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This article argues that the integration of artificial intelligence (AI) into healthcare, particularly under the European Union's Artificial Intelligence Act (AI-Act), poses significant implications for the doctor-patient relationship. While historically paternalistic, Western medicine now emphasises patient autonomy within a consumeristic paradigm, aided by technological advancements. However, hospitals worldwide are adopting AI more rapidly than before, potentially reshaping patient care dynamics. Three potential pathways emerge: enhanced patient autonomy, increased doctor control via AI, or disempowerment of both parties as decision-making shifts to private entities. This article contends that without addressing flaws in the AI-Act's risk-based approach, private entities could be empowered at the expense of patient autonomy. While proposed directives like the AI Liability Directive (AILD) and the revised Directive on Liability for Defective Products (revised PLD) aim to mitigate risks, they may not address the limitations of the AI-Act. Caution must be exercised in the future interpretation of the emerging regulatory architecture to protect patient autonomy and to preserve the central role of healthcare professionals in the care of their patients.

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Importance: Understanding treatment expectations of patients and their clinicians is of great importance in improving personalized medical services and enhancing patient safety systems. Objective: To investigate treatment expectations of patients and their clinicians and compare differences between both, by using a pair of validated structured assessment tools covering three key aspects/dimensions of clinical interests. Design setting and participants: This single-center cross-sectional study was conducted at Peking Union Medical College Hospital in China. The study enrolled patients aged 16 years and older receiving inpatient care and their clinicians. Patient recruitment was conducted from March 2023 to November 2023. Assessments: In addition to demographic and clinical characteristics, this study employed two validated structured assessment tools to evaluate treatment expectations among patients and their clinicians: the Hospitalized Patients' Expectations for Treatment Scale-Patient version (HOPE-P) and its counterpart, the Hospitalized Patients' Expectations for Treatment Scale-Clinician version (HOPE-C). Results: A total of 233 patients (mean [SD] age, 52.3 [15.1] years; 108 [46.4%] female) along with their clinicians, who numbered 75 in total were enrolled in this study. The distribution of total scores for HOPE-P and HOPE-C displayed similar patterns, with most scores concentrated in the higher range (above 50% of the full score). The mean HOPE-P total score was higher than that of HOPE-C (mean [SD] score, 38.78 [4.86] vs 37.49 [4.32]; t = 3.12, P = 0.002). In Dimension 2, the HOPE-P score was higher than HOPE-C (23.67 [3.20] vs 21.72 [3.03]; t = 6.98, P < 0.001). However, in Dimensions 1 and 3, HOPE-P scored lower than HOPE-C (13.37 [2.44] vs 13.84 [1.73]; t = -2.384, P < 0.018; 1.74 [1.14] vs 1.94 [1.00]; t = -2.00, P = 0.047). Certain demographic and clinical characteristics led to variations in patients' treatment expectations, including marital status, monthly family income, and smoking history. Conclusions and relevance: This cross-sectional study revealed significant differences between patients' and doctors' treatment expectations. Notably, it highlighted the need for clinicians to focus on rationalizing patients' expectations concerning treatment outcomes. Trial Registration Chinese Clinical Trial Registry Identifier: ChiCTR2300075262.

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This systematic review aims to identify the elements of doctor-patient communication in telemedicine, emerging challenges, and proposed recommendations. Four databases, including Science Direct, PubMed, Cochrane, and ProQuest, were searched using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The inclusion criteria consisted of original research papers, availability of free full text, and publications during the past 10 years. A total of 13 articles completed the selection process and satisfied the established criteria. The issues and recommendations of telemedicine communication were categorized into three distinct groups: pre-consultation, during-consultation, and post-consultation. Preparation encompasses the arranging of visual elements, safeguarding patient privacy and confidentiality, and addressing any technical challenges that may arise. The consultation encompasses nonverbal behavior, empathy, the doctor-patient connection, and a physical examination. Post-telemedicine consultations refer to medical appointments that occur after a telemedicine session, typically involving follow-up medical interactions. Telemedicine presents unique challenges in doctor-patient consultations that differ from face-to-face interactions. Therefore, clinicians must acquire communication skills specific to telemedicine to ensure effective consultations and achieve optimal health results.

