Background: Particulate matter (PM) exposure is an important health risk, both in daily life and in the workplace. It causes respiratory and cardiovascular diseases and results in 800,000 premature deaths per year worldwide. In earlier research, we assessed workers’ information needs regarding workplace PM exposure, the properties and effects of PM, and the rationale behind various means of protection. We also concluded that workers do not always receive appropriate risk communication tools with regards to PM, and that their PM knowledge appears to be fragmented and incomplete. Methods: We considered several concepts for use as an educational material based on evaluation criteria: ease of use, costs, appropriateness for target audiences and goals, interactivity, implementation issues, novelty, and speed. We decided to develop an educational folder, which can be used to inform employees about the properties, effects and prevention methods concerning PM. Furthermore, we decided on a test setup of a more interactive way of visualisation of exposure to PM by means of exposimeters. For the development of the folder, we based the information needs on our earlier mental models-based research. We adjusted the folder based on the results of ten semi-structured interviews evaluating its usability. Results: The semi-structured interviews yielded commentaries and suggestions for further improvement, which resulted in a number of alterations to the folder. However, in most cases the folder was deemed satisfactory. Conclusion: Based on this study, the folder we developed is suitable for a larger-scale experiment and a practical test. Further research is needed to investigate the efficacy of the folder and the application of the exposimeter in a PM risk communication system.
Abstract: The Problem-Solution Chain (PSC) models proposed in this exploratory paper are conceived as describing chains of problem-solution links, thereby modelling specific multi-link ‘problem-solving’ paths, typically (but not exclusively) from a high-level business problem to lower-level functional solution components. The main elements are ‘Problems’ and ‘Solutions’. These may be selected from purpose-made, domain-specific collections of elements. Single ‘Problem-Solution links’ are comparable to compact, high-level descriptions of design patterns and can be directly related to design problem templates as used in Design Science. Coherent collections of such links would resemble boiled-down representations of pattern languages. Instantiations of PSCs for specific situations aim to help conceptualise and discuss pre-architectural, high-level overviews, for example, of (options for) functionalities or applications representing ‘solutions’ for ‘solving’ some business need or capability ‘problem’. A useful metaphor is that PSCs help describe and discuss basic ingredients (related problems and solutions) for some specific situation, which can later (out of scope here) be developed into a recipe (e.g. an enterprise or process architecture and roadmap) and eventually into an actual dish (realisation of the architecture/solution). Thus, PSCs can, for example, be conceptualisations and conversation aids in the early stages of business-IT alignment efforts and system design. This explorative, practice-oriented paper presents our initial conceptualisation of PSCs. We also present a syntax and notation for problem-solution chains as specified for the Simplified Modelling Platform (SMP), and we briefly discuss the possibility of supporting PSC modelling with guided conversations for PSC modelling. We demonstrate and evaluate our proposed concepts by applying them in a single real case. Much work lies ahead.
In safety science and practice, there have been various safety models, each of them reflecting a particular approach to safety management and accident causality. The large variety of models suggested in literature and applied in practice serve the communication of diverse perspectives towards safety and the need to consider contextual factors, but it does not allow the establishment of a common language within and across organisations and industry sectors. Considering the potential benefits of talking a lingua franca when it comes to safety and inspired by the Standard Model used in particle physics and recent suggestions from relevant studies, we thought of exploring the possibility to introduce a Standard Safety Model (STASAM). As a first step, we focused on four representative safety and accident models widely used, discussed and debated: the Swiss Cheese Model, AcciMap, Functional Resonance Analysis Method (FRAM) and Systems-Theoretic Accident Model and Processes (STAMP). We reviewed literature which compares the particular models, and we listed the strengths and weaknesses of each as a means to set the grounds for the STASAM. The combinations of these models with a focus to host their advantages and avoiding their disadvantages led to a three-level STASAM. The concept STASAM was used in two random incident investigation reports to assess its applicability and visualisation against the original models. The results of the application along with the STASAM concept were reviewed by three safety professionals and three safety researchers. The comments received were in the positive direction and indicated the potential of establishing an inclusive and commonly accepted safety/accident model. The next research phase will be the additional review of the STASAM and its pilot application to a variety of safety events and systems as a means to test its reliability and strengthen its validity.
"Speak the Future" presents a novel test case at the intersection of scientific innovation and public engagement. Leveraging the power of real-time AI image generation, the project empowers festival participants to verbally describe their visions for a sustainable and regenerative future. These descriptions are instantly transformed into captivating imagery using SDXL Turbo, fostering collective engagement and tangible visualisation of abstract sustainability concepts. This unique interplay of speech recognition, AI, and projection technology breaks new ground in public engagement methods. The project offers valuable insights into public perceptions and aspirations for sustainability, as well as understanding the effectiveness of AI-powered visualisation and regenerative applications of AI. Ultimately, this will serve as a springboard for PhD research that will aim to understand How AI can serve as a vehicle for crafting regenerative futures? By employing real-time AI image generation, the project directly tests its effectiveness in fostering public engagement with sustainable futures. Analysing participant interaction and feedback sheds light on how AI-powered visualisation tools can enhance comprehension and engagement. Furthermore, the project fosters public understanding and appreciation of research. The interactive and accessible nature of "Speak the Future" demystifies the research process, showcasing its relevance and impact on everyday life. Moreover, by directly involving the public in co-creating visual representations of their aspirations, the project builds an emotional connection and sense of ownership, potentially leading to continued engagement and action beyond the festival setting. "Speak the Future" promises to be a groundbreaking initiative, bridging the gap between scientific innovation and public engagement in sustainability discourse. By harnessing the power of AI for collective visualisation, the project not only gathers valuable data for researchers but also empowers the public to envision and work towards a brighter, more sustainable future.
