ORCID

https://orcid.org/0000-0002-2041-4126

Date of Award

Summer 2025

Language

English

Embargo Period

7-31-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

College of Emergency Preparedness, Homeland Security and Cybersecurity

Program

Information Science

First Advisor

Archana Krishnan

Committee Members

Luis Luna-Reyes, Eric Kuhn, Xiaojun Yuan

Keywords

mobile apps, abandonment, inhibitors, user satisfaction, mediation analysis, mental health

Subject Categories

Computational Linguistics | Health Communication | Health Sciences and Medical Librarianship

Abstract

The rising prevalence of mental health issues among young adults has driven increased interest in Mental Health Mobile Applications (MHMAs), which offer accessible and cost-effective solutions to traditional barriers such as financial limitations, stigma, and restricted healthcare access. Despite their promise, MHMAs frequently experience high rates of attrition and abandonment, significantly limiting their long-term effectiveness. Employing a mixed-methods, multi-stage research design, this dissertation explores the determinants of MHMA abandonment among young adults, emphasizing the interplay between technological inhibitors and enablers, individual user characteristics, and the mediating roles of user satisfaction and perceived usefulness.

Study 1 utilized quantitative text analysis, including topic modeling and semantic text classification, on 170,127 user-generated MHMA reviews to identify prominent inhibitors and enablers influencing user engagement. Study 2 extended these findings using a cross-sectional survey design with 314 young adult participants to test the relationships between composite inhibitors and enablers, user satisfaction and perceived usefulness, and MHMA abandonment. Results highlighted that while inhibitors such as usability challenges, intrusive features, unclear pricing structures, and privacy concerns were negatively associated with satisfaction and perceived usefulness, they unexpectedly predicted both direct and indirect pathways to abandonment. Notably, higher satisfaction and perceived usefulness, traditionally viewed as protective factors, were paradoxically associated with abandonment in instances of goal completion, a phenomenon termed the "graduation effect." This effect describes users who discontinue MHMA use after achieving their intended mental health outcomes. These findings challenge conventional assumptions in information systems continuance theories and suggest that abandonment in digital mental health contexts often reflects successful user outcomes rather than dissatisfaction or system failure. Practically, this research advises MHMA developers to consider both the reduction of inhibitors and the incorporation of design strategies that support healthy disengagement or transition upon goal fulfillment.

This dissertation contributes to technology adoption and nonuse literature by integrating large-scale quantitative data analyses to mental health apps. Theoretically, this work complements post-adoption models by empirically distinguishing inhibitors from enablers and documenting suppression effects. Practically, MHMA designers are advised to reduce core inhibitors while embedding features that support both sustained engagement and intentional disengagement. Future studies should adopt longitudinal approaches and investigate abandonment behaviors across different populations to validate these mechanisms. Recommendations for future research include longitudinal studies to further validate these abandonment patterns and deeper exploration into demographic variations in MHMA engagement.

License

This work is licensed under the University at Albany Standard Author Agreement.

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