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University of Ontario Institute of Technology

The development and evaluation of a mHealth nutrition education intervention

Abstract

dc:description.abstract

An environmental scan of the app marketplace evaluated publicly available mHealth nutrition apps targeted to children and found that there were few high-quality evidence-based apps available to educate children on healthy eating. To fill this gap in the availability of mHealth child nutrition apps, an iterative multi-method approach was taken to develop a novel app, Foodbot Factory, to help children aged 9-12 improve their food literacy skills and nutrition knowledge. Foodbot Factory was created by an interdisciplinary team with each prototype being informed by data collected in 5 iterative user testing sessions. The app educates users on foods and nutrients, integrating behaviour change and gamification techniques to enhance engagement. Data from the most recent testing session demonstrates that students are able to gain knowledge about nutrition from Foodbot Factory and that the app is an engaging, usable, and acceptable intervention for children to learn about healthy eating and nutrition.

Degree

thesis:*
Name thesis:degree_name
Master of Health Sciences (MHSc)
Discipline thesis:degree_discipline
Community, Public and Population Health
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Brown, Jacqueline M.
Advisor dc:contributor.advisor
  • Arcand, JoAnne

Subjects

dc:subject × 5

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/1068
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/1068

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Brown, Jacqueline M.. The development and evaluation of a mHealth nutrition education intervention. University of Ontario Institute of Technology, 2019. https://hdl.handle.net/10155/1068