In this paper, we analyse the relation between the use of environmental data in contemporary health sciences and related conceptualisations and operationalisations of the notion of environment. We consider three case studies that exemplify a different selection of environmental data and mode of data integration in data-intensive epidemiology. We argue that the diversification of data sources, their increase in scale and scope, and the application of novel analytic tools have brought about three significant conceptual (...) shifts. First, we discuss the EXPOsOMICS project, an attempt to integrate genomic and environmental data which suggests a reframing of the boundaries between external and internal environments. Second, we explore the MEDMI platform, whose efforts to combine health, environmental and climate data instantiate a reframing and expansion of environmental exposure. Third, we illustrate how extracting epidemiological insights from extensive social data collected by the CIDACS institute yields innovative attributions of causal power to environmental factors. Identifying these shifts highlights the benefits and opportunities of new environmental data, as well as the challenges that such tools bring to understanding and fostering health. It also emphasises the constraints that data selection and accessibility pose to scientific imagination, including how researchers frame key concepts in health-related research. (shrink)

Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, (...) and argue that they constitute an example of classificatory theory. This form of theorizing emerges from classification practices in conjunction with experimental know-how and expresses the knowledge underpinning the analysis and interpretation of data disseminated online. (shrink)

Data-intensive science comes with increased risks concerning quality and reliability of data, and while trust in science has traditionally been framed as a matter of scientists being expected to adhere to certain technical and moral norms for behaviour, emerging discourses of open science present openness and transparency as substitutes for established trust mechanisms. By ensuring access to all available information, quality becomes a matter of informed judgement by the users, and trust no longer seems necessary. This strategy (...) does not, however, take into consideration the networks of professionals already enabling data-intensive science by providing high-quality data. In the life sciences, biological data- and knowledge bases managed by expert biocurators have become crucial for data-intensive research. In this paper, I will use the case of biocurators to argue that openness and transparency will not diminish the need for trust in data-intensive science. On the contrary, data-intensive science requires a reconfiguration of existing trust mechanisms in order to include those who take care of and manage scientific data after its production. (shrink)

The digitization of society and academic research endeavours have led to an explosion of interest in the potential uses of population data in research. Alongside this, increasing attention is focussing on the conditions necessary for maintaining a social license for research practices. Previous research has pointed to the importance of demonstrating “public benefits” from research for maintaining public support, yet there has been very little consideration of what the term “public benefits” means or what public expectations of “public benefits” (...) are. In order to address this pressing issue a series of deliberative workshops with members of the public were held across Scotland in May and June 2017. The workshops aimed to engage a cross-section of the Scottish population in in-depth discussions of the ways that the public – or publics – might benefit from data-intensive health research. The findings reported here discuss workshop participants’ understandings and expectations of health research; who they considered to be “the public” that should benefit from health research and; in what ways they felt “the public” should benefit. Workshop participants’ preference was clearly for the widest possible public benefit to be felt by all, but they also acknowledged the value in research aiming to primarily benefit vulnerable groups within society. A key focus of discussions was the extent to which workshop participants were confident that potential public benefits would be realised. A crucial consideration then is the extent to which mechanisms and political support are in place to realise and maximise the public benefits of data-intensive health research. (shrink)

BackgroundThe rise of Big Data-driven health research challenges the assumed contribution of medical research to the public good, raising questions about whether the status of such research as a common good should be taken for granted, and how public trust can be preserved. Scandals arising out of sharing data during medical research have pointed out that going beyond the requirements of law may be necessary for sustaining trust in data-intensive health research. We propose building upon the (...) use of a social licence for achieving such ethical governance.Main textWe performed a narrative review of the social licence as presented in the biomedical literature. We used a systematic search and selection process, followed by a critical conceptual analysis. The systematic search resulted in nine publications. Our conceptual analysis aims to clarify how societal permission can be granted to health research projects which rely upon the reuse and/or linkage of health data. These activities may be morally demanding. For these types of activities, a moral legitimation, beyond the limits of law, may need to be sought in order to preserve trust. Our analysis indicates that a social licence encourages us to recognise a broad range of stakeholder interests and perspectives in data-intensive health research. This is especially true for patients contributing data. Incorporating such a practice paves the way towards an ethical governance, based upon trust. Public engagement that involves patients from the start is called for to strengthen this social licence.ConclusionsThere are several merits to using the concept of social licence as a guideline for ethical governance. Firstly, it fits the novel scale of data-related risks; secondly, it focuses attention on trustworthiness; and finally, it offers co-creation as a way forward. Greater trust can be achieved in the governance of data-intensive health research by highlighting strategic dialogue with both patients contributing the data, and the public in general. This should ultimately contribute to a more ethical practice of governance. (shrink)

Complex organisms thwart the simple rectilinear causality paradigm of “necessary and sufficient,” with its experimental strategy of “knock down and overexpress.” This Essay organizes the eccentricities of biology into four categories that call for new mathematical approaches; recaps for the biologist the philosopher's recent refinements to the causation concept and the mathematician's computational tools that handle some but not all of the biological eccentricities; and describes overlooked insights that make causal properties of physical hierarchies such as emergence and downward causation (...) straightforward. Reviewing and extrapolating from similar situations in physics, it is suggested that new mathematical tools for causation analysis incorporating feedback, signal cancellation, nonlinear dependencies, physical hierarchies, and fixed constraints rather than instigative changes will reveal unconventional biological behaviors. These include “eigenisms,” organisms that are limited to quantized states; trajectories that steer a system such as an evolving species toward optimal states; and medical control via distributed “sheets” rather than single control points. (shrink)