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Lévinas and Derrida speak of the ontological context of human relationships in the context of the absolute priority of the Other and the unconditional law of hospitality. This has direct implications for doctor-patient relationships in the context of health care. This paper explores these philosophical and practical implications in light of a paradox that exists in all hospitality: that hostility is inevitably intertwined with hospitality. The paper explores three ways hostility can present in doctor-patient relationships: in physical violence, through paternalism, and through the violence of categorisation. While acknowledging the paradox, and the complexity of solutions, the paper considers ways to minimize this hostility. In so doing, it encourages HCPs to overcome whatever is possible so as to do the impossible: provide unconditional hospitality.

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Critics of clinical artificial intelligence (AI) suggest that the technology is ethically harmful because it may lead to the dehumanization of the doctor-patient relationship (DPR) by eliminating moral empathy, which is viewed as a distinctively human trait. The benefits of clinical empathy-that is, moral empathy applied in the clinical context-are widely praised, but this praise is often unquestioning and lacks context. In this article, I will argue that criticisms of clinical AI based on appeals to empathy are misplaced. As psychological and philosophical research has shown, empathy leads to certain types of biased reasoning and choices. These biases of empathy consistently impact the DPR. Empathy may lead to partial judgments and asymmetric DPRs, as well as disparities in the treatment of patients, undermining respect for patient autonomy and equality. Engineers should consider the flaws of empathy when designing affective artificial systems in the future. The nature of sympathy and compassion (i.e., displaying emotional concern while maintaining some balanced distance) has been defended by some ethicists as more beneficial than perspective-taking in the clinical context. However, these claims do not seem to have impacted the AI debate. Thus, this article will also argue that if machines are programmed for affective behavior, they should also be given some ethical scaffolding.

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In February 2020, the Federal Constitutional Court of Germany issued a landmark judgement on assisted suicide. It rejected as unconstitutional a law from 2015 that prohibited "assisted suicide services". It emphasized the freedom of people to shape their own lives and deaths and to seek help in doing so. In contrast, other practical problems arise when a doctor is confronted with a request for assisted suicide at the bedside in the current situation. The different perspectives and their tensions are contrasted.

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BACKGROUND: In recent years, the integration of large language models (LLMs) into healthcare has emerged as a revolutionary approach to enhancing doctor-patient communication, particularly in the management of diseases such as prostate cancer. METHODS: Our paper evaluated the effectiveness of three prominent LLMs-ChatGPT (3.5), Gemini (Pro), and Co-Pilot (the free version)-against the official Romanian Patient's Guide on prostate cancer. Employing a randomized and blinded method, our study engaged eight medical professionals to assess the responses of these models based on accuracy, timeliness, comprehensiveness, and user-friendliness. RESULTS: The primary objective was to explore whether LLMs, when operating in Romanian, offer comparable or superior performance to the Patient's Guide, considering their potential to personalize communication and enhance the informational accessibility for patients. Results indicated that LLMs, particularly ChatGPT, generally provided more accurate and user-friendly information compared to the Guide. CONCLUSIONS: The findings suggest a significant potential for LLMs to enhance healthcare communication by providing accurate and accessible information. However, variability in performance across different models underscores the need for tailored implementation strategies. We highlight the importance of integrating LLMs with a nuanced understanding of their capabilities and limitations to optimize their use in clinical settings.

