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Public perceptions of biospecimen sampling and uncertainty in the context of personalised nutrition

Katharine Lee Orcid Logo, Estelle Corbett, Becki Hafner Orcid Logo, Julie Barnett Orcid Logo

PLOS One, Volume: 20, Issue: 11, Start page: e0335733

Swansea University Author: Becki Hafner Orcid Logo

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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 analyt...

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Published in: PLOS One
ISSN: 1932-6203
Published: Public Library of Science (PLoS) 2025
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa70837
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.
College: Faculty of Medicine, Health and Life Sciences
Funders: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 816303.
Issue: 11
Start Page: e0335733