What is medicine? One obvious answer in the context of the contemporary clinical tradition is that medicine is the process of curing sick people. However, this “curative thesis” is not satisfactory, even when “cure” is defined generously and even when exceptions such as cosmetic surgery are set aside. Historian of medicine Roy Porter argues that the position of medicine in society has had, and still has, little to do with its ability to make people better. Moreover, (...) the efficacy of medicine for improving population health has been famously doubted by historians and epidemiologists. The curative thesis demands that we have mostly been stupid, duped, or staggeringly hopeful, given that medicine has not until recently offered more than a handful of effective cures. I suggest, in this article, that the core medical competence is neither to cure, nor to prevent, disease, but to understand and to predict it. I argue that this approach does a better job than the curative thesis at explaining why not all medicine is concerned with curative efforts and that it enjoys historical support from the ancient entanglement of prophecy and medicine and from the fact that medicine thrived for centuries with almost no effective cures and continues to thrive today in various forms that are mostly without curative efficacy. I suggest that this approach grounds a fairer approach to alternative, traditional, and other medical practices, as well as some fresh lessons for the development of mainstream medicine. (shrink)

This article is a reply to two critics of my “Prediction, Understanding, and Medicine,” published elsewhere in this journal issue. In that essay, I argued that medicine is best understood not as essentially a curative enterprise, but rather as one essentially oriented towards prediction and understanding. Here, I defend this position from several criticisms made of it.

In “Prediction, Understanding, and Medicine,” Alex Broadbent rejects the curative thesis, the view that the core medical competence is to cure, in favor of his predictive thesis that the main intellectual medical competence is to explain and the main practical medical competence is to predict. Broadbent thinks his account explains the phenomenon of multiple consultation, which is the fact that people persist in consulting alternative medical traditions despite having access to mainstream medicine. I argue that Broadbent’s explanation (...) of multiple consultation makes sense only from the perspective of patients who migrate from mainstream to alternative consultation. His explanation is not as convincing when we consider alternative-to-mainstream migration. I also provide an argument against Broadbent’s view that prediction is medicine’s main practical competence and argue that, when it comes to explaining most cases of multiple consultation, the curative thesis provides a more convincing explanation than the predictive thesis. (shrink)

This paper addresses the recent rise of the use of alternative medicine in Western countries. It offers a novel explanation of that phenomenon in terms of cognitive and economic factors related to the free-market and patient-centric approach to medicine that is currently in place in those countries, in contrast to some alternative explanations of this phenomenon. Moreover, the paper addresses this troubling trend in terms of the serious harms associated with the use of alternative medical modalities. The explanatory (...) theory defended here is then predicated on the idea that an extreme patient-centric model of medical practice that treats largely ignorant patients as consumers of medical products and services endowed with an essentially unrestricted power of freedom to choose treatments predictably leads serious and avoidable harms. Some important moral and epistemological consequences of this model are then articulated and corrective measures are suggested. (shrink)

This article focuses on a project of « predictive medicine » elaborated in the late 1960s by an American dentist, Emanuel Cheraskin. In his views, this new label was meant to name a preventive medicine based on the knowledge of individual pecularities. The analysis of this unknown episode of medical history allows to uncover the prospective dimension of this medicine, and also the ambiguities which are linked to the idea that understanding individual peculiarities could help rethink (...) the preventive approach. Through the study of Cheraskin’s propositions, I want to show that the ambition of providing a new basis to prevention, namely a science of individuals, casts a light on the predictive project. While paying attention to this ambition, rather than to genomic techniques, I hope to open new paths in our understanding of various aspects of contemporary predictive medicine. (shrink)

Die faszinierenden Fortschritte molekulargenetischen Wissens, vor allem die weitere Entzifferung des menschlichen Genoms, stellen das individuelle Selbstverständnis vor die Forderung nach einer kopernikanischen Revolutionierung der Denkungsart und führen die Anforderungen an Mündigkeit und Selbstverantwortung in neue Dimensionen von Aufklärung und Selbstbestimmung. Die rasante Entwicklung prädiktiver und präventiver Leistungen moderner Risikofaktorenmedizin fordert vom medizinischen Laien Gesundheitsmündigkeit und vom medizinischen Experten neue Formen beratender und begleitender Dienste. Genetische Prädiktion schwerer Erbkrankheiten macht eine ethische Diskussion des Begriffs verantwortlicher Elternschaft unerläßlich, ebenso die Zurückweisung (...) von Forderungen nach einer staatlich administrierten oder geförderten Eugenik. Gesundheitspolitik und -finanzierung werden deshalb Prinzipien wie Selbstbestimmung und Subsidiarität, sowie das traditionelle Prinzip der Solidarität, in der Diskussion um Verantwortung und Finanzierung von Gesundheit neu ausmessen müssen. (shrink)

With the ascent of modern epidemiology in the Twentieth Century came a new standard model of prediction in public health and clinical medicine. In this article, we describe the structure of the model. The standard model uses epidemiological measures-most commonly, risk measures-to predict outcomes (prognosis) and effect sizes (treatment) in a patient population that can then be transformed into probabilities for individual patients. In the first step, a risk measure in a study population is generalized or extrapolated to a (...) target population. In the second step, the risk measure is particularized or transformed to yield probabilistic information relevant to a patient from the target population. Hence, we call the approach the Risk Generalization-Particularization (Risk GP) Model. There are serious problems at both stages, especially with the extent to which the required assumptions will hold and the extent to which we have evidence for the assumptions. Given that there are other models of prediction that use different assumptions, we should not inflexibly commit ourselves to one standard model. Instead, model pluralism should be standard in medical prediction. (shrink)