Complex organisms thwart the simple rectilinear causality paradigm of “necessary and sufficient,” with its experimental strategy of “knock down and overexpress.” This Essay organizes the eccentricities of biology into four categories that call for new mathematical approaches; recaps for the biologist the philosopher's recent refinements to the causation concept and the mathematician's computational tools that handle some but not all of the biological eccentricities; and describes overlooked insights that make causal properties of physical hierarchies such as emergence and downward causation (...) straightforward. Reviewing and extrapolating from similar situations in physics, it is suggested that new mathematical tools for causation analysis incorporating feedback, signal cancellation, nonlinear dependencies, physical hierarchies, and fixed constraints rather than instigative changes will reveal unconventional biological behaviors. These include “eigenisms,” organisms that are limited to quantized states; trajectories that steer a system such as an evolving species toward optimal states; and medical control via distributed “sheets” rather than single control points. (shrink)

Recent claims, mainly from computer scientists, concerning a largely automated and model-free data-intensive science have been countered by critical reactions from a number of philosophers of science. The debate suffers from a lack of detail in two respects, regarding the actual methods used in data-intensive science and the specific ways in which these methods presuppose theoretical assumptions. I examine two widely-used algorithms, classificatory trees and non-parametric regression, and argue that these are theory-laden in an external sense, (...) regarding the framing of research questions, but not in an internal sense concerning the causal structure of the examined phenomenon. With respect to the novelty of data-intensive science, I draw an analogy to exploratory as opposed to theory-directed experimentation. (shrink)

Life sciences research is increasingly international and data-intensive. Researchers work in multi-jurisdictional teams or formally established research consortia to exchange data and conduct research using computation of multiple sources and volumes of data at multiple sites and through multiple pathways. Despite the internationalization and data intensification of research, the same ethics review process as applies to single-site studies in one country tends to apply to multi-site studies in multiple countries. Because of the standard requirement for (...) multi-jurisdictional or multi-site ethics review, international research projects are subjected to multiple ethics reviews of the same research protocol. Consequently, the reviews may be redundant and resource-consuming, whilst the opinions delivered by ethics committees may be inconsistent both within and across jurisdictions. In this article, we present findings based on interviews conducted with international experts in research ethics on the topic of et... (shrink)

For years, attempts at ensuring the social sustainability of digital solutions have focused on ensuring that they are perceived as helpful and easy to use. A smooth and seamless work experience has been the goal to strive for. Based on document analysis and interviews with 15 stakeholders, we trace the setting up of a data infrastructure in Danish General Practice that had achieved just this goal – only to end in a scandal and subsequent loss of public support. The (...) ease of data access made it possible for data to be extracted, exchanged and used by new actors and for new purposes – without those producing the data fully realizing the expansion of the infrastructure. We suggest that the case has wider relevance for a still more data-intensive healthcare sector and a growing data economy: when those who produce the data are not made aware of new uses of data, it makes it more difficult to resolve potential conflicts along the way. In the Danish case, conflicting views on legitimate data use led to the collapse of the infrastructure. Therefore, while seamlessness may be a solution to the old problem of a poor fit between user and technology, this celebrated virtue may also involve new problems relating to social instability. As digital solutions tend to be integrated still more seamlessly in still more of our activities, we need to develop political mechanisms to define and protect the rights and obligations of both data suppliers and users in order to ensure the long-term sustainability of digital infrastructures. (shrink)

This chapter argues for the importance of considering conceptual and normative commitments when addressing questions of responsible practice in data-intensive agricultural research and development. We consider genetic gain-focused plant breeding strategies that envision a data-intensive mode of breeding in which genomic, environmental and socio-economic data are mobilised for rapid crop variety development. Focusing on socio-economic data linkage, we examine methods of product profiling and how they accommodate gendered dimensions of breeding in the field. Through (...) a comparison with participatory breeding methods, we argue that the conceptual commitments underpinning current methods of integrating socioeconomic data into calculations of genetic gain can preclude the achievement of key social development goals, and that better engagement with participatory approaches can help address this problem. We conclude by identifying three key avenues towards a data-intensive approach to plant breeding that utilises the diverse sources of relevant evidence available, including socio-economic data, and maximises the chance of developing sustainable and responsible strategies and research practices in this domain: (1) reliable, long-term management of data infrastructures; (2) ongoing critical analysis of the conceptual foundations of specific strategies; and (3) regular transdisciplinary consultations including expertise in the social studies of agricultural science as well as participatory breeding techniques. (shrink)

Ample scholarship demonstrates that data-intensive technologies have the capacity to cause serious harm and that their developers are obliged to address ethics in their work. This ethnographic paper tells the story of data scientists attempting to instantiate a carefully considered ethical vision into a data infrastructure while balancing competing priorities, negotiating divergent interests, and wrestling with contrasting values. I use their story to develop the concept of “ethical abduction,” which I characterize as an exemplary process by (...) which actors can intentionally and systematically address ethical issues that arise during their day-to-day actions by making decisions with consideration for a foundational ethical worldview. It entails tacking back and forth between divergent but complementary ways of thinking: between establishing ideals and making decisions given practical constraints; between understanding historical context and anticipating future consequences; between acknowledging structural dependencies and accepting responsibility for moral agency. (shrink)

We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and (...) the transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape. (shrink)

