Cross-disciplinary intersections between public health and economics in intimate partner violence research

Research on intimate partner violence (IPV) has progressed in the last decade in the fields of public health and economics, with under-explored potential for cross-fertilisation. We examine the theoretical perspectives and methodological approaches that each discipline uses to conceptualise and study IPV and offer a perspective on their relative advantages. Public health takes a broad theoretical perspective anchored in the socio-ecological framework, considering multiple and synergistic drivers of IPV, while economics focuses on bargaining models which highlight individual power and factors that shape this power. These perspectives shape empirical work, with public health examining multi-faceted interventions, risk and mediating factors, while economics focuses on causal modelling of specific economic and institutional factors and economic-based interventions. The disciplines also have differing views on measurement and ethics in primary research. We argue that efforts to understand and address IPV would benefit if the two disciplines collaborated more closely and combined the best traditions of both fields.

Factors Associated with Favorable Changes in Food Preferences After Bariatric Surgery

PURPOSE

Bariatric surgery may shift food preferences towards less energy-dense foods. Eating behavior is multifactorial, and the mechanisms driving changes in food preferences could be a combination of a physiological response to surgery and social and psychological factors. This exploratory study aimed to identify potential factors explaining the variation in changes in food preferences after bariatric surgery.

MATERIALS AND METHODS

Physiological, social, and psychological data were collected before, 6 weeks or 6 months after surgery. All variables were analyzed in combination using LASSO regression to explain the variation in changes in energy density at an ad libitum buffet meal 6 months after bariatric surgery (n=39).

RESULTS

The following factors explained 69% of the variation in changes in food preferences after surgery and were associated with more favorable changes in food preferences (i.e., a larger decrease in energy density): female gender, increased secretion of glicentin, a larger decrease in the hedonic rating of sweet and fat and a fatty cocoa drink, a lower number of recent life crises, a low degree of social eating pressure, fulfilling the diagnostic criteria for binge eating disorder, less effort needed to obtain preoperative weight loss, a smaller household composition, a lower degree of self-efficacy and a higher degree of depression, nutritional regime competence, and psychosocial risk level.

CONCLUSION

Factors explaining the variation in altered food preferences after bariatric surgery not only include a physiological response to surgery but also social and psychological factors.

A critical realist synthesis of cross-disciplinary health policy and systems research: defining characteristic features, developing an evaluation framework and identifying challenges

BACKGROUND

Health policy and systems research (HPSR) is an inherently cross-disciplinary field of investigation. However, conflicting conceptualisations about inter-, multi- and transdisciplinary research have contributed to confusion about the characteristics of cross-disciplinary approaches in HPSR. This review was conducted to (1) define the characteristic features of context-mechanism-outcome (CMO) configurations in cross-disciplinary HPSR, (2) develop criteria for evaluating cross-disciplinarity and (3) synthesise emerging challenges of the approach.

METHOD

The paper is a critical realist synthesis conducted in three phases, as follows: (1) scoping the literature, (2) searching for and screening the evidence, and (3) extracting and synthesising the evidence. Five databases, namely the International Bibliography of the Social Sciences and Web of Science, PubMed central, Embase and CINHAL, and reference lists of studies that qualified for inclusion in the review were searched. The search covered peer-reviewed original research, reviews, commentary papers, and institutional or government reports published in English between January 1998 and January 2020.

RESULTS

A total of 7792 titles were identified in the online search and 137 publications, comprising pilot studies as well as anecdotal and empirical literature were selected for the final review. The review draws attention to the fact that cross-disciplinary HPSR is not defined by individual characteristics but by the combination of a particular type of research question and setting (context), a specific way of researchers working together (mechanism), and research output (outcome) that is superior to what could be achieved under a monodisciplinary approach. This CMO framework also informs the criteria for assessing whether a given HPSR is truly cross-disciplinary. The challenges of cross-disciplinary HPSR and their accompanying coping mechanisms were also found to be context driven, originating mainly from conceptual disagreements, institutional restrictions, communication and information management challenges, coordination problems, and resource limitations.

