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Online personalised nutrition advice

Franco, R. Z. (2018) Online personalised nutrition advice. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00084935

Abstract/Summary

The Internet has considerable potential to improve health-related food choice at lowcost. In order to provide online personalised nutrition advice, a valid and user-friendly method for recording dietary intake is key. Yet, the author’s review of popular nutritionrelated mobile apps revealed that none of these apps were capable of providing personalised diet advice This work presents a web app (eNutri), which is able to assess dietary intake using a validated food frequency questionnaire (FFQ) and provide personalised food-based diet advice. The initial version of this app presented the food items in a list and its usability was evaluated in Kuwait. In response to user feedback, the design was modified to present a single food item at a time. This app was deployed in an online study to assess usability with 324 participants in the UK, using different devices. The median System Usability Scale (SUS) score (n=322) was 77.5 (IQR 15.0) out of 100, illustrating high acceptance by users. Potential users were consulted during the design process, but assessing whether nutrition professionals (n=32) agree with the automated advice and collecting their insights were important in maximising the success and wider utility of this app. The mean scores for the appropriateness, relevance and suitability of the eNutri diet messages by nutritional professionals were 3.5, 3.3 and 3.3 respectively (maximum 5). Its effectiveness was evaluated during a 12-week online randomly controlled parallel blinded dietary intervention (n=210) (EatWellUK study) in which personalised dietary advice was compared with general population recommendation (control). A significant improvement in the modified Alternative Healthy Eating Index (m-AHEI) score, against which the participants’ diets were compared, of 3.06 (CI 95% 0.91 to 5.21, p=0.005), was reported following personalised compared to population advice. This work indicates the benefit of personalised dietary advice delivered online to motivate dietary change. The eNutri app’s design and source code were made publicly available under a permissive open source license, so that other researchers and organizations can benefit from this work.

Item Type:Thesis (PhD)
Thesis Supervisor:Hwang, F.
Thesis/Report Department:School of Biological Sciences
Identification Number/DOI:https://doi.org/10.48683/1926.00084935
Divisions:Life Sciences > School of Biological Sciences > Department of Bio-Engineering
ID Code:84935

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