Predictive medicine presents opportunities to consider later life under conditions of illness, such as dementia. This paper examines how family caregivers (N = 27) assess the opportunity of prediction and early diagnosis of dementia for oneself based on their particular experience. Furthermore, it compares their attitudes with laypersons’ attitudes (N = 43) towards genetic testing of APOE. By this, we elaborate how much personal experience impacts anticipation and affects, but also moral attitudes towards predictive medicine. Differences (...) in our settings do not allow for direct comparison, so our analysis focuses on multiple similarities in the assessments of predictive (non-genetic vs. genetic) testing. Groups’ reasoning showed also differences influenced mainly by personal experience. Family caregivers addressed more responsibility towards family and had more hopes into medical treatments. To cope with the disease, they expressed expectations to start with medicine and care decisions as early as possible. Laypersons, however, stressed self-determination more and expressed worries about the influence of the pharmaceutical industry by referring to unnecessary medication and, implicitly, the medicalization of aging. (shrink)

Although it is now generally acknowledged that new biomedical technologies often produce new definitions and sometimes even new concepts of disease, this observation is rarely used in research that anticipates potential ethical issues in emerging technologies. This article argues that it is useful to start with an analysis of implied concepts of disease when anticipating ethical issues of biomedical technologies. It shows, moreover, that it is possible to do so at an early stage, i.e. when a technology is only just (...) emerging. The specific case analysed here is that of ‘molecular medicine’. This group of emerging technologies combines a ‘cascade model’ of disease processes with a ‘personal pattern’ model of bodily functioning. Whereas the ethical implications of the first are partly familiar from earlier—albeit controversial—forms of preventive and predictive medicine, those of the second are quite novel and potentially far-reaching. (shrink)

Substituted judgment assumes adequate knowledge of patient’s mind-set. However, surrogates’ prediction of individual healthcare decisions is often inadequate and may be based on shared background rather than patient-specific knowledge. It is not known whether surrogate’s prediction of patient’s integrative life-story narrative is better. Respondents in 90 family pairs rank-ordered 47 end-of-life statements as life-story narrative measure and completed instruments on decision-control preference and healthcare-outcomes acceptability as control measures, from respondent’s view and predicted pair’s view. They also scored their confidence in (...) surrogate’s decision-making and familiarity with pair’s healthcare-preferences. Life-story narratives’ prediction was examined by calculating correlation of statements’ ranking scores between respondent-personal and respondent-surrogate Q-sorts and between respondent-surrogate and pair-personal Q-sorts before and after controlling for correlation with respondent-personal scores, and by comparing percentages of respondent-surrogate Q-sorts co-loading with pair-personal vs. respondent-personal Q-sorts. Accuracy in predicting decision-control preference and healthcare-outcomes acceptability was determined by percent concordance. Results were compared among subgroups defined by intra-pair relationship, surrogate’s decision-making confidence, and healthcare-preferences familiarity. Mean age was 35.4 years, 69% were females, and 73 and 80% reported ≥ very good health and life-quality, respectively. Mean surrogate’s decision-making confidence score was 3.35 and 75% were ≥ familiar with pair’s healthcare-preferences. Mean projection, simulation, and adjusted-simulation correlations were 0.68, 0.42, and 0.26, respectively. Out of 180 respondent-surrogate Q-sorts, 24, 9, and 32% co-loaded with respondent-personal, pair-personal, or both Q-sorts, respectively. Accuracy in predicting decision-control preference and healthcare-outcomes acceptability was 47 and 52%, respectively. Surrogate’s decision-making confidence score correlated with adjusted-simulation’s correlation score. There were significant differences among the husband-wife, parent-child, and sibling-sibling subgroups in percentage of respondent-surrogate Q-sorts co-loading with pair-personal Q-sorts and percent agreement on healthcare-outcomes acceptability. Despite high self-reported surrogate’s decision-making confidence and healthcare-preferences familiarity, family surrogates are variably inadequate in simulating life-story narratives. Simulation accuracy may not follow the next-of-kin concept and is 38% based on shared background. (shrink)

The phrase "personalized medicine" has a built-in positive spin. Simple genetic tests can sometimes predict whether a particular individual will have a positive response to a particular drug or, alternatively, suffer costly and debilitating side effects. But little attention has been given to some challenging issues of justice raised by personalized medicine. How should we determine who would have a just claim to access particular treatments, especially very expensive ones? How effective do those treatments need to be?If there (...) were a thick, bright line separating minimal responders from maximal responders, then we could allocate these treatments in a fair and cost-effective way. But there is no bright line. The .. (shrink)

Precision medicine is an emerging approach to individualized care. It aims to help physicians better comprehend and predict the needs of their patients while effectively adopting in a timely manner the most suitable treatment by promoting the sharing of health data and the implementation of learning healthcare systems. Alongside its promises, PM also entails the risk of exacerbating healthcare inequalities, in particular between ethnoracial groups. One often-neglected underlying reason why this might happen is the impact of structural racism on (...) PM initiatives. Raising awareness as to how structural racism can influence PM initiatives is paramount to avoid that PM ends up reproducing the pre-existing health inequalities between different ethnoracial groups and contributing to the loss of trust in healthcare by minority groups. We analyse three nodes of a process flow where structural racism can affect PM’s implementation. These are: the collection of biased health data during the initial encounter of minority groups with the healthcare system and researchers, the integration of biased health data for minority groups in PM initiatives and the influence of structural racism on the deliverables of PM initiatives for minority groups. We underscore that underappreciation of structural racism by stakeholders involved in the PM ecosystem can be at odds with the ambition of ensuring social and racial justice. Potential specific actions related to the analysed nodes are then formulated to help ensure that PM truly adheres to the goal of leaving no one behind, as endorsed by member states of the United Nations for the 2030 Agenda for Sustainable Development. Structural racism has been entrenched in our societies for centuries and it would be naïve to believe that its impacts will not spill over in the era of PM. PM initiatives need to pay special attention to the discriminatory and harmful impacts that structural racism could have on minority groups involved in their respective projects. It is only by acknowledging and discussing the existence of implicit racial biases and trust issues in healthcare and research domains that proper interventions to remedy them can be implemented. (shrink)

The use of machine learning, or “artificial intelligence” (AI) in medicine is widespread and growing. In this paper, I focus on a specific proposed clinical application of AI: using models to predict incapacitated patients’ treatment preferences. Drawing on results from machine learning, I argue this proposal faces a special moral problem. Machine learning researchers owe us assurance on this front before experimental research can proceed. In my conclusion I connect this concern to broader issues in AI safety.

