Evangelische Hochschule Nürnberg
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The aim of this study was to investigate the impact of different coping styles on situational coping in everyday life situations and gender differences. An ecological momentary assessment study with the mobile health app TrackYourStress was conducted with 113 participants. The coping styles Positive Thinking, Active Stress Coping, Social Support, Support in Faith, and Alcohol and Cigarette Consumption of the Stress and Coping Inventory were measured at baseline. Situational coping was assessed by the question “How well can you cope with your momentary stress level” over 4 weeks. Multilevel models were conducted to test the effects of the coping styles on situational coping. Additionally, gender differences were evaluated. Positive Thinking (p = 0.03) and Active Stress Coping (p = 0.04) had significant positive impacts on situational coping in the total sample. For women, Social Support had a significant positive effect on situational coping (p = 0.046). For men, Active Stress Coping had a significant positive effect on situational coping (p = 0.001). Women had higher scores on the SCI scale Social Support than men (p = 0.007). These results suggest that different coping styles could be more effective in daily life for women than for men. Taking this into account, interventions tailored to users’ coping styles might lead to better coping outcomes than generalized interventions.
Employees of the public employment services (PES) are street-level bureaucrats who shape activation policy on the ground. This paper examines how PES staff use enhanced discretion in an innovation project carried out by the German Federal Employment Agency. Applying a bottom-up perspective, we reconstruct PES employees’ logic of action and the dilemmas they face in improving counselling and placement services. According to our findings, placement staff use enhanced discretion to promote more individualised support and an adequate matching of jobseekers and employers. The use of discretion is framed by organisational norms and reward mechanisms and by the current labour market situation. Our analyses are based on qualitative interviews and group discussions with placement staff.
Employees of the public employment services (PES) are street-level bureaucrats who shape activation policy on the ground. This paper examines how PES staff use enhanced discretion in an innovation project carried out by the German Federal Employment Agency. Applying a bottom-up perspective, we reconstruct PES employees’ logic of action and the dilemmas they face in improving counselling and placement services. According to our findings, placement staff use enhanced discretion to promote more individualised support and an adequate matching of jobseekers and employers. The use of discretion is framed by organisational norms and reward mechanisms and by the current labour market situation. Our analyses are based on qualitative interviews and group discussions with placement staff.
Corona Health
(2021)
Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.
Introduction: In emergency care, geriatric requirements and risks are often not taken sufficiently into account. In addition, there are neither evidence-based recommendations nor scientifically developed quality indicators (QI) for geriatric emergency care in German emergency departments. As part of the GeriQ-ED© research project, quality indicators for geriatric emergency medicine in Germany have been developed using the QUALIFY-instruments. Methods: Using a triangulation methodology, a) clinical experience-based quality aspects were identified and verified, b) research-based quality statements were formulated and assessed for relevance, and c) preliminary quality indicators were operationalized and evaluated in order to recommend a feasible set of final quality indicators. Results: Initially, 41 quality statements were identified and assessed as relevant. Sixty-seven QI (33 process, 29 structure and 5 outcome indicators) were extrapolated and operationalised. In order to facilitate implementation into daily practice, the following five quality statements were defined as the GeriQ-ED© TOP 5: screening for delirium, taking a full medications history including an assessment of the indications, education of geriatric knowledge and skills to emergency staff, screening for patients with geriatric needs, and identification of patients with risk of falls/ recurrent falls. Discussion: QIs are regarded as gold standard to measure, benchmark and improve emergency care. GeriQ-ED© QI focused on clinical experience- and research-based recommendations and describe for the first time a standard for geriatric emergency care in Germany. GeriQ-ED© TOP 5 should be implemented as a minimum standard in geriatric emergency care.
A longitudinal pilot study on stress-levels in the crowdsensing mHealth platform TrackYourStress
(2019)
Background: The mobile phone app, TrackYourStress (TYS), is a new crowdsensing mobile health platform for ecological momentary assessments of perceived stress levels.
Objective: In this pilot study, we aimed to investigate the time trend of stress levels while using TYS for the entire population being studied and whether the individuals’ perceived stress reactivity moderates stress level changes while using TYS.
Methods: Using TYS, stress levels were measured repeatedly with the 4-item version of the Perceived Stress Scale (PSS-4), and perceived stress reactivity was measured once with the Perceived Stress Reactivity Scale (PSRS). A total of 78 nonclinical participants, who provided 1 PSRS assessment and at least 4 repeated PSS-4 measurements, were included in this pilot study. Linear multilevel models were used to analyze the time trend of stress levels and interactions with perceived stress reactivity.
