 Designing Preventive AI-Based Behaviour Change Support Systems: A Nascent Design Theory Based on the Case of Blood DonationHelena Monika Müller Publications of Darmstadt Technical University, Institute for Business Studies (BWL) from Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL) Abstract: In light of pressing societal challenges such as the global rise of chronic diseases and educational deficits, the need for effective, scalable and cost-efficient preventive interventions has received growing attention. Through their potential to intervene in a personalised way, preventive artificial intelligence (AI)-based behaviour change support systems (BCSS) represent a promising approach to address these issues. However, most BCSS fail to achieve sustainable behavioural transformation due to a lack of theoretical grounding, contextual sensitivity and user-centred design. Against this backdrop, this cumulative dissertation investigates how preventive AI-based BCSS can be effectively designed to induce and sustain behaviour change across the two application domains education and healthcare as well as diverse user populations. By applying the design science research (DSR) methodology, the dissertation develops and evaluates artefacts in the form of chatbots and smartphone applications across eight design cycles, with a primary focus on the healthcare domain and blood donation as a representative application context for preventive healthcare. The dissertation comprises two overarching DSR projects. The first project explores the design of learning behaviour change support systems and demonstrates how chatbot-based interventions can support students in higher education to self-regulate their learning process. The second, more comprehensive project focuses on the design of blood donation behaviour change support systems. Across seven iterative design cycles, a chatbot and chatbot-based smartphone application were developed and evaluated with diverse user groups from Germany, South Africa and Ghana. These artefacts embedded behaviour change strategies such as nudging, gamification as well as stage-matched guidance and were evaluated with blood service experts and (potential) blood donors as real end users. Empirical insights were generated on the effectiveness, user engagement and usability of the artefacts as well as on the influence of cultural factors on their perceived persuasiveness. In particular, the dissertation synthesises its design knowledge in a nascent design theory for blood donation behaviour change support systems, which includes generalisable design principles grounded in multi-level behavioural theories such as the self-determination theory, the theory of planned behaviour and the transtheoretical model. This nascent design theory generally provides a transferable conceptual foundation for the design of preventive health BCSS by structuring the design knowledge across different abstraction levels and highlighting how AI-based BCSS can be tailored to user needs to promote both intentional and developmental behavioural change. The eight underlying research papers address distinct yet interconnected questions. Paper A explores the design of learning behaviour change support systems and derives design principles for a chatbot to support students’ self-regulated learning. Papers B to H build iteratively on each other and focus on the design of blood donation behaviour change support systems. Papers B and E address the derivation and instantiation of design principles for blood donation chatbots. Papers F and G evaluate these design principles with potential end users, including a cross-cultural study. Papers C, D and H extend the scope to a chatbot-based blood donation app that integrates the chatbot functionalities with other persuasive design features such as gamification and social media. The final paper H with its conclusive field study consolidates the findings into the nascent design theory specifically for blood donation behaviour change support systems and more broadly applicable to preventive health behaviour change support systems. Taken together, this dissertation advances both theory and practice. From a theoretical perspective, it contributes to the DSR and information systems community by showing how multi-level behavioural theories can be operationalised to inform artefact design and how domain-specific knowledge can be systematically translated into actionable and transferable prescriptive design knowledge adaptable to specific cultures and contexts. From a practical perspective, it offers guidance to designers and developers on how to build accessible and effective preventive interventions that foster individual behaviour change while simultaneously contributing to broader public goals. Overall, this dissertation lays the groundwork for the systematic design of preventive AI-based BCSS, with a particular emphasis on preventive health BCSS, and illustrates their relevance for influencing individual behaviour and societal outcomes alike. Date: 2026-06-05 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:dar:wpaper:161008 Access Statistics for this paper More papers in Publications of Darmstadt Technical University, Institute for Business Studies (BWL) from Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL) Contact information at EDIRC. |
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