This study explores the evaluation of research pathways of self-management health innovations from discovery to implementation in the context of practice-based research. The aim is to understand how a new process model for evaluating practice-based research provides insights into the implementation success of innovations. Data were collected from nine research projects in the Netherlands. Through document analysis and semi-structured interviews, we analysed how the projects start, evolve, and contribute to the healthcare practice. Building on previous research evaluation approaches to monitor knowledge utilization, we developed a Research Pathway Model. The model’s process character enables us to include and evaluate the incremental work required throughout the lifespan of an innovation project and it helps to foreground that innovation continues during implementation in real-life settings. We found that in each research project, pathways are followed that include activities to explore a new solution, deliver a prototype and contribute to theory. Only three projects explored the solution in real life and included activities to create the necessary changes for the solutions to be adopted. These three projects were associated with successful implementation. The exploration of the solution in a real-life environment in which users test a prototype in their own context seems to be a necessary research activity for the successful implementation of self-management health innovations.
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This study explores the evaluation of research pathways of self-management health innovations from discovery to implementation in the context of practice-based research. The aim is to understand how a new process model for evaluating practice-based research provides insights into the implementation success of innovations. Data were collected from nine research projects in the Netherlands. Through document analysis and semi-structured interviews, we analysed how the projects start, evolve, and contribute to the healthcare practice. Building on previous researchevaluation approaches to monitor knowledge utilization, we developed a Research Pathway Model. The model’s process character enables us to include and evaluate the incremental work required throughout the lifespan of an innovation project and it helps to foreground that innovation continues during implementation in real-life settings. We found that in each researchproject, pathways are followed that include activities to explore a new solution, deliver a prototype and contribute to theory. Only three projects explored the solution in real life and included activities to create the necessary changes for the solutions to be adopted. These three projects were associated with successful implementation. The exploration of the solution in a real-life environment in which users test a prototype in their own context seems to be a necessaryresearch activity for the successful implementation of self-management health innovations.
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From the publisher: "Background: The introduction of whole new foods in a population may lead to sensitization and food allergy. This constitutes a potential public health problem and a challenge to risk assessors and managers as the existing understanding of the pathophysiological processes and the currently available biological tools for prediction of the risk for food allergy development and the severity of the reaction are not sufficient. There is a substantial body of in vivo and in vitro data describing molecular and cellular events potentially involved in food sensitization. However, these events have not been organized in a sequence of related events that is plausible to result in sensitization, and useful to challenge current hypotheses. The aim of this manuscript was to collect and structure the current mechanistic understanding of sensitization induction to food proteins by applying the concept of adverse outcome pathway (AOP). Main body: The proposed AOP for food sensitization is based on information on molecular and cellular mechanisms and pathways evidenced to be involved in sensitization by food and food proteins and uses the AOPs for chemical skin sensitization and respiratory sensitization induction as templates. Available mechanistic data on protein respiratory sensitization were included to fill out gaps in the understanding of how proteins may affect cells, cell-cell interactions and tissue homeostasis. Analysis revealed several key events (KE) and biomarkers that may have potential use in testing and assessment of proteins for their sensitizing potential. Conclusion: The application of the AOP concept to structure mechanistic in vivo and in vitro knowledge has made it possible to identify a number of methods, each addressing a specific KE, that provide information about the food allergenic potential of new proteins. When applied in the context of an integrated strategy these methods may reduce, if not replace, current animal testing approaches. The proposed AOP will be shared at the www.aopwiki.org platform to expand the mechanistic data, improve the confidence in each of the proposed KE and key event relations (KERs), and allow for the identification of new, or refinement of established KE and KERs." Authors: Jolanda H. M. van BilsenEmail author, Edyta Sienkiewicz-Szłapka, Daniel Lozano-Ojalvo, Linette E. M. Willemsen, Celia M. Antunes, Elena Molina, Joost J. Smit, Barbara Wróblewska, Harry J. Wichers, Edward F. Knol, Gregory S. Ladics, Raymond H. H. Pieters, Sandra Denery-Papini, Yvonne M. Vissers, Simona L. Bavaro, Colette Larré, Kitty C. M. Verhoeckx and Erwin L. Roggen
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Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
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Comprehensive understanding of the merits of bottom-up urban development is lacking, thus hampering and complicating associated collaborative processes. Therefore, and given the assumed relevancies, we mapped the social, environmental and economic values generated by bottom-up developments in two Dutch urban areas, using theory-based evaluation principles. These evaluations raised insights into the values, beneficiaries and path dependencies between successive values, confirming the assumed effect of placemaking accelerating further spatial developments. It also revealed broader impacts of bottom-up endeavors, such as influences on local policies and innovations in urban development.
