Evidence map›Paper›PMID 35468093›Full record

Trial reportJournal of medical Internet research2022

Effectiveness of Web-Based Personalized Nutrition Advice for Adults Using the eNutri Web App: Evidence From the EatWellUK Randomized Controlled Trial.

Rodrigo Zenun Franco, Rosalind Fallaize, Michelle Weech, Faustina Hwang, Julie A Lovegrove

4 registry-linked trialsOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 4 registered trials, which are not on this map. Cited by 22 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 4 pooled it
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03250858 nacompletednot on this map

Randomized Control Trial to Evaluate the Effectiveness of Online Nutrition Advice in the UK (The EatWellUK Study)

TypeinterventionalSponsorUniversity of ReadingRan2017 to 2018Enrolled324ConditionsDietary Modification, Dietary HabitsArmsPersonalised advice, Non-personalised advice
NCT05449769 nacompletednot on this map

Piloting a Web-based Personalised Nutrition App (eNutriCardio) With Patients Offered Cardiac Rehabilitation

TypeinterventionalSponsorUniversity of ReadingRan2022 to 2024Enrolled61ConditionsCardiac Event, Diet Habit, Diet ModificationArmseNutriCardio personalised nutrition advice
NCT05544461 nacompletednot on this map

Piloting a Web-based Personalised Nutrition App (eNutri) with UK University Students

TypeinterventionalSponsorUniversity of ReadingRan2022 to 2023Enrolled50ConditionsDiet Habit, Diet, Healthy, Diet ModificationArmseNutri personalised nutrition advice
NCT06675630 nacompletednot on this mapstarted 2024, after this paper: background citation

Investigating Food Intake Across the Adult Life Course and Relevant Communication Strategies

TypeinterventionalSponsorUniversity of ReadingRan2024 to 2025Enrolled336ConditionsIndividual Differences, Food Intake, Behaviour ChangeArmsEducation, Control
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 4 syntheses or guidelines pooled it, 45 citations in OpenAlex.

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  4. Digital behaviour change interventions to increase vegetable intake in adults: a systematic review.The international journal of behavioral nutrition and physical activity · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Rodrigo Zenun FrancoBiomedical Engineering, School of Biological Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0002-1998-4367
Rosalind FallaizeHugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, United Kingdom.ORCID 0000-0003-3734-6489
Michelle WeechHugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, United Kingdom.ORCID 0000-0003-1738-877X
Faustina HwangBiomedical Engineering, School of Biological Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0002-3243-3869
Julie A LovegroveHugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, United Kingdom.ORCID 0000-0001-7633-9455
University of Reading · GBUniversity of Hertfordshire · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvidence suggests that eating behaviors and adherence to dietary guidelines can be improved using nutrition-related apps. Apps delivering personalized nutrition (PN) advice to users can provide individual support at scale with relatively low cost.

objectiveThis study aims to investigate the effectiveness of a mobile web app (eNutri) that delivers automated PN advice for improving diet quality, relative to general population food-based dietary guidelines.

methodsNondiseased UK adults (aged >18 years) were randomized to PN advice or control advice (population-based healthy eating guidelines) in a 12-week controlled, parallel, single-blinded dietary intervention, which was delivered on the web. Dietary intake was assessed using the eNutri Food Frequency Questionnaire (FFQ). An 11-item US modified Alternative Healthy Eating Index (m-AHEI), which aligned with UK dietary and nutritional recommendations, was used to derive the automated PN advice. The primary outcome was a change in diet quality (m-AHEI) at 12 weeks. Participant surveys evaluated the PN report (week 12) and longer-term impact of the PN advice (mean 5.9, SD 0.65 months, after completion of the study).

resultsFollowing the baseline FFQ, 210 participants completed at least 1 additional FFQ, and 23 outliers were excluded for unfeasible dietary intakes. The mean interval between FFQs was 10.8 weeks. A total of 96 participants were included in the PN group (mean age 43.5, SD 15.9 years; mean BMI 24.8, SD 4.4 kg/m

conclusionsThese findings suggest that the eNutri app is an effective web-based tool for the automated delivery of PN advice. Furthermore, eNutri was demonstrated to improve short-term diet quality and increase engagement in healthy eating behaviors in UK adults, as compared with population-based healthy eating guidelines. This work represents an important landmark in the field of automatically delivered web-based personalized dietary interventions.

trial registrationClinicalTrials.gov NCT03250858; https://clinicaltrials.gov/ct2/show/NCT03250858.

Indexed as

Mobile ApplicationsAdultDietDiet, HealthyHumansInternetNutritional Statusappdietary interventiondiet quality scoresEatWellUKeNutriFFQfood frequency questionnairehealthy eating indexmHealthnutrition apppersonalized nutritionprecision nutritionweb-based

Identifiers

PMID35468093
PMCPMC9154737
OpenAlexW4224949155

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.