BackgroundThe health sector aims to improve health outcomes and access to healthcare. At the same time, the sector relies on unsustainable environmental practices that are increasingly recognised to be catastrophic threats to human health and health inequities. As such, a moral imperative exists for the sector to address these practices. While strides are currently underway to mitigate the environmental impacts of healthcare, less is known about how health researchers are addressing these issues, if at all.MethodsThis paper uses an interview methodology (...) to explore the attitudes of UK health researchers using data-intensive methodologies about the adverse environmental impacts of their practices, and how they view the importance of these considerations within wider health goals.ResultsInterviews with 26 researchers showed that participants wanted to address the environmental and related health harms associated with their research and they reflected on how they could do so in alignment with their own research goals. However, when tensions emerged, their own research was prioritised. This was related to their own desires as researchers and driven by the broader socio-political context of their research endeavours.ConclusionTo help mitigate the environmental and health harms associated with data-intensive health research, the socio-political context of research culture must be addressed. (shrink)

Current challenges to sustaining public support for health data research have directed attention to the governance of data-intensive health research networks. Accountability is hailed as an important element of trustworthy governance frameworks for data-intensive health research networks. Yet the extent to which adequate accountability regimes in data-intensive health research networks are currently realized is questionable. Current governance of data-intensive health research networks is dominated by the limitations of a drawing board approach. (...) As a way forward, we propose a stronger focus on accountability as learning to achieve accountable governance. As an important step in that direction, we provide two pathways: (1) developing an integrated structure for decision-making and (2) establishing a dialogue in ongoing deliberative processes. Suitable places for learning accountability to thrive are dedicated governing bodies as well as specialized committees, panels or boards which bear and guide the development of governance in data-intensive health research networks. A continuous accountability process which comprises learning and interaction accommodates the diversity of expectations, responsibilities and tasks in data-intensive health research networks to achieve responsible and effective governance. (shrink)

Data on farming systems in Petén, Guatemala, were used to develop an agricultural intensity index. The index can be used to assign an intensity “score” to a given farming system based on the array of practices used by the farmer, each practice’s contribution to production intensity, and the scale at which these practices are used. The scores assigned to 118 farmers in three study areas in Petén were analyzed through analysis of variance (ANOVA) to identify the factors that account (...) for the variation in intensity levels, as measured through the index. The analyses reveal that the factors influencing agricultural intensity in Petén vary greatly from one study area to the next. This is due to differences in livelihood opportunities and strategies that, in turn, affect how agriculture fits into the local economy and how and why intensification is pursued. Variation in intensity levels can best be understood by considering the factors at the household and sub-regional scales that influence (a) whether farmers feel a need to intensify, (b) whether they see some benefit in doing so, and (c) whether they have the resources required to intensify production through particular strategies. Close attention must be paid to these factors by conservation and development organizations seeking to influence land use patterns and conserve forest in Petén. (shrink)

Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal (...) knowledge is necessary for the project, both as a source for handling complexity and as an output for meeting the project’s goals. Consequently, I argue that data-driven claims about causality are fundamentally flawed and causal knowledge should be considered a necessary aspect of Big Data science. In addition, I present the consequences of this result on other data-driven claims, concerning the role of theoretical considerations. I argue that the importance of causal knowledge and other kinds of theoretical engagement in EXPOsOMICS undermine theory-free accounts and suggest alternative ways of framing science based on Big Data. (shrink)

Has the rise of data-intensive science, or ‘big data’, revolutionized our ability to predict? Does it imply a new priority for prediction over causal understanding, and a diminished role for theory and human experts? I examine four important cases where prediction is desirable: political elections, the weather, GDP, and the results of interventions suggested by economic experiments. These cases suggest caution. Although big data methods are indeed very useful sometimes, in this paper’s cases they improve predictions (...) either limitedly or not at all, and their prospects of doing so in the future are limited too. (shrink)

I argue for the causal character of modeling in data-intensive science, contrary to widespread claims that big data is only concerned with the search for correlations. After discussing the concept of data-intensive science and introducing two examples as illustration, several algorithms are examined. It is shown how they are able to identify causal relevance on the basis of eliminative induction and a related difference-making account of causation. I then situate data-intensive modeling within a (...) broader framework of an epistemology of scientific knowledge. In particular, it is shown to lack a pronounced hierarchical, nested structure. The significance of the transition to such “horizontal” modeling is underlined by the concurrent emergence of novel inductive methodology in statistics such as non-parametric statistics. Data-intensive modeling is well equipped to deal with various aspects of causal complexity arising especially in the higher level and applied sciences. (shrink)

In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are (...) in tension with a prominent account of scientific method, often called “Inference to the Best Explanation”. Later on, in Section 3, I consider an argument against IBE that will be congenial to proponents of Big Data, namely, the argument due to Roche and Sober Analysis, 73:659–668, that “explanatoriness is evidentially irrelevant.” This argument is based on Bayesianism, one of the most prominent general accounts of theory-confirmation. In Section 4, I consider some extant responses to this argument, especially that of Climenhaga Philosophy of Science, 84:359–368,. In Section 5, I argue that Roche and Sober’s argument does not show that explanatory reasoning is dispensable. In Section 6, I argue that there is good reason to think explanatory reasoning will continue to prove indispensable in scientific practice. Drawing on Cicero’s oft-neglected De Divinatione, I formulate what I call the “Ciceronian Causal-nomological Requirement”, which states, roughly, that causal-nomological knowledge is essential for relying on correlations in predictive inference. I defend a version of the CCR by appealing to the challenge of “spurious correlations,” chance correlations which we should not rely upon for predictive inference. In Section 7, I offer some concluding remarks. (shrink)