This article explores the ways in which predictive information technologies are used in the field of personalized medicine and the relations between this use and how patients and disease are perceived. This is examined in a qualitative case study of a personalized cancer clinical trial, where oncologists made clinical decisions for each patient based on drug matchings and efficacy predictions produced by bioinformatic technologies and algorithms. I focus on personalized practice itself, as a postgenomic phenomenon, rather than on (...) epistemic, ethical and institutional critiques. Personalized medicine aims to process molecular, clinical, environmental and social data into individually tailored decisions. In this case, however, the engagement of clinicians with data and digital artefacts that processed multiple information sources resulted in treatment choices that were paradoxically both immutable and uncertain. In contrast to the situatedness of the body in postgenomics, this practice subverted the personalized medical approach while decontextualizing both cancer and patients. (shrink)

ABSTRACT: Abstract Most modern knowledge is not science. The physical sciences have successfully validated theories to infer they can be used universally to predict in previously unexperienced circumstances. According to the conventional conception of science such inferences are falsified by a single irregular outcome. And verification is by the scientific method which requires strict regularity of outcome and establishes cause and effect. -/- Medicine, medical research and many “soft” sciences are concerned with individual people in complex heterogeneous populations. These (...) populations cannot be tested to demonstrate strict regularity of outcome in every individual. Neither randomised controlled trials nor observational studies in medicine are science in the conventional conception. Establishing and using medical and other “soft science” theories cannot be scientific. It requires conceptually different means: requiring expert judgement applying all available evidence in the relevant available factual matrix. -/- The practice of medicine is observational. Prediction of outcomes for the individual requires professional expertise applying available medical knowledge and evidence. Expertise in any profession can only be acquired through experience. Prior cases are the fundament of knowledge and expertise in medicine. Case histories, studies and series can provide knowledge of extremely high reliability applicable to establishing reliable general theories and falsifying others. Their collation, study and analysis should be a priority in medicine. Their devaluation as evidence, the failure to apply their lessons, the devaluation of expert professional judgement and the attempt to emulate the scientific method are all historic errors in the theory and practice of modern medicine. (shrink)

Predictive medical information is used by underwriters to assess the future risk of a claim in medically based insurance products such as health, life, and disability insurance. Medical underwriting involves the science of evaluating medical information to determine the risk for groups of individuals with various medical conditions. In disability insurance, this involves an evaluation of medical information to predict the risk of becoming disabled.Before discussing medical underwriting, an understanding of certain terms used by disability insurance companies and the (...) products that are available is required. The first is the definition of disability. The Americans with Disabilities Act defines disability as the following:A physical or mental impairment that substantially limits one or more of the major life activities; or has a record of such an impairment; or is regarded as having such an impairment even when no impairment exists, no substantial limitation results from the impairment, or the impairment is only substantially limiting because of the attitudes of others. (shrink)

Since its advent, predictive DNA testing has been perceived as a technology that may have considerable impact on the quality of people’s life. The decision whether or not to use this technology is up to the individual client. However, to enable well considered decision making both the negative as well as the positive freedom of the individual should be supported. In this paper, we argue that current professional and public discourse on predictive DNA-testing is lacking when it comes (...) to supporting positive freedom, because it is usually framed in terms of risk and risk management. We show how this ‘risk discourse’ steers thinking on the good life in a particular way. We go on to argue that empirical research into the actual deliberation and decision making processes of individuals and families may be used to enrich the environment of personal deliberation in three ways: (1) it points at a richer set of values that deliberators can take into account, (2) it acknowledges the shared nature of genes, and (3) it shows how one might frame decisions in a non-binary way. We argue that the public sharing and discussing of stories about personal deliberations offers valuable input for others who face similar choices: it fosters their positive freedom to shape their view of the good life in relation to DNA-diagnostics. We conclude by offering some suggestions as to how to realize such public sharing of personal stories. (shrink)

Personalized medicine plays an important role in the development of current medicine. Among the numerous statements regarding the future of personalized medicine, some can be found that accord medicine a new scientific status. Medicine will be transformed from an art to a science due to personalized medicine. This prognosis is supported by references to models of historical developments. The article examines what is meant by this prognosis, what consequences it entails, and how feasible it (...) is. It refers to the long tradition of epistemological thinking in medicine and the use of historical models for the development of medicine. The possible answers to the question “art or science” are systematized with respect to the core question about the relationship between knowledge and action. The prediction for medicine to develop from an ‘empirical healing art’ to a ‘rational, molecular science’ is nonsensical from an epistemological point of view. The historical models employed to substantiate the development of personalized medicine are questionable. (shrink)

Proponents of the emerging field of P4 medicine argue that computational integration and analysis of patient-specific “big data” will revolutionize our health care systems, in particular primary care-based disease prevention. While many ambitions remain visionary, steps to personalize medicine are already taken via personalized genomics, mobile health technologies and pilot projects. An important aim of P4 medicine is to enable disease prevention among healthy persons through detection of risk factors. In this paper, we examine the current status (...) of P4 medicine in light of historical and current challenges to predictive and preventive medicine, including overdiagnosis and overtreatment. Moreover, we ask whether it is likely that in silico integration of patient-specific data will be able to better deal such challenges and to turn risk predictions into disease-preventive actions in a wider social context. Given the lack of evidence that P4 medicine can tip the balance between benefits and harms in preventive medicine, we raise concerns about the current promotion of P4 medicine as a solution to the current challenges in public health. (shrink)

