Evidence map›Paper›PMID 32301743›Full record

ArticleJMIR formative research2020

Optimizing Child Nutrition Education With the Foodbot Factory Mobile Health App: Formative Evaluation and Analysis.

Jacqueline Marie Brown, Robert Savaglio, Graham Watson, Allison Kaplansky, Ann LeSage, Janette Hughes, Bill Kapralos, JoAnne Arcand

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05979259 (Efficacy of a Digital School-Based Nutrition Education Intervention to Improve Children's Healthy Eating Knowledge, Attitudes and Behaviours), which is not on this map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
7.0field-weighted citation impact, top 3% 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.

NCT05979259 nacompletednot on this mapstarted 2023, after this paper: background citation

Efficacy of a Digital School-Based Nutrition Education Intervention to Improve Children's Healthy Eating Knowledge, Attitudes and Behaviours

TypeinterventionalSponsorUniversity of Ontario Institute of TechnologyRan2023 to 2025Enrolled616ConditionsNutrition, HealthyArmsSerious game nutrition education intervention, Conventional nutrition education intervention
3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Jacqueline Marie BrownFaculty of Health Sciences, University of Ontario Institute of Technology, Oshawa, ON, Canada.ORCID https://orcid.org/0000-0003-3806-0802
Robert SavaglioFaculty of Business & Information Technology, University of Ontario Institute of Technology, Oshawa, ON, Canada.ORCID https://orcid.org/0000-0002-6725-0616
Graham WatsonFaculty of Business & Information Technology, University of Ontario Institute of Technology, Oshawa, ON, Canada.ORCID https://orcid.org/0000-0002-2279-7431
Allison KaplanskyFaculty of Community Services, Ryerson University, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-2827-847X
Ann LeSageFaculty of Education, University of Ontario Institute of Technology, Oshawa, ON, Canada.ORCID https://orcid.org/0000-0002-5607-4370
Janette HughesFaculty of Education, University of Ontario Institute of Technology, Oshawa, ON, Canada.ORCID https://orcid.org/0000-0002-3463-8382
Bill KapralosFaculty of Business & Information Technology, University of Ontario Institute of Technology, Oshawa, ON, Canada.ORCID https://orcid.org/0000-0003-0434-3847
JoAnne ArcandFaculty of Health Sciences, University of Ontario Institute of Technology, Oshawa, ON, Canada.ORCID https://orcid.org/0000-0002-1995-6905
Ontario Tech University · CAToronto Metropolitan University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly nutrition interventions to improve food knowledge and skills are critical in enhancing the diet quality of children and reducing the lifelong risk of chronic disease. Despite the rise of mobile health (mHealth) apps and their known effectiveness for improving health behaviors, few evidence-based apps exist to help engage children in learning about nutrition and healthy eating.

objectiveThis study aimed to describe the iterative development and user testing of Foodbot Factory, a novel nutrition education gamified app for children to use at home or in the classroom and to present data from user testing experiments conducted to evaluate the app.

methodsAn interdisciplinary team of experts in nutrition, education (pedagogy), and game design led to the creation of Foodbot Factory. First, a literature review and an environmental scan of the app marketplace were conducted, and stakeholders were consulted to define the key objectives and content of Foodbot Factory. Dietitian and teacher stakeholders identified priority age groups and learning objectives. Using a quasi-experimental mixed method design guided by the Iterative Convergent Design for Mobile Health Usability Testing approach, five app user testing sessions were conducted among students (ages 9-12 years). During gameplay, engagement and usability were assessed via direct observations with a semistructured form. After gameplay, qualitative interviews and questionnaires were used to assess user satisfaction, engagement, usability, and knowledge gained.

resultsThe environmental scan data revealed that few evidence-based nutrition education apps existed for children. A literature search identified key nutrients of concern for Canadian children and techniques that could be incorporated into the app to engage users in learning. Foodbot Factory included characters (2 scientists and Foodbots) who initiate fun and engaging dialogue and challenges (minigames), with storylines incorporating healthy eating messages that align with the established learning objectives. A total of five modules were developed: drinks, vegetables and fruit, grain foods, animal protein foods, and plant protein foods. Seven behavior change techniques and three unique gamified components were integrated into the app. Data from each user testing session were used to inform and optimize the next app iteration. The final user testing session demonstrated that participants agreed that they wanted to play Foodbot Factory again (12/17, 71%), that the app is easy to use (12/17, 71%) and fun (14/17, 88%), and that the app goals were clearly presented (15/17, 94%).

conclusionsFoodbot Factory is an engaging and educational mHealth intervention for the Canadian public that is grounded in evidence and developed by an interdisciplinary team of experts. The use of an iterative development approach is a demonstrated method to improve engagement, satisfaction, and usability with each iteration. Children find Foodbot Factory to be fun and easy to use, and can engage children in learning about nutrition.

Indexed as

child nutrition scienceschildrenhealth educationmHealthmobile apps

Identifiers

PMID32301743
PMCPMC7195667
OpenAlexW3004295048

What OpenQuestion 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 OpenQuestion graph.