Abstract
Personalised nutrition based on analysis of biospecimen generates individual-specific dietary recommendations and potentially, improved health. However, the science underpinning these approaches is evolving and uncertain. Additionally, users must provide a biological sample appropriate to the analytic approach being taken. This two-part quasi-experimental study sought to understand the impact of certainty and sample type on affective responses and attitudes to personalised nutrition. Participants (n716) completed a free association task and an attitudinal survey. Participants responded with more positive affect and attitudes to personalised nutrition when the science was characterised as certain. Attitudes to personalised nutrition were not affected by sample type, although contemplating providing a stool sample elicited more negative affective responses than other samples. This suggests that the need to provide a stool sample could be a barrier to microbiome-based personalised nutrition. We consider the implications of our findings in relation to future research and to providers of personalised nutrition.
| Original language | English |
|---|---|
| Journal | PLoS ONE |
| Early online date | 14 Oct 2025 |
| DOIs | |
| Publication status | Published - 5 Nov 2025 |
Data Availability Statement
Bath: University of Bath Research Data Archive. https://doi.org/10.15125/BATH-01605.Funding
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 816303 (https://europa.eu/european-union/abouteu/ symbols/flag_en). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Fingerprint
Dive into the research topics of 'Public perceptions of biospecimen sampling and uncertainty in the context of personalised nutrition'. Together they form a unique fingerprint.Datasets
-
Dataset for "Public perceptions of biospecimen sampling and uncertainty in the context of personalised nutrition"
Lee, K. (Creator), Corbett, E. (Creator), Hafner, R. (Creator) & Barnett, J. (Creator), University of Bath, 4 Nov 2025
DOI: 10.15125/BATH-01605
Dataset