Student and lecturer perceptions of the use of an AI to improve communication skills in healthcare: an interview study

Student and lecturer perceptions of the use of an AI to improve communication skills in healthcare: an interview study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Student and lecturer perceptions of the use of an AI to improve communication skills in healthcare: an interview study Hanna Brodowski, Anna Dammermann, Muriel Marieke Kinyara, Martina Andrea Obst, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4225671/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and objectives Communication is a complex skill and key component for professionals in health care. Complex skills are best learned through experimental learning like role plays or simulated patient encounters. The aim of the present study is to explore how students and lecturers assess the conditions under which the use of an AI-based feedback system can promote the learning process. Methods An interview study with health profession students and lecturers was conducted using a qualitative descriptive design. Recorded audio data was transcribed and evaluated by structuring qualitative content analysis using deductive and inductive coding. The research process was conducted and continually reflected by an interprofessional research team. Ethical approval was obtained. Results Using qualitative content analysis, four major themes were identified. These are “conditions”, “communication scenarios”, “AI-based learning platform” and “debriefing”. Lecturers and students welcome the idea of AI providing feedback on verbal and para-verbal aspects. To implement AI-based feedback into a teaching programme AI functionality should be adaptable to the specific situation. Lecturers and students highlighted that AI could be particularly valuable for speech qualities which are often difficult for humans to assess. AI could give freedom to focus on additional aspects of the conversation by documenting desirable speech qualities. Lecturers and students prefer for the AI-based feedback to be given at the end of rather than within the role play. Furthermore, they wish for communication scenarios to be analysed repeatedly in order to track progress. Conclusion Practicing in a safe environment and receiving competent credible feedback, with lecturers trained in facilitation, is a prerequisite for the entire learning progress.The integration of an AI-based feedback system should be characterised by both flexibility of the AI application and standardisation of the communication scenario. AI acceptance communication debriefing experimental learning healthcare interviews learning platform speech recognition Figures Figure 1 Figure 2 Figure 3 1. Introduction AI-supported systems are increasingly making inroads into education, as evidenced by the growing body of research in this domain (1). AI is defined as ‘the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages’ (2). A valuable application of AI lies in the field of communication skills training. Sufficient communication skills are essential for healthcare professionals’ ability to deliver patient-centred care. Empathetic conversations foster positive relationships between healthcare professionals and patients (3) and contribute to the success of therapy (4). The best way to acquire communication skills is to train in a simulated environment as complex skills like communication are best learned through experimental learning (5,6). Evidence suggests that communication skills training improves students' communication abilities (7,8) and equips them with enhanced communication skills for clinical practice (9). As a result, simulation-based medical education has gained prominence in healthcare profession programmes, including those at the University of Lübeck. The University of Lübeck offers nine health degree programmes, a unique diversity in Germany, which provides an ideal environment for patient-oriented and interprofessional learning, as well as the acquisition of communication skills. Across all healthcare programmes, various teaching modules include active training in communication skills. These modules emphasise self-awareness, involving role plays and exercises based on case studies, with actors simulating patients or interprofessional counterparts. Consequently, over the past three years, a medical skills training and practice centre has expanded, accompanied by the establishment of additional teaching and seminar rooms for feedback-based communication training. The role play scenarios or simulated patient encounters are continually refined, optimised, and updated at Lübeck. They vary in scope and content across different healthcare programmes, encompassing emergency situations, explaining pain mechanisms to patients, and communicating with patients who have dementia. Overall, a substantial number of students and lecturers have undergone communication training and garnered experiences in the context of medical-based learning over the past decades. Both students and especially lecturers can draw on a wealth of experience including debriefing sessions that reflect the fact that debriefing requires skills with complex emotional and cognitive aspects. To further enhance and individualise existing patient-centred communication training, the University of Lübeck is presently developing an AI-supported learning assistance system, hereafter called CoSy (Communication System). CoSy is, at this point, an imaginary system. In contrast to communication platforms like SimConverse©, which uses interactive AI characters to play the role of any patient or colleague, or ChatGPT, users won't be able to engage in conversations with CoSy. CoSy will be a speech recognizer, able to give feedback to verbal (what did you say) and para-verbal (how did you say it) foundations of communication. A crucial step in the development of such a system is a requirement analysis with regard to the future users. This current study aims to explore the experiences and perceptions of students as well as lecturers, seeking to understand what they think about the possible use of an AI-based feedback system, which is supposed to be implemented in their (potentially emotional) challenging learning context. The requirement analysis was conducted to lay the groundwork for the project, to set future users expectations and to document all critical needs. The research questions are: From the students’ and lecturers’ perspectives… … what are the required prerequisites for integrating an AI-based learning platform into communication training in healthcare programmes? … how should the communication scenarios be designed? … which speech qualities are considered useful when integrating an AI-based learning platform? … in what way should the output of the AI-based learning platform be didactically embedded in the communication situation? 2. Methods Design This interview study used a qualitative, descriptive design to explore students’ and lecturers’ experiences and perceptions of communication training. The research was conducted and continuously reflected by an interprofessional research team. In addition, the procedure and the results of the data analysis were presented, discussed, and reflected within the project advisory board consisting of experts from research and practice. In order to ensure the rigor and trustworthiness of the study the recommended standards for reporting qualitative research (SRQR) were followed (10). Sample and recruitment Participants were recruited by specifically addressing lecturers and students (purposive sampling). One module was selected for each healthcare programme in which communication is a central part of the teaching. The aim was to recruit interview partners from every healthcare programme at the University of Lübeck to maximise the variation of perspectives included. Students must have previously participated in practical communication exercises during their studies and attend the corresponding healthcare programmes. Lecturers of the healthcare programmes must have experience in communication education. The sample must also include lecturers and students from monoprofessional as well as interprofessional modules. Information about the study, its aims, and data protection regulations concerning the interviews were provided to potential participants via e-mail. Data collection On the premise that all interviewees were aware of the study procedure and provided their written consent, data collection was conducted on focus groups of health profession students and individual interviews with health profession lecturers. The interviews were based on two semi-structured interview guides, one for lecturers (individual interviews) and one for students (focus groups). Both interview guides were developed based on the research questions and discussions with the interprofessional research team. In an initial expert workshop, in form of a brainstorming session, a list of speech qualities, like “terminology”, “length of pauses” or “adjusting one’s volume depending on the patient” were compiled. Both interview guides included questions on the same four central themes: 1) current communication scenarios in teaching and characteristics of communication, 2) current debriefing for the development of communication skills in the health professions, 3) the use of an AI-based learning platform in communication situations and in relation to speech qualities and 4) conditions for integrating the AI-based learning platform. The guidelines included open questions or narrative invitations. The wordings for lectures and students were e.g: “What are your wishes for feedback by an AI-based learning platform after a conversation with a patient?” Or: “What additional benefits could an assistance system bring to teaching?” In order to explore participants’ views on the speech qualities, they were asked towards the end of the interviews to rate which of these speech qualities an AI should provide feedback on. For this purpose, the participants were asked to assign previously prepared cards with speech qualities to the categories "very important," "important," and merely "nice-to-have”. The interview guide also included an explanation to give interviewees a realistic description of CoSy and what it will actually be capable of. The wording was as follows: “In many everyday appliances, like voice-controlled assistance systems in cars, and entertainment programmes artificial intelligence is already integrated to give feedback. The game Sing-Star© is an example of what feedback on voice pitch can look like. (Sing Star© is a karaoke game that analyses a singers timing and pitch which is then compared to the original track.) Imagine that there is an assistance system, that systematically evaluates conversations and speech behaviour. The following questions focus on what is spoken in a situation and about speech qualities on which the assistance system can provide feedback.” Prior to the start of data collection, the interview guide was pretested in two interviews, and minor adjustments were made, especially regarding the order of the questions and the openness of the wording. Socio-demographic data of the participants was collected using a structured data collection sheet. The interviews took place between May and August 2022. To create a trusting atmosphere and avoid socially desirable answers, focus groups were conducted by members of the interprofessional research team from differing programmes. All interviews were audio-recorded. Following the data collection, the interviewers prepared a protocol (interview postscript). Data analysis The interviews and focus groups were transcribed verbatim according to the rules of Dresing & Pehl (2015). The interviewer was consulted in case of uncertainties within the transcription process. During the transcription, the data was anonymised. The analysis was based on structural content analysis (12) using the software MAXQDA 22 (VERBI Software, 2021). A structuring qualitative content analysis allows the development of central themes within a data-based deductive-inductive approach. The data analysis for this article specifically focused on AI-related findings from the interviews. The interviews were analysed separately in the first step. In order to develop an initial understanding of the data, interviews were read carefully and intensively, taking into account the research questions (initiating text work). Using a deductive approach, a preliminary category system was developed for the main categories based on the central themes of the interview guidelines. Data was coded with these main categories. Subcategories were then formed inductively from the data collected during the initial interviews. Subsequently, the entire dataset was analysed using this category system, and anchor examples were identified. During the data analysis the category system was adapted and refined. Coding was initially performed in teams of two researchers to ensure a consistent approach. The remaining data was then coded individually and crosschecked by a third researcher. Afterwards, the results of the analysis were contrastively related to each other (perspective triangulation) and relationships and connections between the topics were identified using the constant comparative method (13). These interrelations between the themes were visualised. The results of the analysis were continuously discussed and reflected upon by the entire research team. 3. Results 27 health professionals participated in this study: seven lecturers and 20 students (Table 1). Lecturers and students from seven modules took part. Two student focus groups were interprofessional, five monoprofessional. The seven individual interviews with the lecturers lasted an average of 71 minutes (ranging from 59 to 101 minutes), while the five focus group interviews lasted an average of 112 minutes (ranging from 95 to 130 minutes). Overall, a total of 17 hours and 35 minutes of audio has been recorded. Table 1: Characteristics of study population Lecturers N=7 (7 Individual Interviews) Students N=20 (5 Focus Groups) gender, women (N) 5 17 Age M (min-max) 44 (33-52) 24.5 (21-41) Health Profession medicine 1 - emergency medical care 1 5 medical psychology 1 - midwifery 1 3 nursing 1 5 occupational therapy 1 3 physiotherapy 1 4 clinical psychotherapy - - Teaching experience, years M (min - max) 13.0 (6-23) - Number of semesters, M (min-max) - 6 (4-14) Missing=2 Clinical experience, years M (min-max) 12 (0-20) 2.25 (.42-16) Missing=1 Results in this article specifically focus on AI-related findings and revealed four major themes which were addressed in the interviews and focus groups. The four major themes are “conditions”, “communication scenarios”, “AI-based learning platform”, and “debriefing” (Fig 1). The analysis of the interviews shows that the participants have confidence that the AI output will have the potential to deepen the learning process and to complement the debriefing. This shows that CoSy is not perceived as an alien piece of the puzzle. The optimal framework conditions and prerequisites for the communication training became apparent. They are summarised under the topic “conditions”. Analysis shows that the following presented three individual parts “communication scenarios”, “AI-based learning platform”, and “debriefing” influence each other and must be well harmonised. 3.1 Conditions The participants assume that the use of CoSy has an impact on the achievement of communication skills. They have the understanding that CoSy can record and analyse what is being said. According to the interviewees, CoSy needs to have information about a conversation in order to be able to analyse what is being said in a dialogue. Examples of important contextual information was mentioned, e.g. the age of the patient, the room in which the conversation takes place and the time frame. KL5-Lecturer: “Does it [AI] need information about the speakers? (...) so it should know who the patient is and who the therapist is (..) I would think (..) it probably needs information whether it is a man or a woman (..) because something like pitch has a large range of variance but probably differs. […] .” #00:45:31-9# KL6-Student2: “Maybe also an overview of the setting, so if we imagine a practice, in which room is it carried out, what are the room conditions and what is in front of it, behind it? If there are perhaps colleagues in a motor activity room and it is super loud, then of course I have to speak up. […] .” #0:58:51.0# Assumed added value In addition, many interviewees assume that CoSy can give more comprehensive feedback on communication in comparison to the lecturers and peers, as it can record and process more data than humans. Students and lecturers highlighted that CoSy could be particularly valuable for speech qualities which are often difficult for humans to assess. Participants think beyond face-to-face teaching and imagine usability in many other settings such as self-study in the SkillsLab or at home on a computer. The students also imagine the application in practical everyday clinical settings - carrying CoSy in their pocket. KL2-Student3: “Well, what I was just thinking about, which would also be cool, is if you simply had the chance to go back to the ward after university, if there are patients who voluntarily take part in it. It would be similar to the examintaion-courses or anamnesis courses, where you simply go alone or in pairs to the patient’s room, have conversations and record them, without it having to be in such a fixed framework, but that you simply have it for yourself as feedback. […]. ” #01:34:31-4# Nature of the data As in many technology or AI-based cases, the interviewees assume that CoSy will provide objective and neutral feedback. It is assumed that the AI output states facts about communication that are less subjective than feedback from lecturers or fellow students. This presumed objective view of a conversation seems to be an important perspective for students to add. KL6-Lecturer: “That has something objective about it, doesn't it? Because otherwise you have the feeling that I have used a lot of technical terms or the students report back and then it was still only three times, but somehow it felt very dominant. (…) We know this ourselves, when we conduct an interview, you think you have left huge pauses in the interview situation, but when you transcribe it, it was a maximum of one minute and it felt very, very long in the interview. So that would also be something objective, how long a minute really is, in order to develop a feeling for it. (.) It also has something neutral. So when other students give each other feedback, it's not so easy to expose yourself to such an interview situation and then someone else tells you how it was and maybe it's like a machine that says 'you were too fast' is perhaps easier to accept than when the lecturer says it. […]. ” #00:51:55-8# KL6-Student1: “And the AI could perhaps also look at more situations overall, so to speak, and yes, if you get feedback from a lecturer or something, that then always refers to just one situation. And the AI could perhaps more EASILY look at several situations and see whether this is a problem more often.” #1:25:48.5# KL2-Lecturer: “(...) I see a neutral evaluation of situations. Um. Highly standardised. With the possibility of being able to focus on other things in the situations simultaneously. And to create a certain evaluability.” 