Refine
Year of publication
Document Type
- Conference Proceeding (577) (remove)
Language
- English (488)
- German (76)
- Multiple languages (10)
- French (2)
- Russian (1)
Keywords
- social media (5)
- Archiv (4)
- Information Structure (4)
- Nachlass (4)
- COVID-19 (3)
- Cloud Computing (3)
- E-Learning (3)
- E-Mail Tracking (3)
- ERP (3)
- MOOC (3)
Institute
- Extern (139)
- Fachgruppe Betriebswirtschaftslehre (77)
- Institut für Biochemie und Biologie (57)
- Department Sport- und Gesundheitswissenschaften (43)
- Institut für Ernährungswissenschaft (38)
- Department Psychologie (30)
- Institut für Künste und Medien (23)
- Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung (23)
- Institut für Informatik und Computational Science (20)
- Institut für Slavistik (17)
Einleitung
Pflege in Deutschland befindet sich in einem Veränderungsprozess. Die politisch forcierte Zuwanderung von Pflegekräften sowie die Akademisierung führen zu einem enormen Anpassungsdruck bei allen Beteiligten. Wie wirkt sich dies auf den Arbeitsalltag aus?
Methoden
Die qualitative Datenbasis umfasst bisher 36 Tage Teilnehmende Beobachtung, 17 Themenzentrierte Leitfadeninterviews sowie vier Gruppendiskussionen in vier Pflegeteams zweier Krankenhäuser. Die Analyse erfolgt mit der Dokumentarischen Methode.
Ergebnisse
Am Beispiel der Grundpflege (u. A. dem „Waschen“) wird deutlich, wie die Pflegeteams ihren Arbeitsalltag neu aushandeln. Die Teams mit einer hohen migrationsbezogenen Diversität argumentieren eher, dass die Aufgaben der Grund- und Behandlungspflege entsprechend der Qualifikation als Hilfs- oder Fachkraft erledigt werden sollen. Hier treten stereotype (kulturalisierende) Zuschreibungen in den Hintergrund. Demgegenüber berufen sich Pflegeteams mit einer niedrigen migrationsbezogenen Diversität eher darauf, dass die Grundpflege in Deutschland – anders als in anderen Ländern – zu den Aufgaben einer examinierten Pflegefachkraft zählt. Kolleg*innen aus dem Ausland wird die pflegerische Kompetenz daher eher abgesprochen.
Schlussfolgerung
Die Frage nach der Aufteilung von Grund- und Behandlungspflege, ist auf allen Stationen virulent. Die Teams entwickeln jedoch in Abhängigkeit von ihrer spezifischen Heterogenität unterschiedliche Umgangsweisen. Demzufolge sollte sich Personal- und Organisationsentwicklung insbesondere an den Pflegeteams orientieren.
Background:
Like most countries, Germany is currently recruiting international nurses due to staff shortages. While these are mostly academic, the academisation of nursing in Germany has only just begun. This allows for a broader look at the participation of migrant nurses: How do care teams deal with the fact that immigrant colleagues are theoretically more highly qualified than long-established colleagues?
Methods:
Case studies were conducted in four inpatient care teams of two hospitals in 2022. Qualitative data include 26 observation protocols, 4 group discussions and 17 guided interviews. These were analysed using the documentary method and validated intersubjectively.
Results:
Due to current academisation efforts in Germany and the immigration of academised nursing staff from abroad, the areas of activity and responsibility of nursing in Germany are under negotiating pressure. This concerns basic care for example, which in Germany is provided by skilled workers, but in other countries is mostly provided by assistants or relatives. The question of who should provide basic care, whether all nurses or only nursing assistants, documents the struggle between an established and a new understanding of care. In this context, the knowledge and skills of migrant and academicised care workers become a crucial aspect in the struggle for a new professional identity for care in Germany.
Conclusions:
The specific situation in Germany makes it possible to show the potential for change that international care migration can constitute for destination countries. The far-reaching process of change of German nursing is given a further dimension not only by its academization, but by the immigration of international and academically trained nursing staff, where inclusive or exclusive effects can already be observed.
