Stakeholder interactions are increasingly viewed as an important element of research for sustainable development. But to what extent, how, and for which goals should stakeholders be involved? In this article, we explore what degrees of stakeholder interaction show the most promise in research for sustainable development. For this purpose, we examine 16 research projects from the transdisciplinary research programme NRP 61 on sustainable water management in Switzerland. The results suggest that various degrees of stakeholder interaction can be beneficial depending on each project's intended contribution to sustainability, the form of knowledge desired, how contested the issues are, the level of actor diversity, actors' interests, and existing collaborations between actors. We argue that systematic reflection about these six criteria can enable tailoring stakeholder interaction processes according specific project goals and context conditions.
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http://dx.doi.org/10.1007/s11625-017-0507-4 | DOI Listing |
Interact J Med Res
January 2025
Medical Directorate, Lausanne University Hospital, Lausanne, Switzerland.
Large language models (LLMs) are artificial intelligence tools that have the prospect of profoundly changing how we practice all aspects of medicine. Considering the incredible potential of LLMs in medicine and the interest of many health care stakeholders for implementation into routine practice, it is therefore essential that clinicians be aware of the basic risks associated with the use of these models. Namely, a significant risk associated with the use of LLMs is their potential to create hallucinations.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Background: Information exchange regarding the scope and content of health studies is becoming increasingly important. Digital methods, including study websites, can facilitate such an exchange.
Objective: This scoping review aimed to describe how digital information exchange occurs between the public and researchers in health studies.
PLoS One
January 2025
Department of Anthropology, Gender and African Studies, University of Nairobi, Nairobi, Kenya.
East Coast Fever (ECF) is one of the leading causes of livestock mortality and reduced productivity across Eastern Africa, and while a live vaccine against it known as the Infection and Treatment Method has existed for three decades now, its adoption by affected communities remains low. This study sought to provide a detailed examination of the dynamics that shape Infection Treatment Method (ITM) vaccine adoption behaviours. The study examined individual, socio-cultural and ecological- level factors influencing ITM adoption using the socio-ecological model.
View Article and Find Full Text PDFDrug Saf
January 2025
Forum for Collaborative Research, University of California, Berkeley, Washington, DC, USA.
HIV-prevention efforts focusing on women of child-bearing potential are needed to end the HIV epidemic in the African region. The use of antiretroviral drugs as pre-exposure prophylaxis (PrEP) is a critical HIV prevention tool. However, safety data on new antiretrovirals during pregnancy are often limited because pregnant people are excluded from drug development studies.
View Article and Find Full Text PDFComput Struct Biotechnol J
December 2024
NovaMechanics Ltd, Nicosia 1070, Cyprus.
The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs, enhancing both regulatory compliance and international collaboration. By building on established nanoinformatics frameworks, such as those developed in the H2020-funded projects NanoSolveIT and NanoCommons, CompSafeNano addresses critical challenges in nanosafety through development and integration of innovative methodologies, including advanced models, approaches including machine learning (ML) and artificial intelligence (AI)-driven predictive models and 1st-principles computational modelling of NMs properties, interactions and effects on living systems.
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