Doctoral students at the Chair of Digital Public Health

Andrea Dietrich

Contact: Andrea.Dietrich@uni-bielefeld.de

PhD topic: eHealth in the care environment: socio-technical evaluation of a digital strategy for violence prevention

Short description: Violence in care is a serious, often tabooed problem that affects care professionals, caregiving relatives and those in need of care alike. Despite its high relevance, there is a lack of evidence regarding effective prevention approaches and suitable evaluation instruments. Against this background, the doctoral project in cooperation with the NRW Chamber of Nursing is supporting the development of a digital information portal on violence prevention. The focus is on the analysis of needs and prerequisites for use as well as the investigation of effectiveness and feasibility. A mixed-methods approach is being pursued, which includes the curation of evidence-based content, qualitative analyses and piloting. In addition, a measurement tool for violence-related health literacy will be developed. The results are intended to derive transferable quality criteria for digital prevention strategies in the healthcare sector. The potential of AI-based language models for dynamic evidence management and user-adaptive information transfer will also be explored.

Jessica Hafner

Contact: jessica.hafner@uni-bielefeld.de

PhD topic: Digital health applications for mild to moderate depression

Short description: Depressive disorders are widespread worldwide and are among the most common widespread diseases. Due to the frequency and high disease burden of depressive disorders, enormous impairments result on an individual and societal level. Digital health technologies have great potential to reduce access barriers and support care structures. The development of digitally supported care concepts in the context of mental illness is experiencing remarkable momentum both nationally and internationally. Against this background, the overarching objective of the research project is to investigate the acceptance of digital health technologies among people with mild to moderate depression. The central research interest is the identification of factors that promote and inhibit acceptance. In this way, possible reasons for use or non-use can be determined and implications for the successful and sustainable implementation of digital health technologies can be discussed. The research project focuses on the perspectives of the heterogeneous groups of stakeholders on an equal footing with the recording of the healthcare implications of digital innovations. The findings obtained provide an important orientation of the individual expectations and requirements as well as problem perceptions of the stakeholder groups with regard to digital health technologies in mild to moderate depression.

Alexander Hochmuth

Contact: A.Hochmuth@hs-osnabrueck.de

PhD topic: Theory-based evaluation of pilot services in maternity clinics

Short description: The research project focuses on the development of a program theory in the context of a theory-based evaluation of the implementation of digitally supported pilot support in maternity clinics. The study aims to visualize and understand the assumptions about the impact of this digital support. Various questions are examined, including the theoretical basis of digital care interventions, forms of digital support for families by pilots, and organizational, structural and contextual prerequisites for the success of such an intervention. The methodology applied is based on theory-driven evaluation and realist methodology approaches. Data collection and analysis are carried out using qualitative methods of empirical social research. This research project contributes to understanding the assumptions about the impact and conditions for the integration of digital health technologies in maternity hospital pilot services and provides impetus for improved care for families in this sensitive phase.

Carolin Huperz

Contact: Carolin.Huperz@klinikumbielefeld.de

PhD topic: Participatory development of a digital health technology for diabetes care

Short description: Digital health technologies are becoming increasingly important in the care of chronically ill people. Especially in diabetes care, digital solutions such as glucose monitoring systems, mobile apps or hybrid interaction systems offer the potential to improve self-management and make care processes more efficient. Despite these opportunities, long-term use often falls short of expectations. Against this background, the doctoral project aims to develop a digital health technology for diabetes care in a participatory manner. The focus is on the systematic involvement of patients with diabetes mellitus and medical service providers in the development process. Needs, challenges and implementation options are identified with special consideration of ethical, legal and social implications (ELSI). A mixed-methods approach is being pursued, consisting of a scoping review, quantitative and qualitative surveys, focus group interviews and a participatory future workshop. The results provide practice-relevant findings on user-centered technology development and contribute to improved acceptance, everyday integration and sustainable implementation of digital solutions in diabetes care.