00:58:22-4# KL1-Student2: “So I think it makes more sense to use the AI as something additional, outside, giving feedback. […]. ” #00:20:58-3# Time and teaching organisation It is important for the students to have a reasonable degree of data sovereignty and control over their data. Students in particular like the data to be stored in order to use CoSy output to show long-term trends in their learning processes. KL6-Student2: “Maybe also (...) that once you have received a feedback, that there is a follow-up situation or several, that you can also compare things, for example, if they have given you, the system has given you feedback (laughs) and there is something like that again at a later time, that you can draw comparisons or has something improved or not and if not, why not. So that you can use that again. That this AI is simply used several times in situations.” #1:32:18.7# The integration of CoSy output in communication skills training will require more time than the current teaching of communication skills. Lecturers also assume a higher time requirement because they expect a more intensive preparation and follow-up for skills training. KL5-Lecturer: “Yes, I think (.) at least the lecturers should be trained (.), what they can do and what they can't do, so that you know where you can use it [the AI] well, so where you see your own possibilities. I think it would be nice if you could shift part of the teaching to this SkillsLab. (...) in the SkillsLab (..) and that in the self-learning time that belongs to each module you can then also motivate (..) to practise this situation. So I believe that in teaching, when it is here on campus (...) the lecturers must first be activated. They are certainly obliged to (...) really use it (...) and not to find it funny or (...) to be afraid of the technology.” #01:10:00-0# KL4-Lecturer: “But what you can already gather is that there is still a moment when a human being has to be there to pick up the AI again. Someone who also says, what does this mean now, what does this mean, and who also enters into a conversation with the student who then sees this. At least for the first time. For a first contact. As if we were to conduct two interviews, we let the AI run along, we look to see where there are problems, where perhaps not. Um, and then you can let the student train independently. […]. ” #00:50:21-4# Lecturers are aware that the use of CoSy will require workload outside the classroom. They see a need for preparatory training with the practical application, like handling the user interface and the didactic implementation, which includes the decisions when and how to discuss the AI output. Both lecturers and eventually students need to train applying the AI system. Lecturers must be instructed in the use of the system outside of teaching. For the students, sensitising instruction should take place within the framework of the respective teaching module. Rooms and equipment For various steps, such as the first interaction of lecturers and students with the AI system, but also for the later skills training with CoSy itself, certain premises are needed. These must include technical equipment as well as suitable materials and furniture for different scenarios. KL2-Lecturer: “Digital devices (…) to make that as close to reality as possible, with tactile and auditory, visual stimuli [are needed ] (...) Otherwise, at the end of the day it's like a video film when I see the sequences and then decide what to do. I never get the stress level and the level in there to then really say, I forget that this is not real now.” #01:02:42-9# KL8-Lecturer: “So what we actually always need is (…) a certain simulation of the typical conditions for the situation. So, you can also (...) / you could also play it more abstractly in a seminar room, of course. But then it certainly loses some of its authenticity and perhaps makes it more difficult for the students to put themselves in this situation and imagine how they would react. And also for the actors, that's how we perceive it, it's also helpful to have a few CORE utensils with them. So it doesn't have to be the full programme but the bag, the bed, the pyjamas um yes.” #0:10:57.1# 3.2 Communication scenarios This theme outlines the essential prerequisites and preferences of study participants regarding the design of communication scenarios in general. Additionally, the limitations perceived by the participants concerning the use of CoSy are described. Range of content and themes Participants identified several communication scenarios that could potentially be enhanced with AI support, including medical anamnesis, goal-setting and counselling interviews, emergency management, and interprofessional communication situations like handovers and case discussions. What they all have in common is that they are largely standardised and follow a structured conversational format. KL1-Lecturer: “Yes, the scenario must be clearly defined in some way, like / it should be, for example / it should be a feedback conversation, and in a feedback conversation, we define / need to include these specific aspects. And these aspects can be verbally represented by the following words or something like that. […]. ” #00:48:11-2# In contrast to standardised situations, there are more complex situations, such as scenarios primarily involving manual techniques and procedural workflows, or face-to-face patient-care scenarios. In these scenarios, there is an expectation for more variability in the content of the conversation and therefore it is more difficult to specify terms or aspects that need to be said. Often, in the more complex situations, the atmosphere of the conversation and feelings matter more than specific content. The flow of these conversations is less predictable and exhibits greater variability in each individual scenario. In these cases, meaningful AI output seems to be only limitedly conceivable. KL8-Lecturer: “Only very, very limited scenarios where it might be about structuring a conversation or A LOT OF INFORMATION / uh, for example, using the SBAR-framework. And I could imagine that, uh, that maybe a machine could be used for THAT. I could imagine it for highly standardised situations, which actually exclude almost every classic patient-care situation.” #00:49:04# Composition of actors The communication training sessions described in the interviews were structured as one-on-one scenarios, with two possible conversation configurations. In some cases, one student acted in their own profession and the other as a patient or a patient’s relative. In most instances, a professional (paid) actor portrayed the patient’s role to create a more realistic atmosphere. The background information on their role is known to the actors in both options, which is particularly important to bring the scenario close to reality. KL6-S tudent 2: “ I'm thinking of this situation, the patient is in bed as an old woman in need of care and I'm supposed to motivate her to eat breakfast or something. I think it's a very true-to-life situation. And she didn't make it easy for me. I really had to think a bit about "how do I do this now? ” And I really liked that. And of course it's completely different if someone you know was lying there. Then you might lose the ro/ the actual role. (...) That's what I would have liked to see more of throughout my studies, (...) no super artificial situations, but really from life. And this professional actress also did it very well (laughs). Yes. ” #0:45:45.3# In the interests of realism, lecturers and students prefer actors (standardised patients). However, this is only the case for adult patients who are played by actors. Lecturers and students criticise the connection to reality in children as patients; these cannot be staged by adults, regardless of whether they are actors or fellow students. At this point, it can be mentioned that the participants are again thinking beyond the planned capabilities of CoSy and imagined AI-controlled avatars as communication partners alongside actors. KL7-Lecturer: “Maybe that would be a form where something could be done. That means that they have different forms of avatars that have certain information that is important or that is not important. [...].” #01:05:41 # KL6-Lecturer: “Communication with children, as I said, I still have a bit of hope for the AI (laugh) whether there are any great ideas. Yes, because that's something (…) where I think we need more practical relevance to be able to practise it. You somehow can't do that with the actors.” #00:23:40-2# Overall, students had good experiences with both options, actors and fellow students in the role of patients. Beyond communication skills, it can help students to slip into the patient role and experience what that feels like. There were no experiences mentioned for real patients who volunteered to play a role for training purposes. Frequency and location of training The general conditions have already shown that teaching must be organised in such a way that a communication scenarios can be practiced several times. Especially students describe the learning of communication skills as a process with a need for repetition. Participants consider CoSy suitable to be used throughout the learning process and thus in every session. KL6-Student2: “And that it's also used regularly, that [...] that it's somehow a continuous part of it. […]” #1:53:44.7# KL5-Lecturer: “I'd prefer shorter situations, practicing them more frequently, so that the next time you can go back and see if it has improved.” #01:04:55-4# Students shared and reflected their experiences due to the COVID-19 pandemic-related restrictions. There was a clear consensus that communication training in attendance is seen as more beneficial. Benefits of conducting in-person sessions include a better group atmosphere and a more realistic scenario setup, as non-verbal aspects of communication cannot be adequately expressed in an online setting. KL8-Student3: “I found the online communication quite challenging because in communication, there's a lot of body language involved. [...] I found it quite difficult to sit at home and try to do something, you know? I believe it would have been different in person, […] I think body language is an important tool in communication, which was completely absent. […].” #00:15:53-2# 3.3 AI-based learning platform – CoSy The ideas on what special functions and characteristics CoSy must have, what CoSy should look like, and how the system should be accessed in detail vary. There is an agreement that it must be accessible to both students and lecturers. Features The categorisation of speech qualities, on which participants would like to have AI feedback, into "very important", "important" or merely "nice-to-have", was part of the interviews and focus groups. The seven lecturers were given some time to categorise each of the proposed features during their interviews (Fig 2). In the focus groups the categorisation was more freely designed. The students first each categorised for themselves and then got into conversation with each other and discussed their categorisation. Some of the speech qualities were considered very unimportant and were not even categorised by the students. Additionally, the categorisation was partly done in partner work, therefore, the number of categorised qualities varies in comparison to the lecturers (Fig 3). Qualities are arranged in descending order of priority in both figures. The need to repeat communication training creates requirements for the function of CoSy. Students and lecturers suggest that CoSy should document the speech qualities and the development of learning over time. CoSy output should be stored to enable students to compare their CoSy output parameters of current communication with CoSy output parameters of previous communication situations. This additionally implies the existence of a user profile, so that the students gain access to their data. This proposal applies to both the comparison of the own individual performance and the comparison with a reference group. Interviewees suggest that the reference group should consist of students from the same profession or students who have a similar level of learning (from beginners to experts). KL8- Lecturer: “It would certainly be good if the student could somehow save it, especially when he wants to practice it again, so that you can see a progression. I would also like that.” #00:50:37# Design For the CoSy output there are different forms imaginable, which seem almost contradictory. On the one hand, students and lecturers envision neutral and non-judgemental feedback. This form of feedback should be as quantitative as possible including facts and figures. On the other hand, evaluative feedback is envisioned classifying into desirable and undesirable or using a traffic light system e.g., which would relieve lecturers and students of the task of interpretation. Furthermore, they envision that CoSy output uncovers gaps in the conversation and reports back if something in the communication is debatable. In this context CoSy output could point out suggestions for a better performance. A physical output could be a visual or textual print of the feedback. KL4-Lecturer: “Yes, I always find it so exciting with transcripts, how people talk. And sometimes you're not even aware of it, because you pay attention to many other things, um, I don't know, eye contact and um, was the hairstyle correct, um, but when you see what you've said, you can see how often you don't really finish a sentence one hundred percent, that your voice / always goes down at the end, that you leave a pause. Um, that's very conspicuous when it's reflected in writing in black and white.” #00:38:44-9# Overall, the results show that lecturers and students would like CoSy to be clearly structured and designed, allowing an intuitive navigation. Although it is imaginable in principle that the function of CoSy is to provide output on a wide range of speech qualities, participants prefer the selection of specific speech qualities. A suggested function is to be able to select the desired speech qualities individually directly before the communication situation, as not all speech qualities are considered important for feedback in every single situation. This would narrow down the feedback in terms of content. KL6-Student2: “Maybe you can also select certain topics for feedback, which are then only a topic and which are then only reported back. So that it's not too much.” #1:36:12.9# Timing The analysis revealed that both students and lecturers are accustomed to post-event debriefing. Providing feedback within-event appears to be uncommon. Students address speech qualities that can be provided as feedback during the scenario, such as volume or speech rate, if defined in advance. In addition, within-event feedback also requires a reference value, such as "too loud" or "too quiet", to directly adapt one's own speech behaviour and thus creating added value. Even though feedback during the communication situation is conceivable, post-event debriefing is clearly favoured overall. KL2-Student5: “So, I think I would be distracted during that. I mean, that's a good point about the volume, then I can react to it in the moment. But I believe, for me, it would be better to receive it afterward.” KL2-Student3: “I would also say, in the end is actually better because otherwise, during the conversation, you would be constantly preoccupied with what this system is telling me right now. It shifts the focus away from the conversation.” #01:20:38-3# KL-5-Lecturer: “I believe it would disrupt the conversation. (...) I think it would be better at the end (...) after because if I were to get a red light during the conversation, I can imagine it would completely throw me off and disrupt the flow of my conversation (...) so (...) I don't think it would be beneficial.” #01:04:34-9# 3.4 Debriefing Role play scenarios are commonly framed by briefing and debriefing phases as stated by Eppich & Cheng (14) or Zigmont (15). In this current article the "learning conversations" (16) following the role play scenarios are called “feedback” or “debriefing” interchangeably as the interviewees did not differentiate between these terms. Debriefing is considered important by the interviewees, also quite independently of CoSy, and takes up a large part of the narratives. Students in particular share many of their experiences. Facilitation According to the participants of this study, debriefing should be structured using a manual "feedback guide" (for students) or an "observation guide" (for lecturers), which includes aspects to be observed and questions to promote learning. In preparation for this conversational phase, participants also describe