An Analytics Platform to Evaluate Effective Engagement With Pediatric Mobile Health Apps: Design, Development, and Formative Evaluation

Quynh Pham; Gary Graham; Chitra Lalloo; Plinio P Morita; Emily Seto; Jennifer N Stinson; Joseph A Cafazzo

doi:10.2196/11447

An Analytics Platform to Evaluate Effective Engagement With Pediatric Mobile Health Apps: Design, Development, and Formative Evaluation

JMIR Mhealth Uhealth. 2018 Dec 21;6(12):e11447. doi: 10.2196/11447.

Authors

Quynh Pham^{1

2}, Gary Graham², Chitra Lalloo^{1

3}, Plinio P Morita^{1

4}, Emily Seto^{1

2}, Jennifer N Stinson^{1

3

5

6}, Joseph A Cafazzo^{1

2

7}

Affiliations

¹ Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
² Centre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, ON, Canada.
³ Child Health Evaluative Sciences Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.
⁴ School of Public Health and Health Systems, Faculty of Applied Health Sciences, University of Waterloo, Waterloo, ON, Canada.
⁵ Department of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, ON, Canada.
⁶ Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada.
⁷ Institute of Biomaterials and Biomedical Engineering, Faculty of Applied Science and Engineering, University of Toronto, Toronto, ON, Canada.

PMID: 30578179
PMCID: PMC6320392
DOI: 10.2196/11447

Abstract

Background: Mobile health (mHealth) apps for pediatric chronic conditions are growing in availability and challenge investigators to conduct rigorous evaluations that keep pace with mHealth innovation. Traditional research methods are poorly suited to operationalize the agile, iterative trials required to evidence and optimize these digitally mediated interventions.

Objective: We sought to contribute a resource to support the quantification, analysis, and visualization of analytic indicators of effective engagement with mHealth apps for chronic conditions.

Methods: We applied user-centered design methods to design and develop an Analytics Platform to Evaluate Effective Engagement (APEEE) with consumer mHealth apps for chronic conditions and implemented the platform to analyze both retrospective and prospective data generated from a smartphone-based pain self-management app called iCanCope for young people with chronic pain.

Results: Through APEEE, we were able to automate the process of defining, operationalizing, and evaluating effective engagement with iCanCope. Configuring the platform to integrate with the app was feasible and provided investigators with a resource to consolidate, analyze, and visualize engagement data generated by participants in real time. Preliminary efforts to evaluate APEEE showed that investigators perceived the platform to be an acceptable evaluative resource and were satisfied with its design, functionality, and performance. Investigators saw potential in APEEE to accelerate and augment evidence generation and expressed enthusiasm for adopting the platform to support their evaluative practice once fully implemented.

Conclusions: Dynamic, real-time analytic platforms may provide investigators with a powerful means to characterize the breadth and depth of mHealth app engagement required to achieve intended health outcomes. Successful implementation of APEEE into evaluative practice may contribute to the realization of effective and evidence-based mHealth care.

Keywords: analytics; chronic disease; engagement; log data; mobile apps; mobile health.

©Quynh Pham, Gary Graham, Chitra Lalloo, Plinio P Morita, Emily Seto, Jennifer N Stinson, Joseph A Cafazzo. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 21.12.2018.