Svenja Reisinger

contact: Svenja.Reisinger@dakks.de

PhD topic: Problems of risk-adjusted conformity assessment of AI systems

Abstract: Artificial intelligence (AI) has become an integral part of medical care in recent years. AI systems are now able to support complex tasks such as the diagnosis of diseases, the prognosis of treatment outcomes and automated decision-making processes. Given the implications for human life, it is crucial that these systems are regulated. In the context of the current functional-risk-adjusted systematization of regulatory requirements for AI systems in medical care, the doctoral project examines the suitability of the classical risk approach for establishing adequate safety of these systems. In addition, challenges arising from the complexity and predictability of neural networks are analyzed. An integrative methodological approach is used to gain insights into the development of an application-oriented framework for the functional risk-adjusted classification and implementation of AI systems. Practice-relevant recommendations are formulated that contribute to ensuring patient safety, promote the effectiveness and sustainability of the integration of AI systems into medical care and serve as a basis for political and regulatory decision-making processes.

Claudia Schlüfter

contact: Claudia.Schluefter@isi.fraunhofer.de

PhD topic: Digital transitions in the healthcare system

Short description: Digital innovations are complex and their transfer into healthcare is associated with challenges. An in-depth analysis of transition processes can contribute to a better understanding of innovation processes in the healthcare system. To this end, the mechanisms of technological transition processes and changes in users, regulation, stakeholder networks, infrastructure and cultural factors will be examined and the extent to which these can serve as a model for guided transformations will be investigated. The aim of the research project is to understand the targeted transformation from an analog to a digital system using the example of the development of the cancer advice app. The interactions between the micro, meso and macro levels are analyzed in order to derive success and hindrance factors for the digital transformation. Socio-ethical aspects as well as acceptance and impact relationships in the co-creative development process of an app are taken into account. The relevance and explanatory power of the insights gained from theoretical transition approaches are evaluated in order to derive implications for the digital transformation of the healthcare system.

Susanne Stampa

Contact: Susanne.Stampa@student.uni-siegen.de

PhD topic: Implementation conditions of digitally supported services in rehabilitation

Short description: Digitally supported services are becoming increasingly important in medical rehabilitation and rehabilitation aftercare. The COVID-19 pandemic in particular had a catalytic effect on digitalization in the rehabilitation sector. New digital services were often implemented in facilities at short notice and (initially) for a limited period of time. Accordingly, little is known about the implementation processes. The aim of the research project is to conduct a nationwide inventory of digitally supported services in medical rehabilitation and rehabilitation aftercare and to identify factors that promote and hinder their implementation. This will take into account the acceptance of technology on the part of the rehabilitants. Quantitative surveys and problem-centered interviews are used to shed light on experiences, implementation conditions and acceptance of the services. The results provide indications of aspects that should be taken into account when implementing these services and can serve as support for the facilities in digitization projects.

Lea Stark-Blomeier

Contact: lea.stark-blomeier@uni-siegen.de

PhD topic: Modeling competencies in telerehabilitation: Competence development in digital rehabilitation aftercare in Germany

Abstract: Digital service provision in rehabilitation - also known as telerehabilitation - promises a more efficient use of limited financial and human resources while maintaining the same quality of care due to its independence of time and place. However, the use of digital programs also entails new requirements for users. So far, it is unclear which skills are required for successful use and how these are developed among patients and therapists. Against this background, the dissertation project aims to develop a competency model in the context of digital rehabilitation aftercare in Germany. Using a mixed-methods approach, relevant competencies are identified and systematized, existing training needs are determined and requirements for the design of training courses are identified. The results will help rehabilitation facilities and decision-makers to optimally prepare therapists and patients and can support the successful use of telerehabilitation in the future.

Pinar Tokgöz

contact: Pinar.Tokgoez@uni-siegen.de

PhD topic: Determinants for the implementation of AI-based decision support systems for antibiotic therapy in hospitals

Short description: Antibiotic resistance is a global challenge. The development of resistance is facilitated primarily by inadequate antibiotic prescribing practices. Decision support systems (EUS) based on artificial intelligence (AI) can help with rapid prescription decisions. The user-oriented integration of AI-based EUS into everyday clinical practice is necessary for sustainable use. Against this background, the project aims to identify organizational and procedural determinants of conditions that promote and inhibit implementation. It examines how AI-based EUS can be implemented in healthcare practice under everyday conditions, which organizational and contextual factors influence its use and how acceptance among service providers can be optimized. For this purpose, a mixed-method approach is used, which aims at a successful transfer of innovation and benefits into healthcare practice.