the need to review and establish rules or conversation principles. They pointed out that conversation rules should be considered both in the communication scenario and in the debriefing. KL4-L ecturer : “ Feedback rules, the normal standard, that you always learn. So to say, to always convey I-messages, how do things affect me, what impression does it make, how can I imagine that it could perhaps be brought into a more optimi s ed direction. And [I ] give really concrete examples. I use a concrete example, to say what I noticed and [I ] also give concrete ideas on how it could have been packaged differently if necessary. And also the explanation of why I would have liked it differently perhaps, this is very, very important to me. ” #00:11:54-9# KL1-S tudent: “I could imagine that with the help of a tool like this, you wouldn't forget anything and would also emphasi s e such things more, […] so yes, exactly, maybe that wouldn't be such a bad idea, to get a little guide for reflection of communication. ” #00:48:12-4# KL1-L ecturer: “ Sometimes we work out wish lists of what we would like to receive when we get feedback and how we should give feedback. And then based on various feedback steps, so to speak, we also work out formulations on how to formulate something well, exactly, and there are also these, let's say, general rules that you refer to concrete and observable behaviour. And also changeable behaviour. So that you don't give feedback on something that the person can't change anyway. [… ] Observe good conversation management aspects, such as I-messages and also not making moral value judgements in any way. Talking directly to the perso n […]. ” #00:33:22-2# Even though self-reflection of both simulation participants was addressed in some examples, the interviews mainly dealt with the lecturers’ responsibility and their (desired) behaviour. All in all, interviews show that the guiding through the debriefing phase is mostly the responsibility of the lecturers. Students expect lecturers to navigate them through the debriefing and to focus on learning objectives. A self-guided facilitation did not emerge as a central theme. Learning strategy All in all, participants have an idea of the requirements of debriefing and its process elements. It often comes through in the interviews how important and formative this phase is, especially for the students. Interdisciplinary feedback is rated as extremely helpful by the students; one lecturer also emphasises that peer feedback is more effective than feedback from the lecturers. The analysis also confirms that debriefing is a critical component in the process of learning. Even though students stated a positive learning attitude in this context, it comes with little surprise that they also described negative experiences. Too little time for debriefing was discussed. It was mentioned that the debriefing took place afterwards “in the corridor” with the consequence that conversation did not go as deep as it was expected. Additionally, there was mention of a performance paramount. Students compared their conversational performance with each other, thinking about who was better and who was worse. Students said that they felt more evaluated and judged by lecturers than constructively criticised. Signs that the learning environment was no longer perceived as safe are expressions such as “lucky to come out of it“ or feeling “paraded“. KL8-S tudent 2: “ Well, I still remember that we always had very little time for the feedback and I was often somehow still in the situation before and then the next situation was already going on. So that somehow things were brought up and then not finished […] and we would quickly move on, but somehow we were still thinking about the situation before. ” #00:30:48-4# KL2-S tudent 3: “ What I think is important is that there is also a focus on feedback because what I remember, for example, is that some of the professional drama patients gave feedback saying, 'Yes, there was something I didn't like, but I can't really say what'. So, positive feedback from the course leader and from the fellow students, basically everything is fine, and then you get 'I didn't like something' in the last sentence, and you can't do anything with that, because you don't have anything to start with, to improve on. ” #00:28:07-1# Attitude The requirements for rules of conversation and the negative experiences already indicate that participants, lecturers as well as students, expect an attitude of appreciation. In this context, students indirectly point out once again the processual nature of gaining communication skills. They suggest that lecturers should state that students’ communication does not have to be perfect. This is complemented well by the attitude of the lecturers who indicate that they should encourage students and stimulate processes of reflection. KL8-Student: “ That perhaps it is also communicated - by the lecturers - that not everything has to be perfect at the end of the training, because a lot still, yes, comes afterwards. So there will be many situations that I have not yet experienced in my training and that I cannot respond perfectly to every situation and that I, as an individual, do not affect every person the way I would like to. ” #00:55:07-7# Implementation of AI output Lecturers and students welcome the idea of CoSy providing feedback on verbal and para-verbal foundations of communication. For the didactic implementation, the interviews show that there are speech qualities that are considered as highly relevant. But students do not consider themselves as passive recipients of feedback. They state that they want to be involved in the feedback process actively and they phrase that they do not want to be left alone with feedback. Students point out, that CoSy output should not be used to evaluate performance. It must be interpreted and discussed, which requires time. In terms of content, the lecturers and students would like to talk about concrete ideas for improving performance and to identify gaps in professional knowledge, such as forgotten anamnesis modules or treatment errors. KL1-S tudent 1: “ But for example in the choice of words there can be alternative suggestions, so to say: 'look, you have used these, these, these words, there are possibly better alternatives' um (...), so I imagine that is quite feasible. ” #01:01:33-9# KL8-L : “ And I could imagine that one might train a machine to say "okay that was too much background information" or […] certain terms that could have been used in this case I can train a machine well on that, because that is trained first with standardised cases and then comes to the more complex. "the terms that occur in this case were missing", for example, somehow pain, visual analogue scale, delirium, assessment, that would be helpful, I think. […].” #00:49:04# In addition to this imaginable added value of the CoSy output, it also becomes clear that not all speech qualities are considered highly relevant. Students are less interested in feedback on the pitch of their voice. They do however wish for feedback on non-verbal communication such as gestures, facial expressions and body language. Overall, CoSy output alone is not sufficient, but is a piece of the puzzle. 4. Discussion The interviews have given insight into the experiences and perceptions of students and lecturers in communication training in higher education. The analysis revealed multiple elements that informed interviewees’ perceptions. Overall, the participants are very open to the use of CoSy. Without stating it directly, the ideas and perceptions of the interviewees show that participants assume that CoSy will be an instrument that will meet the quality criteria of objectivity and reliability. The high confidence in the objectivity of the CoSy output aligns itself with scientific research, that explains high reliance on AI (17). The issues raised by the interviewees are therefore not related to the quality of the CoSy output, but mainly to the nature of the output and the framework in which the output is embedded. The first question, “What are the required prerequisites for integrating an AI-based learning platform into communication training in healthcare programmes?” led to three main requirements. Firstly, the social interaction with a demand for an appreciative and respectful attitude. As the most mentioned and experienced communication scenarios were lecturer-guided, the attitude of the lecturers rather than that of the students was the subject of discussion. These finding is in accordance with previous research literature since the most used and most studied method for simulation debriefing is the facilitator-guided method and not the self-guided method (18). Students indicated that they would like emotional support from the lecturers, including encouragement when communication skills are not yet perfect. Our findings are in lockstep with empirical evidence as studies have consistently demonstrated that learning processes are impact positively when students perceive their lecturers as supportive, caring and interested in their success (19). Secondly, the analysis shows that participants wish to be guided through the debriefing process. This was already mentioned while talking about the communication scenarios but was demanded more clearly for the debriefing phase. Our results are consistent with literature which stated that it is important that debriefers or facilitators be aware of how they communicate and which questions they ask to promote optimal learning (20,21). The interviewees themselves have mentioned the idea of using a guideline during the debriefing. A debriefing tool, a scripted guide, seems to be an optimal tool to help to transform experience into learning. It would support both, the high level of facilitation by following a defined structure and a high student-centred reflection by using (preformulated) phrases. Students in our interviews provide valuable insights and clearly demand that they want to be involved in the process and participate actively. This agrees with theory which describes that reflection is an essential learning component of debriefing (22) and that students should be iteratively engaged in the reflective cognitive work (23). Thirdly, even though an evaluation of the reported speech qualities by CoSy would be possible, and was mentioned as an idea in the interviews, the interpretation of the data, the cognitive work, should be carried out by the participants. It is much more likely that communication training becomes even more demanding when the implementation of CoSy output is added since this introduces objective data. It is not a question of whether one perceived a speech rate to be fast or slow, because the speech rate can now be quantified. This could lead to taking the CoSy output as a diagnosis, as a fact which does not need to be discussed. Against the background of the interviews, however, CoSy output should be interpreted more as an instrument that gives the participants clues. Just as an x-ray gives clues about a fracture, the CoSy output gives clues about our speech behaviour. However, in both examples, the way one deals with the information received must be interpreted individually: What do I do with the data supplied, how do I interpret it? Is my fast speech rate appropriate or do I want to take care and speak more slowly in similar situations in the future? It seems to be all about the right questions. By exchanging and engaging with other people's knowledge and thinking, ones’ views and the perception of the communication situation can be broadened, with CoSy output being a piece of knowledge. Lecturers and students emphasise that CoSy is an additional and complementary tool and cannot replace existing communication training due to the non-verbal and emotional aspects in communication. These are highly complex and individual, so that, according to the interviewees, corresponding AI-based derivations alone are viewed sceptically. We assume that CoSy output can be used to deepen and to stimulate the discussion and a stimulating discussion in turn leads to the lecturer being able to retreat. Fanning & Gaba (24) already formulated this paradox our interviewees described: A high level of facilitation implies a low level of involvement by the facilitator. Many elements for the design of the communication scenarios could be identified (second question). The participants had positive experiences with both actors and peers, but in the interests of realism, lecturers and students prefer actors. For the communication situations themselves, the integration of the CoSy is more easily imaginable in standardised situations which are more predictable in their structure. Closely related to this, participants state the need to repeat communication training sessions to make skills development visible. Furthermore, standardised situations would have the advantage of higher comparability, when learning trajectories are to be presented idiosyncratically. This in turn presupposes a capability on the part of CoSy, namely the data storage, which leads to many ethical questions like to whom does the data belong, how long and where should it be stored? In this context, the question of who has access to the CoSy output must be answered not only for data storage in the long run, but also be answered directly for the didactic embedding during the debriefing phase. Do all involved, peers, lecturers and actors, have access to the output, does the individual output belong to the actors or is the lecturer the one who introduces the output in a suitable place and puts it up for discussion during debriefing? The interviews showed that the experiences to date were more lecturer-guided than peer-guided. In this current study mainly lecturers were the ones keeping an eye on the target. This suggests that the CoSy output in the debriefing process should be provided by the lecturers. On the other hand, the students emphasised that they want to be actively involved in the process, from which it could be concluded that the actors themselves decide which speech qualities should be discussed in the debriefing and when. Although experiences were mentioned and shared by the lecturers, information on applied methods was vague. Very little mention was made on how the CoSy output should be didactically embedded in the communication training (question 4). This question could not be answered sufficiently and needs to be sensitively tried out in practice and evaluated in future training sessions. The amount of time needed for the whole training depends on different factors. This is an important aspect, as elements that were repeatedly rated negatively by students were time constraints. An experienced lecturer may be highly efficient in the appropriate timing and use of questions in contrast to a novice. Lecturers might place different emphasis on self-guided discussions in contrast to lecturer focused discussions, with learner-centred discussions requiring more time. Overall, communication training needs time. As aforementioned CoSy is seen as an additional piece of the puzzle. For the framework of future skills training with CoSy, interpretation of interviews leads to the assumption that more time will be needed at various points for teaching and for courses themselves. For this, it cannot be assumed that the use of CoSy will save time, quite the contrary. The thought of conversation optimisation by CoSy reflects the high level of openness towards CoSy implementation. This, in connection with the desire and demand for a safe learning environment, means that care must be taken, especially on the part of lecturers, to handle this output responsibly. The implementation of CoSy requires high quality and reliability of AI analysis. To prevent the use of false data and produce a best didactical result CoSy must quantify and explain its output reliably. It is recommended to integrate cognitive forcing functions that provoke analytical thinking (25). The CoSy output should be used to track the learning objective and to report back relevant speech qualities. The lecturers should see themselves as co-learners. CoSy output should not be used, and this was clearly stated by students, to measure performance. The study has several limitations. The results reflect the perspectives of lecturers and students at the University of Lübeck and are applicable to this context. They cannot be transferred to other universities without limitations. Purposive sampling and sampling maximal variation (13) allowed for the participation of faculty and students from a variety of disciplines. However, due to the different levels of development of the healthcare programmes, not all perspectives could be considered. At the time of data collection, the clinical psychology & psychotherapy programme was still in the process of being established, so that no experience of the students could be drawn on. Likewise, the perspective of the speech and language therapy students is missing. Overall, the recruitment and scheduling of appointments for focus groups with the students proved to be challenging. The reason for this was probably the high workload in the healthcare programmes and the number of examinations during the period of data collection. As a result, only three to five students participated in the focus groups, which possibly limited the interactions between them. In addition, only students with positive attitudes towards communication training may have participated, so negative attitudes are underrepresented in the sample. To support critical voices in the discussions the interviewers were from another faculty. The interviewed lecturers had a broad background of experience in teaching. Again, no lecturer from the clinical psychology & psychotherapy and speech and language therapy could be included. At the time of data collection, students and lecturers had no experience with the integration of an AI-based platform into teaching. The identified perspectives and attitudes of the interviewees are based on their imaginations. Especially the students thought beyond the prelims. They