| Creators: |
Mirabootalebi, Narjes and Holl, Felix and Meidani, Zahra and Jeddi, Fatemeh Rangraz and Tagharrobi, Zahra and Akbari, Hossein and Swoboda, Walter |
| Title: |
Determinants of Nurses’ Continuance Intention to Use Mobile Health Apps in Clinical Nursing Practice: Structural Equation Modeling to Extend the Expectation-Confirmation Model |
| Item Type: |
Article or issue of a publication series |
| Projects: |
DigiHealth, GlobalHealthInformatics |
| Journal or Series Title: |
JMIR nursing |
| Page Range: |
e68048 |
| Date: |
2025 |
| Divisions: |
Gesundheitsmanagement |
| Abstract (ENG): |
Background: Mobile health (mHealth) apps enhance clinical nursing by improving access to resources and patient care. Further benefits include reduced errors, time savings, better communication, cost reduction, and training. Understanding factors driving nurses' continued mHealth adoption is key to its sustained success.
Objective: This study extends the expectation-confirmation model (ECM) to explore the determinants of Iranian nurses' continuance intention to use mHealth apps in their daily clinical routines.
Methods: A cross-sectional, descriptive-analytical study was conducted among 315 nurses from hospitals affiliated with Kashan University of Medical Sciences. The Nurses' Mobile Health Device Acceptance Scale (NMHDA-Scale) was developed by the authors in 2022. The Intention to Continue Using Mobile Health Applications for Nurses questionnaire assesses nurses' future willingness to use mHealth apps in their practice. This questionnaire was designed based on the ECM and the approach by Waltz et al. Its primary aim is to identify the factors that influence mHealth device acceptance, specifically among clinical nurses, as previous studies have not focused on this group and have shown inconsistent relationships between various factors. Participants completed structured questionnaires measuring perceived usefulness, perceived ease of use, social influence, habits, and technology anxiety. Data were analyzed using structural equation modeling in AMOS (version 26). The model tested relationships among confirmation, perceived usefulness, social influence, technology anxiety, and mHealth continuance behavior.
Results: The analyzed sample (n=315) consisted primarily of female (252/315, 80%) and married (243/315, 77.1%) nurses, with a mean age of 35.67 (SD 1.24) years. The analysis revealed that perceived usefulness was significantly influenced by both confirmation (P<.001) and social influence (P<.001). Perceived ease of use was negatively impacted by new technology anxiety (P<.001), indicating that higher anxiety levels reduced perceived ease of use. Additionally, mHealth continuance behavior was positively associated with habits (P=.002), social influence (P<.001), and perceived security risks (P=.008). Contrary to expectations, perceived usefulness did not directly influence mHealth continuance (P=.15), suggesting that other factors, such as habits and social influence, play a more significant role in long-term use.
Conclusions: Sustained mHealth app use by nurses hinges more on social influence and confirmed expectations than perceived usefulness. Although new technology anxiety remains a barrier, habits and social influence are key to long-term adoption. Hospital leaders should prioritize strategies that foster positive social reinforcement, minimize security concerns, and reduce anxiety through training and support when integrating mHealth into nursing workflows. These findings offer critical insights for improving digital health implementation, ultimately enhancing patient care and clinical efficiency. |
| Forthcoming: |
No |
| Main areas or research: |
Health |
| Language: |
English |
| Uncontrolled Keywords: |
continuance intention; expectation–confirmation model; habits; mobile health apps; perceived usefulness; technology anxiety; user satisfaction |
| Citation: |
Mirabootalebi, Narjes and Holl, Felix and Meidani, Zahra and Jeddi, Fatemeh Rangraz and Tagharrobi, Zahra and Akbari, Hossein and Swoboda, Walter
(2025)
Determinants of Nurses’ Continuance Intention to Use Mobile Health Apps in Clinical Nursing Practice: Structural Equation Modeling to Extend the Expectation-Confirmation Model.
JMIR nursing, 8 (1).
e68048.
ISSN 2562-7600
|
