Kiemute Oyibo, York University

Research

Behavior Change Support System Culture Digital Health Digital Inequity Machine Learning Mobile App Personalization Persuasive Technology

Latest papers

The application of explainable artificial intelligence in the prediction, diagnoses, treatment, and management of chronic diseases: A systematic review.
Digital health · 2025 · senior author
Exploring the Use of Persuasive System Design Principles to Enhance Medication Incident Reporting and Learning Systems: Scoping Reviews and Persuasive Design Assessment.
JMIR human factors · 2024 · first author
Using Smart Home Technologies to Promote Physical Activity Among the General and Aging Populations: Scoping Review.
Journal of medical Internet research · 2023 · first author

All 5 publications

Latest funding

Using Persuasive Technology and Machine Learning Models to Address Digital Inequity
NSERC · 2023 · Principal investigator
$72,000
Using Persuasive Technology and Machine Learning Models to Address Digital Inequity
NSERC · 2023 · Principal investigator
$12,500

All 2 grants and awards

5 publications.

01

The application of explainable artificial intelligence in the prediction, diagnoses, treatment, and management of chronic diseases: A systematic review.

Hoghooghi Esfahani H, Toyonaga S, Oyibo K

Digital health2025Senior author

DOI: 10.1177/20552076251355669 PMID: 41312145

02

Exploring the Use of Persuasive System Design Principles to Enhance Medication Incident Reporting and Learning Systems: Scoping Reviews and Persuasive Design Assessment.

Oyibo K, Gonzalez PA, Ejaz S, Naheyan T, Beaton C, O'Donnell D, Barker JR

JMIR human factors2024First author

DOI: 10.2196/41557 PMID: 38512325

03

Using Smart Home Technologies to Promote Physical Activity Among the General and Aging Populations: Scoping Review.

Oyibo K, Wang K, Morita PP

Journal of medical Internet research2023First author

DOI: 10.2196/41942 PMID: 37171839

04

Using serious mobile games to improve health literacy in rural Sub-Saharan Africa: A literature review.

Ouedraogo I, Some BMJ, Oyibo K, Benedikter R, Diallo G

Frontiers in public health2022

DOI: 10.3389/fpubh.2022.768252 PMID: 36466518

05

The Effect of Persuasive Design on the Adoption of Exposure Notification Apps: Quantitative Study Based on COVID Alert.

Oyibo K, Morita PP

JMIR formative research2022First author

DOI: 10.2196/34212 PMID: 35580138

Using Persuasive Technology and Machine Learning Models to Address Digital Inequity

Principal investigatorNSERC2023Discovery Grants Program - Individual

Principal investigators: Oyibo, Kiemute

Keywords: persuasive technology; behavior change support system; mobile app; predictive model; machine learning; personalization; culture; digital health; digital inequity; recommender system

$72,000

Using Persuasive Technology and Machine Learning Models to Address Digital Inequity

Principal investigatorNSERC2023Discovery Launch Supplement

Principal investigators: Oyibo, Kiemute

$12,500

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

Write to this professor

A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.

Applying for

Paper to mentionMention their NSERC grant from 2023

Subject: Prospective PhD student: Behavior Change Support System Dear Professor Oyibo, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "The application of explainable artificial intelligence in the prediction, diagnoses, treatment, and management of chronic diseases: A systematic review." (2025), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your NSERC-funded project "Using Persuasive Technology and Machine Learning Models to Address Digital Inequity" (2023), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]