Results: Across the whole sample, stress levels did not change while using TYS (P=.83). Except for one subscale of the PSRS, interindividual differences in perceived stress reactivity did not influence the trajectories of stress levels. However, participants with higher scores on the PSRS subscale reactivity to failure showed a stronger increase of stress levels while using TYS than participants with lower scores (P=.04).
Conclusions: TYS tracks the stress levels in daily life, and most of the results showed that stress levels do not change while using TYS. Controlled trials are necessary to evaluate whether it is specifically TYS or any other influence that worsens the stress levels of participants with higher reactivity to failure.
Mobile apps are increasingly utilized to gather data for various healthcare aspects. Furthermore, mobile apps are used to administer interventions (e.g., breathing exercises)to individuals. In this context, mobile crowdsensing constitutes a technology, which is used to gather valuable medical databased on the power of the crowd and the offered computationalcapabilities of mobile devices. Notably, collecting data withmobile crowdsensing solutions has several advantages comparedto traditional assessment methods when gathering data overtime. For example, data is gathered with high ecological validity, since smartphones can be unobtrusively used in everyday life. Existing approaches have shown that based on these advantages new medical insights, for example, for the tinnitus disease, can be revealed. In the work at hand, data of a developed mHealth crowdsensing platform that assesses the stress level and fluctuations of the platform users in daily life was investigated. More specifically, data of 1797 daily measurements on GPS and stress-related data in 77 users were analyzed. Using this data source, machine learning algorithms have been applied with the goalto predict stress-related parameters based on the GPS data of the platform users. Results show that predictions become possible that (1) enable meaningful interpretations as well as (2) indicate the directions for further investigations. In essence, the findings revealed first insights into the stress situation of individuals over time in order to improve their quality of life. Altogether, the work at hand shows that mobile crowdsensing can be valuably utilized in the context of stress on one hand. On the other, machine learning algorithms are able to utilize geospatial data of stress measurements that was gathered by a crowdsensing platform with the goal to improve the quality of life of its participating crowd users.
Mobile apps are increasingly utilized to gather data for various healthcare aspects. Furthermore, mobile apps are used to administer interventions (e.g., breathing exercises) to individuals. In this context, mobile crowdsensing constitutes a technology, which is used to gather valuable medical data based on the power of the crowd and the offered computational capabilities of mobile devices. Notably, collecting data with mobile crowdsensing solutions has several advantages compared to traditional assessment methods when gathering data over time. For example, data is gathered with high ecological validity, since smartphones can be unobtrusively used in everyday life. Existing approaches have shown that based on these advantages new medical insights, for example, for the tinnitus disease, can be revealed. In the work at hand, data of a developed mHealth crowdsensing platform that assesses the stress level and fluctuations of the platform users in daily life was investigated. More specifically, data of 1797 daily measurements on GPS and stress-related data in 77 users were analyzed. Using this data source, machine learning algorithms have been applied with the goal to predict stress-related parameters based on the GPS data of the platform users. Results show that predictions become possible that (1) enable meaningful interpretations as well as (2) indicate the directions for further investigations. In essence, the findings revealed first insights into the stress situation of individuals over time in order to improve their quality of life. Altogether, the work at hand shows that mobile crowdsensing can be valuably utilized in the context of stress on one hand. On the other, machine learning algorithms are able to utilize geospatial data of stress measurements that was gathered by a crowdsensing platform with the goal to improve the quality of life of its participating crowd users.
Stem cell research has been a problematic endeavour. For the past twenty years it has attracted moral controversies in both the public and the professional sphere. The research involves not only laboratories, clinics and people, but ethics, industries, jurisprudence, and markets. Today it contributes to the development of new therapies and affects increasingly many social arenas. The matrix approach introduced in this book offers a new understanding of this science in its relation to society. The contributions are multidisciplinary and intersectional, illustrating how agency and influence between science and society go both ways.
Conceptually, this volume presents a situated and reflexive approach for philosophy and sociology of the life sciences. The practices that are part of stem cell research are dispersed, and the concepts that tie them together are tenuous; there are persistent problems with the validation of findings, and the ontology of the stem cell is elusive. The array of applications shapes a growing bioeconomy that is dependent on patient donations of tissues and embryos, consumers, and industrial support. In this volume it is argued that this research now denotes not a specific field but a flexible web of intersecting practices, discourses, and agencies. To capture significant parts of this complex reality, this book presents recent findings from researchers, who have studied in-depth aspects of this matrix of stem cell research.
This volume presents state-of-the-art examinations from senior and junior scholars in disciplines from humanities and laboratory research to various social sciences, highlighting particular normative and epistemological intersections. The book will appeal to scholars as well as wider audiences interested in developments in life science and society interactions. The novel matrix approach and the accessible case studies make this an excellent resource for science and society courses.