A Framework of Longitudinal Study to Understand Determinants of Actual Use of the Portable Health Clinic System

• Published in: Distributed, Ambient and Pervasive Interactions pp. 323 - 332
• Main Authors: Sampa, Masuda Begum, Hossain, Md. Nazmul, Hoque, Rakibul, Islam, Rafiqul, Yokota, Fumihiko, Nishikitani, Mariko, Fukuda, Akira, Ahmed, Ashir
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Longitudinal study; Structural equation modeling; Technology acceptance model
• ISBN: 9783030219345; 3030219348
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-21935-2_24

Due to the scarcity of medical infrastructure including doctors and hospitals, ICT based healthcare services is getting popular around the world including low facilities rural areas of Bangladesh. Portable Health Clinic (PHC) system is one of the ICT based healthcare systems. Speciality of this system is that the clinic box is carried and operated by a pre-trained healthcare worker. However, longitudinal study in this context wasn’t undertaken before. In order to draw strong inferences about new technology use we need to do longitudinal study. Therefore, the aim is to identify key determinants of actual use of the PHC system and to understand how their influence changes over time with increasing experience to explain detailed action sequences that might unfold over time. Face to face survey will be conducted to collect data. Structural Equation Modeling will be used to analyze data. By analyzing data using AMOS 25.0 this study will identify most important time that are key to increase actual use of the PHC system. The proposed model can make it possible to offer important practical guidelines to service providers in enhancing actual use of the PHC system. The study can suggest way of increasing health awareness to policy makers and way to build awareness to use the system. The study can also contribute to make policy to improve health care situation i.e., reduce morbidity rate in the country.