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Auflistung BISE 66(3) - Juni 2024 nach Titel
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- ZeitschriftenartikelDesigning Behavior Change Support Systems Targeting Blood Donation Behavior(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Müller, Helena M.; Reuter-Oppermann, MelanieWhile blood is crucial for many surgeries and patient treatments worldwide, it cannot be produced artificially. Fulfilling the demand for blood products on average days is already a major challenge in countries like South Africa and Ghana. In these countries, less than 1 % of the population donates blood and most of the donations come from first-time donors who do not return. Sufficient new, first-time and even lapsed donors must be motivated to donate regularly. This study argues that blood donation behavior change support systems (BDBCSS) can be beneficially applied to support blood donor management in African countries. In this study, the design science research (DSR) approach is applied in order to derive generic design principles for BDBCSS and instantiate the design knowledge in prototypes for a blood donation app and a chatbot. The design principles were evaluated in a field study in South Africa. The results demonstrate the positive effects of BDBCSS on users’ intentional and developmental blood donation behavior. This study contributes to research and practice by proposing a new conceptualization of blood donation information systems support and a nascent design theory for BDBCSS that builds on behavioral theories as well as related work on blood donation information systems. Thus, the study provides valuable implications for designing preventive health BCSS by stating three design principles for a concrete application context in healthcare.
- ZeitschriftenartikelDesigning Virtual Coaching Solutions(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Schlieter, Hannes; Gand, Kai; Weimann, Thure Georg; Sandner, Emanuel; Kreiner, Karl; Thoma, Steffen; Liu, Jin; Caprino, Massimo; Corbo, Massimo; Seregni, Agnese; Tropea, Peppino; Pino, Rocio; Gómez Esteban, Juan Carlos; Gabilondo, Inigo; Lacraru, Andreea Elena; Busnatu, Stefan SebastianEspecially older persons are prone to disabilities and chronic diseases. These chronic conditions pose a worldwide challenge, leading to deteriorating health, economic strain, loss of life, and a decline in the quality of life (QoL). Therefore, healthcare institutions seek to enhance their strategies for disease prevention and management to uphold the well-being of the community. This leads to the need to regain independence and improve QoL to properly rehabilitate the patients. Virtual Coaches (VCs) in the form of Embodied Conversational Agents are seen as a relevant digital intervention to support the continuity of care. The paper at hand reports on a Design Science Research project about implementing a VC solution to support older patients' home rehabilitation. The study underpins four pivotal design principles: Adaptivity, Coaching Strategy, Multi-user Interface, and Sustainable Infrastructure. The final artifact was tested with 80 patients which were supported in continuing their inpatient rehabilitation at home by using a VC. The evaluation shows both positive results for usability and acceptance of the intervention for four different use cases and a positive impact on the QoL. Given the comprehensive clinical evaluation, the system represents a safe and appealing solution for ensuring the continuity of medical rehabilitation care and the access to personalized cognitive and motor function treatments.
- ZeitschriftenartikelDigital Surveillance in Organizations(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Grisold, Thomas; Seidel, Stefan; Heck, Markus; Berente, Nicholas
- ZeitschriftenartikelHow are We Doing Today? Using Natural Speech Analysis to Assess Older Adults’ Subjective Well-Being(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Finze, Nikola; Jechle, Deinera; Faußer, Stefan; Gewald, HeikoThe research presents the development and test of a machine learning (ML) model to assess the subjective well-being of older adults based solely on natural speech. The use of such technologies can have a positive impact on healthcare delivery: the proposed ML model is patient-centric and securely uses user-generated data to provide sustainable value not only in the healthcare context but also to address the global challenge of demographic change, especially with respect to healthy aging. The developed model unobtrusively analyzes the vocal characteristics of older adults by utilizing natural language processing but without using speech recognition capabilities and adhering to the highest privacy standards. It is based on theories of subjective well-being, acoustic phonetics, and prosodic theories. The ML models were trained with voice data from volunteer participants and calibrated through the World Health Organization Quality of Life Questionnaire (WHOQOL), a widely accepted tool for assessing the subjective well-being of human beings. Using WHOQOL scores as a proxy, the developed model provides accurate numerical estimates of individuals’ subjective well-being. Different models were tested and compared. The regression model proves beneficial for detecting unexpected shifts in subjective well-being, whereas the support vector regression model performed best and achieved a mean absolute error of 10.90 with a standard deviation of 2.17. The results enhance the understanding of the subconscious information conveyed through natural speech. This offers multiple applications in healthcare and aging, as well as new ways to collect, analyze, and interpret self-reported user data. Practitioners can use these insights to develop a wealth of innovative products and services to help seniors maintain their independence longer, and physicians can gain much greater insight into changes in their patients’ subjective well-being.
