Sophie van Baalen

Background: Health professionals need to be prepared for interdisciplinary research collaborations aimed at the development and implementation of medical technology. Expertise is highly domain-specific, and learned by being immersed in professional practice. Therefore, the approaches and results from one domain are not easily understood by experts from another domain. Interdisciplinary collaboration in medical research faces not only institutional, but also cognitive and epistemological barriers. This is one of the reasons why interdisciplinary and interprofessional research collaborations are so difficult. To explain the cognitive and epistemological barriers, we introduce the concept of disciplinary perspectives. Making explicit the disciplinary perspectives of experts participating in interdisciplinary collaborations helps to clarify the specific approach of each expert, thereby improving mutual understanding. Method: We developed a framework for making disciplinary perspectives of experts participating in an interdisciplinary research collaboration explicit. The applicability of the framework has been tested in an interdisciplinary medical research project aimed at the development and implementation of diffusion MRI for the diagnosis of kidney cancer, where the framework was applied to analyse and articulate the disciplinary perspectives of the experts involved. Results: We propose a general framework, in the form of a series of questions, based on new insights from the philosophy of science into the epistemology of interdisciplinary research. We explain these philosophical underpinnings in order to clarify the cognitive and epistemological barriers of interdisciplinary research collaborations. In addition, we present a detailed example of the use of the framework in a concrete interdisciplinary research project aimed at developing a diagnostic technology. This case study demonstrates the applicability of the framework in interdisciplinary research projects. Conclusion: Interdisciplinary research collaborations can be facilitated by a better understanding of how an expert’s disciplinary perspectives enables and guides their specific approach to a problem. Implicit disciplinary perspectives can and should be made explicit in a systematic manner, for which we propose a framework that can be used by disciplinary experts participating in interdisciplinary research project. Furthermore, we suggest that educators can explore how the framework and philosophical underpinning can be implemented in HPE to support the development of students’ interdisciplinary expertise.

Given the potentially large ethical and societal implications of human germline gene editing (HGGE) the urgent need for public and stakeholder engagement (PSE) has been repeatedly expressed. However, the explicit goals of such PSE efforts often remain poorly defined. In this program report, we outline the goals of our Dutch project called De DNA dialogen (The DNA dialogues). We believe that setting explicit goals in advance is essential to enable meaningful PSE efforts. Moreover, it enables the evaluation of our engagement efforts. The following four goals, which result from intensive consultations among the transdisciplinary projects’ consortium members and based on the literature, form the foundation for how we will engage the public and stakeholders in deliberation about HGGE: 1) Enable publics and stakeholders to deliberate on “what if” questions, before considering “whether” and “how” questions regarding HGGE, 2) Investigate agreement and disagreement in values and beliefs regarding HGGE in order to agree and disagree more precisely, 3) Involve diverse publics with various perspectives, with a focus on those that are typically underrepresented in PSE, 4) Enable societally aligned policy making by providing policymakers, health care professionals and legal experts insight into how values are weighed and ascribed meaning in the context of HGGE by various publics, and how these values relate to the principles of democratic rule of law and fundamental rights. The effort to describe our goals in detail may serve as an example and can inform future initiatives striving for open science and open governance in the context of PSE.

Biotechnology involves the use and manipulation of living organisms such as plants, animals, humans, and biological systems, or parts of this, to modify their characteristics in order to create desired organisms or products. Biotechnology as a field touches on many aspects that are central to technology assessment (TA), and have been the focus of TA activities since the 1980s. By presenting three key topics in biotechnology—genetically modified food and crops, synthetic biology, and human genome germline editing—we show that a central feature of biotechnology is that the science is evolving globally and the products that it brings forth are traded across the globe. Yet, there are major differences in the regulation and governance of the academic and industrial sectors between countries. These stem from different needs and interests per country, as well as differences in traditions, cultural differences and public perceptions. As global governance is fragmented, with little scope for harmonization, global TA of biotechnology can bring clarity and better understanding, and enable better governance. In order to do so, an integrated global TA framework should consider international trade and differences in risk assessment; cultural variation and different value-systems between countries; and differences in countries’ capacities in R&D and coordination of public engagement efforts.

