PD594 - USER EXPECTATIONS TOWARDS PERSONALISED NUTRITION APPS: RESULTS OF AN ONLINE SURVEY

PD594

USER EXPECTATIONS TOWARDS PERSONALISED NUTRITION APPS: RESULTS OF AN ONLINE SURVEY

S. Antor^1,2,*, A. Strueven^3,4,5, K. Gemesi², G. Weis^3,4,5, K. Lotz¹, H. Hauner⁶, S. Brunner^3,4,5, C. Holzapfel^2,7

¹Department of Health - Personalized Nutrition, Baden-Wuerttemberg Cooperative State University, Heilbronn, ²Institute for Clinical Nutritional Medicine, School of Medicine & Health, Technical University of Munich, ³Department of Medicine I, LMU University Hospital, LMU Munich, ⁴partner site: Munich Heart Alliance, German Centre for Cardiovascular Research (DZHK), ⁵Center for Sports Medicine, LMU University Hospital, LMU Munich, ⁶Senior Professorship of the Else-Kroener-Fresenius-Foundation, Technical University of Munich, Munich, ⁷Department of Nutritional, Food and Consumer Sciences , Fulda University of Applied Sciences, Fulda, Germany

Rationale: Digital health applications (apps) increasingly provide personalised dietary recommendations based on individual user data. Understanding differences in user expectations and willingness to share data is important for developing effective nutrition tools for behaviour change and obesity prevention.

Methods: A cross-sectional online survey was conducted among adults in Germany. A standardised questionnaire assessed attitudes towards personalised nutrition apps, expected benefits, willingness to share personal data, and perceived importance of app features. Behavioural intention (BI) was measured using Technology Acceptance Model 3. Associations with gender, age, BMI, and BI were analysed. An exploratory cluster analysis was performed based on age, BMI, and BI.

Results: A total of 1,070 participants were included (75% female; 42.4 ± 15.3 years; BMI 25.6 ± 6.0 kg/m²). Younger participants rated more app features and aspects of personalised nutrition as important. Participants aged ≥60 years were less willing to share data but reported higher expected benefits. Higher BMI was associated with greater expectations towards personalised dietary advice. Participants with higher BI reported more expected benefits, rated more features as important, and were more willing to share data. Cluster analysis identified three groups differing in expected benefits, shared parameters, and feature importance (all p ≤ 0.01). Disease prevalence was highest in the cluster with older age and higher BMI (p < 0.001). Effect sizes were small to moderate (η² = 0.006–0.10).

Conclusion: Age, BMI, and BI are associated with differences in user expectations towards personalised nutrition apps. However, substantial heterogeneity exists even among users with similar characteristics. Digital nutrition interventions targeting dietary behaviour and obesity prevention may therefore benefit from flexible and customisable app designs.

Disclosure of Interest: S. Antor: None declared, A. Strueven: None declared, K. Gemesi: None declared, G. Weis: None declared, K. Lotz: None declared, H. Hauner Other: HH is a scientific advisory board member of Oviva AG (Zurich, Switzerland) and have a scientific cooperation with Oviva AG (Potsdam, Germany) and Una Health GmbH (Hamburg, Germany). To prevent selective reporting, the study protocol was registered prior to recruitment., S. Brunner: None declared, C. Holzapfel Other: CH is a scientific advisory board member of 4sigma GmbH (Oberhaching, Germany) and have a scientific cooperation with Oviva AG (Potsdam, Germany) and Una Health GmbH (Hamburg, Germany). To prevent selective reporting, the study protocol was registered prior to recruitment.