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Mobile computing acceptance factors in the healthcare industry: a structural equation model
Jen-Her Wu1, Shu-Ching Wang, Li-Min Lin
1Department of Information Management, National Sun Yat-sen University, 70 Lien-Hai Road, Kaohsiung 804, Taiwan. jhwu@mis.nsysu.edu.tw
International Journal of Medical Informatics
|August 12, 2006
Summary
Healthcare professionals are more likely to accept mobile healthcare systems (MHS) when they are compatible, useful, and easy to use. MHS self-efficacy also plays a key role in adoption.
Area of Science:
- Health Informatics
- Information Systems
- Technology Acceptance Models
Background:
- Mobile healthcare systems (MHS) offer potential benefits but face challenges in adoption by healthcare professionals.
- Understanding the determinants of MHS acceptance is crucial for successful implementation.
Purpose of the Study:
- To revise and test a technology acceptance model for healthcare professionals' adoption of MHS.
- To identify key factors influencing behavioral intention to use MHS.
Main Methods:
- Structural Equation Modeling (SEM) was employed to analyze the causal relationships within the proposed model.
- Confirmatory Factor Analysis (CFA) was used to validate the measurement model.
Main Results:
- Compatibility, perceived usefulness, and perceived ease of use significantly predicted behavioral intention to use MHS.
- MHS self-efficacy indirectly influenced behavioral intention through perceived usefulness and ease of use.
- Technical support and training did not significantly impact perceived usefulness or ease of use.
Conclusions:
- The study identified key antecedents for MHS acceptance among healthcare professionals, explaining 70% of the variance in behavioral intention.
- Further research is recommended to explore other factors like privacy, security, system quality, and mobile device limitations.
- Qualitative research may provide deeper insights into these additional factors for successful MHS implementation.
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