CONCLUSION

These findings have important implications. First, the CMO framework of cross-disciplinary HPSR can provide guidance for researchers engaging in new projects and for policy-makers using their findings. Second, the proposed criteria for evaluating theory and practice of cross-disciplinary HPSR may inform the systematic development of new research projects and the structured assessment of existing ones. Third, a better understanding of the challenges of cross-disciplinary HPSR and potential response mechanisms may help researchers to avoid these problems in the future.

"Essentially, all models are wrong, but some are useful"-a cross-disciplinary agenda for building useful models in cell biology and biophysics

Intuition alone often fails to decipher the mechanisms underlying the experimental data in Cell Biology and Biophysics, and mathematical modeling has become a critical tool in these fields. However, mathematical modeling is not as widespread as it could be, because experimentalists and modelers often have difficulties communicating with each other, and are not always on the same page about what a model can or should achieve. Here, we present a framework to develop models that increase the understanding of the mechanisms underlying one's favorite biological system. Development of the most insightful models starts with identifying a good biological question in light of what is known and unknown in the field, and determining the proper level of details that are sufficient to address this question. The model should aim not only to explain already available data, but also to make predictions that can be experimentally tested. We hope that both experimentalists and modelers who are driven by mechanistic questions will find these guidelines useful to develop models with maximum impact in their field.

A framework for a joint hydro-meteorological-social analysis of drought

This article presents an innovative framework for analysing environmental governance challenges by focusing on their Drivers, Responses and Impacts (DRI). It builds on and modifies the widely applied Drivers, Pressures, States, Impacts and Responses (DPSIR) model. It suggests, firstly and most importantly, that the various temporal and spatial scales at which Drivers, Responses and Impacts operate should be included in the DRI conceptual framework. Secondly, the framework focuses on Drivers, Impacts and Responses in order to provide a parsimonious account of a drought system that can be informed by a range of social science, humanities and science data. 'Pressures' are therefore considered as a sub-category of 'Drivers'. 'States' are a sub-category of 'Impacts'. Thirdly, and most fundamentally in order to facilitate cross-disciplinary research of droughts, the DRI framework defines each of its elements, 'Drivers', 'Pressures', 'States', 'Impacts' and 'Responses' as capable of being shaped by both linked natural and social factors. This is different from existing DPSIR models which often see 'Responses' and 'Impacts' as located mainly in the social world, while 'States' are considered to be states within the natural environment only. The article illustrates this argument through an application of the DRI framework to the 1976 and 2003-6 droughts. The article also starts to address how - in cross-disciplinary research that encompasses physical and social sciences - claims about relationships between Drivers as well as Impacts of and Responses to drought over time can be methodologically justified. While the DRI framework has been inductively developed out of research on droughts we argue that it can be applied to a range of environmental governance challenges.

GIFT-Cloud: A data sharing and collaboration platform for medical imaging research

OBJECTIVES

Clinical imaging data are essential for developing research software for computer-aided diagnosis, treatment planning and image-guided surgery, yet existing systems are poorly suited for data sharing between healthcare and academia: research systems rarely provide an integrated approach for data exchange with clinicians; hospital systems are focused towards clinical patient care with limited access for external researchers; and safe haven environments are not well suited to algorithm development. We have established GIFT-Cloud, a data and medical image sharing platform, to meet the needs of GIFT-Surg, an international research collaboration that is developing novel imaging methods for fetal surgery. GIFT-Cloud also has general applicability to other areas of imaging research.

METHODS

GIFT-Cloud builds upon well-established cross-platform technologies. The Server provides secure anonymised data storage, direct web-based data access and a REST API for integrating external software. The Uploader provides automated on-site anonymisation, encryption and data upload. Gateways provide a seamless process for uploading medical data from clinical systems to the research server.

RESULTS

GIFT-Cloud has been implemented in a multi-centre study for fetal medicine research. We present a case study of placental segmentation for pre-operative surgical planning, showing how GIFT-Cloud underpins the research and integrates with the clinical workflow.

CONCLUSIONS

GIFT-Cloud simplifies the transfer of imaging data from clinical to research institutions, facilitating the development and validation of medical research software and the sharing of results back to the clinical partners. GIFT-Cloud supports collaboration between multiple healthcare and research institutions while satisfying the demands of patient confidentiality, data security and data ownership.