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What are the limits of the use of artificial intelligence (AI) in the relational aspects of medical and nursing care? There has been a lot of recent work and applications showing the promise and efficiency of AI in clinical medicine, both at the research and treatment levels. Many of the obstacles discussed in the literature are technical in character, regarding how to improve and optimize current practices in clinical medicine and also how to develop better data bases for optimal parameter adjustments and predictive algorithms. This paper argues that there are also in principle obstacles to the application of AI in clinical medicine and care where empathy is important, and that these problems cannot be solved with any of the technical and theoretical approaches that shape the current application of AI in specific areas of clinical medicine in which care for patients is fundamental. This is important, because it generates specific risks that may be overlooked otherwise, and it justifies the necessity of human monitoring and emotional intervention in clinical medicine. Consequently, difficult issues concerning moral and legal responsibility may ensue if these in principle problems are ignored.

An empathic approach to patient‐centred care is a core of nursing practice. One of the methods to develop empathy, which is gaining currency is the use of virtual reality simulations in education. This paper posits some questions, does it simply reinforce a ‘type’ of patient, neglecting caring for the patient as unique, is empathy what results or is it pity, does it result in a greater distance being created between the patient and the health care provider? Can we ever really know what it is like to walk in a patient's shoes when what we experience through virtual reality provides a small snapshot of the vicissitudes of living with an illness or disability. We suggest that what matters most in simulations using virtual reality is how the student exits the experience and if they leave knowing just what patients ‘like that’ feel, or whether they leave with humility and curiosity.

Due to the high costs of providing long-term care to older adults with cognitive impairment, artificial companions are increasingly considered as a cost-efficient way to provide support. Artificial companions can comfort, entertain, and inform, and even induce a sense of being in a close relationship. Sensors and algorithms are increasingly leading to applications that exude a life-like feel. We focus on a case study of an artificial companion for people with cognitive impairment. This companion is an avatar on an electronic tablet that is displayed as a dog or a cat. Whereas artificial intelligence guides most artificial companions, this application also relies on technicians "behind" the on-screen avatar, who via surveillance, interact with users. This case is notable because it particularly illustrates the tension between the endless opportunities offered by technology and the ethical issues stemming from limited regulations. Reviewing the case through the lens of biomedical ethics, concerns of deception, monitoring and tracking, as well as informed consent and social isolation are raised by the introduction of this technology to users with cognitive impairment. We provide a detailed description of the case, review the main ethical issues and present two theoretical frameworks, the "human-driven technology" platform and the emancipatory gerontology framework, to inform the design of future applications.

We sought to understand the expectations and concerns of older adults with cognitive impairment with regard to their relationship with medical providers. In particular, we observed whether study participants were involved in therapeutic alliances. Medical providers and patients create therapeutic alliances when they agree on the goals of the treatment and share a personal bond. Whereas such alliances have been studied in cancer research, little is known about therapeutic alliances in dementia research. Data were gathered in a qualitative study of 27 older adults with cognitive impairment and analyzed with narrative analysis. We introduce four case studies that illustrate the effects of having or missing a therapeutic alliance. Whereas the participant in the first case benefited from a therapeutic alliance, the other cases are marked by different experiences of abandonment. Findings suggest that interventions should concentrate on ways to enhance the relationship between medical providers and patients with cognitive impairment.

The late 2018 announcement of the claimed births of CRISPR-edited babies has stimulated widespread condemnation and calls by some leading scientists for a moratorium on any further germline genome editing (GGE) for reproductive purposes. Concurrently, national and international bodies are calling for the development of robust guidelines and regulations that will identify permissible conditions under which such GGE efforts might eventually proceed. Crucially, these conditions go beyond rigorous safety standards to address some of the social and ethical concerns that arise with germline interventions. As these bodies convene to navigate this unique terrain, we suggest an important standard for generating ethically robust guidelines. Our approach builds from concerns about social exclusion and social justice with a focus on fundamental human rights. We believe that a deontological or rights-based approach, rather than a utilitarian approach, is needed to ensure that this socially disruptive technology minimizes further marginalization of people with disabilities and does not create a new form of social injustice. In pursuit of a deontological framework, we propose the implementation of an objective assessment tool: the Human Rights Impact Assessment (HRIA). Use of the HRIA establishes necessary constraints on applications of GGE in order to safeguard the most vulnerable members of society.

CRISPR (clustered regularly interspaced short palindromic repeats) somatic genome editing, an important promissory technology, presents a case study of the movement of basic scientists into translational research. In this paper, we explore how scientists experience the pulls of CRISPR's power and the pushes of economic and societal pressures in adopting new translational roles. Given basic scientists' emerging contact with and influence upon individuals with genetic conditions, we also examine how scientists understand the perspectives of affected populations, both as potential subjects of early experiments and as the patients who could receive future treatments. Finally, we consider the ethical implications of our findings and call for innovative approaches to translational research that help scientists engage with people with genetic conditions in early translational research.