Key messages: The increasing proportion of migrant nurses accelerates the current discussion on nursing in Germany. Conflict areas show up in everyday work of care teams and must be addressed there.
Scaling up CSP
(2023)
Concentrating solar power (CSP) is one of the few scalable technologies capable of delivering dispatchable renewable power. Therefore, many expect it to shoulder a significant share of system balancing in a renewable electricity future powered by cheap, intermittent PV and wind power: the IEA, for example, projects 73 GW CSP by 2030 and several hundred GW by 2050 in its Net-Zero by 2050 pathway. In this paper, we assess how fast CSP can be expected to scale up and how long time it would take to get new, high-efficiency CSP technologies to market, based on observed trends and historical patterns. We find that to meaningfully contribute to net-zero pathways the CSP sector needs to reach and exceed the maximum historical annual growth rate of 30%/year last seen between 2010-2014 and maintain it for at least two decades. Any CSP deployment in the 2020s will rely mostly on mature existing technologies, namely parabolic trough and molten-salt towers, but likely with adapted business models such as hybrid CSP-PV stations, combining the advantages of higher-cost dispatchable and low-cost intermittent power. New third-generation CSP designs are unlikely to play a role in markets during the 2020s, as they are still at or before the pilot stage and, judging from past pilot-to-market cycles for CSP, they will likely not be ready for market deployment before 2030. CSP can contribute to low-cost zero-emission energy systems by 2050, but to make that happen, at the scale foreseen in current energy models, ambitious technology-specific policy support is necessary, as soon as possible and in several countries.
Helping overcome distance, the use of videoconferencing tools has surged during the pandemic. To shed light on the consequences of videoconferencing at work, this study takes a granular look at the implications of the self-view feature for meeting outcomes. Building on self-awareness research and self-regulation theory, we argue that by heightening the state of self-awareness, self-view engagement depletes participants’ mental resources and thereby can undermine online meeting outcomes. Evaluation of our theoretical model on a sample of 179 employees reveals a nuanced picture. Self-view engagement while speaking and while listening is positively associated with self-awareness, which, in turn, is negatively associated with satisfaction with meeting process, perceived productivity, and meeting enjoyment. The criticality of the communication role is put forward: looking at self while listening to other attendees has a negative direct and indirect effect on meeting outcomes; however, looking at self while speaking produces equivocal effects.
Physiological and genomic variation among cryptic species of a marsh snail (Melampus bidentatus)
(2021)
Background:
Childhood and adolescence are critical stages of life for mental health and well-being. Schools are a key setting for mental health promotion and illness prevention. One in five children and adolescents have a mental disorder, about half of mental disorders beginning before the age of 14. Beneficial and explainable artificial intelligence can replace current paper- based and online approaches to school mental health surveys. This can enhance data acquisition, interoperability, data driven analysis, trust and compliance. This paper presents a model for using chatbots for non-obtrusive data collection and supervised machine learning models for data analysis; and discusses ethical considerations pertaining to the use of these models.
Methods:
For data acquisition, the proposed model uses chatbots which interact with students. The conversation log acts as the source of raw data for the machine learning. Pre-processing of the data is automated by filtering for keywords and phrases.
Existing survey results, obtained through current paper-based data collection methods, are evaluated by domain experts (health professionals). These can be used to create a test dataset to validate the machine learning models. Supervised learning
can then be deployed to classify specific behaviour and mental health patterns.
Results:
We present a model that can be used to improve upon current paper-based data collection and manual data analysis methods. An open-source GitHub repository contains necessary tools and components of this model. Privacy is respected through
rigorous observance of confidentiality and data protection requirements. Critical reflection on these ethics and law aspects is included in the project.
Conclusions:
This model strengthens mental health surveillance in schools. The same tools and components could be applied to other public health data. Future extensions of this model could also incorporate unsupervised learning to find clusters and patterns
of unknown effects.