# Mobile Technology Adoption in Healthcare—A Behavioral Understanding of Chronic Patients’ Perspective

## TL;DR

This study explores what influences chronic patients in Romania to adopt mobile health apps, focusing on ease of use, usefulness, and perceived risks.

## Contribution

The study validates a risk-integrated technology acceptance model tailored to chronic patients in Romania.

## Key findings

- Perceived ease of use and usefulness strongly predict intention to use mobile health apps.
- Perceived risk, especially cyber-insecurity, negatively affects adoption intentions.
- Digital self-efficacy significantly influences perceived ease of use.

## Abstract

Background: In an era of unprecedented technology adoption in healthcare, it is imperative to understand and predict factors influencing users’ perspective. This study employs a risk-integrated technology acceptance model aiming to identify the determinants of the intention to use mobile health applications among patients with chronic diseases in Romania. Methods: A face-to-face survey method was used to collect research data from 207 subjects, and the partial least squares structural equation modeling approach was employed for data analysis. Results: The behavioral intention to use mobile health applications (INT) was influenced positively by the perceived ease of use (PEOU, f2 = 0.358, β = 0.500, p < 0.001) and perceived usefulness (PU, f2 = 0.271, β = 0.678, p < 0.001). Another core predictor, with a negative effect on the intention to use, was the user’s perceived risk of using the technology (RISK, f2 = 0.239, β = −0.321, p < 0.001), in turn influenced by the perceived degree of cyber-insecurity (CYBER, f2 = 0.492, β = 0.639, p < 0.001). Digital self-efficacy (DSE) was identified as an external determinant with strong positive influence on PEOU (f2 = 0.486, β = 0.610, p < 0.001). The model shows strong performance, reflected in a high Tenenhaus goodness-of-fit index (0.770) and solid explanatory power for the outcome variable (adjusted R2 = 0.718). Conclusions: This study validates an extended risk-integrated technology acceptance model, offering robust insights into the determinants of mobile health application adoption among chronic patients in Romania. The findings provide actionable guidance for designing targeted interventions and healthcare policies to enhance technology adoption in this population.