Lifestyle Medicine (LM) has demonstrated significant potential in reducing morbidity and mortality by addressing behavioural risk factors. However, its clinical application remains limited within the Dutch healthcare system, where clinicians face substantial barriers to integrating lifestyle counselling into routine practice. These challenges stem from time-constrained consultations (10-15 minutes) and inadequate systematic training in relevant skills and knowledge. Current training methods, including traditional workshops and online courses, lack either scalability or the ability to develop practical, hands-on competencies, creating an urgent need for innovative training solutions suitable for real-world hospital environments.

This graduation project, commissioned by Leiden University Medical Centre (LUMC), addressed the research question: "How can conversational agents be designed to train healthcare professionals in delivering lifestyle counselling within the 10–15 minute consultation time frame?" The study employed a comprehensive research methodology including literature review and two phases of user research to identify and reframe the core problem. The research revealed that the commonly cited "lack of time" barrier is actually a symptom of a deeper "professional capability gap," encompassing insufficient practical skills, low confidence, and inadequate LM awareness. Focused interviews with clinicians in hospitals further identified a "systemic support gap," characterised by a lack of structured workflows and integrated infrastructure.

Based on these findings, the study developed WellSaid, an AI-driven digital ecosystem designed to train and support clinicians in lifestyle counselling. The solution comprises three integrated components: Consultation Training featuring an AI conversational agent for role-play practice; a Lifestyle Toolkit providing practical resources and support materials; and a Library serving as a centralised hub for accessible, evidence-based information. Expert review by LUMC clinicians confirmed the prototype's desirability and conceptual feasibility, validating that AI-driven conversational training ecosystems can effectively address professional capability gaps. This project demonstrates that AI-based conversational training ecosystems can effectively equip healthcare professionals with practical skills, confidence, and systematic support necessary for integrating lifestyle counselling into routine hospital care, promoting broader LM adoption and supporting more preventive, patient-centered healthcare delivery.

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The main goal of this thesis is to create remote patient management (RPM) strategy to effectively involve patients’ families into e-health services, and promote the adoption and long-term adherence to lifestyle
modifications of entire families. By exploring the potential of family-centered care ideology for healthcare delivery, this thesis paves a way to include family members of myocardial infarction(MI) patients as co-recipients of formal care. To accomplish the objective, various activities were undertaken, such as researching factors that influence healthcare paradigms, exploring effective strategies to promote healthy behavior, and investigating the role of family members in shaping a patient’s health trajectory.

Through desk research and interviews with key-informants of cardiovascular and home based care, valuable insights were uncovered revealing the diverse roles family members can assume throughout a patient’s health journey. These roles were found to be dynamic and dependent on various factors including personal preferences and the stage in the health trajectory, highlighting the need for personalized healthcare approaches that cater to the unique preferences and dynamics of each family.

Uncovering a research gap of the representation of these roles, a new perspective recognizing the perpetual influential capacity of family members was adopted to further explore individuals preferences of in their ability to be involved in the patients healthcare and to influence the health behaviour of the patient. By adopting this approach, family members are encouraged to prioritize their own health while simultaneously providing support to patients in maintaining positive lifestyle behaviors essential for sustaining cardiovascular health.

Based on the insights gained from a qualitative study highlighting the differences in family contexts and subsequent preferences in health-oriented involvement, a service vision was formulated to demonstrate a family-centered healthcare delivery through a modular approach. The vision emphasized the importance of data-driven insights to inform tailored interventions for sustainable lifestyle adherence. By harnessing data, healthcare providers can gain valuable information about patients and family members, enabling them to tailor interventions and support structures to meet their specific needs.

To move closer to this service vision, it is proposed to follow a data-enabled design process that enables human, technological and organizational considerations and thereby empowering designers to iterate and expand the service ecosystem.

To conclude, this thesis creates an opportunity for engaging stakeholders and ensuring that the envisioned care approach aligns with the interconnected healthcare landscape, driving the system towards a more inclusive and comprehensive care future. ... Read more