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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This chapter provides insights into the complex and adaptive nature of systems and illustrates key characteristics of such systems. These contribute to an understanding of the challenges in health promotion and imply a need for more context-specific research to evaluate the health promotion interventions. CARA can address this need as it can be used to evaluate and support change in complex adaptive systems. To support and inspire other health promotion researchers who want to adopt CARA as their research approach, we have discussed our experiences and provided some guiding principles. Overall, complexity thinking can help to understand the challenges in health promotion, whereby CARA provides a possible strategy for health promotion researchers when dealing with the challenges of evaluating health promotion interventions in complex adaptive systems.
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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 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.
MULTIFILE
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
Developing and realizing an innovative concept for the Active Aging campus in two years, where students, teachers, companies, residents of surrounding Campus neighborhoods will be invited to do exercise, sports, play, meet and participate. This includes, on the one hand, providing input with regard to a mobility-friendly design from an infrastructural perspective and, on the other hand, organizing activities that contribute to Healthy Aeging of the Zernike site and the city of Groningen. It is not only about having an Active Aging campus with an iconic image, but also about the process. In the process of realization, students, teachers, researchers, companies and residents from surrounding districts will be explicitly involved. This includes hardware (physical environment / infrastructure), software (social environment) and orgware (interaction between the two).
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
Lectoraat, onderdeel van NHL Stenden Hogeschool
