Developing a framework to evaluate the types and dose of tailored health information in mobile apps for chronic condition self-management

Most older adults in the U.S. suffer a chronic condition such as diabetes, accounting for two-thirds of U.S. healthcare costs. Self-management interventions can improve outcomes for older adults with chronic conditions, and diabetes in particular exemplifies interventions’ potential to improve self-management. Problematically, managing chronic conditions involves multiple, complex behaviors. A mobile health (mHealth) approach where older adults self-manage conditions with apps presents a cost-effective solution. However, older adults often lack experience with apps, facing challenges include usability, stress, and privacy. Tailoring may improve self-management by providing information developed for a specific individual based on their characteristics, but the mechanisms of tailoring are unclear. This study aimed to develop the mHealth Framework for Investigating Tailoring Version 1 (mFIT V1), which evaluates and quantifies the tailoring types chronic condition self-management apps provide. The tailoring literature informed mFIT V1, which I revised using a sequential, mixed-methods approach with three studies. Study 1 aimed to identify mFIT V1 elements needing revision with a content analysis of diabetes apps using mFIT V1. This study identified five main issues and revisions to address the issues, producing mFIT V2. Study 2 used a survey and individual interviews with older diabetics to identify the tailoring elements facilitating self-management. A thematic analysis identified themes, including three benefits of mFIT V2, four main issue with mFIT V2, and revisions to mFIT V2 that informed mFIT V3. Study 3 involved a survey and individual interviews with app developers to identify the tailoring elements developers perceive as facilitating self-management. A thematic analysis identified themes that included two benefits for mFIT V3 and three main issues with mFIT V3. I developed revisions addressing these issues, producing mFIT V4. This dissertation’s contributions include identifying challenges older adults face using chronic condition self-management apps, clarifying which mechanisms support tailored apps, and developing mFIT. Conceptual contributions include redefining tailoring and developing the information dose concept. Useful contexts to apply mFIT include evaluating the way tailoring types impact self-management, evaluating commercially available apps, and identifying issues in the tailoring type these apps provide. mFIT can also inform intervention design through decision rules that determine the tailoring types interventions use

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Information Studies

Grantor

The University of Texas at Austin

Year dc:date.issued

2019

Author dc:creator

• Watkins, Ivan A., III

Advisor dc:contributor.advisor

• Xie, Bo, Ph. D.

Committee members dc:contributor.committeemember

• Zhang, Yan
• Gwizdka, Jacek
• Kim, Miyong
• Charness, Neil
• Aspray, William

• Chronic conditions
• Health information
• Older adults
• Self-management apps
• Mobile apps
• Older adult apps
• Self-management mobile apps
• Chronic condition self-management
• Chronic condition mobile apps
• Tailoring mobile apps
• Older adult app tailoring

Language dc:language.iso

en

Identifier URI

http://dx.doi.org/10.26153/tsw/2932

OAI identifier oai:identifier

oai:repositories.lib.utexas.edu:2152/75830