Despite the great promises that artificial intelligence (AI) holds for health care, the uptake of such technologies into medical practice is slow. In this paper, we focus on the epistemological issues arising from the development and implementation of a class of AI for clinical practice, namely clinical decision support systems (CDSS). We will first provide an overview of the epistemic tasks of medical professionals, and then analyse which of these tasks can be supported by CDSS, while also explaining why some of them should remain the territory of human experts. Clinical decision making involves a reasoning process in which clinicians combine different types of information into a coherent and adequate ‘picture of the patient’ that enables them to draw explainable and justifiable conclusions for which they bear epistemological responsibility. Therefore, we suggest that it is more appropriate to think of a CDSS as clinical reasoning support systems (CRSS). Developing CRSS that support clinicians' reasoning process therefore requires that: (a) CRSSs are developed on the basis of relevant and well‐processed data; and (b) the system facilitates an interaction with the clinician. Therefore, medical experts must collaborate closely with AI experts developing the CRSS. In addition, responsible use of an CRSS requires that the data generated by the CRSS is empirically justified through an empirical link with the individual patient. In practice, this means that the system indicates what factors contributed to arriving at an advice, allowing the user (clinician) to evaluate whether these factors are medically plausible and applicable to the patient. Finally, we defend that proper implementation of CRSS allows combining human and artificial intelligence into hybrid intelligence, were both perform clearly delineated and complementary empirical tasks. Whereas CRSSs can assist with statistical reasoning and finding patterns in complex data, it is the clinicians' task to interpret, integrate and contextualize.

Background: Societal challenges that call for a new type of engineer suggest the need for the implementation of interdisciplinary engineering education (IEE). The aim of IEE is to train engineering students to bring together expertise from different disciplines in a single context. This review synthesizes IEE research with a focus on characterizing vision, teaching practices, and support.Purpose: We aim to show how IEE is conceptualized, implemented, and facilitated in higher engineering education at the levels of curricula and courses. This aim leads to two research questions:What aspects of vision, teaching, and support have emerged as topics of interest in empirical studies of IEE?What points of attention regarding vision, teaching, and support can be identified in empirical studies of IEE as supporting or challenging IEE?Scope/Method: Ninety‐nine studies published between 2005 and 2016 were included in a qualitative analysis across studies. The procedure included formulation of research questions, searching and screening of studies according to inclusion/exclusion criteria, description of study characteristics, appraisal, and synthesis of results.Conclusions: Challenges exist for identifying clear learning goals and assessments for interdisciplinary education in engineering (vision). Most pedagogy for interdisciplinary learning is designed to promote collaborative teamwork requiring organization and team management. Our review suggests that developing interdisciplinary skills, knowledge, and values needs sound pedagogy and teaming experiences that provide students with authentic ways of engaging in interdisciplinary practice (teaching). Furthermore, there is a limited understanding of what resources hinder the development of engineering programs designed to support interdisciplinarity (support).

In science policy, it is generally acknowledged that science-based problem-solving requires interdisciplinary research. For example, policy makers invest in funding programs such as Horizon 2020 that aim to stimulate interdisciplinary research. Yet the epistemological processes that lead to effective interdisciplinary research are poorly understood. This article aims at an epistemology for interdisciplinary research (IDR), in particular, IDR for solving ‘real-world’ problems. Focus is on the question why researchers experience cognitive and epistemic difficulties in conducting IDR. Based on a study of educational literature it is concluded that higher-education is missing clear ideas on the epistemology of IDR, and as a consequence, on how to teach it. It is conjectured that the lack of philosophical interest in the epistemology of IDR is due to a philosophical paradigm of science (called a physics paradigm of science), which prevents recognizing severe epistemological challenges of IDR, both in the philosophy of science as well as in science education and research. The proposed alternative philosophical paradigm (called an engineering paradigm of science) entails alternative philosophical presuppositions regarding aspects such as the aim of science, the character of knowledge, the epistemic and pragmatic criteria for accepting knowledge, and the role of technological instruments. This alternative philosophical paradigm assume the production of knowledge for epistemic functions as the aim of science, and interprets ‘knowledge’ (such as theories, models, laws, and concepts) as epistemic tools that must allow for conducting epistemic tasks by epistemic agents, rather than interpreting knowledge as representations that objectively represent aspects of the world independent of the way in which it was constructed. The engineering paradigm of science involves that knowledge is indelibly shaped by how it is constructed. Additionally, the way in which scientific disciplines (or fields) construct knowledge is guided by the specificities of the discipline, which can be analyzed in terms of disciplinary perspectives. This implies that knowledge and the epistemic uses of knowledge cannot be understood without at least some understanding of how the knowledge is constructed. Accordingly, scientific researchers need so-called metacognitive scaffolds to assist in analyzing and reconstructing how ‘knowledge’ is constructed and how different disciplines do this differently. In an engineering paradigm of science, these metacognitive scaffolds can also be interpreted as epistemic tools, but in this case as tools that guide, enable and constrain analyzing and articulating how knowledge is produced (i.e., explaining epistemological aspects of doing research). In interdisciplinary research, metacognitive scaffolds assist interdisciplinary communication aiming to analyze and articulate how the discipline constructs knowledge.