imagined interaction with CoSy, assuming that it would have the characteristics of a voice chatbot or conversational agent, by expressing the wish that it could make suggestions for conversational optimisation or by providing an avatar. This goes beyond the planned capabilities of CoSy as a learning platform and speech recogniser without the capability of response in a natural way. It is possible that more detailed and concrete settings for the integration of the AI-based learning platform would be described if practical experience had already been gained. Overall, the sample showed diversity in teaching and study experience, age, and clinical expertise. The structuring qualitative content analysis (12) enabled a systematic approach, the identification of central themes and the interrelationships of the categories. Strengths of the analysis are the systematic linking of perspectives through triangulation and the analysis by an interprofessional team. Individual pre-assumptions and category development were continuously reflected and discussed in the interprofessional team. In addition, the results were presented and reflected several times in the entire team and in the scientific advisory board of the project LABORATORY. Students are also members of the advisory board; unfortunately, a member checking (13) with the students participating in the data collection was not possible due to organisational reasons. For these various reasons, data saturation could not be achieved and was not the goal of the study. Further qualitative surveys are planned in the project to collect the experiences of lecturers and students in the use of CoSy in communication training. Conclusions By implementing CoSy output in an appropriate way, namely with facilitation and with lecturers as co-learners, it seems to be able to support the process of learning and to enrich the communication skill training. Lecturers are key to students learning in simulation training, but facilitating through debriefing is not a linear, one-way distribution of learning. As the skill of the debriefer is of great importance in ensuring the best learning experience, lecturers should receive facilitation training. A tool for structured debriefings should be used to facilitate the debriefing phase and sufficient time must be available for debriefing sessions. Although the participants, especially the lecturers, see great potential for contributions to reflective learning, concrete ideas for methodological embedding need to be developed in the future. More homogeneity in the curricula and evaluation of communication training should be sought in the future. This will allow for a better understanding of how communication skills training works. In some healthcare programmes at the University of Lübeck, currently, only one single communication training takes place. This must be critically reconsidered in the future design of communication training. Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the University of Lübeck (number 2022-408). Informed consent to participate was obtained from all the participants for study. Participants had the opportunity to withdraw their written consent for the interview at any time. The participating students were compensated with 20 €. Consent for publication Not applicable. Availability of data and materials The anonymised dataset used and/or analysed during the current study is available from the corresponding author (Hanna Brodowski, [email protected] ) on reasonable request. Competing interests The authors declare that they have no competing interest. Funding This work is funded by the German Federal Ministry of Education and Research (BMBF) and the regional government of the state of Schleswig-Holstein, Germany under project number 16DHBKI075. Authors' contributions The manuscript has been read and approved by all named authors. All authors have contributed substantially to the work presented in this article. H.B. was the major contributor in writing the manuscript. She recruited participants, conducted interviews, analysed, and interpreted data. A.D. contributed to the writing of the results. She recruited participants, conducted interviews, analysed, and interpreted data. M.M.K. contributed to the writing of the results. She recruited participants, conducted interviews, analysed, and interpreted data. M.A.O. contributed to the writing of the introduction. She critically revised the manuscript and interpreted data. F.S. critically revised the manuscript and interpreted data. C.P. critically revised the manuscript and interpreted data. K.R. conceived the original idea and supervised the project. She contributed to the writing of the methods. She analysed and interpreted data and critically revised the manuscript. Acknowledgement Not applicable. References Ouyang F, Zheng L, Jiao P. Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Educ Inf Technol. Juli 2022;27(6):7893–925. Knowles E. The Oxford dictionary of phrase and fable. 2nd ed. Oxford: Oxford University Press; 2005. Howick J, Moscrop A, Mebius A, Fanshawe TR, Lewith G, Bishop FL, u. a. Effects of empathic and positive communication in healthcare consultations: a systematic review and meta-analysis. J R Soc Med. Juli 2018;111(7):240–52. Horvath AO, Del Re AC, Flückiger C, Symonds D. Alliance in individual psychotherapy. Psychotherapy. 2011;48(1):9–16. Da Cunha Oliveira M, Silva Menezes M, Cunha De Oliveira Y, Marques Vilas Bôas L, Villa Nova Aguiar C, Gomes Silva M. Novice medical students’ perception about bad news training with simulation and spikes strategy. PEC Innov. Dezember 2023;2:100106. Schildmann J, Kupfer S, Burchardi N, Vollmann J. Teaching and evaluating breaking bad news: A pre–post evaluation study of a teaching intervention for medical students and a comparative analysis of different measurement instruments and raters. Patient Educ Couns. Februar 2012;86(2):210–9. Liu X, Rohrer W, Luo A, Fang Z, He T, Xie W. Doctor–patient communication skills training in mainland China: A systematic review of the literature. Patient Educ Couns. Januar 2015;98(1):3–14. Smith S, Hanson JL, Tewksbury LR, Christy C, Talib NJ, Harris MA, u. a. Teaching Patient Communication Skills to Medical Students: A Review of Randomized Controlled Trials. Eval Health Prof. März 2007;30(1):3–21. Moral RR, Andrade-Rosa C, Molina JD, Barba EC, De Torres LP, Martín DM. Effectiveness of a communication skills training program for medical students to identify patients communicative clues. Patient Educ Couns. November 2020;103(11):2384–7. O’Brien BC, Harris IB, Beckman TJ, Reed DA, Cook DA. Standards for Reporting Qualitative Research: A Synthesis of Recommendations. Acad Med. September 2014;89(9):1245–51. Dresing T, Pehl T. Manual (on) Transcription: Transcription Conventions, Software Guides and Practical Hints for Qualitative Researchers. 2015. Kuckartz U, Rädiker S. Qualitative content analysis: methods, practice and software. SAGE; 2023. Flick U. An Introduction to Qualitative Research. 7th edition. Los Angeles London New Delhi Singapore Washington, DC Melbourne: SAGE; 2023. 606 S. Eppich W, Cheng A. Promoting Excellence and Reflective Learning in Simulation (PEARLS): Development and Rationale for a Blended Approach to Health Care Simulation Debriefing. Simul Healthc J Soc Simul Healthc. April 2015;10(2):106–15. Zigmont JJ, Kappus LJ, Sudikoff SN. The 3D Model of Debriefing: Defusing, Discovering, and Deepening. Semin Perinatol. April 2011;35(2):52–8. Tavares W, Eppich W, Cheng A, Miller S, Teunissen PW, Watling CJ, u. a. Learning Conversations: An Analysis of the Theoretical Roots and Their Manifestations of Feedback and Debriefing in Medical Education. Acad Med. Juli 2020;95(7):1020–5. Passi S, Vorvoreanu M. Overreliance on AI: Literature Review [Internet]. Microsoft; 2022 Juni. Report No.: MSR-TR-2022-12. Verfügbar unter: https://www.microsoft.com/en-us/research/publication/overreliance-on-ai-literature-review/ Sawyer T, Eppich W, Brett-Fleegler M, Grant V, Cheng A. More Than One Way to Debrief: A Critical Review of Healthcare Simulation Debriefing Methods. Simul Healthc J Soc Simul Healthc. Juni 2016;11(3):209–17. Li Y, Zhang L. Exploring the relationships among teacher–student dynamics, learning enjoyment, and burnout in EFL students: the role of emotional intelligence. Front Psychol. 8. Januar 2024;14:1329400. Husebø SE, Dieckmann P, Rystedt H, Søreide E, Friberg F. The Relationship Between Facilitators’ Questions and the Level of Reflection in Postsimulation Debriefing. Simul Healthc J Soc Simul Healthc. Juni 2013;8(3):135–42. Kihlgren P, Spanager L, Dieckmann P. Investigating novice doctors’ reflections in debriefings after simulation scenarios. Med Teach. 4. Mai 2015;37(5):437–43. Nagle A, Foli KJ. Student-Centered Reflection in Debriefing: A Concept Analysis. Clin Simul Nurs. Februar 2020;39:33–40. Kolb DA. Experiential learning: experience as the source of learning and development. Second edition. Upper Saddle River, New Jersey: Pearson Education LTD; 2015. Fanning RM, Gaba DM. The Role of Debriefing in Simulation-Based Learning. Simul Healthc J Soc Simul Healthc. 2007;2(2):115–25. Buçinca Z, Malaya MB, Gajos KZ. To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making. 2021 [zitiert 19. September 2023]; Verfügbar unter: https://arxiv.org/abs/2102.09692 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4225671","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":289141306,"identity":"68a44fa1-ec25-41a5-a6bf-cf41fa5f5bf1","order_by":0,"name":"Hanna Brodowski","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABKElEQVRIie2RP2rDMBSHXwjEixOvMi7tFWQKagOlZ5EI2IvrDoGQoRRDwVl8gUAO4RvUwaDJbVeVePDkyYNHQ0tb/0knJ9BsHfSBeJLQx/vxBCCR/ENwV6J60aaic4CBB1l7HAGof1AuW4WeoADzoNsfVa6UF55VkN5ryozrVXJth7snD5h/42oKp1Ase8o0cG0zgHy6DnLLUAW6C9Nto1hzPbCiwSbpB4scglSIMRYO2UFZK4KtKubHLBSKNxz7feWtIPrnXnmvSmRjwZou3+y5Vb76Sv3S+O0i6mB0r0QsRKNoOPYOKAUxznCO9SC3P9QEmetGoa+zOUosut3wA8EcohfLFNcTi82KP15MhJ1Bubh1tRU3s+KhP+VOPHLf/pdEIpFITucHx9Z2zlw+keoAAAAASUVORK5CYII=","orcid":"","institution":"University of Lübeck","correspondingAuthor":true,"prefix":"","firstName":"Hanna","middleName":"","lastName":"Brodowski","suffix":""},{"id":289141307,"identity":"d6db8255-49e9-41bd-ba64-9d4be15a568a","order_by":1,"name":"Anna Dammermann","email":"","orcid":"","institution":"University of Lübeck","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Dammermann","suffix":""},{"id":289141308,"identity":"356a56b6-1810-44d0-a180-e1aadd52676e","order_by":2,"name":"Muriel Marieke Kinyara","email":"","orcid":"","institution":"University of Lübeck","correspondingAuthor":false,"prefix":"","firstName":"Muriel","middleName":"Marieke","lastName":"Kinyara","suffix":""},{"id":289141309,"identity":"1e0d070e-a862-4c8e-9550-9c37ab2b083d","order_by":3,"name":"Martina Andrea Obst","email":"","orcid":"","institution":"University of Lübeck","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"Andrea","lastName":"Obst","suffix":""},{"id":289141310,"identity":"533aa506-ac57-4093-bbbc-d32e54fdee44","order_by":4,"name":"Fabian Samek","email":"","orcid":"","institution":"University of Lübeck","correspondingAuthor":false,"prefix":"","firstName":"Fabian","middleName":"","lastName":"Samek","suffix":""},{"id":289141311,"identity":"40421e2a-16f8-4c62-8df1-fc56a7bfca56","order_by":5,"name":"Corinna Peifer","email":"","orcid":"","institution":"University of Lübeck","correspondingAuthor":false,"prefix":"","firstName":"Corinna","middleName":"","lastName":"Peifer","suffix":""},{"id":289141312,"identity":"d4961960-ee65-48a9-bcfd-593a19602464","order_by":6,"name":"Katharina Roese","email":"","orcid":"","institution":"University of Lübeck","correspondingAuthor":false,"prefix":"","firstName":"Katharina","middleName":"","lastName":"Roese","suffix":""}],"badges":[],"createdAt":"2024-04-06 04:59:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4225671/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4225671/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54594578,"identity":"03429f34-7e89-4ef1-b3ca-ff744cbb9d50","added_by":"auto","created_at":"2024-04-12 18:28:31","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105747,"visible":true,"origin":"","legend":"\u003cp\u003eIdentified major themes\u003c/p\u003e","description":"","filename":"image1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4225671/v1/556e7d04e80731cce4d0a928.jpg"},{"id":54594574,"identity":"556f5ad2-b63d-4c8c-9190-7d769b626638","added_by":"auto","created_at":"2024-04-12 18:28:30","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":99446,"visible":true,"origin":"","legend":"\u003cp\u003eOn which speech qualities would you like to have AI feedback – lecturers\u003c/p\u003e","description":"","filename":"image2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4225671/v1/271d191dfd1e0a6bd176f662.jpg"},{"id":54594635,"identity":"9e292a1b-f8ec-4373-8d0f-936a83436502","added_by":"auto","created_at":"2024-04-12 18:28:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87402,"visible":true,"origin":"","legend":"\u003cp\u003eOn which speech qualities would you like to have AI feedback – students\u003c/p\u003e","description":"","filename":"image3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4225671/v1/37c007d538fdb8f816c426f4.jpg"},{"id":64211851,"identity":"7fb5d9f9-0735-4a10-a587-62eaf904f81c","added_by":"auto","created_at":"2024-09-10 07:48:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":876194,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4225671/v1/ae0922b6-d0b2-47f0-b71d-e6d11bdb3217.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Student and lecturer perceptions of the use of an AI to improve communication skills in healthcare: an interview study","fulltext":[{"header":"1. Introduction ","content":"\u003cp\u003eAI-supported systems are increasingly making inroads into education, as evidenced by the growing body of research in this domain (1). AI is defined as \u0026lsquo;the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages\u0026rsquo; (2). A valuable application of AI lies in the field of communication skills training. Sufficient communication skills are essential for healthcare professionals\u0026rsquo; ability to deliver patient-centred care. Empathetic conversations foster positive relationships between healthcare professionals and patients (3) and contribute to the success of therapy (4). The best way to acquire communication skills is to train in a simulated environment as complex skills like communication are best learned through experimental learning (5,6). Evidence suggests that communication skills training improves students' communication abilities (7,8) and equips them with enhanced communication skills for clinical practice (9).\u003c/p\u003e\n\u003cp\u003eAs a result, simulation-based medical education has gained prominence in healthcare profession programmes, including those at the University of L\u0026uuml;beck. The University of L\u0026uuml;beck offers nine health degree programmes, a unique diversity in Germany, which provides an ideal environment for patient-oriented and interprofessional learning, as well as the acquisition of communication skills. Across all healthcare programmes, various teaching modules include active training in communication skills. These modules emphasise self-awareness, involving role plays and exercises based on case studies, with actors simulating patients or interprofessional counterparts. Consequently, over the past three years, a medical skills training and practice centre has expanded, accompanied by the establishment of additional teaching and seminar rooms for feedback-based communication training. The role play scenarios or simulated patient encounters are continually refined, optimised, and updated at L\u0026uuml;beck. They vary in scope and content across different healthcare programmes, encompassing emergency situations, explaining pain mechanisms to patients, and communicating with patients who have dementia. Overall, a substantial number of students and lecturers have undergone communication training and garnered experiences in the context of medical-based learning over the past decades. Both students and especially lecturers can draw on a wealth of experience including debriefing sessions that reflect the fact that debriefing requires skills with complex emotional and cognitive aspects. To further enhance and individualise existing patient-centred communication training, the University of L\u0026uuml;beck is presently developing an AI-supported learning assistance system, hereafter called CoSy (Communication System). CoSy is, at this point, an imaginary system. In contrast to communication platforms like SimConverse\u0026copy;, which uses interactive AI characters to play the role of any patient or colleague, or ChatGPT, users won't be able to engage in conversations with CoSy. CoSy will be a speech recognizer, able to give feedback to verbal (what did you say) and para-verbal (how did you say it) foundations of communication.\u003c/p\u003e\n\u003cp\u003eA crucial step in the development of such a system is a requirement analysis with regard to the future users. This current study aims to explore the experiences and perceptions of students as well as lecturers, seeking to understand what they think about the possible use of an AI-based feedback system, which is supposed to be implemented in their (potentially emotional) challenging learning context. The requirement analysis was conducted to lay the groundwork for the project, to set future users expectations and to document all critical needs. The research questions are:\u003c/p\u003e\n\u003cp\u003eFrom the students\u0026rsquo; and lecturers\u0026rsquo; perspectives\u0026hellip;\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cp\u003e\u0026hellip; what are the required prerequisites for integrating an AI-based learning platform into communication training in healthcare programmes?\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u0026hellip; how should the communication scenarios be designed?\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u0026hellip; which speech qualities are considered useful when integrating an AI-based learning platform?