Background Moral distress has negative effects on physical and mental health. However, there is little information about nurses’ coping strategies reducing moral distress. Aim The purpose of this study was to investigate the coping strategies of intensive care unit nurses reducing moral distress in Iran. Study design This is a qualitative study with a content analysis approach. Participants and research context The research sample consisted of nurses working in intensive care units of teaching hospitals affiliated to Tehran University (...) of Medical Sciences. Samples were selected among eligible nurses by purposive sampling. Data were obtained through 17 in-depth, individual, and semi-structured interviews with 17 nurses. Graneheim and Lundman’s (2004) 6-step content analysis method was used to analyze the data. Data management was also performed by MAXQDA software version 20. The COREQ checklist was used to report the study. Ethical considerations This project was approved by the Ethics Committee of Tehran University of Medical Sciences. All ethical guidelines in research were followed. Finding The data analysis resulted in the formation of two main categories of desirable coping strategies (with two subcategories of compensation and rejuvenation) and less desirable coping strategies (with three subclasses of indifference over time, escape and concealment). Discussion The intensive care unit nurses in dealing with ethical problems first try to solve the problem through discussion, but when they fail to resolve it peacefully, they resort to several coping strategies. Factors, such as increasing experience, lack of support from hospital managers and officials, poor communication between colleagues, the need to maintain hierarchy, fear of reprimand, and a sense of powerlessness, changed the nurses’ preferred strategies. It is important for managers to provide a blame/punishment-free atmosphere for expression of ethical experiences; a supportive atmosphere in which staff can engage in ethical discussions without fear of punishment. They should also provide opportunities for rest, rejuvenation, and adequate training for their employees. (shrink)

In recent years, calls have been made to address the relative dearth of qualitative sociological investigation into the sensory dimensions of embodiment, including within physical cultures. This article contributes to a small, innovative and developing literature utilizing sociological phenomenology to examine sensuous embodiment. Drawing upon data from three research projects, here we explore some of the ‘sensuousities’ of ‘intense embodiment’ experiences as a distance-running-woman and a boxing-woman, respectively. Our analysis addresses the relatively unexplored haptic senses, particularly the ‘touch’ of (...) heat. Heat has been argued to constitute a specific sensory mode, a trans-boundary sense. Our findings suggest that ‘lived’ heat, in our own physical-cultural experiences, has highly proprioceptive elements and is experienced as both a form of touch and as a distinct perceptual mode, dependent upon context. Our analysis coheres around two key themes that emerged as salient: (1) warming up, and (2) thermoregulation, which in lived experience were encountered as strongly interwoven. (shrink)

Researchers have identified the phenomena of moral distress through many studies in Western countries. This research reports the first study of moral distress in Iran. Because of the differences in cultural values and nursing education, nurses working in intensive care units may experience moral distress differently than reported in previous studies. This research used a qualitative method involving semistructured and in-depth interviews of a purposive sample of 31 (28 clinical nurses and 3 nurse educators) individuals to identify the types (...) of moral distress among clinical nurses and nurse educators working in 12 cities in Iran. A content analysis of the data produced four themes to describe the nurses’ moral distress. The four themes were as follows: (a) institutional barriers and constraints; (b) communication problems; (c) futile actions, malpractice, and medical/care errors; (d) inappropriate responsibilities, resources, and competencies. The results demonstrate that moral distress for intensive care unit nurses is different and that the nursing leaders must reduce moral distress among nursing in intensive care. (shrink)

Data-intensive techniques, now widely referred to as 'big data', allow for novel ways to address complexity in science. I assess their impact on the scientific method. First, big-data science is distinguished from other scientific uses of information technologies, in particular from computer simulations. Then, I sketch the complex and contextual nature of the laws established by data-intensive methods and relate them to a specific concept of causality, thereby dispelling the popular myth that big (...) class='Hi'>data is only concerned with correlations. The modeling in data-intensive science is characterized as 'horizontal'—lacking the hierarchical, nested structure familiar from more conventional approaches. The significance of the transition from hierarchical to horizontal modeling is underlined by a concurrent paradigm shift in statistics from parametric to non-parametric methods. (shrink)

Suffering repeated experiences of moral distress in intensive care units due to applications of futility reflects on nurses’ patient care negatively, increases their burnout, and reduces their job satisfaction. This study was carried out to investigate the levels of job satisfaction and exhaustion suffered by intensive care nurses and the relationship between them through the futility dimension of the issue. The study included 138 intensive care nurses. The data were obtained with the futility questionnaire developed by (...) the researchers, Maslach Burnout Inventory and Minnesota Satisfaction Questionnaire. It was determined that nurses who agreed to the proposition that the application of futility demoralizes health-care professionals had low levels of job satisfaction but high levels of depersonalization. It was determined that nurses had moderate levels of job satisfaction, emotional exhaustion, and personal achievements but high levels of sensitivity. Nurses’ job satisfaction and sensitivities are positively affected when they consider that futility does not contradict the purposes of medicine. (shrink)

This article examines whether the likelihood and amount of firm charitable giving in response to catastrophic events are related to firm advertising intensity, and whether industry competition level moderates this relationship. Using data on Chinese firms’ philanthropic response to the 2008 Sichuan earthquake, we find that firm advertising intensity is positively associated with both the probability and the amount of corporate giving. The results also indicate that this positive advertising intensity-philanthropic giving relationship is stronger in competitive industries, and firms (...) in competitive industries are more likely to donate. This study thus provides evidence suggesting that even in the wake of catastrophic events, corporate philanthropic giving is strategic. (shrink)

