M. Sc. - Psychology
Since October 2018, Katharina Pflügner has been a research associate at the Department of Information Systems and Services. She studied Psychology at the Universities of Regensburg and Bamberg and spent one semester abroad at Murray State University, USA. In the course of work experience, e. g. at KMPG AG, Deutsche Lufthansa AG and BF/M-Bayreuth, she has primarily been working in the field of personnel development and health care management.
Her main research interest lies in the area of the individual use of digital technologies and resulting health-relevant aspects (e. g. technostress and addiction to technology in work and private life).
Selected Publications
Pflügner, K., Maier, C., Hielscher, M., and Weitzel, T. (2021)
Online Stress Management Interventions: The Role of Application Features
Proceedings of the 42nd International Conference on Information Systems (ICIS), Austin, Texas, USA
View AbstractOnline stress management applications have the potential to reduce chronic stress, depression, cardiovascular diseases, and other severe mental and physical health problems. Basing on the clinical effectiveness of these applications and the relevance of user satisfaction for the success of information systems, we take a user perspective and investigate the role of application features for the satisfaction of potential users with such applications. We identify that there are 44 application features and reveal that these can be classified into different categories, depending on how they bring about satisfaction or dissatisfaction with the application. We show how each application feature influences potential user satisfaction and highlight that the influence can be linear, but also asymmetrical and non-existent. Based on the results, we derive recommendations for the development of online stress management applications and contribute that the complex relationship between application features and user satisfaction requires a feature- and context-specific investigation.
Valta, M., Pflügner, K., and Maier, C. (2021)
Guiding Companies to Reduce Technostress: A Mixed-Methods Study Deriving Practice-Oriented Recommendations
Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS)
View AbstractTechnostress is a major challenge for employees using information technology. Technostress research has revealed the causes, i.e. techno-stressors, and resulting adverse consequences for employees and companies. However, there is a lack of practical insights guiding companies on how to reduce technostress. To offer such practical insights, we follow a mixed-methods approach. The qualitative study bases on eleven expert interviews and reveals seven measures that reduce technostress. We then elaborate on these interview results with a quantitative study of 110 employees. The quantitative results reveal the degree to which the seven measures are useful to reduce specific techno-stressors. Our results show that although there are measures used in practice, none reduces all different techno-stressors. We complement existent theoretical technostress research by offering practice-oriented recommendations on how to reduce technostress. Based on the illustration of which measures are useful for which techno-stressors, practitioners can choose the measures that best fits their needs.
Pflügner, K., Maier, C., and Weitzel, T. (2021)
The direct and indirect influence of mindfulness on techno-stressors and job burnout: A quantitative study of white-collar workers
Computers in Human Behavior (CHB) (115:4), , https://doi.org/10.1016/j.chb.2020.106566 (VHB-JOURQUAL 3 Rating: k.R.)
View AbstractThis study investigates how mindfulness at work influences white-collar workers’ technostress. Building on our understanding that perceived techno-stressors lead to job burnout, we apply the transactional model of stress and the model of mindfulness to understand to what degree mindfulness reduces the perception of techno-stressors and whether mindfulness mitigates the effect of perceived techno-stressors on job burnout. Our analysis of quantitative data collected in a survey of 134 white-collar workers who use information systems regularly at work confirms that mindfulness leads to lower levels of perceived techno-stressors, but does not also mitigate the effect of perceived techno-stressors on job burnout. The study contributes to technostress research by showing how mindfulness can help manage technostress but also by illustrating the boundaries of mindfulness in terms of technostress mitigation. We provide practical recommendations for applying our research results to develop technostress prevention measures and assess psychological risk factors at work.
Pflügner, K., Maier, C., Mattke, J., and Weitzel, T. (2021)
Personality Profiles that Put Users at Risk of Perceiving Technostress: A Qualitative Comparative Analysis with the Big Five Personality Traits
Business & Information Systems Engineering (BISE) (63:4), p.389-402, https://doi.org/10.1007/s12599-020-00668-7 (VHB-JOURQUAL 3 Rating: B)
View AbstractSome information systems research has considered that individual personality traits influence whether users feel stressed by information and communication technologies. Personality research suggests, however, that personality traits do not act individually, but interact interdependently to constitute a personality profile that guides individual perceptions and behavior. The study relies on the differential exposure-reactivity model to investigate which personality profiles of the Big Five personality traits predispose users to perceive techno-stressors. Using a questionnaire, data was collected from 221 users working in different organizations. That data was analyzed using fuzzy set Qualitative Comparative Analysis (fsQCA). Based on the results, six different personality profiles that predispose to perceive high techno-stressors are identified. By investigating personality traits in terms of profiles, it is shown that a high and a low level of a personality trait can influence the perception of techno-stressors. The results will allow users and practitioners to identify individuals who are at risk of perceiving techno-stressors based on their personality profile. The post-survey analysis offers starting points for the prevention of perceived techno-stressors and the related negative consequences for specific personality profiles.