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INTRODUCTION: Coproduction learning health system models clearly define the use of clinical and patient-reported data for system learning and quality improvement, but less is known about how to document formative learning about coproduction value creation over the course of a quality improvement initiative. The authors aimed to 1) assess the feasibility, utility, and acceptability of novel self-assessment tools for coproduction value creation and 2) identify domains of coproduction value creation. METHODS: The authors conducted 4 focus groups with quality improvement teams from 4 health systems in the United States and Sweden between June 2021 and September 2023. A single analyst coded transcripts and proposed themes, with investigator triangulation validating results. RESULTS: Participants found the self-assessment tools acceptable and useful. The improvement passport was seen as more feasible for routine use than the full self-assessment guide. Peer learning within the community of practice, diverse multidisciplinary improvement teams, and leadership support facilitated teams' work. Domains of coproduction value creation included communication, self-efficacy, interconnectedness, direct and indirect costs of health care utilization, health professional experience, and access to the right care. DISCUSSION: Peer learning and camaraderie within the community of practice maintained momentum among participating teams during a challenging time of limited resources and mounting responsibilities in health care settings, suggesting enhanced resiliency through approaching difficult tasks in community. CONCLUSION: The authors identified themes of coproduction value creation and drivers of engagement. Future research will draw on the measurement domains established in this study to inform the development of measures of coproduction value creation. Those measures could then be incorporated into the data-rich environments of coproduction learning health systems to enhance focus on value from service user and professional perspectives.

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Trust forms the bedrock of the doctor-patient relationship. While establishing trust is a foundational skill for healthcare providers who care for children, there is no systematic approach to teaching this skill set, nor is there formal training during medical school or residency. Traditionally, these skills have been taught by example, in an unstructured and ad hoc manner, with trainees picking it up along the way by observing and modeling their instructors. Here, we define and examine the elements of establishing trust and describe a methodology for establishing trust and managing a child's emotional state during medical encounters.

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Today the doctor-patient relationship typically takes place in a face-to-face setting. However, with the advent of artificial intelligence (AI) systems, two further interaction scenarios are possible: an AI system supports the doctor's decision regarding diagnosis and/or treatment while interacting with the patient, or an AI system could even substitute the doctor and hence a patient interacts with a chatbot (i.e., a machine) alone. Against this background, we report on an online experiment in which we analyzed data from N = 1,183 people. The data was collected in German-speaking countries (Germany, Austria, Switzerland). The participants were asked to imagine they had been suffering from medical conditions of unknown origin for some time and that they were therefore visiting a health center to seek advice from a doctor. We developed descriptions of patient-doctor interactions (referred to as vignettes), thereby manipulating the patient's interaction partner: (i) human doctor, (ii) human doctor with an AI system, and (iii) an AI system only (i.e., chatbot). Furthermore, we manipulated medical discipline: (i) cardiology, (ii) orthopedics, (iii) dermatology, and (iv) psychiatry. Based on this 3 × 4 experimental within-subjects design, our results indicate that people prefer a human doctor, followed by a human doctor with an AI system, and an AI system alone came in last place. Specifically, based on these 12 hypothetical interaction situations, we found a significant main effect of a patient's interaction partner on trust, distrust, perceived privacy invasion, information disclosure, treatment adherence, and satisfaction. Moreover, perceptions of trust, distrust, and privacy invasion predicted information disclosure, treatment adherence, and satisfaction as a function of interaction partner and medical discipline. We found that the situation in psychiatry is different from the other three disciplines. Specifically, the six outcome variables differed strongly between psychiatry and the three other disciplines in the "human doctor with an AI system" condition, while this effect was not that strong in the other conditions (human doctor, chatbot). These findings have important implications for the use of AI in medical care and in the interaction between patients and their doctors.