Biomedical deployments of data science capitalise on vast, heterogeneous data sources. This promotes a diversified understanding of what counts as evidence for health-related interventions, beyond the strictures associated with evidence-based medicine. Focusing on COVID-19 transmission and prevention research, I consider the epistemic implications of this diversification of evidence in relation to: (1) experimental design, especially the revival of natural experiments as sources of reliable epidemiological knowledge; and (2) modelling practices, particularly the recognition of transdisciplinary expertise as crucial to (...) developing and interpreting data models. Acknowledging such shifts in evidential, experimental and modelling practices helps avoid harmful applications of data-intensive methods. (shrink)

Researchers have considered individual and organizational factors of ethical decision making. However, they have little interest in situational factors :101–125, 2013) which is surprising given the many situations sales persons face. We address this issue using two pilot qualitative studies successively and a 2 by 2 within-subject experiment with sales scenarios. Qualitative and quantitative data are obtained from front-line employees of the main French retail banks that serve low-income customers. We show that the recognition of an ethical issue differs (...) depending on the role behavior salespersons are engaged in and the nature of the conflict of interest they face. Moreover, the combined effect of these two situational characteristics is mediated by moral intensity. This study not only adds evidence on situational factors affecting ethical decision but also extends empirical research on sales ethics by revealing sales situations that are not considered in the empirical literature. The research implications of the findings are discussed along with the study’s limitations and suggestions for future research. (shrink)

Background:Moral distress is a common problem among professionals working in the field of healthcare. Moral distress is the distress experienced by a professional when he or she cannot fulfill the correct action due to several obstacles, although he or she is aware of what it is. The level of moral distress experienced by nurses working in intensive care units varies from one country/culture/institution to another. However, in Turkey, there is neither a measurement tool used to assess moral distress suffered (...) by nurses nor a study conducted on the issue.Aim/objective:The study aims to (a) validate the Turkish version of the Moral Distress Scale–Revised to be used in intensive care units and to examine the validity and reliability of the Turkish version of the scale, and (b) explore Turkish intensive care nurses’ moral distress level.Method:The sample of this methodological, descriptive, and cross-sectional design study comprises 200 nurses working in the intensive care units of internal medicine and surgical departments of four hospitals in three cities in Turkey. The data were collected with the Socio-Demographic Characteristics Form and The Turkish Version of Moral Distress Scale–Revised.Ethical considerations:The study proposal was approved by the ethics committee of the Faculty of Medicine, Cumhuriyet University. All participating nurses provided informed consent and were assured of data confidentiality.Results:In parallel with the original scale, Turkish version of Moral Distress Scale–Revised consists of 21 items, and shows a one-factor structure. It was determined that the moral distress total and item mean scores of the nurses participating in the study were 70.81 ± 48.23 and 3.36 ± 4.50, respectively.Conclusion:Turkish version of Moral Distress Scale–Revised can be used as a reliable and valid measurement tool for the evaluation of moral distress experienced by nurses working in intensive care units in Turkey. In line with our findings, it can be said that nurses suffered low level of moral distress. However, factors which caused the nurses in our study to experience higher levels of moral distress are inadequate communication within the team, working with professionals they considered as incompetent, and futile care. (shrink)

Background:Moral distress is a common problem among professionals working in the field of healthcare. Moral distress is the distress experienced by a professional when he or she cannot fulfill the correct action due to several obstacles, although he or she is aware of what it is. The level of moral distress experienced by nurses working in intensive care units varies from one country/culture/institution to another. However, in Turkey, there is neither a measurement tool used to assess moral distress suffered (...) by nurses nor a study conducted on the issue.Aim/objective:The study aims to (a) validate the Turkish version of the Moral Distress Scale–Revised to be used in intensive care units and to examine the validity and reliability of the Turkish version of the scale, and (b) explore Turkish intensive care nurses’ moral distress level.Method:The sample of this methodological, descriptive, and cross-sectional design study comprises 200 nurses working in the intensive care units of internal medicine and surgical departments of four hospitals in three cities in Turkey. The data were collected with the Socio-Demographic Characteristics Form and The Turkish Version of Moral Distress Scale–Revised.Ethical considerations:The study proposal was approved by the ethics committee of the Faculty of Medicine, Cumhuriyet University. All participating nurses provided informed consent and were assured of data confidentiality.Results:In parallel with the original scale, Turkish version of Moral Distress Scale–Revised consists of 21 items, and shows a one-factor structure. It was determined that the moral distress total and item mean scores of the nurses participating in the study were 70.81 ± 48.23 and 3.36 ± 4.50, respectively.Conclusion:Turkish version of Moral Distress Scale–Revised can be used as a reliable and valid measurement tool for the evaluation of moral distress experienced by nurses working in intensive care units in Turkey. In line with our findings, it can be said that nurses suffered low level of moral distress. However, factors which caused the nurses in our study to experience higher levels of moral distress are inadequate communication within the team, working with professionals they considered as incompetent, and futile care. (shrink)

This article adapts the ethnographic medium of the diary to develop a method for studying data and related data practices. The article focuses on the creation of one data diary, developed iteratively over three years in the context of a national centre for monitoring disasters and natural hazards in Brazil. We describe four points of focus involved in the creation of a data diary – spaces, interfaces, types and situations – before reflecting on the value of (...) this method. We suggest data diaries are able to capture the informal dimension of data-intensive organisations; enable empirical analysis of the specific ways that data intervene in the unfolding of situations; and as a document, data diaries can foster interdisciplinary and inter-expert dialogue by bridging different ways of knowing data. (shrink)