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The transition from home to a nursing home can be stressful and traumatic for both older persons and informal caregivers and is often associated with negative outcomes. Additionally, transitional care interventions often lack a comprehensive approach, possibly leading to fragmented care. To avoid this fragmentation and to optimize transitional care, a comprehensive and theory-based model is fundamental. It should include the needs of both older persons and informal caregivers. Therefore, this study, conducted within the European TRANS-SENIOR research consortium, proposes a model to optimize the transition from home to a nursing home, based on the experiences of older persons and informal caregivers. These experiences were captured by conducting a literature review with relevant literature retrieved from the databases CINAHL and PubMed. Studies were included if older persons and/or informal caregivers identified the experiences, needs, barriers, or facilitators during the transition from home to a nursing home. Subsequently, the data extracted from the included studies were mapped to the different stages of transition (pre-transition, mid-transition, and post-transition), creating the TRANSCITmodel. Finally, results were discussed with an expert panel, leading to a final proposed TRANSCIT model. The TRANSCIT model identified that older people and informal caregivers expressed an overall need for partnership during the transition from home to a nursing home. Moreover, it identified 4 key components throughout the transition trajectory (ie, pre-, mid-, and post-transition): (1) support, (2) communication, (3) information, and (4) time. The TRANSCIT model could advise policy makers, practitioners, and researchers on the development and evaluation of (future) transitional care interventions. It can be a guideline reckoning the needs of older people and their informal caregivers, emphasizing the need for a partnership, consequently reducing fragmentation in transitional care and optimizing the transition from home to a nursing home.
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Summary: Xpaths is a collection of algorithms that allow for the prediction of compound-induced molecular mechanisms of action by integrating phenotypic endpoints of different species; and proposes follow-up tests for model organisms to validate these pathway predictions. The Xpaths algorithms are applied to predict developmental and reproductive toxicity (DART) and implemented into an in silico platform, called DARTpaths.
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A review has been completed for a verification and validation (V&V) of the (Excel) BioGas simulator or EBS model. The EBS model calculates the environmental impact of biogas production pathways using Material and Energy Flow Analysis, time dependent dynamics, geographic information, and Life Cycle analysis. Within this article a V&V method is researched, selected and applied to validate the EBS model. Through the use of the method described within this article: mistakes in the model are resolved, the strengths and weaknesses of the model are found, and the concept of the model is tested and strengthened. The validation process does not only improve the model but also helps the modelers in widening their focus and scope. This article can, therefore, also be used in the validation process of similar models. The main result from the V&V process indicates that the EBS model is valid; however, it should be considered as an expert model and should only be used by expert users.
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Across Dutch municipalities, unusual collaborative initiatives emerge that aim to stimulate the creation of value from municipal waste resources. Circular economy literature proposes that experimentation competences are important for developing initiatives towards circular business models and a wide range of innovation frameworks and business model toolkits have been developed to support the development of circular business models based on experimentation.However, more insight is needed to understand how experimentation contributes to the development of urban upcycling initiatives, in particular those where collaborative business models are created. Literature suggest that business model experimentation occurs differently in various collaborative contexts. For example, depending on the type of initiating focal actors involved, collaborative business models develop along different pathways Therefore, we aim to understand how experimentation occurs in various types of collaborative urban upcycling initiatives and we investigate the following research question: How do stakeholders in collaborative urban upcycling initiatives use experimentation to develop circular business models?
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Biogas produced through Anaerobic Digestion can be seen as a flexible and storable energy carrier. However, the environmental sustainability and efficiency of biogas production is not fully understood. Within this article the use, operation, structure, validation, and results of a model for the environmental assessment of anaerobic biogas production pathways is discussed. The (Excel) BioGas Simulator or EBS model is capable of calculating the economic cost, efficiency, carbon footprint, and sustainability of small scale anaerobic digestion biogas production pathways (from 2000 up to 50000 ton/a biomass input). The results from the model are expressed in four main indicators: the economic cost in Net Present Value (NPV), the efficiency in Process Energy Returned On Invested or (P)EROI, the carbon footprint in Global Warming potential 100 year scale (GWP100), and the environmental impact in EcoPoints. The economic indicator is given in Euros in Net Present Value over a period of 25 years, the other indicators are given per Giga Joule of energy produced (e.g. kgCO2eq/GJ). The EBS model is based on a clear methodology, structured around the modular approach, energy and material flow analysis, and life cycle analysis. The modular approach separates the biogas production pathway into individual physical processes, which makes the model more transparent, flexible in use, and programmable with different settings. The aforementioned allows the research of several aspects of the biogas production pathway. Furthermore, the indication of sustainability in four clear indicators gives an understandable reference for comparison with other scenarios. Overall, the EBS model can help give insight on the sustainability of specific biogas production pathways and help indicate options for improvement. Results from the model indicate that from an energy efficiency and sustainability point of view, the anaerobic digestion process should be utilized for treating locally available waste feedstocks with the added advantage of producing energy, which should preferentially be used internally for powering the waste treatment process.
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