Personalised medicine has been discussed as a medical paradigm shift that will improve health while reducing inefficiency and waste. At the same time, it raises new practical, regulatory, and ethical challenges. In this paper, we examine PM strategies epistemologically in order to develop capacities to address these challenges, focusing on a recently proposed strategy for developing patient-specific models from induced pluripotent stem cells so as to make individualised treatment predictions. We compare this strategy to two main PM strategies—stratified (...) class='Hi'>medicine and computational models. Drawing on epistemological work in the philosophy of medicine, we explain why these two methods, while powerful, are neither truly personalised nor, epistemologically speaking, novel strategies. Both are forms of correlational black box. We then argue that the iPSC models would count as a new kind of black box. They would not rely entirely on mechanistic knowledge, and they would utilise correlational evidence in a different way from other strategies—a way that would enable personalised predictions. In arguing that the iPSC models would present a novel method of gaining evidence for clinical practice, we provide an epistemic analysis that can help to inform the practical, regulatory, and ethical challenges of developing an iPSC system. (shrink)

Abstractabstract:Expectations about future events underlie practically every decision we make, including those in medical research. This paper reviews five studies undertaken to assess how well medical experts could predict the outcomes of clinical trials. It explains why expert trial forecasting was the focus of study and argues that forecasting skill affords insights into the quality of expert judgment and might be harnessed to improve decision-making in care, policy, and research. The paper also addresses potential criticisms of the research agenda and (...) summarizes key findings from the five studies of trial forecasting. Together, the studies suggest that trials frequently deliver surprising results to expert communities and that individual experts are often uninformative when it comes to forecasting trial outcome and recruitment. However, the findings also suggest that expert forecasts often contain a "signal" about whether a trial will be positive, especially when forecasts are aggregated. The paper concludes with needs for further research and tentative policy recommendations. (shrink)

Part of a symposium devoted to ‘Prediction, Understanding, and Medicine’, in which Alex Broadbent argues that the nature of medicine is determined by its competences, i.e., which things it can do well. He argues that, although medicine cannot cure well, it can do a good job of enabling people not only to understand states of the human organism and of what has caused them, but also to predict future states of it. From this Broadbent concludes that (...) class='Hi'>medicine is (at least in part) essentially a practice of understanding and predicting, not curing. In reply to this bold position, I mount two major criticisms. First, I maintain that the reasons Broadbent gives for doubting that medicine can cure provide comparable reason for doubting that medicine can provide an understanding; roughly, the best explanation of why medicine cannot reliably cure is that we still lack much understanding of health and disease. Second, I object to the claim that a practice is medical only if it facilitates understanding and prediction. Although Broadbent has brought to light certain desirable purposes of medicine that are under-appreciated, my conclusion is that he has not yet provided enough reason to think that understanding and prediction are essential to it. Instead of supposing that medicine has an essence, in fact, I suggest that its nature is best understood in terms of a property cluster. (shrink)

Recent scientific developments, in particular advances in pharmacogenetics and molecular genetics, have given rise to numerous predictive procedures for detecting predispositions to diseases in patients. This knowledge, however, does not necessarily promise benign results for either patients or health care professionals. The aim of this volume is to analyse issues related to prediction and prognosis as a burgeoning field of medicine, which is revolutionizing the way we understand and approach diagnosis and treatment. Combining epistemic and ethical reflection with (...) medical expertise on contemporary practice and research, an interdisciplinary group of international experts critically examine anticipatory medicine from various perspectives, including history of medicine, bioethics, theories of science, and health economics. The highly complex issues involved in medical prediction call for a far-reaching debate on the value and scope of foreknowledge. For example, which responsibilities and burdens arise when still healthy people learn of their predisposition to diseases? How should health care insurance reflect risky life styles? Is the increasing medicalization of life connected with prevention ethically sustainable and financially possible in the developing world? These and other related issues are the subject of this timely and important book, which not only serves as an introduction to the area, but also proposes many feasible solutions to the problems outlined. (shrink)

As opposed to a ‘one size fits all’ approach, precision medicine uses relevant biological, medical, behavioural and environmental information about a person to further personalize their healthcare. This could mean better prediction of someone’s disease risk and more effective diagnosis and treatment if they have a condition. Big data allows for far more precision and tailoring than was ever before possible by linking together diverse datasets to reveal hitherto-unknown correlations and causal pathways. But it also raises ethical issues relating (...) to the balancing of interests, viability of anonymization, familial and group implications, as well as genetic discrimination. This article analyses these issues in light of the values of public benefit, justice, harm minimization, transparency, engagement and reflexivity and applies the deliberative balancing approach found in theEthical Framework for Big Data in Health and Research to a case study on clinical genomic data sharing. Please refer to that article for an explanation of how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. Our discussion is meant to be of use to those involved in the practice as well as governance and oversight of precision medicine to address ethical concerns that arise in a coherent and systematic manner. (shrink)

BackgroundHaving moral courage is a crucial characteristic for nurses to handle ethical quandaries, stay true to their professional obligations towards patients, and uphold ethical principles. This concept can be influenced by various factors including personal, professional, organizational, and leadership considerations. The purpose of this study was to explore the predictors of moral courage among nurses working in hospitals.MethodsIn 2018, an observational cross-sectional study was carried out on 267 nurses employed in six hospitals located in the northern region of Iran. The (...) participants were selected through a simple random sampling technique. To collect data, a demographic information form was used along with two questionnaires. The first questionnaire was a standard survey on moral courage, while the second questionnaire was designed to assess the ethical climate. Linear regression was used to assess the predictors of moral courage.ResultsNurses had an average moral courage score of 87.07 ± 15.52 and an average moral climate score of 96.12 ± 17.17. The study showed that 16% of the variation in moral courage scores among nurses was explained by ethical climate and monthly overtime hours.ConclusionThis study underscores the significance of establishing an ethical work environment and minimizing overtime hours in order to enhance moral courage among nurses. These findings carry weight for both nursing practice and organizational policies focused on fostering ethical conduct within healthcare settings. (shrink)

What ethical justification can be found for informing a person that he or she will later develop a lethal disease for which no therapy is available? This question has been discussed during the past twenty years by specialists concerned with the prevention of Huntington's Disease, an incurable late-onset hereditary disorder. Many of them have played an active role in developing experimental testing programmes for at-risk persons. This paper is based on a corpus of 119 articles; it reviews the development of (...) their reflection and includes an outline of the ethical problems identified and the solutions adopted in pre-clinical protocols. Seen in a broader perspective, the experience of presymptomatic testing for Huntington's Disease has given medical geneticists the opportunity to clarify their ethical position in the as yet little explored field of predictive medicine. (shrink)

