Reference card for researchers on anonymization - in order to engage them with research supporters and privacy specialists in their research institutions to deal with research data about people and risk management in a proper way. Also a Dutch version available through www.lcrdm.nl
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This presentation explores how AI face anonymization impacts empathy and source credibility in documentaries, balancing privacy protection with audience engagement.
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This matrix is generic. It is a tool for data stewards or other research supporters to assist researchers in taking appropriate measures for the safe use and protection of data about people in scientific research. It is a template that you can adjust to the context of your own institution, faculty and / or department by taking into consideration your setting’s own policies, guidelines, infrastructure and technical solutions. In this way you can more effectively determine the appropriate technical and organizational measures to protect the data based on the context of the research and the risks associated with the data.
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ABSTRACT Purpose: This short paper describes the dashboard design process for online hate speech monitoring for multiple languages and platforms. Methodology/approach: A case study approach was adopted in which the authors followed a research & development project for a multilingual and multiplatform online dashboard monitoring online hate speech. The case under study is the project for the European Observatory of Online Hate (EOOH). Results: We outline the process taken for design and prototype development for which a design thinking approach was followed, including multiple potential user groups of the dashboard. The paper presents this process's outcome and the dashboard's initial use. The identified issues, such as obfuscation of the context or identity of user accounts of social media posts limiting the dashboard's usability while providing a trade-off in privacy protection, may contribute to the discourse on privacy and data protection in (big data) social media analysis for practitioners. Research limitations/implications: The results are from a single case study. Still, they may be relevant for other online hate speech detection and monitoring projects involving big data analysis and human annotation. Practical implications: The study emphasises the need to involve diverse user groups and a multidisciplinary team in developing a dashboard for online hate speech. The context in which potential online hate is disseminated and the network of accounts distributing or interacting with that hate speech seems relevant for analysis by a part of the user groups of the dashboard. International Information Management Association
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In this paper we explore the extent to which privacy enhancing technologies (PETs) could be effective in providing privacy to citizens. Rapid development of ubiquitous computing and ‘the internet of things’ are leading to Big Data and the application of Predictive Analytics, effectively merging the real world with cyberspace. The power of information technology is increasingly used to provide personalised services to citizens, leading to the availability of huge amounts of sensitive data about individuals, with potential and actual privacy-eroding effects. To protect the private sphere, deemed essential in a state of law, information and communication systems (ICTs) should meet the requirements laid down in numerous privacy regulations. Sensitive personal information may be captured by organizations, provided that the person providing the information consents to the information being gathered, and may only be used for the express purpose the information was gathered for. Any other use of information about persons without their consent is prohibited by law; notwithstanding legal exceptions. If regulations are properly translated into written code, they will be part of the outcomes of an ICT, and that ICT will therefore be privacy compliant. We conclude that privacy compliance in the ‘technological’ sense cannot meet citizens’ concerns completely, and should therefore be augmented by a conceptual model to make privacy impact assessments at the level of citizens’ lives possible.
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Abstract: Technological innovation in the healthcare sector is increasing, but integration of information technology (IT) in the care process is difficult. Healthcare workers are important agents in this IT integration. The purpose of this study is to explore factors that feed motivation to use IT. Self-determination theory (SDT) is applied to study how motivational factors impact effective IT use among frontline caregivers in residential care settings. As the team is very important to these caregivers, the team is our unit of analysis. In an embedded single case study design, interviews were conducted with all nine members of a team effectively using IT. All three basic psychological needs from SDT - autonomy, competence and relatedness - were found to have impact on effective IT use, though autonomy was primarily experienced at team level. Conversely, the effective use of an IT collaboration tool influences relatedness.
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Introduction: A trauma resuscitation is dynamic and complex process in which failures could lead to serious adverse events. In several trauma centers, evaluation of trauma resuscitation is part of a hospital's quality assessment program. While video analysis is commonly used, some hospitals use live observations, mainly due to ethical and medicolegal concerns. The aim of this study was to compare the validity and reliability of video analysis and live observations to evaluate trauma resuscitations. Methods: In this prospective observational study, validity was assessed by comparing the observed adherence to 28 advanced trauma life support (ATLS) guideline related tasks by video analysis to life observations. Interobserver reliability was assessed by calculating the intra class coefficient of observed ATLS related tasks by live observations and video analysis. Results: Eleven simulated and thirteen real-life resuscitations were assessed. Overall, the percentage of observed ATLS related tasks performed during simulated resuscitations was 10.4% (P < 0.001) higher when the same resuscitations were analysed using video compared to live observations. During real-life resuscitations, 8.7% (p < 0.001) more ATLS related tasks were observed using video review compared to live observations. In absolute terms, a mean of 2.9 (during simulated resuscitations) respectively 2.5 (during actual resuscitations) ATLS-related tasks per resuscitation were not identified using live observers, that were observed through video analysis. The interobserver variability for observed ATLS related tasks was significantly higher using video analysis compared to live observations for both simulated (video analysis: ICC 0.97; 95% CI 0.97-0.98 vs. live observation: ICC 0.69; 95% CI 0.57-0.78) and real-life witnessed resuscitations (video analyse 0.99; 95% CI 0.99-1.00 vs live observers 0.86; 95% CI 0.83-0.89). Conclusion: Video analysis of trauma resuscitations may be more valid and reliable compared to evaluation by live observers. These outcomes may guide the debate to justify video review instead of live observations.