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Objectives: To assess the perceptions of patients with rheumatic diseases about the doctor-patient relationship and the impact on their treatment and their quality of life. Methods: A quantitative study collecting data from patients with rheumatic diseases using the following tools: (a) the Doctor-Patient Relationship Assessment Questionnaire-16 (DoPRAQ-16), assessed the quality of doctor-patient relationship, (b) the Short Form 36 (SF-36) assessed the quality of life of patients, and (c) the Health Assessment Questionnaire (HAQ), assessed the functional ability of patients. From the statistical analysis, it appears that there is no linear correlation between the DoPRAQ-16 scales and the dimensions of the SF-36 Health Survey, except for the scale of negative emotions and the dimension of Physical Functioning. The nonparametric Kruskal-Wallis H test was performed to investigate the existence of statistically significant differences between the categories of duration of the relationship with the doctor to Physical Functioning, Physical Role, Emotional Role, and Social Functioning. The test was significant (p<0.05) for the dimensions of Body Role and Social Functioning. Conclusions: Patients with long term relationship with the doctor have better health quality in the dimension of Physical Role and Social Functioning compared to people whose relationship with the doctor lasts fewer years.

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Purpose: To investigate the influence mechanism of doctor-patient communication on patients' trust, especially the mediating role of patient-physician consistency and the moderating role of perceived threat of disease. Methods: A total of 699 patients in Guangzhou, China was investigated by questionnaire. The main effect, mediating effect, and moderating effect of the model was verified by SPSS23.0 and LISREL8.71 statistical software. Results: It was revealed that doctor-patient communication has a significant positive effect on patients' trust. The consistency between patient and physician partially mediates the relationship between doctor-patient communication and patients' trust. Additionally, the perceived threat of the disease moderates the psychological process through which doctor-patient communication affects patients' trust. Conclusion: Both doctor-patient communication and patient-physician consistency have predictive effects on patients' trust. Doctor-patient communication is not only a direct influence on patient trust but also an indirect influence mediated by patient-physician consistency. Perceived threat of disease moderates the psychological process through which doctor-patient communication affects patients' trust. Specifically, compared to a high level of perceived threat of disease, a low level of perceived threat of disease can enhance the effect of doctor-patient communication on patients' trust. The results of this study underscore the importance of doctor-patient communication and the value of patient-physician consistency for building patients' trust. To foster a harmonious doctor-patient relationship, medical colleges should place great emphasis on cultivating medical students' communication skills. Hospitals should enhance on-the-job training and provide institutional support for doctors, encourage agreements between doctors and patients regarding disease diagnosis and decision-making, and be attentive to patients' perceived threat of disease, particularly for those with high level of perceived threat of disease.

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BACKGROUND: The risks associated with negative doctor-patient relationships have seriously hindered the healthy development of medical and healthcare and aroused widespread concern in society. The number of public comments on doctor-patient relationship risk events reflects the degree to which the public pays attention to such events. AIM: To explore public emotional differences, the intensity of comments, and the positions represented at different levels of doctor-patient disputes. METHODS: Thirty incidents of doctor-patient disputes were collected from Weibo and TikTok, and 3655 related comments were extracted. The number of comment sentiment words was extracted, and the comment sentiment value was calculated. The Kruskal-Wallis H test was used to compare differences between each variable group at different levels of incidence. Spearman's correlation analysis was used to examine associations between variables. Regression analysis was used to explore factors influencing scores of comments on incidents. RESULTS: The study results showed that public comments on media reports of doctor-patient disputes at all levels are mainly dominated by "good" and "disgust" emotional states. There was a significant difference in the comment scores and the number of partial emotion words between comments on varying levels of severity of doctor-patient disputes. The comment score was positively correlated with the number of emotion words related to positive, good, and happy) and negatively correlated with the number of emotion words related to negative, anger, disgust, fear, and sadness. CONCLUSION: The number of emotion words related to negative, anger, disgust, fear, and sadness directly influences comment scores, and the severity of the incident level indirectly influences comment scores.

