Hochschule für Angewandte Psychologie FHNW
Dauerhafte URI für den Bereichhttps://irf.fhnw.ch/handle/11654/1
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Publikation Mehrdimensionale Skala zur Messung von Dankbarkeit (MCGM-G)(ZIS, 2021) Hudecek, Matthias; Blabst, Nicole; Morgen, Blaire; Lermer, EvaDie hier dokumentierte mehrdimensionale Skala zur Messung von Dankbarkeit (MCGM-G) ist die deutschsprachige Version des Multi-Component Gratitude Measure (MCGM). Der MCGM wurde als ein ganzheitlicher Ansatz zur Messung von Dankbarkeit von Morgan et al. (2017) entwickelt und umfasst emotionale, einstellungsbezogene und verhaltensbezogene Komponenten von Dankbarkeit. Die Validierung erfolgte mittels einer Online-Umfrage und umfasste die Daten von 508 Versuchspersonen. Der MCGM-G verfügt über eine gute interne Konsistenz und sowohl die Konstrukt- als auch die Kriteriumsvalidität konnten nachgewiesen werden. Darüber hinaus besteht partielle skalare Messinvarianz (d.h. kulturelle Invarianz) mit der englischsprachigen Version für fünf der sechs Faktoren. Zudem liegt vollständige Messinvarianz hinsichtlich des Geschlechts der TeilnehmerInnen für alle Dimensionen des MCGM-G vor.05 - Forschungs- oder ArbeitsberichtPublikation Unsicherheit. Globale Herausforderungen psychologisch verstehen und bewältigen(Reinhardt, 2022) Lermer, Eva; Hudecek, MatthiasOb Covid-19-Pandemie, Fake Stories oder politische Erdbeben: Der Umgang mit Unsicherheit ist eine wesentliche Herausforderung im menschlichen Alltag. Obwohl viele beunruhigende Ereignisse der Vergangenheit (z. B. Sonnenfinsternis)erklärt werden konnten, verharren wir bei neuen Unsicherheitslagen in unseren alten Denk- und Verhaltensmustern. Diese sind geprägt durch Phänomene wie verzerrte Wahrnehmung oder (Selbst-)Überschätzung. Dieses Buch leistet einen Beitrag zum kompetenten Umgang mit Unsicherheit. Mithilfe von psychologischem Wissen werden Denkprozesse und Interaktionen besser verständlich gemacht, um künftig reflektierter (re-)agieren zu können. Das Buch ist ein Plädoyer für eine neue Aufklärung mit einem Appell an die individuelle Verantwortlichkeit, sich seines Verstandes zu bedienen.02 - MonographiePublikation Who thinks COVID-19 is a hoax? Psychological correlates of beliefs in conspiracy theories and attitudes towards anti-Coronavirus measures at the end of the first lockdown in Germany(Ubiquity Press, 2022) Hudecek, Matthias; Fischer, Peter; Gaube, Susanne; Lermer, Eva12 - PatentPublikation Aggressives Verhalten von Kindern und Interventionen auf der elterlichen Paarebene(Vandenhoeck & Ruprecht, 2015) Lux, Ulrike; Hudecek, Matthias01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Kommunikation in Zeiten gesellschaftlicher Spaltung(Dr. Otto Schmidt, 2020) Hudecek, Matthias; Fischer, Peter01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Measuring gratitude in Germany: validation study of the German version of the Gratitude Questionnaire-Six Item Form (GQ-6-G) and the Multi-Component Gratitude Measure (MCGM-G)(Frontiers Research Foundation, 2020) Hudecek, Matthias; Blabst, Nicole; Morgan, Blaire; Lermer, Eva01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Insights on the current state and future outlook of AI in health care: expert interview study(JMIR Publications, 2023) Hummelsberger, Pia; Koch, Timo K.; Rauh, Sabrina; Dorn, Julia; Lermer, Eva; Raue, Martina; Hudecek, Matthias; Schicho, Andreas; Colak, Errol; Ghassemi, Marzyeh; Gaube, SusanneBackground Artificial intelligence (AI) is often promoted as a potential solution for many challenges health care systems face worldwide. However, its implementation in clinical practice lags behind its technological development. Objective This study aims to gain insights into the current state and prospects of AI technology from the stakeholders most directly involved in its adoption in the health care sector whose perspectives have received limited attention in research to date. Methods For this purpose, the perspectives of AI researchers and health care IT professionals in North America and Western Europe were collected and compared for profession-specific and regional differences. In this preregistered, mixed methods, cross-sectional study, 23 experts were interviewed using a semistructured guide. Data from the interviews were analyzed using deductive and inductive qualitative methods for the thematic analysis along with topic modeling to identify latent topics. Results Through our thematic analysis, four major categories emerged: (1) the current state of AI systems in health care, (2) the criteria and requirements for implementing AI systems in health care, (3) the challenges in implementing AI systems in health care, and (4) the prospects of the technology. Experts discussed the capabilities and limitations of current AI systems in health care in addition to their prevalence and regional differences. Several criteria and requirements deemed necessary for the successful implementation of AI systems were identified, including the technology’s performance and security, smooth system integration and human-AI interaction, costs, stakeholder involvement, and employee training. However, regulatory, logistical, and technical issues were identified as the most critical barriers to an effective technology implementation process. In the future, our experts predicted both various threats and many opportunities related to AI technology in the health care sector. Conclusions Our work provides new insights into the current state, criteria, challenges, and outlook for implementing AI technology in health care from the perspective of AI researchers and IT professionals in North America and Western Europe. For the full potential of AI-enabled technologies to be exploited and for them to contribute to solving current health care challenges, critical implementation criteria must be met, and all groups involved in the process must work together.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Predicting acceptance of autonomous shuttle buses by personality profiles: a latent profile analysis(Springer, 2023) Schandl, Franziska; Fischer, Peter; Hudecek, MatthiasAbstract Autonomous driving and its acceptance are becoming increasingly important in psychological research as the application of autonomous functions and artificial intelligence in vehicles increases. In this context, potential users are increasingly considered, which is the basis for the successful establishment and use of autonomous vehicles. Numerous studies show an association between personality variables and the acceptance of autonomous vehicles. This makes it more relevant to identify potential user profiles to adapt autonomous vehicles to the potential user and the needs of the potential user groups to marketing them effectively. Our study, therefore, addressed the identification of personality profiles for potential users of autonomous vehicles (AVs). A sample of 388 subjects answered questions about their intention to use autonomous buses, their sociodemographics, and various personality variables. Latent Profile Analysis was used to identify four personality profiles that differed significantly from each other in their willingness to use AVs. In total, potential users with lower anxiety and increased self-confidence were more open toward AVs. Technology affinity as a trait also contributes to the differentiation of potential user profiles and AV acceptance. The profile solutions and the correlations with the intention to use proved to be replicable in cross validation analyses.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Voraussetzungen für die erfolgreiche Nutzung von agilen Methoden und agiler Führung im Schulkontext(Springer, 2022) Hudecek, Matthias; Fischer, Julia; Stricker, Tobias04A - Beitrag SammelbandPublikation Die Nutzung von KI in Unternehmen aus Sicht der Selbstbestimmungstheorie(Springer, 2020) Hudecek, Matthias; Mc Auley, Steven; Buchkremer, Rüdiger; Heupel, Thomas; Koch, Oliver04A - Beitrag Sammelband
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