Proponents of the emerging field of P4 medicine argue that computational integration and analysis of patient-specific “big data” will revolutionize our health care systems, in particular primary care-based disease prevention. While many ambitions remain visionary, steps to personalize medicine are already taken via personalized genomics, mobile health technologies and pilot projects. An important aim of P4 medicine is to enable disease prevention among healthy persons through detection of risk factors. In this paper, we examine the current status (...) of P4 medicine in light of historical and current challenges to predictive and preventive medicine, including overdiagnosis and overtreatment. Moreover, we ask whether it is likely that in silico integration of patient-specific data will be able to better deal such challenges and to turn risk predictions into disease-preventive actions in a wider social context. Given the lack of evidence that P4 medicine can tip the balance between benefits and harms in preventive medicine, we raise concerns about the current promotion of P4 medicine as a solution to the current challenges in public health. (shrink)

Individual autonomy is a concept highly appreciated in modern Western societies. Its significance is reflected by the central importance and broad use of the model of informed consent in all fields of medicine. In predictive genetic testing, individual autonomy gains particular importance, for what is in focus here is not so much a concrete medical treatment but rather options for taking preventive measures and the influence that the test results have on long-term lifestyle and preferences. Based on an (...) analysis of autonomy-related issues in predictive genetic diagnosis and genetic screening programmes, this contribution stresses the central relevance of a broad notion of autonomy for the discussion of ethical issues raised in connection with predictive genetic testing and genetic screening programmes. Only against the background of such a broad notion of autonomy, which stresses not only free and informed decision-making but also the relevance of long-term prospects for leading a self-determined life in familial and social contexts, can the manifold autonomy-related issues linked to predictive genetic testing be given adequate consideration. (shrink)

When intensive care for newborns was introduced thirty years ago its primary goal was to improve the rates of survival of sick and premature infants. Medicine has been successful in attaining this goal; however, as more infants survive, the cost of intensive care and the additional cost of services and care for handicapped survivors continue to escalate. In order to curb the increasing cost of newborn intensive care, heightened initiatives directed at the prevention of premature births will be necessary.

In tennis, service requires a variety of complicated movements. Given the importance of taking the initiative to obtain points in a tennis match, it is crucial to make full use of speed and spin rate of service. Generally, a service that requires a higher spin rate would slow down, and a service that has increased speed would have a decreased spin rate. For players who are disadvantaged in height, although controlling spin rate is essential, slowing down service speed should be (...) avoided. For these players, the challenge of service is to improve the speed without decreasing the spin rate. Players must also be trained to build physical strength required for this skill. It is not uncommon to work on physical training without a racket; however, few studies have reported on the effects of cultivated physical strength on on-court tennis performance. Therefore, this study aimed to propose physical measurements that could be used as indices to improve service performance in 58 elite Japanese junior male players. To test service performance, we used TrackMan tennis radar device to assess speed, spin rate, impact height, and impact depth. To test physical strength, we measured 5- and 20-m sprint, broad jump, medicine ball throw. We used a significant multiple regression equation to predict the first service speed obtained from the broad jump and the Medicine ball throw. Additionally, a strong correlation was obtained between the predicted and measured values. In addition to physical strength, we suggest that the depth of the impact point is important for improving the first service speed. However, we were not able to identify the physical strength test items that improve service spin rate. Other item should be examined in the future to determine the physical strength associated with spin rate. This result could help connect physical training and service performance. (shrink)

All the powerful influences exertedby the subjective-interpersonal dimension onthe organic or technical-functional dimensionof sickness and health do not make anintersubjective test concerning medicaltherapeutic results impossible. Theseinfluences are not arbitrary; on the contrary,they obey laws that are de facto sufficientlystable to allow predictions and explanationssimilar to those of experimental sciences.While, in this respect, the rules concerninghuman action are analogous to the scientificlaws of nature, they can at any time be revokedby becoming aware of them. Law-like andreproducible regularities in the sciences ofman (...) are by no means separated from a patient'spersonal-hermeneutic mediation. This makes itpossible for human beings to modify, improve orsometimes even entirely (or better almostentirely) suspend these psychological,sociological, ethnological, medical,regularities. For this reason the sciences ofman including medicine are under the obligationof constantly inspecting the continuingvalidity of the rules on which theirpredictions and explanations are based, namelyby indirect, statistical methods. Thisrequires a synergistic collaboration ofextra-clinical and clinical tests through whichmedicine can obtain a good level ofintersubjective testability. (shrink)

The ability to predict events within its field indicates that a science has reached a high level of development, that its essential facts stand in systematic relationship to each other. It is important to note that prediction does not always culminate in control, but effective control is impossible without it. Thus, medicine can predict the course of certain fatal diseases with which it is unable to cope, and the astronomer can forsee eclipses and other cosmic events, yet remain powerless (...) to intervene. Since events occurring at the human level are essentially the products of human effort and experience, it is reasonable to suppose that greater predictability in the social sciences will enhance man's control over his destiny as a social being. (shrink)

The often-emphasized tension between the singularity of the patient and technical–scientific reproducibility in medicine cannot be resolved without a discussion of the epistemological and methodological status of the human sciences. On the one hand, the rules concerning human action are analogous to the scientific laws of nature. They are de facto sufficiently stable to allow predictions and explanations similar to those of experimental sciences. From this point of view, it is only a trivial truth, but still a methodological irrelevancy, (...) that the patient and the doctor–patient relationship represent an ontologically irreproducible reality. On the other hand, however, one can never exclude that one can fail in the application of "laws" of the human sciences to the individual patient, for such laws are by no means wholly separated from a patient's personal-hermeneutic mediation, and can at any time be revoked by becoming aware of them. This requires a synergistic collaboration of clinical and statistical methods, and shows a methodologically relevant sense in which one cannot disregard the singularity of the patient. The reason for the crucial role of the patient's singularity in medicine is every individual patient's capacity to revoke, in principle, routines and quasi-automatisms, even though the personal mediation by the patient's consciousness de facto changes them in such a small degree that predictions and explanations modeled in experimental science remain possible. (shrink)