\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u0026hellip; in what way should the output of the AI-based learning platform be didactically embedded in the communication situation?\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"2. Methods ","content":"\u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e This interview study used a qualitative, descriptive design to explore students\u0026rsquo; and lecturers\u0026rsquo; experiences and perceptions of communication training. The research was conducted and continuously reflected by an interprofessional research team. In addition, the procedure and the results of the data analysis were presented, discussed, and reflected within the project advisory board consisting of experts from research and practice. In order to ensure the rigor and trustworthiness of the study the recommended standards for reporting qualitative research (SRQR) were followed (10).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample and recruitment\u0026nbsp;\u003c/strong\u003eParticipants were recruited by specifically addressing lecturers and students (purposive sampling). One module was selected for each healthcare programme in which communication is a central part of the teaching. The aim was to recruit interview partners from every healthcare programme at the University of L\u0026uuml;beck to maximise the variation of perspectives included. Students must have previously participated in practical communication exercises during their studies and attend the corresponding healthcare programmes. Lecturers of the healthcare programmes must have experience in communication education. The sample must also include lecturers and students from monoprofessional as well as interprofessional modules. Information about the study, its aims, and data protection regulations concerning the interviews were provided to potential participants via e-mail.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u0026nbsp;\u003c/strong\u003eOn the premise that\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eall interviewees were aware of the study procedure and provided their written consent, data collection was conducted on focus groups of health profession students and individual interviews with health profession lecturers. The interviews were based on two semi-structured interview guides, one for lecturers (individual interviews) and one for students (focus groups). Both interview guides were developed based on the research questions and discussions with the interprofessional research team. In an initial expert workshop, in form of a brainstorming session, a list of speech qualities, like \u0026ldquo;terminology\u0026rdquo;, \u0026ldquo;length of pauses\u0026rdquo; or \u0026ldquo;adjusting one\u0026rsquo;s volume depending on the patient\u0026rdquo; were compiled. Both interview guides included questions on the same four central themes: 1) current communication scenarios in teaching and characteristics of communication, 2) current debriefing for the development of communication skills in the health professions, 3) the use of an AI-based learning platform in communication situations and in relation to speech qualities and 4) conditions for integrating the AI-based learning platform. The guidelines included open questions or narrative invitations. The wordings for lectures and students were e.g: \u0026ldquo;What are your wishes for feedback by an AI-based learning platform after a conversation with a patient?\u0026rdquo; Or: \u0026ldquo;What additional benefits could an assistance system bring to teaching?\u0026rdquo; In order to explore participants\u0026rsquo; views on the speech qualities, they were asked towards the end of the interviews to rate which of these speech qualities an AI should provide feedback on. For this purpose, the participants were asked to assign previously prepared cards with speech qualities to the categories \u0026quot;very important,\u0026quot; \u0026quot;important,\u0026quot; and merely \u0026quot;nice-to-have\u0026rdquo;. The interview guide also included an explanation to give interviewees a realistic description of CoSy and what it will actually be capable of. The wording was as follows: \u003cem\u003e\u0026ldquo;In many everyday appliances, like voice-controlled assistance systems in cars, and entertainment programmes artificial intelligence is already integrated to give feedback. The game Sing-Star\u0026copy; is an example of what feedback on voice pitch can look like. (Sing Star\u0026copy; is a karaoke game that analyses a singers timing and pitch which is then compared to the original track.) Imagine that there is an assistance system, that systematically evaluates conversations and speech behaviour. The following questions focus on what is spoken in a situation and about speech qualities on which the assistance system can provide feedback.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePrior to the start of data collection, the interview guide was pretested in two interviews, and minor adjustments were made, especially regarding the order of the questions and the openness of the wording. Socio-demographic data of the participants was collected using a structured data collection sheet. The interviews took place between May and August 2022. To create a trusting atmosphere and avoid socially desirable answers, focus groups were conducted by members of the interprofessional research team from differing programmes. All interviews were audio-recorded. Following the data collection, the interviewers prepared a protocol (interview postscript).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u0026nbsp;\u003c/strong\u003eThe interviews and focus groups were transcribed verbatim according to the rules of Dresing \u0026amp; Pehl (2015). The interviewer was consulted in case of uncertainties within the transcription process. During the transcription, the data was anonymised. The analysis was based on structural content analysis (12) using the software MAXQDA 22 (VERBI Software, 2021). A structuring qualitative content analysis allows the development of central themes within a data-based deductive-inductive approach. The data analysis for this article specifically focused on AI-related findings from the interviews. The interviews were analysed separately in the first step. In order to develop an initial understanding of the data, interviews were read carefully and intensively, taking into account the research questions (initiating text work). Using a deductive approach, a preliminary category system was developed for the main categories based on the central themes of the interview guidelines. Data was coded with these main categories. Subcategories were then formed inductively from the data collected during the initial interviews. Subsequently, the entire dataset was analysed using this category system, and anchor examples were identified. During the data analysis the category system was adapted and refined. Coding was initially performed in teams of two researchers to ensure a consistent approach. The remaining data was then coded individually and crosschecked by a third researcher. Afterwards, the results of the analysis were contrastively related to each other (perspective triangulation) and relationships and connections between the topics were identified using the constant comparative method (13). These interrelations between the themes were visualised. The results of the analysis were continuously discussed and reflected upon by the entire research team.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e27 health professionals participated in this study: seven lecturers and 20 students (Table 1). Lecturers and students from seven modules took part. Two student focus groups were interprofessional, five monoprofessional. The seven individual interviews with the lecturers lasted an average of 71 minutes (ranging from 59 to 101 minutes), while the five focus group interviews lasted an average of 112 minutes (ranging from 95 to 130 minutes). Overall, a total of 17 hours and 35 minutes of audio has been recorded.\u003c/p\u003e\n\u003cp\u003eTable 1: Characteristics of study population\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"84%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLecturers\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=7\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e(7 Individual Interviews)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudents\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=20\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e(5 Focus Groups)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003egender, women (N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003eAge M (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e44 (33-52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e24.5 (21-41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth Profession\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003emedicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003eemergency medical care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003emedical psychology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003emidwifery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003enursing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003eoccupational therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003ephysiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\" valign=\"top\"\u003e\n \u003cp\u003eclinical psychotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\"\u003e\n \u003cp\u003eTeaching experience, years M (min\u003cstrong\u003e-\u003c/strong\u003emax)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\"\u003e\n \u003cp\u003e13.0 (6-23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\"\u003e\n \u003cp\u003eNumber of semesters, M (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\"\u003e\n \u003cp\u003e6 (4-14)\u0026nbsp;\u003cem\u003eMissing=2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.464646464646464%\"\u003e\n \u003cp\u003eClinical experience, years M (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\"\u003e\n \u003cp\u003e12 (0-20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\"\u003e\n \u003cp\u003e2.25 (.42-16)\u0026nbsp;\u003cem\u003eMissing=1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eResults in this article specifically focus on AI-related findings and revealed four major themes which were addressed in the interviews and focus groups. The four major themes are \u0026ldquo;conditions\u0026rdquo;, \u0026ldquo;communication scenarios\u0026rdquo;, \u0026ldquo;AI-based learning platform\u0026rdquo;, and \u0026ldquo;debriefing\u0026rdquo; (Fig 1). The analysis of the interviews shows that the participants have confidence that the AI output will have the potential to deepen the learning process and to complement the debriefing. This shows that CoSy is not perceived as an alien piece of the puzzle. The optimal framework conditions and prerequisites for the communication training became apparent. They are summarised under the topic \u0026ldquo;conditions\u0026rdquo;. Analysis shows that the following presented three individual parts \u0026ldquo;communication scenarios\u0026rdquo;, \u0026ldquo;AI-based learning platform\u0026rdquo;, and \u0026ldquo;debriefing\u0026rdquo; influence each other and must be well harmonised.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.1 Conditions\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participants assume that the use of CoSy has an impact on the achievement of communication skills. They have the understanding that CoSy can record and analyse what is being said. According to the interviewees, CoSy needs to have information about a conversation in order to be able to analyse what is being said in a dialogue. Examples of important contextual information was mentioned, e.g. the age of the patient, the room in which the conversation takes place and the time frame.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL5-Lecturer: \u0026ldquo;Does it [AI] need information about the speakers? (...) so it should know who the patient is and who the therapist is (..) I would think (..) it probably needs information whether it is a man or a woman (..) because something like pitch has a large range of variance but probably differs. [\u0026hellip;]\u003c/em\u003e\u003cem\u003e.\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;#00:45:31-9#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL6-Student2: \u0026ldquo;Maybe also an overview of the setting, so if we imagine a practice, in which room is it carried out, what are the room conditions and what is in front of it, behind it? If there are perhaps colleagues in a motor activity room and it is super loud, then of course I have to speak up. [\u0026hellip;]\u003c/em\u003e\u003cem\u003e.\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;#0:58:51.0#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssumed added value\u003c/strong\u003e In addition, many interviewees assume that CoSy can give more comprehensive feedback on communication in comparison to the lecturers and peers, as it can record and process more data than humans. Students and lecturers highlighted that CoSy could be particularly valuable for speech qualities which are often difficult for humans to assess. Participants think beyond face-to-face teaching and imagine usability in many other settings such as self-study in the SkillsLab or at home on a computer. The students also imagine the application in practical everyday clinical settings - carrying CoSy in their pocket.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL2-Student3: \u0026ldquo;Well, what I was just thinking about, which would also be cool, is if you simply had the chance to go back to the ward after university, if there are patients who voluntarily take part in it. It would be similar to the examintaion-courses or anamnesis courses, where you simply go alone or in pairs to the patient\u0026rsquo;s room, have conversations and record them, without it having to be in such a fixed framework, but that you simply have it for yourself as feedback. [\u0026hellip;].\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u0026nbsp;\u003c/em\u003e\u003cem\u003e#01:34:31-4#\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNature of the data\u0026nbsp;\u003c/strong\u003eAs in many technology or AI-based cases, the interviewees assume that CoSy will provide objective and neutral feedback. It is assumed that the AI output states facts about communication that are less subjective than feedback from lecturers or fellow students. This presumed objective view of a conversation seems to be an important perspective for students to add.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL6-Lecturer: \u0026ldquo;That has something objective about it, doesn\u0026apos;t it? Because otherwise you have the feeling that I have used a lot of technical terms or the students report back and then it was still only three times, but somehow it felt very dominant. (\u0026hellip;) We know this ourselves, when we conduct an interview, you think you have left huge pauses in the interview situation, but when you transcribe it, it was a maximum of one minute and it felt very, very long in the interview. So that would also be something objective, how long a minute really is, in order to develop a feeling for it. (.) It also has something neutral. So when other students give each other feedback, it\u0026apos;s not so easy to expose yourself to such an interview situation and then someone else tells you how it was and maybe it\u0026apos;s like a machine that says \u0026apos;you were too fast\u0026apos; is perhaps easier to accept than when the lecturer says it. [\u0026hellip;].\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;#00:51:55-8#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL6-Student1: \u0026ldquo;And the AI could perhaps also look at more situations overall, so to speak, and yes, if you get feedback from a lecturer or something, that then always refers to just one situation. And the AI could perhaps more EASILY look at several situations and see whether this is a problem more often.\u0026rdquo; #1:25:48.5#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL2-Lecturer: \u0026ldquo;(...) I see a neutral evaluation of situations. Um. Highly standardised. With the possibility of being able to focus on other things in the situations simultaneously. And to create a certain evaluability.\u0026rdquo; 00:58:22-4#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL1-Student2: \u0026ldquo;So I think it makes more sense to use the AI as something additional, outside, giving feedback. [\u0026hellip;].\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;#00:20:58-3#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTime and teaching organisation\u0026nbsp;\u003c/strong\u003eIt is important for the students to have a reasonable degree of data sovereignty and control over their data. Students in particular like the data to be stored in order to use CoSy output to show long-term trends in their learning processes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL6-Student2: \u0026ldquo;Maybe also (...) that once you have received a feedback, that there is a follow-up situation or several, that you can also compare things, for example, if they have given you, the system has given you feedback (laughs) and there is something like that again at a later time, that you can draw comparisons or has something improved or not and if not, why not. So that you can use that again. That this AI is simply used several times in situations.\u0026rdquo; #1:32:18.7#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe integration of CoSy output in communication skills training will require more time than the current teaching of communication skills. Lecturers also assume a higher time requirement because they expect a more intensive preparation and follow-up for skills training.