Alzheimer’s disease and related dementias (ADRD) are progressive illnesses characterized by decline in cognitive function that impairs performing daily activities. People with ADRD are at an increased risk of suicide, especially those who have comorbid mental health conditions, have specific types of ADRD, or have been recently diagnosed. The coronavirus disease 2019 (COVID-19) pandemic has increased the distress of people with ADRD, a population also at increased risk of contracting the COVID-19 virus. In this article, we draw on a case study and use the Interpersonal Theory of Suicide to help describe the association between ADRD and suicide risk. Secondly, we call for new strategies to mitigate suicide risk in people living with ADRD during and beyond the current pandemic by using lessons learned from cancer care. Our goal is not to dictate solutions but rather to start the conversation by outlining a framework for future research aimed at preventing death by suicide in people with ADRD. Specifically, we draw on the updated Framework for Developing and Evaluating Complex Interventions to reflect on the complexity of the issue and to break it down into achievable parts to reduce the risk of suicidal behavior (ideation, plans, attempts) in those living with ADRD.

Adolescents and adults with intellectual and/or developmental disabilities who have partial capacities to exercise autonomy require respect as well as protection throughout medical decision making. Using an ethical lens that prioritizes respect for persons based on a conception of relational autonomy over beneficence, this chapter explores two contrasting yet related cases where developmental issues may complicate shared decision making. Young adolescents and some adults with intellectual or developmental disabilities may have limited capacities to form and express their values and yet may also need sensitive empathic communication and cognitive scaffolding to make decisions that enact their fundamental values. This chapter examines the conscious and unconscious emotional aspects of conveying diagnoses, prognoses, and other aspects of shared decision making. Empathic scaffolding looks different for each patient in their specific care and familial context but tracks how the patient’s sense of futurity and agency are affected by the clinician’s communication—is the communication accessible, empowering, and offering options that the patient can work with? Empathic health care communication also requires that the clinicians strive for awareness of how their own unconscious psychological processes might be conveying emotional messages to vulnerable patients, including, for example, their suppressed grief after witnessing pediatric patients go through failed bone marrow transplants. Shared decision making thus requires much more than a procedural commitment to respecting individual autonomy but rather calls for addressing the inescapable emotional, relational basis of clinician-patient decision making at vulnerable moments for especially vulnerable patients.

PURPOSE Primary care clinicians disproportionately report symptoms of burnout, threatening workforce sustainability and quality of care. Recent surveys report that these symptoms are greater when clinicians perceive fewer clinic resources to address patients’ social needs. We undertook this study to better understand the relationship between burnout and clinic capacity to address social needs. METHODS We completed semistructured, in-person interviews and brief surveys with 29 primary care clinicians serving low-income populations. Interview and survey topics included burnout and clinic capacity to address social needs. We analyzed interviews using a modified grounded theory approach to qualitative research and used survey responses to contextualize our qualitative findings. RESULTS Four key themes emerged from the interview analyses: (1) burnout can affect how clinicians evaluate their clinic’s resources to address social needs, with clinicians reporting high emotional exhaustion perceiving low efficacy even in when such resources are available; (2) unmet social needs affect practice by influencing clinic flow, treatment planning, and clinician emotional wellness; (3) social services embedded in primary care clinics buffer against burnout by increasing efficiency, restoring clinicians’ medical roles, and improving morale; and (4) clinicians view clinic-level interventions to address patients’ social needs as a necessary but insufficient strategy to address burnout. CONCLUSIONS Primary care clinicians described multiple pathways whereby increased clinic capacity to address patients’ social needs mitigates burnout symptoms. These findings may inform burnout prevention strategies that strengthen the capacity to address patients’ social needs in primary care clinical settings.

Unrealistic therapeutic beliefs are very common—the majority of patient-subjects (up to 94%) enrol in phase 1 trials seeking and expecting significant medical benefit, even though the likelihood of such benefit has historically proven very low. The high prevalence of therapeutic misestimation and unrealistic optimism in particular has stimulated debate about whether unrealistic therapeutic beliefs in early-phase clinical trials preclude adequate informed consent. We seek here to help resolve this controversy by showing that a crucial determination of when such therapeutic beliefs are ethically problematic turns on whether they are causally linked and instrumental to the motivation to participate in the trial. Thus, in practice, it is ethically incumbent on researchers to determine which understanding and beliefs lead to the participant’s primary motivation for enrolling, not to simply assess understanding, beliefs and motivations independently. We further contend that assessing patient-subjects’ appreciation as a component of informed consent—it is already an established component of decision-making capacity assessments—can help elucidate the link between understanding-beliefs and motivation; appreciation refers to an individual’s understanding of the personal significance of both the medical facts and the experience of trial participation. Therefore, we recommend that: (1) in addition to the usual question, ‘Why do you want to participate in this trial?’, all potential participants should be asked the question: ‘What are you giving up by participating in this trial?’ and (2) researchers should consider the settings in which it may be possible and practical to obtain ‘two-point consent’.

