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Evaluation of the eNutri automated personalised nutrition advice by users and nutrition professionals in the UK

Fallaize, R., Franco, R. Z., Hwang, F. ORCID: https://orcid.org/0000-0002-3243-3869 and Lovegrove, J. ORCID: https://orcid.org/0000-0001-7633-9455 (2019) Evaluation of the eNutri automated personalised nutrition advice by users and nutrition professionals in the UK. PLoS ONE, 14 (4). e0214931. ISSN 1932-6203

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To link to this item DOI: 10.1371/journal.pone.0214931

Abstract/Summary

Nutrition apps have great potential to support people to improve their diets, but few apps give automated validated personalised nutrition advice. A web app capable of delivering automated personalised food-based nutrition advice (eNutri) was developed. The aims of this study were to i) evaluate and optimise the personalised nutrition report provided by the app and ii) compare the personalised food-based advice with nutrition professionals’ standards to aid validation. A study with nutrition professionals (NP) compared the advice provided by the app against professional Registered Dietitians (RD) (n=16) and Registered Nutritionists (RN) (n=16) standards. Each NP received two pre-defined scenarios, comprising an individual’s characteristics and dietary intake based on an analysis of a food frequency questionnaire, along with the nutrition food-based advice that was automatically generated by the app for that individual. NPs were asked to use their professional judgment to consider the scenario, provide their three most relevant recommendations for that individual, then consider the app’s advice and rate their level of agreement via 5-star scales (with 5 as complete agreement). NPs were also asked to comment on the eNutri recommendations, scores generated and overall impression. The mean scores for the appropriateness, relevance and suitability of the eNutri diet messages were 3.5, 3.3 and 3.3 respectively.

Item Type:Article
Refereed:Yes
Divisions:Life Sciences > School of Biological Sciences > Biomedical Sciences
Life Sciences > School of Chemistry, Food and Pharmacy > Department of Food and Nutritional Sciences > Human Nutrition Research Group
ID Code:82966
Publisher:Public Library of Science

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