The acceptance of military directives violating medical ethics and international covenants encouraged by the demonisation of the enemy by the US president in 2002 has effectively removed the right of medical personnel to refuse participation in internationally proscribed actionsMedicine and its traditional ethic of care is today a victim of the current conflict in Iraq and Afghanistan, its uniquely humanising mission rejected by US President George W Bush and his advisors. In denying the applicability of international agreements guaranteeing medicine’s (...) ecumenical role in this conflict they have transformed medicine into just another weapon of tactical significance. The result, predictable in retrospect, has been to make military physicians and nurses complicit—actively or passively—in what Litton calls an “atrocity-producing situation”, resulting in detainee or prisoner abuse.1From the first revelations of detainee torture in US detention camps to recent allegations of continued abuse , the focus of international attention has shifted from the US prosecution of low ranking, non-commissioned military personnel to the context in which the atrocities they committed occurred. “No one up the chain of command has ever been held accountable for what is in these horrifying images,” Center for Constitutional Rights Director Bill Goodman said of recently published photographs of 2004 prisoner torture and abuse.2 “The situation in several areas violates international law and conventions on human rights and torture,” said the UN Special Rapporteur on Torture following a 2006 investigation.3The denial of international law and convention involved the overt disavowal of covenants and conventions that for almost 150 years required medical personnel in the US military to act within the guidelines of a Hippocratic vision of medicine. To understand how fundamental this change has been requires a brief review of the history of medicine’s previously protected status and then a description of …. (shrink)

Personalized Medicine (PM) is an evolving and often missinterpreted concept and no agreement of personalization exist. We examined the PM discourse towards foucauldian archeological and genealogical analysis to understand the meaning of “personalization” in medicine. In the archaeological analysis, the historical evolution is characterized by the coexistence of two epistemologies: the holistic vision and the omic sciences. The genealogical analysis shows how these epistemologies may affect the meaning of “person” and, consequently, the ontology of patients. Additionally, substitutions/confusions of (...) the term PM are related to continuously evolving medical knowledge and new technologies; different etymological roots of “personalization” and “person”; and cultural differences. In conclusion, if the definition of “personalization” in medicine is not clear, patients might get wrong expectations about what is achievable for their health. Therefore, epistemological trends should not be separated as they drive same goals: providing accurate diagnosis and treatments based on large data to predict disease progression. (shrink)

This study examines factors associated with the decision of Malaysian youth to participate in a voluntary urban agriculture program. Urban agriculture has generated significant interest in developing countries to address concerns over food security, growing urbanization and employment. While an abundance of data shows attracting the participation of young people in traditional agriculture has become a challenge for many countries, few empirical studies have been conducted on youth motivation to participate in urban agriculture programs, particularly in non-Western settings. Drawing on (...) the theories of planned behavior and the functional approach to volunteer motivation, we surveyed 890 students from a public university in Malaysia about their intention to join a new urban agriculture program. Hierarchical regression findings indicated that the strongest predictor of participation was students’ attitude toward urban agriculture, followed by subjective norms, career motives and perceived barriers to participation. The findings from this study may provide useful information to the university program planners in Malaysia in identifying mechanisms for future students’ involvement in the program. (shrink)

BackgroundSystems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology ; “big data” statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers (...) working to generate systems medicine knowledge and clinicians working to apply it.DiscussionThis article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through “big data” approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the “death computer,” to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their “quantified self.”SummaryThis paper examines possible ethical challenges that are likely to be raised as systems medicine to be translated into clinical medicine. These include the epistemological challenges for clinical decision-making, the use of scoring systems optimized by big data techniques and the risk that incidental and secondary findings will significantly increase. While some ethical implications remain still hypothetical we should use the opportunity to prospectively identify challenges to avoid making foreseeable mistakes when systems medicine inevitably arrives in routine care. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Moral Distress in Academic Medicine: My Brother’s Keeper?Lauren B. SmithAs a member of the hospital ethics committee, I’ve become the go–to person for any ethical issues that arise in our Department. Being a pathologist who is interested in ethics, I’m a rare bird. In this role, I get the occasional curbside consult when anyone has a question or concern. Shortly after an ethics lecture to our trainees, one (...) of the junior residents approached me and asked to speak privately. We headed to the cafeteria and found a private table where we could talk. She hesitated, running her fingers through her hair and gazing around the room before speaking.She told me that the trainees were concerned because they had noticed that the pathologists at another institution were not grading one type of cancer the way that they had learned to do this at our hospital. This type of cancer grading is a surrogate for aggressiveness, and, while somewhat flawed, it often determines the staging and adjuvant therapy that the patient will receive. The resident argued that at this hospital, patients were getting assigned cancer grades that were higher than the ones they would receive at our institution. Therefore, a cancer presenting at the other hospital would be considered more aggressive by the clinicians treating the patient.The resident and many of her colleagues had tried to broach this subject with the pathologists. [End Page E18] Many had been brave enough to voice their confusion and concern over the practices. Their efforts, she explained, had been rebuffed. The pathologists assured the residents that they were grading their cases correctly and cited a reference that they used for this purpose. Due to the hierarchical nature of medicine, it is understandably difficult for trainees to confront attending physicians when they have concerns about their clinical cases and diagnostic acumen. Residents and fellows often do not express their concerns for fear of overstepping their roles. In spite of this, many trainees felt that their concerns for the patient made them set aside their own best interest and they spoke up. Moral distress and genuine concern trumped self–interest in this case, which was admirable.At the time of our meeting, I wondered what I could do to help. I am a hematopathologist who specializes in diagnosing leukemias and lymphomas. I know very little about solid tumor diagnosis and treatment. I have not looked at many solid tumors since I was a trainee six years ago. I do not read the literature in that area and I’m not up–to–date on any controversies regarding grading. In summary, I am far from an expert.However, the problem, on a broader scale, was familiar. As pathologists, we may disagree with or question the diagnoses of our colleagues. What is the appropriate course of action when this occurs? This question is an interesting and infinitely complex issue in the realm of pathological diagnosis. If you aren’t a pathologist or a physician, it may be difficult to grasp why there isn’t a right answer in every case. Diagnosing cancer, in many ways, is truly an art as much as a science. Many intersecting variables are at play, including the size and quality of the sample, the experience and training of the pathologist, and the clinical information available at the time of the diagnosis. Some areas are fraught with subjectivity and inter–observer reliability. Some pathologists are more skilled than others. These are realities that no one wishes to freely admit.It is important, however, to differentiate between systematic and random errors. There are many errors that are difficult to predict or avoid. However, systematic errors are the ones that we most want to uncover as they can be fixed with education and awareness. This case appeared to represent a systematic error in which the pathologists at the other hospital were all performing grading in a way that differed from usual practice.I wondered if it would be overstepping my role to speak to the pathologists. I ran the situation by some of the senior pathologists that I know. Many understood my concern but subtly discouraged any action. Many felt... (shrink)

