How digital communication shapes nutrition priorities in obesity care: insights from AI-generated patient scenarios

Introduction
Obesity is a complex, multifactorial condition requiring sustained engagement with nutrition-related behaviours across the lifecycle. While digital communication tools are increasingly used to support scalable care (1,2), less is known about how they influence the interpretation and prioritisation of nutrition needs. In sensitive contexts such as obesity, where stigma and psychosocial factors are prominent, communication plays a critical role in shaping how care priorities are understood. This study aimed to examine how AI-generated video case study communication scenarios are interpreted by health professionals and members of the public in obesity and mental health care, with a focus on biopsychosocial care priorities, lifestyle-related content and perceived impact of AI-mediated communication.

Methods
A cross-sectional online survey incorporating a randomised case-based experiment was conducted (n=276; 93 health professionals, 183 public participants). Participants viewed one of four AI-generated video case studies depicting a patient presenting with obesity and psychological distress. Narrative content was standardised, while sociocultural characteristics, including age, gender, ethnicity, occupation, were varied. Participants ranked biopsychosocial care priorities and lifestyle-related content, including diet and physical activity, and evaluated the perceived impact of AI-mediated communication. Data were analysed using non-parametric and chi-square tests.

Results
Across both cohorts, psychological and lifestyle-related priorities were consistently ranked higher than biomedical interventions, indicating a shared biopsychosocial framing of obesity care in which nutrition is embedded within broader behavioural and emotional contexts. Health professionals placed greater emphasis on cultural and social factors (p=.016), while public participants prioritised diet-related content such as gut health (p=.001). Among public participants, prioritisation varied significantly across case studies despite identical narrative content, suggesting that sociocultural cues influence how nutrition needs are interpreted. Perceptions of AI-mediated communication were characterised by ambivalence rather than polarisation, with similar proportions reporting that AI would help, hinder, or have no impact. Concerns centred on loss of human interaction, miscommunication, and trust.

Conclusion
Findings suggest that nutrition priorities in obesity care are not fixed but are shaped by how patient narratives are communicated and contextualised. Standardised digital communication does not eliminate variability in interpretation, particularly where sociocultural context is salient. Trust in digital tools appears conditional and dependent on their ability to support relational, person-centred care. Optimising nutrition across the lifecycle requires approaches that recognise obesity as a context-dependent, biopsychosocial condition. Digital communication strategies should be designed to support interpretation, trust, and engagement, ensuring nutrition guidance is meaningful across diverse populations. These findings highlight that effective obesity interventions must move beyond information delivery to address how nutrition messages are interpreted in context. Designing digitally supported, relational approaches to communication may enhance engagement, reduce inequalities, and improve the effectiveness of nutrition interventions at population level.