Faster R-CNN architecture is used to solve the problems of moving path uncertainty, changeable coverage, and high complexity in cold-air induced large-scale intensive temperature-reduction detection and classification, since those problems usually lead to path identification biases as well as low accuracy and generalization ability of recognition algorithm. In this paper, an improved recognition method of national ITR path in China based on faster R-CNN in complicated meteorological systems is proposed. Firstly, quality control of the original dataset of strong cooling (...) processes is carried out by means of data filtering. Then, according to the NITR standard and the characteristics of NITR, the NITR dataset in China is established by the intensive temperature-reduction areas located through spatial transformation. Meanwhile, considering that the selection of regularization parameters of Softmax classification method will cause the problem of probability calculation, support vector machine is used for path classification to enhance the confidence of classification. Finally, the improved faster R-CNN model is used to identify, classify, and locate the path of NITR events. The experimental results show that, compared to other models, the improved faster R-CNN algorithm greatly improves the performance of NITR’s path recognition, especially for the mixed NITR paths and single NITR paths. Therefore, the improved faster R-CNN model has fast calculation speed, high recognition accuracy, good robustness, and generalization ability of NITR path recognition. (shrink)

BackgroundThe Authors have laid out an analysis of Italian COVID-19 confirmed data and fatality rates, pointing out how a dearth of health care resources in northern regions has resulted in hard, ethically challenging decisions in terms of granting patient access to intensive care units (ICU).Main textHaving to make such decisions certainly entails substantial difficulties, and that has led many health care professional to seek ethical guidance. The Italian Society of Anesthesia, Analgesia, Resuscitation and Intensive Care (SIAARTI) has (...) attempted to meet that growing need by a set of recommendations, applying “clinical soundness” as a beacon standard; that approach tends to prioritize patients with higher life expectancy, which could be characterized as a “moderately utilitarian” approach. Yet, such a selection has engendered daunting ethical quandaries. The authors believe it can only be warranted and acceptable if rooted in a transparent decision-making process and verifiable, reviewed criteria. Moreover, the authors have stressed how clinical experimentation in a pandemic setting is a subtext of great interest from an ethical perspective. In Italy, no drug therapy and trials were undertaken for COVID-19 patients for a rather long period of time. When the epidemic was already circulating, an intervention proved necessary on the system of administrative procedures, aimed at expediting the authorization and validation of protocols, then bogged down by bureaucracy. A new system has since been instituted by a government decree that was signed about one month after the first Covid-19 case was officially recorded in the country. Such a swift implementation, which took just a few weeks, is noteworthy and proves that clinical trials can be initiated in a timely fashion, even with a pandemic unfolding. The concerted, action of supportive care and RCTs is the only way to attain effective forms of treatments for COVID-19 and any other future outbreak.ConclusionsThe authors have arrived at the conclusion that the most effective and ethically sound response on the part of any national health care system would be to adequately reconfigure its organizational mechanisms, by making clinical trials and all related administrative procedures consistent with the current state of emergency. (shrink)

This research aims to identify the ethical issues perceived by intensive care nurses in their everyday practice. It also aims to understand why these situations were considered an ethical issue and what interventions/strategies have been or are expected to be developed so as to minimize them. Data were collected using a semi-structured interview with 15 nurses working at polyvalent intensive care units in 4 Portuguese hospitals, who were selected by the homogenization of multiple samples. The qualitative content (...) analysis identified end-of-life decisions, privacy, interaction, team work, and health-care access as emerging ethical issues. Personal, team, and institutional aspects emerge as reasons behind the experience of these issues. Personal and team resources are used in and for solving these issues. Moral development and training are the most significant strategies. (shrink)

BackgroundEthics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts.Main textIn this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we (...) map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC’s scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC’s way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science.ConclusionsWe believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large. (shrink)

Ethicists differ considerably in their reasons for using empirical data. This paper presents a brief overview of four traditional approaches to the use of empirical data: “the prescriptive applied ethicists,” “the theorists,” “the critical applied ethicists,” and “the particularists.” The main aim of this paper is to introduce a fifth approach of more recent date (i.e. “integrated empirical ethics”) and to offer some methodological directives for research in integrated empirical ethics. All five approaches are presented in a table (...) for heuristic purposes. The table consists of eight columns: “view on distinction descriptive-prescriptive sciences,” “location of moral authority,” “central goal(s),” “types of normativity,” “use of empirical data,” “method,” “interaction empirical data and moral theory,” and “cooperation with descriptive sciences.” Ethicists can use the table in order to identify their own approach. Reflection on these issues prior to starting research in empirical ethics should lead to harmonization of the different scientific disciplines and effective planning of the final research design. Integrated empirical ethics (IEE) refers to studies in which ethicists and descriptive scientists cooperate together continuously and intensively. Both disciplines try to integrate moral theory and empirical data in order to reach a normative conclusion with respect to a specific social practice. IEE is not wholly prescriptive or wholly descriptive since IEE assumes an interdepence between facts and values and between the empirical and the normative. The paper ends with three suggestions for consideration on some of the future challenges of integrated empirical ethics. (shrink)