- ZeitschriftenartikelHow Artificial Intelligence Challenges Tailorable Technology Design(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Fechner, Pascal; König, Fabian; Lockl, Jannik; Röglinger, MaximilianArtificial intelligence (AI) has significantly advanced healthcare and created unprecedented opportunities to enhance patient-centeredness and empowerment. This progress promotes individualized medicine, where treatment and care are tailored to each patient’s unique needs and characteristics. The Theory of Tailorable Technology Design has considerable potential to contribute to individualized medicine as it focuses on information systems (IS) that users can modify and redesign in the context of use. While the theory accounts for both the designer and user perspectives in the lifecycle of an IS, it does not reflect the inductive learning and autonomy of AI throughout the tailoring process. Therefore, this study posits the conjecture that current knowledge about tailorable technology design does not effectively account for IS that incorporate AI. To investigate this conjecture and challenge the Theory of Tailorable Technology Design, a revelatory design study of an AI-enabled individual IS in the domain of bladder monitoring is conducted. Based on the empirical evidence from the design study, the primary contribution of this work lies in three propositions for the design of tailorable technology, culminating in a Revised Theory of Tailorable Technology Design. As the outcome of the design study, the secondary contribution of this work is concrete design knowledge for AI-enabled individualized bladder monitoring systems that empower patients with neurogenic lower urinary tract dysfunction (NLUTD). Overall, this study highlights the value of AI for patient-centeredness in IS design.
- ZeitschriftenartikelInvestigating Innovation Diffusion in Gender-Specific Medicine: Insights from Social Network Analysis(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Baum, Katharina; Baumann, Annika; Batzel, KatharinaThe field of healthcare is characterized by constant innovation, with gender-specific medicine emerging as a new subfield that addresses sex and gender disparities in clinical manifestations, outcomes, treatment, and prevention of disease. Despite its importance, the adoption of gender-specific medicine remains understudied, posing potential risks to patient outcomes due to a lack of awareness of the topic. Building on the Innovation Decision Process Theory, this study examines the spread of information about gender-specific medicine in online networks. The study applies social network analysis to a Twitter dataset reflecting online discussions about the topic to gain insights into its adoption by health professionals and patients online. Results show that the network has a community structure with limited information exchange between sub-communities and that mainly medical experts dominate the discussion. The findings suggest that the adoption of gender-specific medicine might be in its early stages, focused on knowledge exchange. Understanding the diffusion of gender-specific medicine among medical professionals and patients may facilitate its adoption and ultimately improve health outcomes.
- ZeitschriftenartikelPrecision Digital Health(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Baird, Aaron; Xia, YusenAccounting for individual and situational heterogeneity (i.e., precision) is now an important area of research and treatment in the field of medicine. This essay argues that precision should also be embraced within digital health artifacts, such as by designing digital health apps to tailor recommendations to individual user characteristics, needs, and situations, rather than only providing generic advice. The challenge, however, is that not much guidance is available for embracing precision when designing or researching digital health artifacts. The paper suggests that a shift toward precision in digital health will require embracing heterogeneous treatment effects (HTEs), which are variations in the effectiveness of treatment, such as variations in effects for individuals of different ages. Embracing precision via HTEs is not trivial, however, and will require new approaches to the research and design of digital health artifacts. Thus, this essay seeks to not only define precision digital health, but also to offer suggestions as to where and how machine learning, deep learning, and artificial intelligence can be used to enhance the precision of interventions provisioned via digital health artifacts (e.g., personalized advice from mental health wellbeing apps). The study emphasizes the value of applying emerging causal ML methods and generative AI features within digital health artifacts toward the goal of increasing the effectiveness of digitially provisioned interventions.
- ZeitschriftenartikelReimagining Digital Health(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Sunyaev, Ali; Fürstenau, Daniel; Davidson, Elizabeth
- ZeitschriftenartikelTrust in Public and Private Providers of Health Apps and Usage Intentions(Business & Information Systems Engineering: Vol. 66, No. 3, 2024) Binzer, Björn; Kendziorra, Jennifer; Witte, Anne-Katrin; Winkler, Till J.Mobile health apps, particularly personal health records (PHRs), play a vital role in healthcare digitalization. However, the varying governance approaches for providing PHR platforms have led to a growing debate on the adequate regulation of health technology with regard to their adoption. This article investigates how provider governance, whether public or private, influences users’ intentions to use and decisions to download a PHR app. Drawing on institutional trust, privacy calculus, and privacy control frameworks, the study develops hypotheses about how provider governance affects the pathways through which trust influences users’ intentions to adopt the app. Data acquired from an online experiment in the German market reveals that users exhibit a higher level of trust in public providers compared to the same app provided by private companies. Furthermore, provider governance significantly alters the paths in how trust influences usage intentions through perceived benefits, perceived risks, and privacy control. These findings contribute to the development of a sectoral theory of privacy calculus and privacy control in Information Systems (IS). Moreover, they offer practical insights for healthcare regulators and health app providers with the aim of promoting the acceptance and usage of PHRs and other mobile health apps.