Evangelische Hochschule Nürnberg
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Background Health information systems have developed rapidly and considerably during the last decades, taking advantage of many new technologies. Robots used in operating theaters represent an exceptional example of this trend. Yet, the more these systems are designed to act autonomously and intelligently, the more complex and ethical questions arise about serious implications of how future hybrid clinical team–machine interactions ought to be envisioned, in situations where actions and their decision-making are continuously shared between humans and machines.
Objectives To discuss the many different viewpoints—from surgery, robotics, medical informatics, law, and ethics—that the challenges of novel team–machine interactions raise, together with potential consequences for health information systems, in particular on how to adequately consider what hybrid actions can be specified, and in which sense these do imply a sharing of autonomous decisions between (teams of) humans and machines, with robotic systems in operating theaters as an example.
Results Team–machine interaction and hybrid action of humans and intelligent machines, as is now becoming feasible, will lead to fundamental changes in a wide range of applications, not only in the context of robotic systems in surgical operating theaters. Collaboration of surgical teams in operating theaters as well as the roles, competencies, and responsibilities of humans (health care professionals) and machines (robotic systems) need to be reconsidered. Hospital information systems will in future not only have humans as users, but also provide the ground for actions of intelligent machines.
Conclusions The expected significant changes in the relationship of humans and machines can only be appropriately analyzed and considered by inter- and multidisciplinary collaboration. Fundamentally new approaches are needed to construct the reasonable concepts surrounding hybrid action that will take into account the ascription of responsibility to the radically different types of human versus nonhuman intelligent agents involved.
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.
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.
Following Michael Lipsky's well‐known argument that policy is made in the daily encounters between street‐level bureaucracy and citizens, a growing body of research emphasizes that actors and organizations delivering social and labor‐market policy play a crucial role in welfare‐state politics. Using qualitative data collected at three local employment agencies in Germany, this article explores worker‐client relations as a crucial mechanism through which activation policies are translated into practice. The analysis investigates how caseworkers define their role and their relationships with clients. The findings show that it is essential for caseworkers to achieve client compliance. In such a context, building relationships of trust is a strategic instrument in overcoming possible barriers to co‐operation in the caseworker‐client interaction. Caseworkers develop strategies to create the impression of trustworthiness and to motivate both unemployed clients and employers to become trust‐givers in the caseworker‐client relation. While research has often stressed the dichotomy between disciplining and enabling elements of activation policies, our explorative study shows that persuasion and trust‐building are a further important dimension of the frontline delivery of activation policies. These strategies reflect the importance of emotional aspects of frontline work.
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.
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.
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.