This study investigated potential risk factors (coping, perfectionism, and self-regulation) for substantial injuries in contemporary dance students using a prospective cohort design, as high-quality studies focusing on mental risk factors for dance injuries are lacking. Student characteristics (age, sex, BMI, educational program, and history of injury) and psychological constructs (coping, perfectionism, and self-regulation) were assessed using the Performing artist and Athlete Health Monitor (PAHM), a web-based system. Substantial injuries were measured with the Oslo Sports Trauma Research Center (OSTRC) Questionnaire on Health Problems and recorded on a monthly basis as part of the PAHM system. Univariate and multivariate logistic regression analyses were conducted to test the associations between potential risk factors (i.e., student characteristics and psychological constructs) and substantial injuries. Ninety-nine students were included in the analyses. During the academic year 2016/2017, 48 students (48.5%) reported at least one substantial injury. Of all factors included, coping skills (OR: 0.91; 95% CI: 0.84–0.98), age (OR: 0.67; 95% CI: 0.46–0.98), and BMI (OR: 1.38; 95% CI: 1.05–1.80) were identified as significant risk factors in the multivariate analysis. The model explained 24% of the variance in the substantial injury group. Further prospective research into mental risk factors for dance injuries with larger sample sizes is needed to develop preventive strategies. Yet, dance schools could consider including coping skills training as part of injury prevention programs and, perhaps, providing special attention to younger dancers and those with a higher BMI through transitional programs to assist them in managing the stress they experience throughout their (academic) career.
This study investigated potential risk factors (coping, perfectionism, and self-regulation) for substantial injuries in contemporary dance students using a prospective cohort design, as high-quality studies focusing on mental risk factors for dance injuries are lacking. Student characteristics (age, sex, BMI, educational program, and history of injury) and psychological constructs (coping, perfectionism, and self-regulation) were assessed using the Performing artist and Athlete Health Monitor (PAHM), a web-based system. Substantial injuries were measured with the Oslo Sports Trauma Research Center (OSTRC) Questionnaire on Health Problems and recorded on a monthly basis as part of the PAHM system. Univariate and multivariate logistic regression analyses were conducted to test the associations between potential risk factors (i.e., student characteristics and psychological constructs) and substantial injuries. Ninety-nine students were included in the analyses. During the academic year 2016/2017, 48 students (48.5%) reported at least one substantial injury. Of all factors included, coping skills (OR: 0.91; 95% CI: 0.84–0.98), age (OR: 0.67; 95% CI: 0.46–0.98), and BMI (OR: 1.38; 95% CI: 1.05–1.80) were identified as significant risk factors in the multivariate analysis. The model explained 24% of the variance in the substantial injury group. Further prospective research into mental risk factors for dance injuries with larger sample sizes is needed to develop preventive strategies. Yet, dance schools could consider including coping skills training as part of injury prevention programs and, perhaps, providing special attention to younger dancers and those with a higher BMI through transitional programs to assist them in managing the stress they experience throughout their (academic) career.
Digital transformation has been recognized for its potential to contribute to sustainability goals. It requires companies to develop their Data Analytic Capability (DAC), defined as their ability to collect, manage and analyze data effectively. Despite the governmental efforts to promote digitalization, there seems to be a knowledge gap on how to proceed, with 37% of Dutch SMEs reporting a lack of knowledge, and 33% reporting a lack of support in developing DAC. Participants in the interviews that we organized preparing this proposal indicated a need for guidance on how to develop DAC within their organization given their unique context (e.g. age and experience of the workforce, presence of legacy systems, high daily workload, lack of knowledge of digitalization). While a lot of attention has been given to the technological aspects of DAC, the people, process, and organizational culture aspects are as important, requiring a comprehensive approach and thus a bundling of knowledge from different expertise. Therefore, the objective of this KIEM proposal is to identify organizational enablers and inhibitors of DAC through a series of interviews and case studies, and use these to formulate a preliminary roadmap to DAC. From a structure perspective, the objective of the KIEM proposal will be to explore and solidify the partnership between Breda University of Applied Sciences (BUas), Avans University of Applied Sciences (Avans), Logistics Community Brabant (LCB), van Berkel Logistics BV, Smink Group BV, and iValueImprovement BV. This partnership will be used to develop the preliminary roadmap and pre-test it using action methodology. The action research protocol and preliminary roadmap thereby developed in this KIEM project will form the basis for a subsequent RAAK proposal.
