Abstract
There are many attempts at creating self-diagnosis apps that can potentially replace visiting doctors for at least the primary care conditions. However, the literature suggests that users are hesitant to fully trust the diagnosis results of these apps. Additionally, healthcare professionals constantly discourage patients from using mobile apps for health-related purposes. This study views the phenomenon using a technology trust perspective. It is argued that when users trust the technology, they begin to immerse more into adoption behaviors. The study is underpinned by the technology trust model theory, and provides empirical evidence demonstrating factors shaping trust and its potential consequences. The study collects data from users of a well-recognized self-diagnosis app and then performs SEM analyses on the data. Results suggest that trust can be shaped by perceptions of reliability, functionality, helpfulness, and social influence. Additionally, potential consequences of technology trust are the diagnostic satisfaction and the continuance intention.
Recommended Citation
Samhan, Bahae, "Self-Diagnosis Mobile Applications A Technology Trust Perspective" (2019). AMCIS 2019 Proceedings. 34.
https://aisel.aisnet.org/amcis2019/healthcare_it/healthcare_it/34
Self-Diagnosis Mobile Applications A Technology Trust Perspective
There are many attempts at creating self-diagnosis apps that can potentially replace visiting doctors for at least the primary care conditions. However, the literature suggests that users are hesitant to fully trust the diagnosis results of these apps. Additionally, healthcare professionals constantly discourage patients from using mobile apps for health-related purposes. This study views the phenomenon using a technology trust perspective. It is argued that when users trust the technology, they begin to immerse more into adoption behaviors. The study is underpinned by the technology trust model theory, and provides empirical evidence demonstrating factors shaping trust and its potential consequences. The study collects data from users of a well-recognized self-diagnosis app and then performs SEM analyses on the data. Results suggest that trust can be shaped by perceptions of reliability, functionality, helpfulness, and social influence. Additionally, potential consequences of technology trust are the diagnostic satisfaction and the continuance intention.