Understanding Pharmacists’ Intention to Use Medical Apps

Sze-Nee Ng, David Matanjun, Urban D'Souza, Rayner Alfred


Objectives: The goal of this study is to investigate pharmacists’ perception towards mobile medical apps use in pharmacy practice and to explore both the enabling and inhibiting factors that govern the adoption of this Mobile Health tool.

Methods: This study employed quantitative research methodology to examine the relationships between key constructs and pharmacists’ intention to use medical apps. Multi-items questionnaire was developed to draw participation of pharmacists from various fields of practice in Malaysia. Quantitative data was analyzed using partial least squares (PLS) modeling statistical technique.

Results: The findings provided strong empirical support for six positive determinants (perceived usefulness, perceived ease of use, result demonstrability, subjective norm, compatibility, facilitating conditions) and two negative (security, resistance to change) determinants of intention to use medical apps. The proposed model had good predictive relevance to infer actual medical apps.

Discussion: Pharmacy informaticists are able to manipulate the key factors presented in the research model in such a way to maximize the adoption of medical apps amongst the pharmacists. The study showed that the usefulness of the apps along with their reliability were the most effective influence on intention to use. Pharmacists were also worried about the data security which could potentially hinder the adoption.

Conclusions: This study represents a pioneer dual-factor model technology adoption study. It has shed light on the aspects where decision makers from managerial stand-point are able to manipulate to achieve maximum diffusion of mobile technology within the health institution.


Mobile Health; Medical Application; Technology Adoption; Pharmacoinformatics; Barriers; Health Informatics

Full Text:


::::::::::::::  eJHI - electronic Journal of Health Informatics - ISSN 1446-4381  ::::::::::::::

                                     Privacy Statement - Uptime