Background: Patient decision aids (PDAs) can support the treatment decision making process and empower patients to take a proactive role in their treatment pathway while using a shared decision-making (SDM) approach making participatory medicine possible. The aim of this study was to develop a PDA for prostate cancer that is accurate and user-friendly. Methods: We followed a user-centered design process consisting of five rounds of semi-structured interviews and usability surveys with topics such as informational/decisional needs of users and requirements for PDAs. Our userbase consisted of 8 urologists, 4 radiation oncologists, 2 oncology nurses, 8 general practitioners, 19 former prostate cancer patients, 4 usability experts and 11 healthy volunteers. Results: Informational needs for patients centered on three key factors: treatment experience, post-treatment quality of life, and the impact of side effects. Patients and clinicians valued a PDA that presents balanced information on these factors through simple understandable language and visual aids. Usability questionnaires revealed that patients were more satisfied overall with the PDA than clinicians; however, both groups had concerns that the PDA might lengthen consultation times (42 and 41%, respectively). The PDA is accessible on http://beslissamen.nl/. Conclusions: User-centered design provided valuable insights into PDA requirements but challenges in integrating diverse perspectives as clinicians focus on clinical outcomes while patients also consider quality of life. Nevertheless, it is crucial to involve a broad base of clinical users in order to better understand the decision-making process and to develop a PDA that is accurate, usable, and acceptable.
Introduction: Shared decision-making is considered to be a key aspect of woman-centered care and a strategy to improve communication, respect, and satisfaction. This scoping review identified studies that used a shared decision-making support strategy as the primary intervention in the context of perinatal care. Methods: A literature search of PubMed, CINAHL, Cochrane Library, PsycINFO, and SCOPUS databases was completed for English-language studies conducted from January 2000 through November 2019 that examined the impact of a shared decision-making support strategy on a perinatal decision (such as choice of mode of birth after prior cesarean birth). Studies that only examined the use of a decision aid were excluded. Nine studies met inclusion criteria and were examined for the nature of the shared decision-making intervention as well as outcome measures such as decisional evaluation, including decisional conflict, decisional regret, and certainty. Results: The 9 included studies were heterogeneous with regard to shared decision-making interventions and measured outcomes and were performed in different countries and in a variety of perinatal situations, such as women facing the choice of mode of birth after prior cesarean birth. The impact of a shared decision-making intervention on women’s perception of shared decision-making and on their experiences of the decision-making process were mixed. There may be a decrease in decisional conflict and regret related to feeling informed, but no change in decisional certainty. Discussion: Despite the call to increase the use of shared decision-making in perinatal care, there are few studies that have examined the effects of a shared decision-making support strategy. Further studies that include antepartum and intrapartum settings, which include common perinatal decisions such as induction of labor, are needed. In addition, clear guidance and strategies for successfully integrating shared decision-making and practice recommendations would help women and health care providers navigate these complex decisions.
Proper decision-making is one of the most important capabilities of an organization. Therefore, it is important to have a clear understanding and overview of the decisions an organization makes. A means to understanding and modeling decisions is the Decision Model and Notation (DMN) standard published by the Object Management Group in 2015. In this standard, it is possible to design and specify how a decision should be taken. However, DMN lacks elements to specify the actors that fulfil different roles in the decision-making process as well as not taking into account the autonomy of machines. In this paper, we re-address and-present our earlier work [1] that focuses on the construction of a framework that takes into account different roles in the decision-making process, and also includes the extent of the autonomy when machines are involved in the decision-making processes. Yet, we extended our previous research with more detailed discussion of the related literature, running cases, and results, which provides a grounded basis from which further research on the governance of (semi) automated decision-making can be conducted. The contributions of this paper are twofold; 1) a framework that combines both autonomy and separation of concerns aspects for decision-making in practice while 2) the proposed theory forms a grounded argument to enrich the current DMN standard.
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.
The energy transition is a highly complex technical and societal challenge, coping with e.g. existing ownership situations, intrusive retrofit measures, slow decision-making processes and uneven value distribution. Large scale retrofitting activities insulating multiple buildings at once is urgently needed to reach the climate targets but the decision-making of retrofitting in buildings with shared ownership is challenging. Each owner is accountable for his own energy bill (and footprint), giving a limited action scope. This has led to a fragmented response to the energy retrofitting challenge with negligible levels of building energy efficiency improvements conducted by multiple actors. Aggregating the energy design process on a building level would allow more systemic decisions to happen and offer the access to alternative types of funding for owners. “Collect Your Retrofits” intends to design a generic and collective retrofit approach in the challenging context of monumental areas. As there are no standardised approaches to conduct historical building energy retrofits, solutions are tailor-made, making the process expensive and unattractive for owners. The project will develop this approach under real conditions of two communities: a self-organised “woongroep” and a “VvE” in the historic centre of Amsterdam. Retrofit designs will be identified based on energy performance, carbon emissions, comfort and costs so that a prioritisation strategy can be drawn. Instead of each owner investing into their own energy retrofitting, the neighbourhood will invest into the most impactful measures and ensure that the generated economic value is retained locally in order to make further sustainable investments and thus accelerating the transition of the area to a CO2-neutral environment.
The impacts of tourism on destinations and the perceptions of local communities have been a major concern both for the industry and research in the past decades. However, tourism planning has been mainly focused on traditions that promote the increase of tourism without taking under consideration the wellbeing of both residents and visitors. To develop a more sustainable tourism model, the inclusion of local residents in tourism decision-making is vital. However, this is not always possible due to structural, economic and socio-cultural restrictions that residents face resulting to their disempowerment. This study aims to explore and interpret the formal processes around tourism decision-making and community empowerment in urban settings. The research proposes a comparative study of three urban destinations in Europe (The Hague in the Netherlands, San Sebastian in Spain and, Ioannina in Greece) that experience similar degree of tourism growth. The proposed study will use a design-based approach in order to understand tourism decision-making and what empowers or disempowers community participation within the destinations. Based on the findings of primary and secondary data, a community empowerment model will be applied in one the destinations as a pilot for resident engagement in tourism planning. The evaluation of the pilot will allow for an optimized model to be created with implications for tourism planning at a local level that can contribute to sustainable destinations that safeguard the interests of local residents and tourists.
