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.
Introduction The Integrated Recovery Scales (IRS) was developed by the Dutch National Expertise board for routine outcome monitoring with severe mental illnesses. This board aimed to develop a multidimensional recovery measure directed at 1. clinical recovery, 2. physical health, 3. social recovery (work, social contacts, independent living) and 4. existential, personal recovery. The measure had to be short, suited for routine outcome monitoring and present the perspective of both mental health professionals and service users with severe mental illnesses. All aspects are assessed over a period of the pas 6 months. Objectives The objective of this research is validation of the Integral Recovery Scales and to test the revelance for clinical practice and police evaluation. Methods The instrument was tested with 500 individuals with severe mental illnesses (80% individuals with a psychotic disorder), of whom 200 were followed up for 1 year. For the questions concerning clinical recovery, physical health and social recovery mental health care workers conducted semi structured interviews with people living with serious illnesses. The questions concerning personal health were self-rated. We analyzed interrater reliability, convergent and divergent validity and sensitivity to change. Results The instrument has a good validity and is easy to complete for service users and mental health care workers and appropriate for clinical and policy evaluation goals. Conclusions The Integrated Recovery Scales can be a useful instrument for a simple and meaningful routine outcome monitoring. Page: 121
Background: Outcome assessment is essential to understand the impact and recovery of burns of the hand and tailor treatment. There is however, a large variety of measures and outcome assessment is often incomplete. The aim was therefore to initiate a set of outcome assessments for use in a clinical setting. Method: A concept set was drafted, based on the framework of the International Classification of Functioning, which distinguished two phases, three patient states and included both patient reported and clinical outcomes. Subsequently, potential assessments were allocated to the various outcomes. This concept was discussed during the European Burns Association congress in 2013 and revised. The revision was sent to 65 colleagues from 28 institutions, accompanied by a survey. Results: Eleven surveys were returned from 16 persons representing 9 institutions from 6 countries. Based on the feedback, final revisions were made. Points raised were time investment and translations of not all assessments already available. Conclusions: With multidisciplinary and international input, a multidimensional set of outcome assessments for burns of the hand has been established, covering almost all domains of functioning. This first step towards more uniform clinical evaluation, will contribute to knowledge on outcome and effectiveness of treatment of hand burns.
The results will be consensus between departments of physiotherapy universities of allied health care about learning outcomes CommunicationThere is no consensus between Dutch Physiotherapy departments on learning outcome of bachelors
In the Netherlands approximately 2 million inhabitants have one or more disabilities. However, just like most people they like to travel and go on holiday.In this project we have explored the customer journey of people with disabilities and their families to understand their challenges and solutions (in preparing) to travel. To get an understanding what ‘all-inclusive’ tourism would mean, this included an analysis of information needs and booking behavior; traveling by train, airplane, boat or car; organizing medical care and; the design of hotels and other accommodations. The outcomes were presented to members of ANVR and NBAV to help them design tourism and hospitality experiences or all.
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.