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Despite the existence of various methods and abstraction techniques to reduce the privacy risk of process models generated by process mining algorithms, it is unclear how process mining stakeholders perceive privacy violations. In this pilot-study various process model visualisations were shown to 6 stakeholders of a travel expense claim process. While changing the abstraction levels of these visualisations, the stakeholders were asked whether they perceived a violation of their privacy. The results show that there are differences in how individual stakeholders perceive privacy violations of process models generated via process mining algorithms. Results differ per type of visualization, type of privacy risk reducing methods, changes of abstraction level and stakeholder role. To reduce the privacy risk, the interviewees suggested to include an authorization table in the process mining tool, communicate the goal of the analysis with all stakeholders, and validate the analysis with a privacy officer. It is suggested that future research focuses on discussing and validating process visualisations and privacy risk reducing methods and techniques with various process mining stakeholders in organisations. This is expected to reduce perceived violations and prevents developing techniques that are aimed at reducing privacy risk but are not considered as such by stakeholders.
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Purpose: The increasing number of cancer survivors has heightened demands on hospital-based follow-up care resources. To address this, involving general practitioners (GPs) in oncological follow-up is proposed. This study explores secondary care providers’ views on integrating GPs into follow-up care for curatively treated breast and colorectal cancer survivors. Methods: A qualitative exploratory study was conducted using semi-structured interviews with Dutch medical specialists and nurse practitioners. Interviews were recorded, transcribed verbatim, and analyzed using thematic analysis by two independent researchers. Results: Fifteen medical specialists and nine nurse practitioners participated. They identified barriers such as re-referral delays, inexperience to perform structured follow-up, and worries about the lack of oncological knowledge among GPs. Benefits included the GPs’ accessibility and their contextual knowledge. For future organization, they emphasized the need for hospital logistics changes, formal GP training, sufficient case-load, proper staffing, remuneration, and time allocation. They suggested that formal GP involvement should initially be implemented for frail older patients and for prevalent cancer types. Conclusions: The interviewed Dutch secondary care providers generally supported formal involvement of primary care in cancer follow-up. A well-organized shared-care model with defined roles and clear coordination, supported by individual patients, was considered essential. This approach requires logistics adaptation, resources, and training for GPs. Implications for cancer survivors: Integrating oncological follow-up into routine primary care through a shared-care model may lead to personalized, effective, and efficient care for survivors because of their long-term relationships with GPs.
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French/English abstract: Les systèmes d’aide à la prise de décision jouent un rôle important dans la pratique juridique aux Pays-Bas. Divers organismes gouvernementaux utilisent de tels systèmes automatisés pour la prise de décisions juridiques (de masse). Les départements juridiques, les cabinets d’avocats, les éditeurs juridiques et d’autres organismes ont de plus en plus recours à ces outils pour appuyer et améliorer les services d’aide juridique aux particuliers et aux entreprises. Ces outils permettent d’améliorer l’efficacité des processus et des services juridiques, mais ils peuvent aussi avoir d’importants effets préjudiciables sur les droits des personnes ou sur la qualité juridique des services produits, en particulier lorsqu’il n’existe pas de processus de conception minutieux et transparent. Cet article donne un aperçu de l’utilisation de ces systèmes dans la pratique juridique néerlandaise, discute de leurs avantages, pièges et défis, puis il identifie certaines questions de recherche pour le futur.---Rule-based systems for decision support and decision-making play an important role in Dutch legal practice. Government agencies use rule-based systems for (mass) legal decision-making. Legal departments, law firms, legal publishers and various other organizations increasingly use rule-basedsystems to support and improve the provision of legal aid to private individuals and corporate clients. Rule-based systems can improve efficiency of legal processes and services, but can also have important detrimental effects on the rights of individuals or legal quality, especially when there is no careful and transparent design process. This article provides an overview of the use of these systems in Dutch legal practice, discusses benefits, pitfallsand challenges and identifies questions for future research.
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