De maatschappelijke discussies over de invloed van AI op ons leven tieren welig. De terugkerende vraag is of AI-toepassingen – en dan vooral recommendersystemen – een dreiging of een redding zijn. De impact van het kiezen van een film voor vanavond, met behulp van Netflix' recommendersysteem, is nog beperkt. De impact van datingsites, navigatiesystemen en sociale media – allemaal systemen die met algoritmes informatie filteren of keuzes aanraden – is al groter. De impact van recommendersystemen in bijvoorbeeld de zorg, bij werving en selectie, fraudedetectie, en beoordelingen van hypotheekaanvragen is enorm, zowel op individueel als op maatschappelijk niveau. Het is daarom urgent dat juist recommendersystemen volgens de waarden van Responsible AI ontworpen worden: veilig, eerlijk, betrouwbaar, inclusief, transparant en controleerbaar.Om op een goede manier Responsible AI te ontwerpen moeten technische, contextuele én interactievraagstukken worden opgelost. Op het technische en maatschappelijke niveau is al veel vooruitgang geboekt, respectievelijk door onderzoek naar algoritmen die waarden als inclusiviteit in hun berekening meenemen, en door de ontwikkeling van wettelijke kaders. Over implementatie op interactieniveau bestaat daarentegen nog weinig concrete kennis. Bekend is dat gebruikers die interactiemogelijkheden hebben om een algoritme bij te sturen of aan te vullen, meer transparantie en betrouwbaarheid ervaren. Echter, slecht ontworpen interactiemogelijkheden, of een mismatch tussen interactie en context kosten juist tijd, veroorzaken mentale overbelasting, frustratie, en een gevoel van incompetentie. Ze verhullen eerder dan dat ze tot transparantie leiden.Het ontbreekt ontwerpers van interfaces (UX/UI designers) aan systematische concrete kennis over deze interactiemogelijkheden, hun toepasbaarheid, en de ethische grenzen. Dat beperkt hun mogelijkheid om op interactieniveau aan Responsible AI bij te dragen. Ze willen daarom graag een pattern library van interactiemogelijkheden, geannoteerd met onderzoek over de werking en inzetbaarheid. Dit bestaat nu niet en met dit project willen we een substantiële bijdrage leveren aan de ontwikkeling ervan.
The pace of technology advancements continues to accelerate, and impacts the nature of systems solutions along with significant effects on involved stakeholders and society. Design and engineering practices with tools and perspectives, need therefore to evolve in accordance to the developments that complex, sociotechnical innovation challenges pose. There is a need for engineers and designers that can utilize fitting methods and tools to fulfill the role of a changemaker. Recognized successful practices include interdisciplinary methods that allow for effective and better contextualized participatory design approaches. However, preliminary research identified challenges in understanding what makes a specific method effective and successfully contextualized in practice, and what key competences are needed for involved designers and engineers to understand and adopt these interdisciplinary methods. In this proposal, case study research is proposed with practitioners to gain insight into what are the key enabling factors for effective interdisciplinary participatory design methods and tools in the specific context of sociotechnical innovation. The involved companies are operating at the intersection between design, technology and societal impact, employing experts who can be considered changemakers, since they are in the lead of creative processes that bring together diverse groups of stakeholders in the process of sociotechnical innovation. A methodology will be developed to capture best practices and understand what makes the deployed methods effective. This methodology and a set of design guidelines for effective interdisciplinary participatory design will be delivered. In turn this will serve as a starting point for a larger design science research project, in which an educational toolkit for effective participatory design for socio-technical innovation will be designed.