Empirical evidence suggests that while people hold the capacity to control their data in high regard, they increasingly experience a loss of control over their data in the online world. The capacity to exert control over the generation and flow of personal information is a fundamental premise to important values such as autonomy, privacy, and trust. In healthcare and clinical research this capacity is generally achieved indirectly, by agreeing to specific conditions of informational exposure. Such conditions can be (...) openly stated in informed consent documents or be implicit in the norms of confidentiality that govern the relationships of patients and healthcare professionals. However, with medicine becoming a data-intense enterprise, informed consent and medical confidentiality, as mechanisms of control, are put under pressure. In this paper we explore emerging models of informational control in data-intense healthcare and clinical research, which can compensate for the limitations of currently available instruments. More specifically, we discuss three approaches that hold promise in increasing individual control: the emergence of data portability rights as means to control data access, new mechanisms of informed consent as tools to control data use, and finally, new participatory governance schemes that allow individuals to control their data through direct involvement in data governance. We conclude by suggesting that, despite the impression that biomedical big data diminish individual control, the synergistic effect of new data management models can in fact improve it. (shrink)

Background:Maintaining patient’s dignity in intensive care units is difficult because of the unique conditions of both critically-ill patients and intensive care units.Objectives:The aim of this study was to uncover the cultural factors that impeded maintaining patients’ dignity in the cardiac surgery intensive care unit.Research Design:The study was conducted using a critical ethnographic method proposed by Carspecken.Participants and research context:Participants included all physicians, nurses and staffs working in the study setting. Data collection methods included participant observations, formal (...) and informal interviews, and documents assessment. In total, 200 hours of observation and 30 interviews were performed. Data were analyzed to uncover tacit cultural knowledge and to help healthcare providers to reconstruct the culture of their workplace.Ethical Consideration:Ethical approval for the study from Ethics committee of Isfahan University of Medical Sciences was obtained.Findings:The findings of the study fell into the following main themes: “Presence: the guarantee for giving enough attention to patients’ self-esteem”, “Instrumental and objectified attitudes”, “Adherence to the human equality principle: value-action gap”, “Paternalistic conduct”, “Improper language”, and “Non-interactive communication”. The final assertion was “Reductionism as a major barrier to the maintaining of patient’s dignity”.Discussion:The prevailing atmosphere in subculture of the CSICU was reductionism and paternalism. This key finding is part of the biomedical discourse. As a matter of fact, it is in contrast with dignified care because the latter necessitate holistic attitudes and approaches.Conclusion:Changing an ICU culture is not easy; but through increasing awareness and critical self-reflections, the nurses, physicians and other healthcare providers, may be able to reaffirm dignified care and cure in their therapeutic relationships. (shrink)

Video data has now become the most common form of data for educational researchers studying classroom interaction and school culture. Software protocols for analysing vast archives of video data are deployed regularly, allowing researchers to annotate, code and sort images. These protocols are often applied by researchers without reflection or reference to the extensive philosophical work in film and media studies. Without exception, this research treats the video image as movement-image or picture, a recording of ‘raw (...) class='Hi'>data’, indexical of a given time-space relationship. In this article I situate this kind of research within the history of scientific cinema, drawing on Deleuze's books on cinema, as well as his ideas on colour and figure from The Logic of Sensation, to propose an alternative way of analysing video data. One of the central claims of Deleuze in Cinema 2 is that the time-image reconfigures bodies as expressions of force – the body becomes a ‘shock of forces’. I argue that such an approach allows us to study the student body as less a phenomenological organism with built-in ‘I can’ cognitive and motor capacities, and more an indeterminate crystalline contraction and expansion of intensity. I present an example of how to study classroom video data as time-image, and explore the implications of such work for education research. (shrink)

This article will describe two forthcoming art/science projects, ‘Heliosphere’ (Grant, Kin, Matthias) and ‘The Sun Project’ (Grant, Kin, Matthias). Each project materializes data from solar flare activity by tracking the solar wind across the Earth. Using information streamed from satellites orbiting the Earth’s atmosphere and from terrestrial detectors, the Sun’s activity will be visualized and sonified at sites across the Earth. The article also describes the research context undertaken in developing the work including solar physics, anthropology the history of (...) science. (shrink)

The rise of big digital data is changing the framework within which linguists, sociologists, anthropologists, and other researchers are working. Semiotics is not spared by this paradigm shift. A data-driven computational semiotics is the study with an intensive use of computational methods of patterns in human-created contents related to semiotic phenomena. One of the most promising frameworks in this research program is the Semantic Vector Space (SVS) models and their methods. The objective of this article is to (...) contribute to the exploration of the SVS for a computational semiotics by showing what types of semiotic analysis can be accomplished within this framework. The study is applied to a unique body of digitized artworks. We conducted three short experiments in which we explore three types of semiotic analysis: paradigmatic analysis, componential analysis, and topic modelling analysis. The results reported show that the SVS constitutes a powerful framework within which various types of semiotic analysis can be carried out. (shrink)

The large-scale and intensive collection and analysis of digital data (commonly called “Big Data”) has become a common, popular, and consensual research method for the social sciences, as the automation of data collection, mathematization of analysis, and digital objectification reinforce both its efficiency and truth-value. This article opens with a critical review of the literature on data collection and analysis, and summarizes current ethical discussions focusing on these technologies. A semiotic model of data production (...) and circulation is then introduced to problematize the view that digital data has ceased to stand for a formalization method (a possible kind of representation among others), and effectively “becomes the world itself” (a direct presentation of the world outperforming all other modes of representation). Following Charles Sanders Peirce’s semiotics and pragmaticist philosophy, we characterize digitalization as a hypersymbolic semiotic process, and we highlight the naturalization of meaning, the illusion of iconicity, and rhetorical efficiency on which data’s truth value relies within the context of its large-scale, profit-driven, and results-oriented research uses. This outlines some epistemological and ethical implications of data’s visualization, use, and authority, and indicates avenues for critical semiotics of contemporary data science and analysis. (shrink)