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL5-Lecturer: \u0026ldquo;Yes, I think (.) at least the lecturers should be trained (.), what they can do and what they can\u0026apos;t do, so that you know where you can use it [the AI] well, so where you see your own possibilities. I think it would be nice if you could shift part of the teaching to this SkillsLab. (...) in the SkillsLab (..) and that in the self-learning time that belongs to each module you can then also motivate (..) to practise this situation. So I believe that in teaching, when it is here on campus (...) the lecturers must first be activated. They are certainly obliged to (...) really use it (...) and not to find it funny or (...) to be afraid of the technology.\u0026rdquo; #01:10:00-0#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL4-Lecturer: \u0026ldquo;But what you can already gather is that there is still a moment when a human being has to be there to pick up the AI again. Someone who also says, what does this mean now, what does this mean, and who also enters into a conversation with the student who then sees this. At least for the first time. For a first contact. As if we were to conduct two interviews, we let the AI run along, we look to see where there are problems, where perhaps not. Um, and then you can let the student train independently.\u003c/em\u003e\u003cem\u003e\u0026nbsp;[\u0026hellip;].\u003c/em\u003e\u003cem\u003e\u0026rdquo; #00:50:21-4#\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eLecturers are aware that the use of CoSy will require workload outside the classroom. They see a need for preparatory training with the practical application, like handling the user interface and the didactic implementation, which includes the decisions when and how to discuss the AI output. Both lecturers and eventually students need to train applying the AI system. Lecturers must be instructed in the use of the system outside of teaching. For the students, sensitising instruction should take place within the framework of the respective teaching module.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRooms and equipment\u0026nbsp;\u003c/strong\u003eFor various steps, such as the first interaction of lecturers and students with the AI system, but also for the later skills training with CoSy itself, certain premises are needed. These must include technical equipment as well as suitable materials and furniture for different scenarios.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL2-Lecturer: \u0026ldquo;Digital devices (\u0026hellip;) to make that as close to reality as possible, with tactile and auditory, visual stimuli\u0026nbsp;\u003c/em\u003e\u003cem\u003e[are needed\u003c/em\u003e\u003cem\u003e] (...) Otherwise, at the end of the day it\u0026apos;s like a video film when I see the sequences and then decide what to do. I never get the stress level and the level in there to then really say, I forget that this is not real now.\u0026rdquo; #01:02:42-9#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL8-Lecturer: \u0026ldquo;So what we actually always need is (\u0026hellip;) a certain simulation of the typical conditions for the situation. So, you can also (...) / you could also play it more abstractly in a seminar room, of course. But then it certainly loses some of its authenticity and perhaps makes it more difficult for the students to put themselves in this situation and imagine how they would react. And also for the actors, that\u0026apos;s how we perceive it, it\u0026apos;s also helpful to have a few CORE utensils with them. So it doesn\u0026apos;t have to be the full programme but the bag, the bed, the pyjamas um yes.\u0026rdquo; #0:10:57.1#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.2 Communication scenarios\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis theme outlines the essential prerequisites and preferences of study participants regarding the design of communication scenarios in general. Additionally, the limitations perceived by the participants concerning the use of CoSy are described.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRange of content and themes\u0026nbsp;\u003c/strong\u003eParticipants identified several communication scenarios that could potentially be enhanced with AI support, including medical anamnesis, goal-setting and counselling interviews, emergency management, and interprofessional communication situations like handovers and case discussions. What they all have in common is that they are largely standardised and follow a structured conversational format.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL1-Lecturer: \u0026ldquo;Yes, the scenario must be clearly defined in some way, like / it should be, for example / it should be a feedback conversation, and in a feedback conversation, we define / need to include these specific aspects. And these aspects can be verbally represented by the following words or something like that. [\u0026hellip;].\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e \u003cem\u003e#00:48:11-2#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn contrast to standardised situations, there are more complex situations, such as scenarios primarily involving manual techniques and procedural workflows, or face-to-face patient-care scenarios. In these scenarios, there is an expectation for more variability in the content of the conversation and therefore it is more difficult to specify terms or aspects that need to be said. Often, in the more complex situations, the atmosphere of the conversation and feelings matter more than specific content. The flow of these conversations is less predictable and exhibits greater variability in each individual scenario. In these cases, meaningful AI output seems to be only limitedly conceivable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL8-Lecturer: \u0026ldquo;Only very, very limited scenarios where it might be about structuring a conversation or A LOT OF INFORMATION / uh, for example, using the SBAR-framework. And I could imagine that, uh, that maybe a machine could be used for THAT. I could imagine it for highly standardised situations, which actually exclude almost every classic patient-care situation.\u0026rdquo; #00:49:04#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComposition of actors\u0026nbsp;\u003c/strong\u003eThe communication training sessions described in the interviews were structured as one-on-one scenarios, with two possible conversation configurations. In some cases, one student acted in their own profession and the other as a patient or a patient\u0026rsquo;s relative. In most instances, a professional (paid) actor portrayed the patient\u0026rsquo;s role to create a more realistic atmosphere. The background information on their role is known to the actors in both options, which is particularly important to bring the scenario close to reality.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL6-S\u003c/em\u003e\u003cem\u003etudent\u003c/em\u003e\u003cem\u003e2:\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003cem\u003eI\u0026apos;m thinking of this situation, the patient is in bed as an old woman in need of care and I\u0026apos;m supposed to motivate her to eat breakfast or something. I think it\u0026apos;s a very true-to-life situation. And she didn\u0026apos;t make it easy for me. I really had to think a bit about \u0026quot;how do I do this now?\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;And I really liked that. And of course it\u0026apos;s completely different if someone you know was lying there. Then you might lose the ro/ the actual role. (...) That\u0026apos;s what I would have liked to see more of throughout my studies, (...) no super artificial situations, but really from life. And this professional actress also did it very well (laughs). Yes.\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;#0:45:45.3#\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the interests of realism, lecturers and students prefer actors (standardised patients). However, this is only the case for adult patients who are played by actors. Lecturers and students criticise the connection to reality in children as patients; these cannot be staged by adults, regardless of whether they are actors or fellow students. At this point, it can be mentioned that the participants are again thinking beyond the planned capabilities of CoSy and imagined AI-controlled avatars as communication partners alongside actors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL7-Lecturer: \u0026ldquo;Maybe that would be a form where something could be done. That means that they have different forms of avatars that have certain information that is important or that is not important.\u0026nbsp;\u003c/em\u003e\u003cem\u003e[...].\u0026rdquo;\u0026nbsp;\u003c/em\u003e\u003cem\u003e#01:05:41\u003c/em\u003e\u003cem\u003e#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL6-Lecturer: \u0026ldquo;Communication with children, as I said, I still have a bit of hope for the AI (laugh) whether there are any great ideas. Yes, because that\u0026apos;s something (\u0026hellip;) where I think we need more practical relevance to be able to practise it. You somehow can\u0026apos;t do that with the actors.\u0026rdquo; #00:23:40-2#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOverall, students had good experiences with both options, actors and fellow students in the role of patients. Beyond communication skills, it can help students to slip into the patient role and experience what that feels like. There were no experiences mentioned for real patients who volunteered to play a role for training purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFrequency and location of training\u0026nbsp;\u003c/strong\u003eThe general conditions have already shown that teaching must be organised in such a way that a communication scenarios can be practiced several times. Especially students describe the learning of communication skills as a process with a need for repetition. Participants consider CoSy suitable to be used throughout the learning process and thus in every session.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL6-Student2: \u0026ldquo;And that it\u0026apos;s also used regularly, that [...] that it\u0026apos;s somehow a continuous part of\u0026nbsp;\u003c/em\u003eit.\u003cem\u003e\u0026nbsp;[\u0026hellip;]\u0026rdquo; #1:53:44.7#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL5-Lecturer: \u0026ldquo;I\u0026apos;d prefer shorter situations, practicing them more frequently, so that the next time you can go back and see if it has improved.\u0026rdquo; #01:04:55-4#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStudents shared and reflected their experiences due to the COVID-19 pandemic-related restrictions. There was a clear consensus that communication training in attendance is seen as more beneficial.\u003c/p\u003e\n\u003cp\u003eBenefits of conducting in-person sessions include a better group atmosphere and a more realistic scenario setup, as non-verbal aspects of communication cannot be adequately expressed in an online setting.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL8-Student3: \u0026ldquo;I found the online communication quite challenging because in communication, there\u0026apos;s a lot of body language involved. [...] I found it quite difficult to sit at home and try to do something, you know? I believe it would have been different in person, [\u0026hellip;] I think body language is an important tool in communication, which was completely absent. [\u0026hellip;].\u0026rdquo; #00:15:53-2#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.3 AI-based learning platform \u0026ndash; CoSy\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ideas on what special functions and characteristics CoSy must have, what CoSy should look like, and how the system should be accessed in detail vary. There is an agreement that it must be accessible to both students and lecturers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFeatures\u003c/strong\u003e The categorisation of speech qualities, on which participants would like to have AI feedback, into \u0026quot;very important\u0026quot;, \u0026quot;important\u0026quot; or merely \u0026quot;nice-to-have\u0026quot;, was part of the interviews and focus groups. The seven lecturers were given some time to categorise each of the proposed features during their interviews (Fig 2). In the focus groups the categorisation was more freely designed. The students first each categorised for themselves and then got into conversation with each other and discussed their categorisation. Some of the speech qualities were considered very unimportant and were not even categorised by the students. Additionally, the categorisation was partly done in partner work, therefore, the number of categorised qualities varies in comparison to the lecturers (Fig 3). Qualities are arranged in descending order of priority in both figures.\u003c/p\u003e\n\u003cp\u003eThe need to repeat communication training creates requirements for the function of CoSy. Students and lecturers suggest that CoSy should document the speech qualities and the development of learning over time. CoSy output should be stored to enable students to compare their CoSy output parameters of current communication with CoSy output parameters of previous communication situations. This additionally implies the existence of a user profile, so that the students gain access to their data. This proposal applies to both the comparison of the own individual performance and the comparison with a reference group. Interviewees suggest that the reference group should consist of students from the same profession or students who have a similar level of learning (from beginners to experts).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL8- Lecturer: \u0026ldquo;It would certainly be good if the student could somehow save it, especially when he wants to practice it again, so that you can see a progression. I would also like that.\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e#00:50:37#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign\u0026nbsp;\u003c/strong\u003eFor the CoSy output there are different forms imaginable, which seem almost contradictory. On the one hand, students and lecturers envision neutral and non-judgemental feedback. This form of feedback should be as quantitative as possible including facts and figures. On the other hand, evaluative feedback is envisioned classifying into desirable and undesirable or using a traffic light system e.g., which would relieve lecturers and students of the task of interpretation. Furthermore, they envision that CoSy output uncovers gaps in the conversation and reports back if something in the communication is debatable. In this context CoSy output could point out suggestions for a better performance. A physical output could be a visual or textual print of the feedback.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL4-Lecturer: \u0026ldquo;Yes, I always find it so exciting with transcripts, how people talk. And sometimes you\u0026apos;re not even aware of it, because you pay attention to many other things, um, I don\u0026apos;t know, eye contact and um, was the hairstyle correct, um, but when you see what you\u0026apos;ve said, you can see how often you don\u0026apos;t really finish a sentence one hundred percent, that your voice / always goes down at the end, that you leave a pause. Um, that\u0026apos;s very conspicuous when it\u0026apos;s reflected in writing in black and white.\u0026rdquo; #00:38:44-9#\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOverall, the results show that lecturers and students would like CoSy to be clearly structured and designed, allowing an intuitive navigation. Although it is imaginable in principle that the function of CoSy is to provide output on a wide range of speech qualities, participants prefer the selection of specific speech qualities. A suggested function is to be able to select the desired speech qualities individually directly before the communication situation, as not all speech qualities are considered important for feedback in every single situation. This would narrow down the feedback in terms of content.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL6-Student2: \u0026ldquo;Maybe you can also select certain topics for feedback, which are then only a topic and which are then only reported back. So that it\u0026apos;s not too much.\u0026rdquo; #1:36:12.9#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTiming\u003c/strong\u003e The analysis revealed that both students and lecturers are accustomed to post-event debriefing. Providing feedback within-event appears to be uncommon. Students address speech qualities that can be provided as feedback during the scenario, such as volume or speech rate, if defined in advance. In addition, within-event feedback also requires a reference value, such as \u0026quot;too loud\u0026quot; or \u0026quot;too quiet\u0026quot;, to directly adapt one\u0026apos;s own speech behaviour and thus creating added value. Even though feedback during the communication situation is conceivable, post-event debriefing is clearly favoured overall.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL2-Student5: \u0026ldquo;So, I think I would be distracted during that. I mean, that\u0026apos;s a good point about the volume, then I can react to it in the moment. But I believe, for me, it would be better to receive it afterward.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL2-Student3: \u0026ldquo;I would also say, in the end is actually better because otherwise, during the conversation, you would be constantly preoccupied with what this system is telling me right now. It shifts the focus away from the conversation.\u0026rdquo; #01:20:38-3#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL-5-Lecturer: \u0026ldquo;I believe it would disrupt the conversation. (...) I think it would be better at the end (...) after because if I were to get a red light during the conversation, I can imagine it would completely throw me off and disrupt the flow of my conversation (...) so (...) I don\u0026apos;t think it would be beneficial.