https://hdl.handle.net/20.500.12738/3 Publications without full text files / Publikationen ohne Volltext(dateien) Sat, 18 Jul 2026 08:08:14 GMT 2026-07-18T08:08:14Z https://hdl.handle.net/20.500.12738/19626 Title: Uncertainties and coping strategies among nurses during the first wave of Covid-19 in Germany : nursing students’ use of diary entries to document their experiences during the first wave of infections in the Covid-19 pandemic Authors: Wöhlke, Sabine; Ruwe, Gisela Abstract: Background: In March 2020, German hospitals were preparing for the first major wave of Covid-19 infections, implementing crisis management procedures without precedent or prior testing. At this time, we asked stu-dent nurses in their eighth semester of study to complete a nursing diary for a period of four weeks. The aim of this research was to ascertain students’ perceptions of the constantly evolving crisis and retrace their re-flections on the situation on the basis of the knowledge they had at the time. Methods: Eleven students completed a nursing diary, which entailed writing entries on the care they provided on the wards to which they were assigned. They added images such as pictures, screenshots and drawings to their diary entries. We analysed the data using ethnographic methods as follows: a) categorisation of the entries in accordance with general thematic similarities; b) comparison of the entries with published nursing literature from this time period, with the aim of identifying possible gaps in the content of our data. Results: The student nurses worked on different wards; some volunteered to staff the newly established Covid-19 wards. Nursing students felt the unfolding crisis to be defined by a sense of uncertainty and potential threat, associated with various fears. The students described their own actions and behaviour in specific sit¬uations and outlined observations of others. We categorised our findings in four sub-topics: a) crisis manage¬ment; b) the invisible crisis; c) a sense of crisis; and d) coping with the crisis. Discussion: In giving insights into the day-to-day work of nurses under extreme conditions, the diaries col-lected and analysed for this study highlight experiences of ambivalence and uncertainty during the first wave of Covid-19 infections. Specifically, the students’ reflections on professional responsibility point to this princi¬ple’s importance within the system of values espoused by members of the nursing profession. Fri, 17 Jul 2026 16:03:00 GMT https://hdl.handle.net/20.500.12738/19626 2026-07-17T16:03:00Z https://hdl.handle.net/20.500.12738/19625 Title: Forschungspraxis, Diskriminierungsformen und Handlungsmöglichkeiten in der Pflege, Versorgung und Betreuung von trans*Kindern und Jugendlichen : ein Forschungsbericht Authors: Bolz, Manuel; Wöhlke, Sabine Abstract: In unserem Forschungsbericht stellen wir unser empirisches Forschungsdesign, erste Ergebnisse des Verbundprojektes TRANS*KIDS und des Hamburger Teilprojektes vor. Unser Projekt hat zum Ziel, (potenzielle) Diskriminierungen und Stigmatisierungen von professionell Pflegenden und (medizinischen) Fach- und Verwaltungsangestellten in Kliniken und in Ärzt*innenpraxen im Umgang mit trans*-Kindern und -Jugendlichen herauszuarbeiten. Diese, so zeigt es unsere Auswertung, zeigen sich als Hindernis für eine wertschätzende, diversitäts- und geschlechtssensible Pflege, Betreuung und Versorgung. Der Beitrag fungiert als Werkstattbericht um die Forschungspraxis, das Material und die Methode vorzustellen, zu diskutieren und kritisch zu evaluieren. Fri, 17 Jul 2026 15:44:38 GMT https://hdl.handle.net/20.500.12738/19625 2026-07-17T15:44:38Z https://hdl.handle.net/20.500.12738/19624 Title: Research ethics governance with responsible AI sandboxes Authors: Gille, Michael; Tropmann-Frick, Marina Abstract: University research ethics committees (REC) face challenges in overseeing artificial intelligence (AI) research. Historically rooted in biomedical and social science paradigms, REC were not designed to evaluate the epistemic, temporal, and normative complexities of AI and machine learning research. The EU’s AI Act exacerbates this tension by exempting academic research from its scope while at the same time promoting the application of ethics guidelines, thereby creating a zone of normative ambiguity. This paper critically examines the resulting governance vacuum. We argue that conventional ethical review processes are inadequate in many cases for reasons inherent in AI research, which is often iterative and interdisciplinary, characterized by shifting goals and emerging risks, as well as because of the normative and socio-technical co-construction of AI technology development. We propose the Responsible Artificial Intelligence Sandbox as a model for research ethics governance. It reframes the role of REC from static evaluators to co-constructors of ethical oversight within experimental research environments. Drawing on insights from regulatory sandboxes in EU law and national contexts, this conceptual model enables dynamic, participatory, and reflexive engagement with ethics throughout the research lifecycle. Two main contributions are made: we diagnose structural misalignments of existing research ethics infrastructure and conceptualize responsible AI sandboxes as an institutional and methodological innovation that aligns ethical governance with the nature of research on and with AI. Fri, 17 Jul 2026 15:05:55 GMT https://hdl.handle.net/20.500.12738/19624 2026-07-17T15:05:55Z https://hdl.handle.net/20.500.12738/19623 Title: Rethinking trust in responsible AI Authors: Tropmann-Frick, Marina; Gille, Michael; Draheim, Susanne; Pommerencke, Philine; Kiener, Maximilian; Bozenhard, Jonas Abstract: Trust is widely recognized as a core principle of Responsible AI, yet its interpretation varies significantly across disciplines. This paper examines how computer science, sociology, philosophy, and law conceptualize trust in AI systems, highlighting both tensions and complementarities. From a computer science perspective, trust is often approached as a set of system-level properties that should be formalized and evaluated with metrics. In contrast, the social sciences and humanities emphasize its relational, normative, and institutional dimensions. We argue that trust cannot be reduced to a single system property or technical measure, as it emerges from social-technical interactions involving users, developers, legal norms, and social expectations. To support interdisciplinary dialogue, we propose treating trust as a boundary concept that enables cooperation across epistemic communities acknowledging conceptual differences. Trust is widely recognized as a core principle of Responsible AI, yet its interpretation varies significantly across disciplines. This paper examines how computer science, sociology, philosophy, and law conceptualize trust in AI systems, highlighting both tensions and complementarities. From a computer science perspective, trust is often approached as a set of system-level properties that should be formalized and evaluated with metrics. In contrast, the social sciences and humanities emphasize its relational, normative, and institutional dimensions. We argue that trust cannot be reduced to a single system property or technical measure, as it emerges from social-technical interactions involving users, developers, legal norms, and social expectations. To support interdisciplinary dialogue, we propose treating trust as a boundary concept that enables cooperation across epistemic communities acknowledging conceptual differences. Fri, 17 Jul 2026 14:42:11 GMT https://hdl.handle.net/20.500.12738/19623 2026-07-17T14:42:11Z