Invested with the capacity to reinstate physiological order, medicines are at the centre of contemporary health care. Their purpose and efficacy are generally seen as predictable and concrete: disease = therapy = outcome. These culturally specific understandings shape the practices and meanings of taking medicines. This article, however, queries what actually takes place when human bodies and medical drugs converge. Is it a solely therapeutic affair, a restoration of bodily normality, or one of multiple transformations? The ambivalent meaning of the (...) original Greek word for drug, pharmakon, intimates the potential of medicines to act as ‘remedy’ as well as ‘poison’. Using pharmakon as a conceptual tool, the article explores the complex, and often paradoxical corporeal effects of HIV combination therapy, with particular focus on lipodystrophy, a peculiar change in people‘s body shape. This unintended and frequently distressing iatro-genic phenomenon challenges common notions of therapeutic efficacy and causality and foregrounds the productive dimension of medical drugs - their capacity to reconfigure bodies, diseases and identities in multiple, unpredictable ways. (shrink)

The emerging concept of systems medicine (or ‘P4 medicine’—predictive, preventive, personalized and participatory) is at the vanguard of the post-genomic movement towards ‘precision medicine’. It is the medical application of systems biology, the biological study of wholes. Of particular interest, P4 systems medicine is currently promised as a revolutionary new biomedical approach that is holistic rather than reductionist. This article analyzes its concept of holism, both with regard to methods and conceptualization of health and disease. (...) Rather than representing a medical holism associated with basic humanistic ideas, we find a technoscientific holism resulting from altered technological and theoretical circumstances in biology. We argue that this holism, which is aimed at disease prevention and health optimization, points towards an expanded form of medicalization, which we call ‘holistic medicalization’: Each person’s whole life process is defined in biomedical, technoscientific terms as quantifiable and controllable and underlain a regime of medical control that is holistic in that it is all-encompassing. It is directed at all levels of functioning, from the molecular to the social, continual throughout life and aimed at managing the whole continuum from cure of disease to optimization of health. We argue that this medicalization is a very concrete materialization of a broader trend in medicine and society, which we call ‘the medicalization of health and life itself’. We explicate this holistic medicalization, discuss potential harms and conclude by calling for preventive measures aimed at avoiding eventual harmful effects of overmedicalization in systems medicine (quaternary prevention). (shrink)

A decade after the completion of the Human Genome Project, the widespread appeal of personalized genomic medicine's vision and potential virtues for health care remains compelling. Advocates argue that our current medical regime “is in crisis as it is expensive, reactive, inefficient, and focused largely on one size fits all treatments for events of late stage disease.” What is revolutionary about this kind of medicine, its advocates maintain, is that it promises to resolve that crisis by simultaneously increasing (...) the ability to be “personalized,” “predictive,” “preventive,” and “participatory.” Some call personalized genomic medicine “P4 Medicine,” inscribing these cardinal virtues into the movement's name. All of these putative virtues have interesting implications for the future of health care. In this essay, we are especially interested in the claims that personalized medicine will lead to a more “participatory” or “patient‐centered” approach to health care, in which patients are “empowered” to take more personal control over their care. The rhetoric of patient empowerment is nothing new in health care, but personalized medicine is an interesting case study because it portrays empowerment as one of its key virtues and as a mechanism for fixing the health care “crisis.”. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Evidence-Based Medicine and EvaluativismTim Thornton (bio)KeywordsPhilosophy, psychiatry, values, causalThe rise of evidence-based medicine (EBM) in psychiatry has brought, in its train, a concentration on the validity of psychiatric taxonomy to augment the previous focus on reliability (in the medical sense of inter-subject agreement). This is not surprising. If EBM is to be a trustworthy guide to future events, such as patient recovery, it must be based on (...) projectible predicates (Goodman 1983). Not all the predicates that apparently fit past observations would produce true predictions for the future. Furthermore, there is reason to think that employing projectible predicates goes a long way to satisfy the (widespread if contested) aim of being based on a nomological science (Papineau 1986). Thus, the successful implementation of EBM within psychiatry requires the successful articulation of a valid psychiatric taxonomy.This connection helps to explain why fears about the application of EBM to psychiatry often turn on fears about the application of the criteriological model of diagnosis to individuals. In her commentary in this issue, Gloria Ayob has examined some of the arguments concerning the application of EBM to individuals. In this brief commentary, I examine a different potential source of disquiet focused on the underlying nature of psychiatric taxonomy.Dimensions for Psychiatric TaxonomyIn their recent paper, Peter Zachar and Kenneth Kendler suggest a number of different dimensions according to which rival conceptions of psychiatric taxonomy can be mapped. These include (1) causalism–descriptivism, (2) essentialism– nominalism, (3) objectivism–evaluativism, (4) internalism–externalism, (5) entities–agents, and (6) categories–continua (2007, 557). At the heart of the objectivism-evaluativism dimension is the question:Is deciding whether or not something is a psychiatric disorder a simple factual matterY (objectivism), or does it inevitably involve a value-laden judgment (evaluativism)?(Zachar and Kendler 2007, 558)Objectivists argue that the concept of disorder is a simple or plain factual matter by contrast with an evaluation. The apparently evaluative connotations of disorder, they argue, can either be reduced to, or explained away in, more basic terms, which are not themselves essentially evaluative. Thus, for example, the attempt to explain disorder in statistical terms is a form of objectivism. The more plausible attempt to explain disorder through the idea of a biological or proper function is also usually presented as a form of objectivism. (The most famous proponent of a biological approach, however, Jerome Wakefield, adds to an objectivist-aspiring core an explicit value in the form of harm [End Page 175] [Wakefield 1999].) Whether or not it can be successful as a form of objectivism, in addition to whether an analysis in biological terms is possible, depends on whether the account of function can fully discharge any initial evaluative or normative assumptions.There seems to be good evidence that current psychiatric taxonomy, at least, contains values. John Sadler, for example, makes a powerful case for this in his substantial work Values and Psychiatric Diagnosis (2005). Sadler, furthermore, addresses in some detail a further set of questions concerning the kinds and nature of the values involved. I outline just one further question about the nature of values involved.Zachar and Kendler contrast the presence of values with objectivism. Objectivity has at least two relevant senses reflecting contrasts with two senses of subjectivity. It—objectivity—might mean requiring no special subject for the conception and framing of relevant judgments. (This mirrors primary, by contrast with secondary qualities, and Williams' idea of an absolute conception [Williams 1978]). Or, it might mean disciplining and providing a contrast between correctness and incorrectness, or truth and falsity, for the relevant judgments. This contrasts with subjective whimsy.Although it seems relatively straight forward that the conception and framing of value judgments requires that subjects have a particular kind of mind, that still leaves open the other issue. Are value judgments disciplined by anything or does the "truth" of a value judgment collapse back into its being sincerely made?Evaluativism in Psychiatric Taxonomy and EBMThis question relates to the application of EBM to psychiatry in this way. On a disciplined account, psychiatric taxonomy can aim to get right the mixture or, better, the compound of simple facts and values... (shrink)