\u0026rdquo; #01:04:34-9#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.4 Debriefing\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRole play scenarios are commonly framed by briefing and debriefing phases as stated by Eppich \u0026amp; Cheng (14) or Zigmont (15). In this current article the \u0026quot;learning conversations\u0026quot; (16) following the role play scenarios are called \u0026ldquo;feedback\u0026rdquo; or \u0026ldquo;debriefing\u0026rdquo; interchangeably as the interviewees did not differentiate between these terms. Debriefing is considered important by the interviewees, also quite independently of CoSy, and takes up a large part of the narratives. Students in particular share many of their experiences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFacilitation\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAccording to the participants of this study, debriefing should be structured using a manual \u0026quot;feedback guide\u0026quot; (for students) or an \u0026quot;observation guide\u0026quot; (for lecturers), which includes aspects to be observed and questions to promote learning. In preparation for this conversational phase, participants also describe the need to review and establish rules or conversation principles. They pointed out that conversation rules should be considered both in the communication scenario and in the debriefing.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL4-L\u003c/em\u003e\u003cem\u003eecturer\u003c/em\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003cem\u003eFeedback rules, the normal standard, that you always learn. So to say, to always convey I-messages, how do things affect me, what impression does it make, how can I imagine that it could perhaps be brought into a more optimi\u003c/em\u003e\u003cem\u003es\u003c/em\u003e\u003cem\u003eed direction. And [I\u003c/em\u003e\u003cem\u003e]\u0026nbsp;\u003c/em\u003e\u003cem\u003egive really concrete examples. I use a concrete example, to say what I noticed and [I\u003c/em\u003e\u003cem\u003e]\u0026nbsp;\u003c/em\u003e\u003cem\u003ealso give concrete ideas on how it could have been packaged differently if necessary. And also the explanation of why I would have liked it differently perhaps, this is very, very important to me.\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;#00:11:54-9#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL1-S\u003c/em\u003e\u003cem\u003etudent:\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026ldquo;I could imagine that with the help of a tool like this, you wouldn\u0026apos;t forget anything and would also emphasi\u003c/em\u003e\u003cem\u003es\u003c/em\u003e\u003cem\u003ee such things more, [\u0026hellip;]\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eso yes, exactly, maybe that wouldn\u0026apos;t be such a bad idea, to get a little guide for reflection of communication.\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u0026nbsp;\u003c/em\u003e\u003cem\u003e#00:48:12-4#\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL1-L\u003c/em\u003e\u003cem\u003eecturer: \u0026ldquo;\u003c/em\u003e\u003cem\u003eSometimes we work out wish lists of what we would like to receive when we get feedback and how we should give feedback. And then based on various feedback steps, so to speak, we also work out formulations on how to formulate something well, exactly, and there are also these, let\u0026apos;s say, general rules that you refer to concrete and observable behaviour. And also changeable behaviour. So that you don\u0026apos;t give feedback on something that the person can\u0026apos;t change anyway. [\u0026hellip;\u003c/em\u003e\u003cem\u003e] Observe good conversation management aspects, such as I-messages and also not making moral value judgements in any way. Talking directly to the perso\u003c/em\u003e\u003cem\u003en [\u0026hellip;].\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u0026nbsp;\u003c/em\u003e\u003cem\u003e#00:33:22-2#\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEven though self-reflection of both simulation participants was addressed in some examples, the interviews mainly dealt with the lecturers\u0026rsquo; responsibility and their (desired) behaviour. All in all, interviews show that the guiding through the debriefing phase is mostly the responsibility of the lecturers. Students expect lecturers to navigate them through the debriefing and to focus on learning objectives. A self-guided facilitation did not emerge as a central theme.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLearning strategy\u003c/strong\u003e All in all, participants have an idea of the requirements of debriefing and its process elements. It often comes through in the interviews how important and formative this phase is, especially for the students. Interdisciplinary feedback is rated as extremely helpful by the students; one lecturer also emphasises that peer feedback is more effective than feedback from the lecturers. The analysis also confirms that debriefing is a critical component in the process of learning. Even though students stated a positive learning attitude in this context, it comes with little surprise that they also described negative experiences. Too little time for debriefing was discussed. It was mentioned that the debriefing took place afterwards \u0026ldquo;in the corridor\u0026rdquo; with the consequence that conversation did not go as deep as it was expected. Additionally, there was mention of a performance paramount. Students compared their conversational performance with each other, thinking about who was better and who was worse. Students said that they felt more evaluated and judged by lecturers than constructively criticised. Signs that the learning environment was no longer perceived as safe are expressions such as \u0026ldquo;lucky to come out of it\u0026ldquo; or feeling \u0026ldquo;paraded\u0026ldquo;.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL8-S\u003c/em\u003e\u003cem\u003etudent\u003c/em\u003e\u003cem\u003e2:\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003cem\u003eWell, I still remember that we always had very little time for the feedback and I was often somehow still in the situation before and then the next situation was already going on. So that somehow things were brought up and then not finished [\u0026hellip;]\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eand we would quickly move on, but somehow we were still thinking about the situation before.\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e#00:30:48-4#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL2-S\u003c/em\u003e\u003cem\u003etudent\u003c/em\u003e\u003cem\u003e3:\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003cem\u003eWhat I think is important is that there is also a focus on feedback because what I remember, for example, is that some of the professional drama patients gave feedback saying, \u0026apos;Yes, there was something I didn\u0026apos;t like, but I can\u0026apos;t really say what\u0026apos;. So, positive feedback from the course leader and from the fellow students, basically everything is fine, and then you get \u0026apos;I didn\u0026apos;t like something\u0026apos; in the last sentence, and you can\u0026apos;t do anything with that, because you don\u0026apos;t have anything to start with, to improve on.\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;#00:28:07-1#\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAttitude\u003c/strong\u003e The requirements for rules of conversation and the negative experiences already indicate that participants, lecturers as well as students, expect an attitude of appreciation. In this context, students indirectly point out once again the processual nature of gaining communication skills. They suggest that lecturers should state that students\u0026rsquo; communication does not have to be perfect. This is complemented well by the attitude of the lecturers who indicate that they should encourage students and stimulate processes of reflection.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL8-Student:\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003cem\u003eThat perhaps it is also communicated - by the lecturers - that not everything has to be perfect at the end of the training, because a lot still, yes, comes afterwards. So there will be many situations that I have not yet experienced in my training and that I cannot respond perfectly to every situation and that I, as an individual, do not affect every person the way I would like to.\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e#00:55:07-7#\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplementation of AI output\u0026nbsp;\u003c/strong\u003eLecturers and students welcome the idea of CoSy providing feedback on verbal and para-verbal foundations of communication. For the didactic implementation, the interviews show that there are speech qualities that are considered as highly relevant. But students do not consider themselves as passive recipients of feedback. They state that they want to be involved in the feedback process actively and they phrase that they do not want to be left alone with feedback. Students point out, that CoSy output should not be used to evaluate performance. It must be interpreted and discussed, which requires time. In terms of content, the lecturers and students would like to talk about concrete ideas for improving performance and to identify gaps in professional knowledge, such as forgotten anamnesis modules or treatment errors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL1-S\u003c/em\u003e\u003cem\u003etudent\u003c/em\u003e\u003cem\u003e1:\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003cem\u003eBut for example in the choice of words there can be alternative suggestions, so to say: \u0026apos;look, you have used these, these, these words, there are possibly better alternatives\u0026apos; um (...), so I imagine that is quite feasible.\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e\u003cem\u003e\u0026nbsp;#01:01:33-9#\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKL8-L\u003c/em\u003e\u003cem\u003e: \u0026ldquo;\u003c/em\u003e\u003cem\u003eAnd I could imagine that one might train a machine to say \u0026quot;okay that was too much background information\u0026quot; or\u0026nbsp;\u003c/em\u003e\u003cem\u003e[\u0026hellip;]\u003c/em\u003e\u003cem\u003e\u0026nbsp;certain terms that could have been used in this case I can train a machine well on that, because that is trained first with standardised cases and then comes to the more complex. \u0026quot;the terms that occur in this case were missing\u0026quot;, for example, somehow pain, visual analogue scale, delirium, assessment, that would be helpful, I think.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e[\u0026hellip;].\u0026rdquo;\u0026nbsp;\u003c/em\u003e\u003cem\u003e#00:49:04#\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn addition to this imaginable added value of the CoSy output, it also becomes clear that not all speech qualities are considered highly relevant. Students are less interested in feedback on the pitch of their voice. They do however wish for feedback on non-verbal communication such as gestures, facial expressions and body language. Overall, CoSy output alone is not sufficient, but is a piece of the puzzle.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe interviews have given insight into the experiences and perceptions of students and lecturers in communication training in higher education. The analysis revealed multiple elements that informed interviewees\u0026rsquo; perceptions. Overall, the participants are very open to the use of CoSy. Without stating it directly, the ideas and perceptions of the interviewees show that participants assume that CoSy will be an instrument that will meet the quality criteria of objectivity and reliability. The high confidence in the objectivity of the CoSy output aligns itself with scientific research, that explains high reliance on AI (17). The issues raised by the interviewees are therefore not related to the quality of the CoSy output, but mainly to the nature of the output and the framework in which the output is embedded.\u003c/p\u003e\n\u003cp\u003eThe first question, \u0026ldquo;What are the required prerequisites for integrating an AI-based learning platform into communication training in healthcare programmes?\u0026rdquo; led to three main requirements. Firstly, the social interaction with a demand for an appreciative and respectful attitude. As the most mentioned and experienced communication scenarios were lecturer-guided, the attitude of the lecturers rather than that of the students was the subject of discussion. These finding is in accordance with previous research literature since the most used and most studied method for simulation debriefing is the facilitator-guided method and not the self-guided method (18). Students indicated that they would like emotional support from the lecturers, including encouragement when communication skills are not yet perfect. Our findings are in lockstep with empirical evidence as studies have consistently demonstrated that learning processes are impact positively when students perceive their lecturers as supportive, caring and interested in their success (19).\u003c/p\u003e\n\u003cp\u003eSecondly, the analysis shows that participants wish to be guided through the debriefing process. This was already mentioned while talking about the communication scenarios but was demanded more clearly for the debriefing phase. Our results are consistent with literature which stated that it is important that debriefers or facilitators be aware of how they communicate and which questions they ask to promote optimal learning (20,21). The interviewees themselves have mentioned the idea of using a guideline during the debriefing. A debriefing tool, a scripted guide, seems to be an optimal tool to help to transform experience into learning. It would support both, the high level of facilitation by following a defined structure and a high student-centred reflection by using (preformulated) phrases. Students in our interviews provide valuable insights and clearly demand that they want to be involved in the process and participate actively. This agrees with theory which describes that reflection is an essential learning component of debriefing (22) and that students should be iteratively engaged in the reflective cognitive work (23).\u003c/p\u003e\n\u003cp\u003eThirdly, even though an evaluation of the reported speech qualities by CoSy would be possible, and was mentioned as an idea in the interviews, the interpretation of the data, the cognitive work, should be carried out by the participants. It is much more likely that communication training becomes even more demanding when the implementation of CoSy output is added since this introduces objective data. It is not a question of whether one perceived a speech rate to be fast or slow, because the speech rate can now be quantified. This could lead to taking the CoSy output as a diagnosis, as a fact which does not need to be discussed. Against the background of the interviews, however, CoSy output should be interpreted more as an instrument that gives the participants clues. Just as an x-ray gives clues about a fracture, the CoSy output gives clues about our speech behaviour. However, in both examples, the way one deals with the information received must be interpreted individually: What do I do with the data supplied, how do I interpret it? Is my fast speech rate appropriate or do I want to take care and speak more slowly in similar situations in the future? It seems to be all about the right questions. By exchanging and engaging with other people\u0026apos;s knowledge and thinking, ones\u0026rsquo; views and the perception of the communication situation can be broadened, with CoSy output being a piece of knowledge. Lecturers and students emphasise that CoSy is an additional and complementary tool and cannot replace existing communication training due to the non-verbal and emotional aspects in communication. These are highly complex and individual, so that, according to the interviewees, corresponding AI-based derivations alone are viewed sceptically. We assume that CoSy output can be used to deepen and to stimulate the discussion and a stimulating discussion in turn leads to the lecturer being able to retreat. Fanning \u0026amp; Gaba (24) already formulated this paradox our interviewees described: A high level of facilitation implies a low level of involvement by the facilitator.\u003c/p\u003e\n\u003cp\u003eMany elements for the design of the communication scenarios could be identified (second question). The participants had positive experiences with both actors and peers, but in the interests of realism, lecturers and students prefer actors. For the communication situations themselves, the integration of the CoSy is more easily imaginable in standardised situations which are more predictable in their structure. Closely related to this, participants state the need to repeat communication training sessions to make skills development visible. Furthermore, standardised situations would have the advantage of higher comparability, when learning trajectories are to be presented idiosyncratically.\u003c/p\u003e\n\u003cp\u003eThis in turn presupposes a capability on the part of CoSy, namely the data storage, which leads to many ethical questions like to whom does\u0026nbsp;the data belong, how long and where should\u0026nbsp;it\u0026nbsp;be stored?