three validated instruments—the German Pain Questionnaire, the Depression Anxiety Stress Scale (DASS), and the Marburg Questionnaire of Habitual WellBeing—were used to identify pain-specific psychosocial determinants and mental disorders. Descriptive analyses, a group differences analysis, and a logistic regression analysis were performed using SPSS.ResultsThe patients most frequently reported low back pain as the primary location of their CP, and in attributing the condition to tissue damage, most had largely adopted a somatic orientation in conceptualizing their illness. Most had experienced CP for more than 5 years (M = 5.13 years, SD = 1.41) and, as a consequence, faced significant restrictions in their everyday life and exhibited low subjective wellbeing (MFHW median = 4.00, N = 43, Q1: 2.00, Q3: 9.00, range: 0–20). Comorbidities among the patients included depression, (DASS-Depression, median: 11.50, Q1: 7.00, Q3: 16.25), anxiety (DASS-Anxiety, median: 4.50, Q1: 2.75, Q3: 8.00), and stress (DASS-Stress, median: 11.00, Q1: 7.00, Q3: 15.00). Between the two cannabis-based treatments with a course lasting either less or more than a year, the duration of treatment showed no between-group differences in terms of sociodemographic factors, pain-specific factors, conceptualizations of the illness, or mental disorders. Psychosocial determinants such as subjective wellbeing and mental comorbidities were not significant predictors of the duration of cannabis-based treatment.ConclusionWe found no evidence indicating that the benefits of short-term vs. long-term cannabis-based treatment can be predicted by mental comorbidities or psychosocial factors. However, because CBM may be included in approaches to treat CP, questions about the ideal duration of such treatment remain to be answered.

IntroductionFace-to-face medical and psychotherapeutic treatments during the Corona pandemic often involve patients and health care providers wearing face masks. We performed a pilot survey assessing the subjective experience of wearing face masks during psychotherapy sessions regarding (i) feasibility, (ii) psychotherapeutic treatment and (iii) communication, emotion and working alliance in patients and healthcare professionals.MethodsA total of n = 62 inpatients (RR = 95.4%) and n = 33 healthcare professionals (RR = 86.8%) at an academic department of Psychosomatic Medicine and Psychotherapy participated in this survey anonymously. The items of the questionnaire were created by the interprofessional expert team and were based on existing instruments: (i) the Therapeutic Relationship Questionnaire and (ii) the German translation of Yalom’s Questionnaire on Experiencing in Group Psychotherapy.ResultsThe majority of patients rate their psychotherapy as highly profitable despite the mask. In individual therapy, face masks seem to have a rather low impact on subjective experience of psychotherapy and the relationship to the psychotherapist. Most patients reported using alternative facial expressions and expressions. In the interactional group therapy, masks were rather hindering. On the healthcare professional side, there were more frequent negative associations of face masks in relation to (i) experiencing connectedness with colleagues, (ii) forming relationships, and (iii) therapeutic treatment.DiscussionInformation should be given to patients about the possible effects of face masks on the recognition of emotions, possible misinterpretations and compensation possibilities through alternative stimuli (e.g., eye area) and they should be encouraged to ask for further information. Especially in group therapy, with patients from other cultural backgrounds and in cases of need for help (e.g., hearing impairment) or complex disorders, appropriate non-verbal gestures and body language should be used to match the intended emotional expression.

