Laura Schmidt

Predicting and Explaining Students' Stress with the Demand-Control Model: Does Neuroticism Also Matter?.

University students often report high stress levels, and studies even suggest a recent increase. However, there is a lack of theoretically based research on the structural conditions that influence students’ perceived stress. The current study compared the effects of Karasek’s demand–control dimensions with the influence of neuroticism to address environmental and individual characteristics related to stress. Two points of measurement were included: T1 in the middle of the term and T2 during the examination period. Participants were 146 psychology students at two German universities (Mage = 22.6 years). We applied an adapted version of Karasek’s Job Content Questionnaire, a self-developed stress scale, and the 21-item Big-Five-Inventory. At T1, both neuroticism and demands significantly predicted stress (total adjusted R² = .40), although relative weights analyses indicated that the contribution of demands was more pronounced (relative importance: 63%). Longitudinally, controlling for stress at T1, the demand–control dimensions explained additional variance in the increased stress level at T2, whereas neuroticism did not contribute additionally (R² = .52). Results indicate that self-reports on stress among university students are not only a reflection of underlying negative affectivity. We conclude that perceived stress can be explained by structural conditions rather than personality, providing opportunities to reduce stress among students.

Predictors of Performance in Everyday Technology Tasks in Older Adults With and Without Mild Cognitive Impairment

Background and Objectives The ability to use everyday technology has become a key competence for conducting activities of daily living, maintaining an autonomous life, as well as participating in society. However, studying this issue in older adults needs more attention, particularly among those with mild cognitive impairment (MCI). Research Design and Methods We assessed the performance of N = 80 older adults (M = 73 years) in a range of tasks representing important life domains, i.e., using a blood pressure monitor, a mobile phone, and an eBook reader. Thirty-nine participants had been diagnosed with MCI by experienced geropsychiatrists and 41 healthy controls were matched for age, sex, and education. Standardized observation based on video-recording and coding was combined with cognitive testing and assessment of social-cognitive variables (self-efficacy, perceived obsolescence, attitudes towards technology). Results Cognitively healthy participants outperformed those with MCI regarding completion time and errors. An interaction effect of device and study group indicated larger differences in completion time for tasks with multilayered interfaces. In hierarchical regression models, aggregated cognitive factors (fluid and memory component) predicted performance and interactions with education level emerged. Obsolescence, addressing a perceived lack of competence to cope with modern society, mediated the effect of cognitive status on performance, both regarding time (partial mediation, adj.R2 = 28%) and errors (full mediation, adj.R2 = 23%). Discussion and Implications Findings show that social-cognitive factors contribute to differences in performance on everyday technology tasks in addition to cognitive abilities. Training programs may profit from considering respective individual resources or limitations in the cognitive, personality-related or emotional-motivational domain.

Technology and Ageing: Potential for European Societies

The issue of aging and technology has been and remains to be a key issue in European aging research as well as in major European funding schemes such as the Framework Programs (see the issue of “Ambient Assisted Living/AAL” in particular). In this chapter, we address the various roles which technology may take over in order to serve the quality of life and autonomy of older adults. To achieve this goal, we compile the evidence gathered in the respective European as well as the Asian and North American research communities and examine synergies, complementarities and existing research and implementation gaps. In order to illustrate, we also draw from our own research, such as research projects targeting the role of technology in long-term institutions, the potential and constraints of technology for cognitively impaired older adults, and the role of technology acceptance in general for aging well. This chapter concludes that technology can be seen as a major context able to infuse development in old age and closes with future research challenges.