\u003cem\u003e\u0026nbsp;\u003c/em\u003eIn this context, the question of who has access to the CoSy output must be answered not only for data storage in the long run, but also be answered directly for the didactic embedding during the debriefing phase. Do all involved, peers, lecturers and actors, have access to the output, does the individual output belong to the actors or is the lecturer the one who introduces the output in a suitable place and puts it up for discussion during debriefing? The interviews showed that the experiences to date were more lecturer-guided than peer-guided. In this current study mainly lecturers were the ones keeping an eye on the target. This suggests that the CoSy output in the debriefing process should be provided by the lecturers. On the other hand, the students emphasised that they want to be actively involved in the process, from which it could be concluded that the actors themselves decide which speech qualities should be discussed in the debriefing and when. Although experiences were mentioned and shared by the lecturers, information on applied methods was vague. Very little mention was made on how the CoSy output should be didactically embedded in the communication training (question 4). This question could not be answered sufficiently and needs to be sensitively tried out in practice and evaluated in future training sessions.\u003c/p\u003e\n\u003cp\u003eThe amount of time needed for the whole training depends on different factors. This is an important aspect, as elements that were repeatedly rated negatively by students were time constraints. An experienced lecturer may be highly efficient in the appropriate timing and use of questions in contrast to a novice. Lecturers might place different emphasis on self-guided discussions in contrast to lecturer focused discussions, with learner-centred discussions requiring more time. Overall, communication training needs time. As aforementioned CoSy is seen as an additional piece of the puzzle. For the framework of future skills training with CoSy, interpretation of interviews leads to the assumption that more time will be needed at various points for teaching and for courses themselves. For this, it cannot be assumed that the use of CoSy will save time, quite the contrary.\u003c/p\u003e\n\u003cp\u003eThe thought of conversation optimisation by CoSy reflects the high level of openness towards CoSy implementation. This, in connection with the desire and demand for a safe learning environment, means that care must be taken, especially on the part of lecturers, to handle this output responsibly. The implementation of CoSy requires high quality and reliability of AI analysis. To prevent the use of false data and produce a best didactical result CoSy must quantify and explain its output reliably. It is recommended to integrate cognitive forcing functions that provoke analytical thinking (25). The CoSy output should be used to track the learning objective and to report back relevant speech qualities. The lecturers should see themselves as co-learners. CoSy output should not be used, and this was clearly stated by students, to measure performance.\u003c/p\u003e\n\u003cp\u003eThe study has several limitations. The results reflect the perspectives of lecturers and students at the University of L\u0026uuml;beck and are applicable to this context. They cannot be transferred to other universities without limitations. Purposive sampling and sampling maximal variation (13) allowed for the participation of faculty and students from a variety of disciplines. However, due to the different levels of development of the healthcare programmes, not all perspectives could be considered. At the time of data collection, the clinical psychology \u0026amp; psychotherapy programme was still in the process of being established, so that no experience of the students could be drawn on. Likewise, the perspective of the speech and language therapy students is missing. Overall, the recruitment and scheduling of appointments for focus groups with the students proved to be challenging. The reason for this was probably the high workload in the healthcare programmes and the number of examinations during the period of data collection. As a result, only three to five students participated in the focus groups, which possibly limited the interactions between them. In addition, only students with positive attitudes towards communication training may have participated, so negative attitudes are underrepresented in the sample. To support critical voices in the discussions the interviewers were from another faculty. The interviewed lecturers had a broad background of experience in teaching. Again, no lecturer from the clinical psychology \u0026amp; psychotherapy and speech and language therapy could be included.\u003c/p\u003e\n\u003cp\u003eAt the time of data collection, students and lecturers had no experience with the integration of an AI-based platform into teaching. The identified perspectives and attitudes of the interviewees are based on their imaginations. Especially the students thought beyond the prelims. They imagined interaction with CoSy, assuming that it would have the characteristics of a voice chatbot or conversational agent, by expressing the wish that it could make suggestions for conversational optimisation or by providing an avatar. This goes beyond the planned capabilities of CoSy as a learning platform and speech recogniser without the capability of response in a natural way. It is possible that more detailed and concrete settings for the integration of the AI-based learning platform would be described if practical experience had already been gained.\u003c/p\u003e\n\u003cp\u003eOverall, the sample showed diversity in teaching and study experience, age, and clinical expertise. The structuring qualitative content analysis (12) enabled a systematic approach, the identification of central themes and the interrelationships of the categories. Strengths of the analysis are the systematic linking of perspectives through triangulation and the analysis by an interprofessional team. Individual pre-assumptions and category development were continuously reflected and discussed in the interprofessional team. In addition, the results were presented and reflected several times in the entire team and in the scientific advisory board of the project LABORATORY. Students are also members of the advisory board; unfortunately, a member checking (13) with the students participating in the data collection was not possible due to organisational reasons. For these various reasons, data saturation could not be achieved and was not the goal of the study. Further qualitative surveys are planned in the project to collect the experiences of lecturers and students in the use of CoSy in communication training.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eBy implementing CoSy output in an appropriate way, namely with facilitation and with lecturers as co-learners, it seems to be able to support the process of learning and to enrich the communication skill training. Lecturers are key to students learning in simulation training, but facilitating through debriefing is not a linear, one-way distribution of learning. As the skill of the debriefer is of great importance in ensuring the best learning experience, lecturers should receive facilitation training. A tool for structured debriefings should be used to facilitate the debriefing phase and sufficient time must be available for debriefing sessions. Although the participants, especially the lecturers, see great potential for contributions to reflective learning, concrete ideas for methodological embedding need to be developed in the future. More homogeneity in the curricula and evaluation of communication training should be sought in the future. This will allow for a better understanding of how communication skills training works. In some healthcare programmes at the University of L\u0026uuml;beck, currently, only one single communication training takes place. This must be critically reconsidered in the future design of communication training.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the University of L\u0026uuml;beck (number 2022-408). Informed consent to participate was obtained from all the participants for study. Participants had the opportunity to withdraw their written consent for the interview at any time. The participating students were compensated with 20 \u0026euro;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe anonymised dataset used and/or analysed during the current study is available from the corresponding author (Hanna Brodowski, [email protected]) on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is funded by the German Federal Ministry of Education and Research (BMBF) and the regional government of the state of Schleswig-Holstein, Germany under project number 16DHBKI075.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe manuscript has been read and approved by all named authors. All authors have contributed substantially to the work presented in this article. H.B. was the major contributor in writing the manuscript. She recruited participants, conducted interviews, analysed, and interpreted data. A.D. contributed to the writing of the results. She recruited participants, conducted interviews, analysed, and interpreted data. M.M.K. contributed to the writing of the results. She recruited participants, conducted interviews, analysed, and interpreted data. M.A.O. contributed to the writing of the introduction. She critically revised the manuscript and interpreted data. F.S. critically revised the manuscript and interpreted data. C.P. critically revised the manuscript and interpreted data. K.R. conceived the original idea and supervised the project. She contributed to the writing of the methods. She analysed and interpreted data and critically revised the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOuyang F, Zheng L, Jiao P. Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Educ Inf Technol. Juli 2022;27(6):7893\u0026ndash;925. \u003c/li\u003e\n\u003cli\u003eKnowles E. The Oxford dictionary of phrase and fable. 2nd ed. Oxford: Oxford University Press; 2005. \u003c/li\u003e\n\u003cli\u003eHowick J, Moscrop A, Mebius A, Fanshawe TR, Lewith G, Bishop FL, u. a. Effects of empathic and positive communication in healthcare consultations: a systematic review and meta-analysis. J R Soc Med. Juli 2018;111(7):240\u0026ndash;52. \u003c/li\u003e\n\u003cli\u003eHorvath AO, Del Re AC, Fl\u0026uuml;ckiger C, Symonds D. Alliance in individual psychotherapy. Psychotherapy. 2011;48(1):9\u0026ndash;16. \u003c/li\u003e\n\u003cli\u003eDa Cunha Oliveira M, Silva Menezes M, Cunha De Oliveira Y, Marques Vilas B\u0026ocirc;as L, Villa Nova Aguiar C, Gomes Silva M. Novice medical students\u0026rsquo; perception about bad news training with simulation and spikes strategy. PEC Innov. Dezember 2023;2:100106. \u003c/li\u003e\n\u003cli\u003eSchildmann J, Kupfer S, Burchardi N, Vollmann J. Teaching and evaluating breaking bad news: A pre\u0026ndash;post evaluation study of a teaching intervention for medical students and a comparative analysis of different measurement instruments and raters. Patient Educ Couns. Februar 2012;86(2):210\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eLiu X, Rohrer W, Luo A, Fang Z, He T, Xie W. Doctor\u0026ndash;patient communication skills training in mainland China: A systematic review of the literature. Patient Educ Couns. Januar 2015;98(1):3\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eSmith S, Hanson JL, Tewksbury LR, Christy C, Talib NJ, Harris MA, u. a. Teaching Patient Communication Skills to Medical Students: A Review of Randomized Controlled Trials. Eval Health Prof. M\u0026auml;rz 2007;30(1):3\u0026ndash;21. \u003c/li\u003e\n\u003cli\u003eMoral RR, Andrade-Rosa C, Molina JD, Barba EC, De Torres LP, Mart\u0026iacute;n DM. Effectiveness of a communication skills training program for medical students to identify patients communicative clues. Patient Educ Couns. November 2020;103(11):2384\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Brien BC, Harris IB, Beckman TJ, Reed DA, Cook DA. Standards for Reporting Qualitative Research: A Synthesis of Recommendations. Acad Med. September 2014;89(9):1245\u0026ndash;51. \u003c/li\u003e\n\u003cli\u003eDresing T, Pehl T. Manual (on) Transcription: Transcription Conventions, Software Guides and Practical Hints for Qualitative Researchers. 2015. \u003c/li\u003e\n\u003cli\u003eKuckartz U, R\u0026auml;diker S. Qualitative content analysis: methods, practice and software. SAGE; 2023. \u003c/li\u003e\n\u003cli\u003eFlick U. An Introduction to Qualitative Research. 7th edition. Los Angeles London New Delhi Singapore Washington, DC Melbourne: SAGE; 2023. 606 S. \u003c/li\u003e\n\u003cli\u003eEppich W, Cheng A. Promoting Excellence and Reflective Learning in Simulation (PEARLS): Development and Rationale for a Blended Approach to Health Care Simulation Debriefing. Simul Healthc J Soc Simul Healthc. April 2015;10(2):106\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eZigmont JJ, Kappus LJ, Sudikoff SN. The 3D Model of Debriefing: Defusing, Discovering, and Deepening. Semin Perinatol. April 2011;35(2):52\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eTavares W, Eppich W, Cheng A, Miller S, Teunissen PW, Watling CJ, u. a. Learning Conversations: An Analysis of the Theoretical Roots and Their Manifestations of Feedback and Debriefing in Medical Education. Acad Med. Juli 2020;95(7):1020\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003ePassi S, Vorvoreanu M. Overreliance on AI: Literature Review [Internet]. Microsoft; 2022 Juni. Report No.: MSR-TR-2022-12. Verf\u0026uuml;gbar unter: https://www.microsoft.com/en-us/research/publication/overreliance-on-ai-literature-review/\u003c/li\u003e\n\u003cli\u003eSawyer T, Eppich W, Brett-Fleegler M, Grant V, Cheng A. More Than One Way to Debrief: A Critical Review of Healthcare Simulation Debriefing Methods. Simul Healthc J Soc Simul Healthc. Juni 2016;11(3):209\u0026ndash;17. \u003c/li\u003e\n\u003cli\u003eLi Y, Zhang L. Exploring the relationships among teacher\u0026ndash;student dynamics, learning enjoyment, and burnout in EFL students: the role of emotional intelligence. Front Psychol. 8. Januar 2024;14:1329400. \u003c/li\u003e\n\u003cli\u003eHuseb\u0026oslash; SE, Dieckmann P, Rystedt H, S\u0026oslash;reide E, Friberg F. The Relationship Between Facilitators\u0026rsquo; Questions and the Level of Reflection in Postsimulation Debriefing. Simul Healthc J Soc Simul Healthc. Juni 2013;8(3):135\u0026ndash;42. \u003c/li\u003e\n\u003cli\u003eKihlgren P, Spanager L, Dieckmann P. Investigating novice doctors\u0026rsquo; reflections in debriefings after simulation scenarios. Med Teach. 4. Mai 2015;37(5):437\u0026ndash;43. \u003c/li\u003e\n\u003cli\u003eNagle A, Foli KJ. Student-Centered Reflection in Debriefing: A Concept Analysis. Clin Simul Nurs. Februar 2020;39:33\u0026ndash;40. \u003c/li\u003e\n\u003cli\u003eKolb DA. Experiential learning: experience as the source of learning and development. Second edition. Upper Saddle River, New Jersey: Pearson Education LTD; 2015. \u003c/li\u003e\n\u003cli\u003eFanning RM, Gaba DM. The Role of Debriefing in Simulation-Based Learning. Simul Healthc J Soc Simul Healthc. 2007;2(2):115\u0026ndash;25. \u003c/li\u003e\n\u003cli\u003eBu\u0026ccedil;inca Z, Malaya MB, Gajos KZ. To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making. 2021 [zitiert 19. September 2023]; Verf\u0026uuml;gbar unter: https://arxiv.org/abs/2102.09692\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"AI acceptance, communication, debriefing, experimental learning, healthcare, interviews, learning platform, speech recognition","lastPublishedDoi":"10.21203/rs.3.rs-4225671/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4225671/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and objectives\u003c/strong\u003e Communication is a complex skill and key component for professionals in health care. Complex skills are best learned through experimental learning like role plays or simulated patient encounters. The aim of the present study is to explore how students and lecturers assess the conditions under which the use of an AI-based feedback system can promote the learning process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e An interview study with health profession students and lecturers was conducted using a qualitative descriptive design. Recorded audio data was transcribed and evaluated by structuring qualitative content analysis using deductive and inductive coding. The research process was conducted and continually reflected by an interprofessional research team. Ethical approval was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eUsing qualitative content analysis, four major themes were identified. These are “conditions”, “communication scenarios”, “AI-based learning platform” and “debriefing”. Lecturers and students welcome the idea of AI providing feedback on verbal and para-verbal aspects. To implement AI-based feedback into a teaching programme AI functionality should be adaptable to the specific situation. Lecturers and students highlighted that AI could be particularly valuable for speech qualities which are often difficult for humans to assess. AI could give freedom to focus on additional aspects of the conversation by documenting desirable speech qualities. Lecturers and students prefer for the AI-based feedback to be given at the end of rather than within the role play. Furthermore, they wish for communication scenarios to be analysed repeatedly in order to track progress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion \u003c/strong\u003ePracticing in a safe environment and receiving competent credible feedback, with lecturers trained in facilitation, is a prerequisite for the entire learning progress.The integration of an AI-based feedback system should be characterised by both flexibility of the AI application and standardisation of the communication scenario.\u003c/p\u003e","manuscriptTitle":"Student and lecturer perceptions of the use of an AI to improve communication skills in healthcare: an interview study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-12 18:25:40","doi":"10.21203/rs.3.rs-4225671/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d261841-18c6-4854-b610-be47b04fb583","owner":[],"postedDate":"April 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-10T07:40:24+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-12 18:25:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4225671","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4225671","identity":"rs-4225671","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}