IT Adoption, Diffusion, and Evaluation in Healthcare

Permanent URI for this collectionhttps://hdl.handle.net/10125/112480

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Now showing 1 - 8 of 8

Evaluating Persuasive Reminders and Suggestions in a Weight Management mHealth Intervention
(2026-01-06) Nabwire, Sharon; Savian Colvero De Oliveira, Renata; Merikallio, Heta; Savolainen, Markku; Hukkanen, Janne; Oinas-Kukkonen, Harri
The widespread use of mobile phones has created new mHealth opportunities that allow individuals to track and change their behavior. Designing engaging and practical behavior change support systems remains central to mHealth. Computer-human dialogue support features are recognized as effective in prompting compliance, enhancing desired habits, and changing attitudes, making them widely used in mHealth applications. Although these features may reinforce task completion and overall adherence to the intervention, their influence on maintaining compliance and related outcomes remains underexplored. We conducted an observational study (n = 79) to examine the role of reminders and suggestions in a weight management mobile intervention. High compliance rates with reminders and suggestions were observed in more than 70% of users. Task completion was linked to weight loss; however, the association between opening content and weight loss was reduced when overall app interaction was considered. These findings may inform the design of future mHealth interventions.
The Impact of Social Features and Application Design on User Behavior and Long-Term Engagement of Strava Users
(2026-01-06) Kuure, Oula; Kähkönen, Karri; Hekkala, Riitta
The growth of the health and fitness industry, simultaneously with the emergence of platform-based technology, has led to the incorporation of social features into fitness applications. This study uses the UTAUT2 framework as a theoretical lens to explore the ways in which Strava users interact with the social features embedded into the user experience, as well as how application design affects user engagement. Sixteen semi-structured interviews were conducted to obtain user insights into why and how application design and social features drive user behavior on Strava. Thematic analysis was used to analyze the data, and the findings show the role of application design in driving sustained long-term use. Furthermore, this research offers an adapted version of the UTAUT2 model that better suits the study of platform-based technology use in consumer contexts. This study also highlights the role of social sharing in positively impacting user motivation.
From Buzz to Blind Spots: Examining AI Readiness and AI Exploration Reality in German Statutory Health Insurances
(2026-01-06) Stöber, Anna-Luisa; Habicht, Hagen
This study investigates the expectations and preparedness of German statutory health insurance companies (SHIs) regarding the adoption of artificial intelligence (AI) as a driver of digital transformation in healthcare. Employing an exploratory survey of managers from 25 SHIs, the research examines strategic orientation, organizational readiness, and the operational reality of AI exploration. Findings reveal that SHIs widely recognize AI as a cross- sectional technology with substantial potential for improving efficiency and service quality, significant gaps persist in translating AI-related knowledge into innovative processes and products, and self- assessments of AI readiness tend to be overly optimistic compared to actual implementation progress. The study highlights the importance of strategic alignment and absorptive capacity for successful AI adoption, and identifies a particular weakness of SHIs to transform AI related knowledge into new processes and products.
Explainable AI: Characteristics, Intended and Unintended Consequences and Mitigation Strategies in Decision-Making in Healthcare
(2026-01-06) Kinde, Alehegn; Xu, Jingjun (David)
Integrating artificial intelligence (AI) systems in healthcare offers significant benefits for assisting human decision-making. However, understanding the decisions of black-box AI-driven medical systems is a significant challenge. This has spurred research in explainable AI (XAI), emphasizing how explanations can enhance comprehension and trust and ensure compliance with regulatory standards. Prior research on XAI mainly focused on developing algorithms for predictions, often overlooking their impact on humans. Instead, this paper identifies other XAI design characteristics influencing doctors’ (experts and juniors) decision-making processes and outcomes and proposes strategies to address unintended consequences in healthcare. Based on a literature review in healthcare, this paper develops a conceptual model with propositions. One of our findings shows that poorly designed XAI (incoherent and irrelevant) can cause harm, including deskilling doctors, making wrong decisions, and creating perceptions of unfairness. It also identifies future research areas for scholars and guides practitioners in designing the XAI system effectively.
Optimistic or Uncomfortable? Examining Privacy Perceptions of Immigrants Towards Blockchain-based Personal Health Record Adoption
(2026-01-06) Vanderkooi, Dane; Mashatan, Atefeh (Atty)
Personal medical health records (PHRs) have improved patient access and control over personal health information. However, adoption rates remain low due to barriers, including accessibility and privacy concerns. These challenges are further amplified among immigrants through digital divides. Solutions such as blockchain-based PHRs have been touted to alleviate challenges while providing agency to patients. Yet, implementing blockchain elicits novel privacy challenges. As such, this study explores immigrant adoption intentions towards blockchain-based PHR systems from a privacy perspective. An extended privacy calculus model is developed to include technology perceptions, optimism, discomfort, cultural dimensions, uncertainty avoidance and collectivism. The model was tested using cross-sectional survey data, which were analyzed using partial least squares structural equation modelling (PLS-SEM). The results support the majority of the model hypotheses. Technological optimism and uncertainty avoidance enhance perceived adoption benefits while discomfort raises privacy risks. Risks and benefits are then weighed against each other to determine adoption intentions.
Exploring Drivers of Technology Adoption in Public Healthcare through the TOE Lens
(2026-01-06) Svensson, Ann
This study seeks to contribute to a deeper understanding of the adoption of technological innovations within the public health sector. By examining the interplay between technological characteristics, organizational capacity, and environmental context, the research aims to uncover how and why public healthcare organizations adopt, or resist adopting, new technologies. The Technology-Organization-Environment framework is used to understand the determinants of innovation adoption. To gain an in-depth understanding of the context of public healthcare organizations, a multiple case study design was employed. The study concludes that technology adoption in public healthcare is shaped not only by technical performance but also by organizational structures, cultural norms, and institutional dynamics. Successful adoption requires clear governance, trust, collaboration, and alignment be-tween technological solutions and the needs and values of users.
Meeting Users’ Needs in National Health Information Infrastructures - Lessons from the Case of Germany
(2026-01-06) Hoevel, Gilbert; Rehmer, Torben; Trang, Simon
National health information infrastructures (HII) are critical for enabling interoperable and efficient healthcare delivery. However, many national initiatives struggle with misaligned stakeholder interests and unclear roles of regulators. This study investigates a national HII, which includes three important public health applications. Drawing on interviews, participatory observations, and regulatory documents, we examine how stakeholder dynamics and regulatory constraints shape the development process. While existing research has often described such cases, our study adopts a solution-oriented perspective. We derive three actionable recommendations to better align national HII with end-user needs, emphasizing balanced stakeholder involvement, user-centered design, and governance structures that promote healthcare delivery outcomes. Our findings contribute to the literature by extending empirical insights on national HII and offering guidance for governments and policymakers designing similar infrastructures in other countries.
Introduction to the Minitrack on IT Adoption, Diffusion, and Evaluation in Healthcare
(2026-01-06) Bozan, Karoly; Kamis, Arnold; Schmidt-Kraepelin, Manuel; Thiebes, Scott

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