Rid and Wendler propose the development of a Patient Preference Predictor (PPP), an actuarial model for predicting incapacitated patient’s life-sustaining treatment preferences across a wide range of end-of-life scenarios. An actuarial approach to end-of-life decision making has enormous potential, but transferring the logic of actuarial prediction to end-of-life decision making raises several conceptual complexities and logistical problems that need further consideration. Actuarial models have proven effective in targeted prediction tasks, but no evidence supports their effectiveness in the kind of broad (...) spectrum prediction task that is the proposed goal of the PPP. We argue that a more focused approach, targeting specific medical conditions and generating treatment predictions based on the preferences of individuals with actual disease experience, is both more firmly grounded in past research and is a more prudent initial strategy for exploring the efficacy of actuarial prediction in end-of-life decision making. (shrink)

Genomic medicine has the potential to contribute to the development of an array of novel technologies within the clinical armoury, making possible early detection and management of high-risk conditions such as cancer. While significant impact has already been felt in the context of rare inherited single gene disorders, much of the advancement in patient care through genomic medicine more broadly is going to be made possible by research involving large data sets that enable analyses of multiple genetic variants (...) that contribute to risk of common diseases. 1 As well as informing diagnosis and treatment of these diseases, these advances will support prediction and prevention. Considering risk prediction, combining data from multiple variants can produce a polygenic (or integrated) score (PGS/IGS). This will provide more accurate prediction than simply relying on environmental risk factors. While still in their early stages of development and implementation, it is clear that translation... (shrink)

Although cases are central to the epistemic practices utilized within clinical medicine, they appear to be limited in their ability to provide evidence about causal relations because they provide detailed accounts of particular patients without explicit filtering of those attributes most likely to be relevant for explaining the phenomena observed. This paper uses a series of recent case reports to explore the role of cases in casual attribution in medical diagnosis. It is argued that cases are brought together by (...) practitioners to generate causal attributions and testable predictions using a manipulability view of causation. (shrink)

Since the late 1980s, the human genetics and genomics research community has been promising to usher in a “new paradigm for health care”—one that uses molecular profiling to identify human genetic variants implicated in multifactorial health risks. After the completion of the Human Genome Project in 2003, a wide range of stakeholders became committed to this “paradigm shift,” creating a confluence of investment, advocacy, and enthusiasm that bears all the marks of a “scientific/intellectual social movement” within biomedicine. Proponents of this (...) movement usually offer four ways in which their approach to medical diagnosis and health care improves upon current practices, arguing that it is more “personalized,” “predictive,” “preventive,” and “participatory” than the medical status quo. Initially, it was personalization that seemed to best sum up the movement's appeal. By 2012, however, powerful opinion leaders were abandoning “personalized medicine” in favor of a new label: “precision medicine.” The new label received a decisive seal of approval when, in January 2015, President Obama unveiled plans for a national “precision medicine initiative” to promote the development and use of genomic tools in health care. (shrink)

Since its advent, predictive DNA testing has been perceived as a technology that may have considerable impact on the quality of people’s life. The decision whether or not to use this technology is up to the individual client. However, to enable well considered decision making both the negative as well as the positive freedom of the individual should be supported. In this paper, we argue that current professional and public discourse on predictive DNA-testing is lacking when it comes (...) to supporting positive freedom, because it is usually framed in terms of risk and risk management. We show how this ‘risk discourse’ steers thinking on the good life in a particular way. We go on to argue that empirical research into the actual deliberation and decision making processes of individuals and families may be used to enrich the environment of personal deliberation in three ways: (1) it points at a richer set of values that deliberators can take into account, (2) it acknowledges the shared nature of genes, and (3) it shows how one might frame decisions in a non-binary way. We argue that the public sharing and discussing of stories about personal deliberations offers valuable input for others who face similar choices: it fosters their positive freedom to shape their view of the good life in relation to DNA-diagnostics. We conclude by offering some suggestions as to how to realize such public sharing of personal stories. (shrink)