To compare diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and tri-exponential models of the diffusion magnetic resonance imaging (MRI) signal for the characterization of renal lesions in relationship to histopathological findings. Sixteen patients planned to undergo nephrectomy for kidney tumour were scanned before surgery at 3 T magnetic resonance imaging (MRI), with T2-weighted imaging, DTI and diffusion weighted imaging (DWI) using ten b-values. DTI parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squared fitting of the DTI data and bi-, and tri-exponential fit parameters (Dbi, fstar,and Dtri, ffast,finterm) using a nonlinear fit of the multiple b-value DWI data. Average parameters were calculated for regions of interest, selecting the lesions and healthy kidney tissue. Tumour type and specificities were determined after surgery by histological examination. Mean parameter values of healthy tissue and solid lesions were compared using a Wilcoxon-signed ranked test and MANOVA. Thirteen solid lesions (nine clear cell carcinomas, two papillary renal cell carcinoma, one haemangioma and one oncocytoma) and four cysts were included. The mean MD of solid lesions are significantly (p < 0.05) lower than healthy cortex and medulla, (1.94 ± 0.32*10− 3 mm2/s versus 2.16 ± 0.12*10− 3 mm2/s and 2.21 ± 0.14*10− 3 mm2/s, respectively) whereas ffast is significantly higher (7.30 ± 3.29% versus 4.14 ± 1.92% and 4.57 ± 1.74%) and finterm is significantly lower (18.7 ± 5.02% versus 28.8 ± 5.09% and 26.4 ± 6.65%). Diffusion coefficients were high (≥2.0*10− 3 mm2/s for MD, 1.90*10− 3 mm2/s for Dbi and 1.6*10− 3 mm2/s for Dtri) in cc-RCCs with cystic structures and/or haemorrhaging and low (≤1.80*10− 3 mm2/s for MD, 1.40*10− 3 mm2/s for Dbi and 1.05*10− 3 mm2/s for Dtri) in tumours with necrosis or sarcomatoid differentiation. Parameters derived from a two- or three-component fit of the diffusion signal are sensitive to histopathological features of kidney lesions.

In recent years there has been growing attention to the epistemology of clinical decision‐making, but most studies have taken the individual physicians as the central object of analysis. In this paper we argue that knowing in current medical practice has an inherently social character and that imaging plays a mediating role in these practices. We have analyzed clinical decision‐making within a medical expert team involved in diagnosis and treatment of patients with pulmonary hypertension (PH), a rare disease requiring multidisciplinary team involvement in diagnosis and management. Within our field study, we conducted observations, interviews, video tasks, and a panel discussion. Decision‐making in the PH clinic involves combining evidence from heterogeneous sources into a cohesive framing of a patient, in which interpretations of the different sources can be made consistent with each other. Because pieces of evidence are generated by people with different expertise and interpretation and adjustments take place in interaction between different experts, we argue that this process is socially distributed. Multidisciplinary team meetings are an important place where information is shared, discussed, interpreted, and adjusted, allowing for a collective way of seeing and a shared language to be developed. We demonstrate this with an example of image processing in the PH service, an instance in which knowledge is distributed over multiple people who play a crucial role in generating an evaluation of right heart function. Finally, we argue that images fulfill a mediating role in distributed knowing in 3 ways: first, as enablers or tools in acquiring information; second, as communication facilitators; and third, as pervasively framing the epistemic domain. With this study of clinical decision‐making in diagnosis and treatment of PH, we have shown that clinical decision‐making is highly social and mediated by technologies. The epistemology of clinical decision‐making needs to take social and technological mediation into account.