Objective Digital transformation in higher education has presented medical students with new challenges, which has increased the difficulty of organising their own studies. The main objective of this study is to evaluate the effectiveness of a chatbot in assessing the stress levels of medical students in everyday conversations and to identify the main condition for accepting a chatbot as a conversational partner based on validated stress instruments, such as the Perceived Stress Questionnaire (PSQ20). Methods In this mixed-methods research design, medical-student stress level was assessed using a quantitative (digital- and paper-based versions of PSQ20) and qualitative (chatbot conversation) study design. PSQ20 items were also shortened to investigate whether medical students’ stress levels can be measured in everyday conversations. Therefore, items were integrated into the chat between medical students and a chatbot named Melinda. Results PSQ20 revealed increased stress levels in 43.4% of medical students who participated ( N = 136). The integrated PSQ20 items in the conversations with Melinda obtained similar subjective stress degree results in the statistical analysis of both PSQ20 versions. Qualitative analysis revealed that certain functional and technical requirements have a significant impact on the expected use and success of the chatbot. Conclusion The results suggest that chatbots are promising as personal digital assistants for medical students; they can detect students’ stress factors during the conversation. Increasing the chatbot's technical and social capabilities could have a positive impact on user acceptance.

COVID-19 had a tremendous effect on medical education. Most teaching sessions had to be shifted online, posing additional stress and potential isolation on medical students. However, it also offered the promotion of innovative digital teaching concepts. In this article, an approach to undergraduate mental health training is presented and evaluated. The curriculum was designed according to Kern's six-step approach and consisted of asynchronous online material as well synchronous digital teaching and was accompanied by a plethora of newly developed teaching material (videos, fact sheets, etc.). Content covered the whole spectrum of diseases seen in a service of psychosomatic medicine and psychotherapy (i.e. anxiety, depression, trauma, somatoform and eating disorders, as well as motivational interviewing). Feedback from participants was collected, and exam results (written and practical) were compared to pre-COVID-19 times using t-tests for dependent and independent samples. Students were highly satisfied with the teaching (rating of 1.3 ± 0.6, n = 139 students). There was no significant difference from course evaluations before COVID-19 (1.5 ± 0.5, p > .05). The teaching also received an award in the students' competition "best digital teaching concept in summer term 2020". In the written exams, there was no significant difference between before COVID-19 (2.4 ± 0.45) and during COVID-19 times (1.6 ± 0.39; p > .05). In the practical objective structured clinical examination (OSCE), there was also no significant difference between students' judgement of the difficulty of the station (1.9 ± 0.22 vs 1.9 ± 0.31; p > .05) or how well-prepared they felt for the exam (2.0 ± 0.24 vs 2.0 ± 0.31; p > .05). However, there was a significant difference in terms of grades, with the pre-COVID-19 grades being significantly better (2.7 ± 0.37 vs 2.0 ± 0.44; p < .05), which reflects the difficulty of transferring practical skills training to an online setting. Students particularly valued the possibility of self-directed learning combined with personal guidance by departmental experts, reflecting the importance of wellbeing-centred medical education. The pandemic triggered overnight challenges for teaching mental health that may also offer the opportunity to think about worldwide teaching standards with easily accessible material and courses online. This may offer the opportunity to enthral medical students to become mental health specialists themselves.

Background and objectivesThe study aims to investigate the attitudes of medical students regarding the importance and relevance of vaccinations, whether vaccinations should be compulsory and how to employ a new teaching concept to deal with vaccination-critical parents.MethodsThis mixed-method study consists of a quantitative questionnaire and focus groups. Quantitative data were analysed by calculating the descriptive statistics, and interviews were analysed using Mayring's content analysis.ResultsA total of 170 medical students completed the questionnaire, and 59 students participated in 9 focus groups. Students reported that they felt more confident dealing with vaccination-critical parents after learning the new teaching concept. Similar results were found for medical students prior to and during the pandemic. During the pandemic, medical students viewed vaccinations for several diseases, such as measles or COVID-19, as important (range: M = 3.56, SD = 0.54 to M = 3.97, SD = 0.17). Similar results were found for medical students prior to the pandemic (range: M = 3.26, SD = 0.77 to M = 3.94, SD = 0.24). In the focus groups, however, medical students displayed controversial attitudes regarding compulsory vaccinations.ConclusionsWhile the medical students agreed on the use of vaccination for highly infectious diseases, their level of agreement decreased depending on the severity of the disease. Practical recommendations that come out of the study are creating a trustful relationship with and delivering information to patients.