sential roles in my academic journey while completing my Ph.D. dissertation. Their support, mentorship, and presence have been invaluable, and I am deeply appreciative. I must begin by acknowledging the support of my family: Edalat, Parivash, and Milad. Their belief in my aspirations and constant encouragement has strengthened me throughout this demanding journey.I am profoundly grateful to my distinguished Ph.D. committee, particularly Professor Friedhelm Schwenker, to whom I owe special thanks for his mentorship.

In our modern industrial society the group of the older (generation 65+) is constantly growing. Many subjects of this group are severely affected by their health and are suffering from disability and pain. The problem with chronic illness and pain is that it lowers the patient's quality of life, and therefore accurate pain assessment is needed to facilitate effective pain management and treatment. In the future, automatic pain monitoring may enable health care professionals to assess and manage pain in a more and more objective way. To this end, the goal of our SenseEmotion project is to develop automatic painand emotion-recognition systems for successful assessment and effective personalized management of pain, particularly for the generation 65+. In this paper the recently created SenseEmotion Database for pain-vs. emotion-recognition is presented. Data of 45 healthy subjects is collected to this database. For each subject approximately 30 min of multimodal sensory data has been recorded. For a comprehensive understanding of pain and affect three rather different modalities of data are included in this study: biopotentials, camera images of the facial region, and, for the first time, audio signals. Heat stimulation is applied to elicit pain, and affective image stimuli accompanied by sound stimuli are used for the elicitation of emotional states.

Background: Nurses are facing unprecedented amounts of pressure because of the ongoing global health challenges. Improving nurses' resilience to job-related stress and enhancing their strategies to cope effectively with stressors are key issues facing many health care institutions during the COVID-19 pandemic. This literature review aimed to: a) provide a thorough overview of individual-level interventions for stress management among nurses, b) identify measurement tools utilized to evaluate nurses' stress level, and c) provide the best evidence-based recommendations for future research and practice adapted to the current restrictions.Design: Systematic review.Data Sources: Studies published between January 2000 and October 2020 were retrieved from the following sources: EBSCOhost, Dortmund University Library, PubMed, Medline, Google Scholar, Applied Nursing Research, and reference lists from relevant articles.Review methods: Individual-level interventions with a control group or a placebo intervention were included in the final sample. Primary outcome was defined as a change in individual stress level or stress symptoms which were measured by objective or subjective instruments with evidence of validity. Articles published in English or German were included in the present review.Results: In total, 27 relevant studies were included into the current review. There are some indications that technology-delivered interventions with relaxation and stress management interventions comprising cognitive-behavioral components might be effective in decreasing stress among nurses and improving their well-being. Furthermore, although there were some attempts to collect objectively measured parameters for assessing the primary outcome of stress, the majority of the interventions utilized self-reported stress scales.Conclusion: A wide range of interventions are available for nurses. However, it is of utmost importance to develop and implement stress management programs that are conveniently accessible in the workplace and above all, meet the current restrictions for minimizing human contacts. To this end, innovative interventions delivered through digital technology, such as virtual reality, seem to be a promising solution for combating the detrimental impact of stress on nurses. Special attention should be also paid to applying standardized objective measurement tools to allow the assessment of sensitive physiological indices and the generalizability of scientific knowledge.

The rapid changes in human contacts due to the COVID-19 crisis have not only posed a huge burden on the population’s health but may have also increased the demand for evidence-based psychological programs delivered through digital technology. A systematic review, following the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)” guidelines, was therefore conducted to explore the advances in stress management interventions utilizing VR and suggest up-to-date directions for future practice. The relevant literature was screened and the search resulted in 22,312 records, of which 16 studies were considered for analysis. The Methodological Index for Non-Randomized Studies (MINORS) was also employed to assess the quality of the included studies. The results suggest that VR-based interventions can facilitate positive changes in subjective stress levels and stress-related biomarkers. However, special attention should be paid to the development of rigorous VR protocols that embrace natural elements and concepts deriving from traditional treatment approaches, such as cognitive behavioral therapy techniques. Overall, this review aims to empower future researchers to grasp the opportunity that the COVID-19 pandemic generated and utilize digital technologies for strengthening individuals’ mental health. Future projects need to conduct large-scale VR studies to evaluate their effectiveness compared to other mental health interventions.

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