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Background: Prior studies reveal a lack of illness understanding and prognostic awareness among patients with hematological malignancies. We evaluated prognostic awareness and illness understanding among patients with acute leukemia and multiple myeloma (MM) and measured patient-hematologist discordance. Methods: We prospectively enrolled patients with acute leukemia and MM at Mount Sinai Hospital or Yale New Haven Hospital between August 2015 and February 2020. Patients were administered a survey assessing prognostic awareness, goals of care (GOC), and quality of life. Hematologists completed a similar survey for each patient. We assessed discordance across the cohort of patients and hematologists using the likelihood-ratio chi-square test and within patient-hematologist pairs using the kappa (κ) statistic. Results: We enrolled 185 patients (137 with leukemia and 48 with MM) and 29 hematologists. Among patients, 137 (74%) self-identified as White, 27 (15%) as Black, and 21 (11%) as Hispanic. Across the entire cohort, patients were significantly more optimistic about treatment goals compared with hematologists (p = 0.027). Within patient-hematologist pairs, hematologists were significantly more optimistic than patients with respect to line of treatment (κ = 0.03). For both leukemia and MM cohorts, patients were significantly more likely to respond "don't know" or deferring to a faith-based response with 88 (64%) and 34 (71%), respectively, compared with only 28 (20%) and 11 (23%) of hematologists, respectively. Conclusions: We observed significant discordance regarding prognosis and GOC among patients with hematological malignancies and their hematologists. These data support future interventions to improve prognostic understanding among this patient population to facilitate informed treatment choices.

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Doctors' interactional competencies play a crucial role in patient satisfaction, well-being, and compliance. Accordingly, it is in medical schools' interest to select candidates with strong interactional abilities. While Multiple Mini Interviews (MMIs) provide a useful context to assess such abilities, the evaluation of candidate performance during MMIs is not always based on a solid theoretical framework. The newly developed selection procedure "Interactional Competencies - Medical Doctors (IC-MD)" uses an MMI circuit with five simulation patient scenarios and is rated based on the theoretically and empirically grounded construct of emotional availability. A first validation study with N = 70 first-semester medical students took place in 2021. In terms of convergent validity, IC-MD ratings showed strong correlations with simulation patients' satisfaction with the encounter (r =.57) but no association with emotional intelligence measures. IC-MD ratings were not related to high school performance or a cognitive student aptitude test, indicating divergent validity. Inter-rater reliability (ICC = 0.63) and generalizability (Eρ2 = 0.64) were satisfactory. The IC-MD proved to be fair regarding participants' age and gender. Participants with prior work experience in healthcare outperformed those without such experience. Participant acceptance of the procedure were good. The IC-MD is a promising selection procedure capable of assessing interactional competencies relevant to the medical setting. Measures of interactional competencies can complement the use of cognitive selection criteria in medical student admission. The predictive validity of the IC-MD needs to be addressed in future studies.

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Purpose: Psoriasis is a highly debilitating chronic inflammatory disease. Increased understanding of its pathophysiology has enabled development of targeted treatments such as biologics. Several medical treatments have been shown to be influenced by patients' experiences and expectations. However, only little is known about patients' experiences with and expectations towards biologics. Our objectives were to identify patients' treatment experiences and treatment expectations and assess their trajectories over the course of treatment with the IL-17A inhibitor secukinumab. Moreover, we aimed to document effects of psoriasis, factors that influence symptomatology, and prior treatment experiences. Patients and Methods: We conducted semi-structured interviews with n = 24 patients with moderate-to-severe plaque psoriasis and employed a qualitative content analysis to derive thematic and evaluative codes. Findings were validated via peer debriefings with experienced dermatologists. Results: Patients reported burdensome physical and psychological psoriasis symptoms and identified factors that can improve or worsen symptomatology, including stress and self-efficacy. Prior treatment experiences were mostly negative. Past barriers to effective treatment included time constraints or limited access. Concerning secukinumab, patients initially expected complete to partial remission of symptoms and occurrence or absence of side effects. Closer inspection of expectations and experiences revealed three trajectories. For most patients, initial expectations were met and future expectations remained unchanged. For the other patients, however, the experience did not match their initial expectation. One group then adapted their future expectations according to their experience, while the other group did not. Conclusion: To our knowledge, this is the first qualitative study to assess expectations towards treatment effectiveness and side effects, their trajectories, and interplay with experiences among psoriasis patients. Our findings highlight the value of further research on the subject in order to optimize care for psoriasis patients and to learn more about the trajectories and influence of treatment expectations in general.