Research questions and backgroundThis study explores a highly controversial issue of medical care in Germany: the decision to withhold or withdraw mechanical ventilation in critically ill patients. It analyzes difficulties in making these decisions and the physicians’ uncertainty in understanding the German terminology of Sterbehilfe, which is used in the context of treatment limitation. Used in everyday language, the word Sterbehilfe carries connotations such as helping the patient in the dying process or helping the patient to enter the dying process. (...) Yet, in the legal and ethical discourse Sterbehilfe indicates several concepts: (1) treatment limitation, i.e., withholding or withdrawing life-sustaining treatment (passive Sterbehilfe), (2) the use of medication for symptom control while taking into account the risk of hastening the patient’s death (indirekte Sterbehilfe), and (3) measures to deliberately terminate the patient’s life (aktive Sterbehilfe). The terminology of Sterbehilfe has been criticized for being too complex and misleading, particularly for practical purposes. Materials and methods An exploratory study based on qualitative interviews was conducted with 28 physicians from nine medical intensive care units in tertiary care hospitals in the German federal state of Baden-Wuerttemberg. The method of data collection was a problem-centered, semi-structured interview using two authentic clinical case examples. In order to shed light on the relation between the physicians’ concepts and the ethical and legal frames of reference, we analyzed their way of using the terms passive and aktive Sterbehilfe. Results Generally, the physicians were more hesitant in making decisions to withdraw rather than withhold mechanical ventilation. Almost half of them assumed a categorical prohibition to withdraw any mechanical ventilation and more than one third felt that treatment ought not to be withdrawn at all. Physicians showed specific uncertainty about classifying the withdrawal of mechanical ventilation as passive Sterbehilfe, and had difficulties understanding that terminating ventilation is not basically illegal, but the permissibility of withdrawal depends on the situation. Conclusions The physicians’ knowledge and skills in interpreting clinical ethical dilemmas require specific improvement on the one hand; on the other hand, the terms passive and aktive Sterbehilfe are less clear than desirable and not as easy to use in clinical practice. Fear of making unjustified or illegal decisions may motivate physicians to continue (even futile) treatment. Physicians strongly opt for more open discussion about end-of-life care to allow for discontinuation of futile treatment and to reduce conflict. (shrink)

The ethical and social implications of data mining, algorithmic curation and automation in the context of social media have been of heightened concern for a range of researchers with interests in digital media in recent years, with particular concerns about privacy arising in the context of mobile and locative media. Despite their wide adoption and economic importance, mobile dating apps have received little scholarly attention from this perspective – but they are intense sites of data generation, algorithmic processing, (...) and cross-platform data-sharing; bound up with competing cultures of production, exploitation and use. In this paper, we describe the ways various forms of data are incorporated into, and emerge from, hook-up apps’ business logics, socio-technical arrangements, and cultures of use to produce multiple and intersecting data cultures. We propose a multi-layered research agenda for critical and empirical inquiry into this field, and suggest appropriate conceptual and methodological frameworks for exploring the social and political challenges of data cultures. (shrink)

Background and aim: Surgical intensive care nurses should have ethical sensitivity allowing them to identify ethical issues in order that they can recognize them and make the right decisions. This descriptive study was conducted with the aim of evaluating the ethical sensitivity of surgical intensive care nurses. Materials and methods: The research was carried out with the participation of 160 nurses in six Turkish hospitals, four state, one university, and one private. The data were collected using the (...) “Nurse Description Form” developed by the researcher and the “Ethical Sensitivity Questionnaire.” The percent, mean, standard deviation, median, minimum and maximum values, significance test for the difference between two means, variance analysis, Mann–Whitney U test, and Kruskal–Wallis Variance Analysis test were used to evaluate the data. Ethical considerations: Ethical commission permission and the corporate permission of the hospitals were received before conducting the research. Results: It was determined that the ethical sensitivities of surgical intensive care nurses were moderate based on the Ethical Sensitivity Questionnaire total score and subdimension score averages. A statistical difference was determined between the Ethical Sensitivity Questionnaire total score of surgical intensive care nurses and the institution where they worked, the period of working in the occupation, and the period of working in the intensive care unit. Conclusion: Based on the results of the research, the organization of training and studies devoted to the elimination of ethical sensitivity differences between institutions and workers is suggested. (shrink)

Big data biology—bioinformatics, computational biology, systems biology (including ‘omics’), and synthetic biology—raises a number of issues for the philosophy of science. This article deals with several such: Is data-intensive biology a new kind of science, presumably post-reductionistic? To what extent is big data biology data-driven? Can data ‘speak for themselves?’ I discuss these issues by way of a reflection on Carl Woese’s worry that “a society that permits biology to become an engineering discipline, that (...) allows that science to slip into the role of changing the living world without trying to understand it, is a danger to itself.” And I argue that scientific perspectivism, a philosophical stance represented prominently by Giere, Van Fraassen, and Wimsatt, according to which science cannot as a matter of principle transcend our human perspective, provides the best resources currently at our disposal to tackle many of the philosophical issues implied in the modeling of complex, multilevel/multiscale phenomena. (shrink)