@article{QiBruchKropetal.2021,
  author    = {Qi, Yanyan and Bruch, Dorothee and Krop, Philipp and Herrmann, Martin J. and Latoschik, Marc E. and Deckert, J{\"u}rgen and Hein, Grit},
  title     = {Social buffering of human fear is shaped by gender, social concern, and the presence of real vs virtual agents},
  series = {Translational Psychiatry},
  volume    = {11},
  journal   = {Translational Psychiatry},
  doi       = {10.1038/s41398-021-01761-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-265782},
  year      = {2021},
  abstract  = {The presence of a partner can attenuate physiological fear responses, a phenomenon known as social buffering. However, not all individuals are equally sociable. Here we investigated whether social buffering of fear is shaped by sensitivity to social anxiety (social concern) and whether these effects are different in females and males. We collected skin conductance responses (SCRs) and affect ratings of female and male participants when they experienced aversive and neutral sounds alone (alone treatment) or in the presence of an unknown person of the same gender (social treatment). Individual differences in social concern were assessed based on a well-established questionnaire. Our results showed that social concern had a stronger effect on social buffering in females than in males. The lower females scored on social concern, the stronger the SCRs reduction in the social compared to the alone treatment. The effect of social concern on social buffering of fear in females disappeared if participants were paired with a virtual agent instead of a real person. Together, these results showed that social buffering of human fear is shaped by gender and social concern. In females, the presence of virtual agents can buffer fear, irrespective of individual differences in social concern. These findings specify factors that shape the social modulation of human fear, and thus might be relevant for the treatment of anxiety disorders.},
  language  = {en}
}
@article{KerwagenFuchsUllrichetal.2023,
  author    = {Kerwagen, Fabian and Fuchs, Konrad F. and Ullrich, Melanie and Schulze, Andres and Straka, Samantha and Krop, Philipp and Latoschik, Marc E. and Gilbert, Fabian and Kunz, Andreas and Fette, Georg and St{\"o}rk, Stefan and Ertl, Maximilian},
  title     = {Usability of a mHealth solution using speech recognition for point-of-care diagnostic management},
  series = {Journal of Medical Systems},
  volume    = {47},
  journal   = {Journal of Medical Systems},
  number    = {1},
  doi       = {10.1007/s10916-022-01896-y},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324002},
  year      = {2023},
  abstract  = {The administrative burden for physicians in the hospital can affect the quality of patient care. The Service Center Medical Informatics (SMI) of the University Hospital W{\"u}rzburg developed and implemented the smartphone-based mobile application (MA) ukw.mobile1 that uses speech recognition for the point-of-care ordering of radiological examinations. The aim of this study was to examine the usability of the MA workflow for the point-of-care ordering of radiological examinations. All physicians at the Department of Trauma and Plastic Surgery at the University Hospital W{\"u}rzburg, Germany, were asked to participate in a survey including the short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and Use of Technology (UTAUT). For the analysis of the different domains of user experience (overall attractiveness, pragmatic quality and hedonic quality), we used a two-sided dependent sample t-test. For the determinants of the acceptance model, we employed regression analysis. Twenty-one of 30 physicians (mean age 34 ± 8 years, 62\% male) completed the questionnaire. Compared to the conventional desktop application (DA) workflow, the new MA workflow showed superior overall attractiveness (mean difference 2.15 ± 1.33), pragmatic quality (mean difference 1.90 ± 1.16), and hedonic quality (mean difference 2.41 ± 1.62; all p < .001). The user acceptance measured by the UTAUT (mean 4.49 ± 0.41; min. 1, max. 5) was also high. Performance expectancy (beta = 0.57, p = .02) and effort expectancy (beta = 0.36, p = .04) were identified as predictors of acceptance, the full predictive model explained 65.4\% of its variance. Point-of-care mHealth solutions using innovative technology such as speech-recognition seem to address the users' needs and to offer higher usability in comparison to conventional technology. Implementation of user-centered mHealth innovations might therefore help to facilitate physicians' daily work.},
  language  = {en}
}