Patients' expectations towards a certain treatment can influence how well it will work and whether side effects occur or not. Such effects have been shown for a wide range of conditions, including dermatological ones. For patients suffering from psoriasis, a chronic inflammatory skin disease, modern biologics offer promising treatment options. Therefore, modern biologics are likely associated with high expectations by patients. Yet, the roles of treatment expectations and the experiences of patients undergoing biologic treatment have only received little attention to date. With this qualitative study, we aimed to understand patients' perspectives on these treatments, the symptoms they suffer from, expectations towards treatment effectiveness and side effects as well as treatment experiences in the past and over the course of treatment with a modern biologic. To this end, we conducted and transcribed interviews with 24 patients after several months of biologic treatment. We then analyzed interview transcripts to determine underlying categories and summarized these in a common framework. We found that patients' debilitating physical and psychological symptoms were often not well controlled in past treatments. Still, patients had positive expectations with regard to biologic treatment. For a large group of patients, their actual experiences met their expectations, leaving them with unchanged expectations for the future. Another important finding was the good understanding of factors influencing their symptomatology that patients had, like stress and self-efficacy. The reported findings may aid doctors in their clinical work, to further improve care for psoriasis patients.

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BACKGROUND: Diagnostic uncertainty is common, but its communication to patients is under-explored. This study aimed to (1) characterise variation in doctors' communication of diagnostic uncertainty and (2) explore why variation occurred. METHODS: Four written vignettes of clinical scenarios involving diagnostic uncertainty were developed. Doctors were recruited from five hospitals until theoretical saturation was reached (n = 36). Participants read vignettes in a randomised order, and were asked to discuss the diagnosis/plan with an online interviewer, as they would with a 'typical patient'. Semi-structured interviews explored reasons for communication choices. Interview transcripts were coded; quantitative and qualitative (thematic) analyses were undertaken. RESULTS: There was marked variation in doctors' communication: in their discussion about differential diagnoses, their reference to the level of uncertainty in diagnoses/investigations and their acknowledgement of diagnostic uncertainty when safety-netting. Implicit expressions of uncertainty were more common than explicit. Participants expressed both different communication goals (including reducing patient anxiety, building trust, empowering patients and protecting against diagnostic errors) and different perspectives on how to achieve these goals. Training in diagnostic uncertainty communication is rare, but many felt it would be useful. CONCLUSIONS: Significant variation in diagnostic uncertainty communication exists, even in a controlled setting. Differing communication goals-often grounded in conflicting ethical principles, for example, respect for autonomy versus nonmaleficence-and differing ideas on how to prioritise and achieve them may underlie this. The variation in communication behaviours observed has important implications for patient safety and health inequalities. Patient-focused research is required to guide practice. PATIENT OR PUBLIC CONTRIBUTION: In the design stage of the study, two patient and public involvement groups (consisting of members of the public of a range of ages and backgrounds) were consulted to gain an understanding of patient perspectives on the concept of communicating diagnostic uncertainty. Their feedback informed the formulations of the research questions and the choice of vignettes used.

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For more than sixty years, surgeons have used bioethical strategies to promote patient self-determination, many of these now collectively described as "informed consent." Yet the core framework-understanding, risks, benefits, and alternatives-fails to support patients in deliberation about treatment. We find that surgeons translate this framework into an overly complicated technical explanation of disease and treatment and an overly simplified narrative that surgery will "fix" the problem. They omit critical information about the goals and downsides of surgery and present untenable options as a matter of patient choice. We propose a novel framework called "better conversations." Herein, surgeons provide context about clinical norms, establish the goals of surgery, and comprehensively delineate the downsides of surgery to generate a deliberative space for patients to consider whether surgery is right for them. This paradigm shift meets the standards for informed consent, supports deliberation, and allows patients to anticipate and prepare for the experience of treatment.

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