Surveillance cameras are increasingly being deployed in nursing homes and assisted living facilities, with insufficient attention to what is ethically fraught about this way of assuaging concerns about abuse and other personnel challenges. With seven state laws now regulating camera monitoring and more on the way, it is urgent for us to consider the ethical implications of how we use technology to keep older adults safe. Drawing on findings from the first facility survey on this topic, we address three ethical issues: the risk that in-room cameras pose to residents' privacy and dignity, the risk of undermining care workers' sense of being fiduciaries for residents, and the probable extension of camera use by facilities to monitor staff and residents. We argue that with an aging population, intensifying strain on the care workforce, and ease of access to Web-connected cameras, this is a critical moment to address these ethical challenges.

Summary Genome sequencing is enabling precision medicine—tailoring treatment to the unique constellation of variants in an individual’s genome. The impact of recurrent pathogenic variants is often understood, however there is a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequential variants and associated mechanisms. Variants of uncertain significance (VUSs) in these genes are discovered at a rate that outpaces current ability to classify them with databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation., Genome sequencing is enabling precision medicine—tailoring treatment to the unique constellation of variants in an individual’s genome. The impact of recurrent pathogenic variants is often understood, leaving a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequential variants and associated mechanisms. Variants of uncertain significance (VUSs) in these genes are discovered at a rate that outpaces current ability to classify them with databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.

The Covid‐19 crisis has accelerated a trend toward burnout in health care workers, making starkly clear that burnout is especially likely when providing health care is not only stressful and sad but emotionally alienating; in such situations, there is no mental space for clinicians to experience authentic clinical empathy. Engaged curiosity toward each patient is a source of meaning and connection for health care providers, and it protects against sympathetic distress and burnout. In a prolonged crisis like Covid‐19, clinicians provide care out of a sense of duty, especially the duty of nonabandonment. We argue that when duty alone is relied on too heavily, with fear and frustration continually suppressed, the risk of burnout is dramatically increased. Even before Covid‐19, clinicians often worked under dehumanizing and unjust conditions, and rates of burnout were 50 percent for physicians and 33 percent for nurses. The Covid‐19 intensification of burnout can serve as a wake‐up call that the structure of health care needs to be improved if we are to prevent the loss of a whole generation of empathic clinicians.

Background and Objectives Even before the COVID-19 pandemic, older adults with cognitive impairment living alone (an estimated 4.3 million individuals in the United States) were at high risk for negative health outcomes. There is an urgent need to learn how this population is managing during the pandemic. Research Design and Methods This is a qualitative study of 24 adults aged 55 and older living alone with cognitive impairment from diverse racial/ethnic backgrounds. Participants’ lived experiences during the pandemic were elicited via 59 ethnographic interviews conducted over the phone either in English, Spanish, or Cantonese. Using a qualitative content analysis approach, interview transcripts were analyzed to identify codes and themes. Results Qualitative analysis of transcripts revealed 5 themes: (a) fear generated by the pandemic, (b) distress stemming from feeling extremely isolated, (c) belief in misinformation, (d) strategies for coping during the pandemic, and (e) the importance of access to essential services. Discussion and Implications This pandemic put a spotlight on the precarity and unmet needs of older adults living alone with cognitive impairment. Findings underscore the need to expand access to home care aides and mental health services for this population.

Genome sequencing is enabling precision medicine—tailoring treatment to the unique constellation of variants in an individual’s genome. The impact of recurrent pathogenic variants is often understood, leaving a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequent frequent variants and associated mechanisms. Variants of unknown significance (VUS) in these genes are discovered at a rate that outpaces current ability to classify them using databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns, and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.

BACKGROUND Providing HIV and hepatitis C virus (HCV) testing on an "opt-out" basis is often considered the "gold standard" because it contributes to higher testing rates when compared with "opt-in" strategies. Although rates are crucial, an individual's testing preferences are also important, especially in correctional settings where legal and social factors influence a person's capacity to freely decide whether or not to test. Our study explored factors influencing HIV and HCV testing decisions and individuals' preferences and concerns regarding opt-in vs. opt-out testing at the time of jail entry. METHODS We conducted semistructured interviews to explore individuals' previous testing experiences, reasons to test, understanding of their health care rights, HIV and HCV knowledge, and preferences for an opt-out vs. an opt-in testing script. RESULTS We interviewed 30 individuals detained in the Santa Clara County Jail at intake. Participants reported that their testing decisions were influenced by their level of HIV and HCV knowledge, self-perceived risk of infection and stigma associated with infection and testing, the degree to which they felt coerced, and understanding of testing rights in a correctional setting. Most preferred the opt-in script because they valued the choice of whether or not to be tested. Participants who did prefer the opt-out script did so because they felt that the script was less likely to make people feel "singled out" for testing. CONCLUSIONS Our findings demonstrate that people care about how testing is offered and suggest a need for further research to see how much this influences their decision about whether to test.