The demographic shift marks the beginning of a social transformation with far reaching implications, and differences in aging processes across individuals render one-size fits-all policies ineffective. An area of increasing importance is assistive technology, including physical and Social Assistance Robots (SARs) for elderly support. In order to increase the effectiveness of such technologies, their design, functionality, and acceptance by target users must be evaluated. This paper presents a study that examines SAR technology acceptance among the future elderly (aged 20–60) in a German-speaking population (N=188). In doing this, we investigated the relationships between personality, resilience, technology experience, expectations for technology, fulfilment of expectations for technology, and technology acceptance. The study found significant correlations between age, gender, education, personality, resilience, experience, expectations, and technology acceptance and its subdimensions. Of the personality dimensions, agreeableness and neuroticism were found most relevant. Small effects were found between resilience and acceptance, and highly significant ones between technology acceptance, technology experience, expectations for SARs, and fulfilment of expectations for SARs. In keeping with previous research, the findings suggest that personality plays a significant role in the acceptance of SAR technologies. This study may be one of the first that considers and evaluates resilience as a factor in technology acceptance.

Background: Self-management and healthy habits (long-term health-related behaviors) are life-long requirements for the prevention of chronic back pain. Adherence to health interventions is often low because of the target groups' lack of interest. Electronic health (e-Health) information offers an opportunity to solve this issue, but many e-Health interventions are of poor quality. This study explores factors in the effectiveness of e-Health interventions and health-related behavioral changes and, thus, is among the first to develop a theoretical basis for e-Health programs. Materials and Methods: An online survey was conducted among the target groups of primary and secondary health programs promoting the management of possibly chronic back pain in Germany and Austria ( N  = 224). Measurements of e-Health literacy (eHL), self-efficacy, organized physical exercise, and the patients' social and mental balance were applied in all cases. Participants were categorized into dichotomous subgroups regarding the severity of their back pain. In addition to several significance tests, a correlation analysis and mediation analysis were both performed using PROCESS version 2.0 for SPSS. Results: It was observed in the nonrisk group that self-efficacy has a mediation effect on the connection between eHL and healthy habits. Significant correlations between eHL and self-efficacy in both groups revealed associations between the major driving forces of healthy habits. Conclusion: In keeping with previous research, the findings suggest that a high level of self-efficacy plays a significant role in correctly performing e-Health interventions. Nevertheless, further research should identify the effects of online social surroundings on eHL and self-efficacy in detail.

Innovation has been regarded as the crucial driving force for competitiveness. Recently, new approaches to innovation have transformed the innovation activities of firms. Open innovation, for instance, has emphasized the role of external partners in increasing innovation performance and competitiveness. In this analysis we link the implementation of open innovation practices to the competitive environment of the firm. We use a comprehensive firm level dataset for firms in 30 countries in Eastern Europe and Central Asia. We find that innovation activities are significantly affected by the competitive environment of the firm. The competitive intensity exerts an inverse u-shaped effect on innovation activities. For the implementation of open innovation practices we do not find significant effects exerted by the competitive environment. Rather, we see that it is international ownership linkages that facilitate the diffusion and implementation of open innovation practices in firms in Eastern Europe and Central Asia.

While self-reported Coronavirus Disease 2019 (COVID-19) symptom checklists have been extensively used during the pandemic, they have not been sufficiently validated from a psychometric perspective. We, therefore, used advanced psychometric modelling to explore the construct validity and internal consistency of an online self-reported COVID-19 symptom checklist and suggested adaptations where necessary. Fit to the Rasch model was examined in a sample of 1638 Austrian citizens who completed the checklist on up to 20 days during a lockdown. The items’ fatigue’, ‘headache’ and ‘sneezing’ had the highest likelihood to be affirmed. The longitudinal application of the symptom checklist increased the fit to the Rasch model. The item ‘cough’ showed a significant misfit to the fundamental measurement model and an additional dependency to ‘dry cough/no sputum production’. Several personal factors, such as gender, age group, educational status, COVID-19 test status, comorbidities, immunosuppressive medication, pregnancy and pollen allergy led to systematic differences in the patterns of how symptoms were affirmed. Raw scores’ adjustments ranged from ±0.01 to ±0.25 on the metric scales (0 to 10). Except for some basic adaptations that increases the scale’s construct validity and internal consistency, the present analysis supports the combination of items. More accurate item wordings co-created with laypersons would lead to a common understanding of what is meant by a specific symptom. Adjustments for personal factors and comorbidities would allow for better clinical interpretations of self-reported symptom data.