A field study of database communication issues peculiar to users of a voice activated medical tracking application

This paper investigates database communication issues peculiar to users of a voice activated medical tracking application (VAMTA). Specifically, this study investigates voice activated user–database interaction, in terms of user gender, speech speed in words per minute (WPM) and technical computer experience of the users. A VAMTA device is employed to help solve the business and clinical needs of medical personnel, and to help them facilitate communication and interaction with database systems and designers, who are interested in improving technical specifications. The VAMTA device was integrated into a Dragon Naturally Speaking commercial system. The ability of the VAMTA to interact effectively and efficiently with the database of medical patient signs and symptoms has enhanced the productive usage of database systems that are vital components of the medical organization information systems. In this paper, we address the communication issues in voice activated user–database interaction and the philosophical perspectives of database modeling, by identifying gender and experience factors as important barriers and issues that must be further investigated to improve communication between user and database systems. Our research studies the impact of user's gender, speech speed in WPM and user's computer experience on the performance of a speech recognition system. We also investigated the interactive effects of gender and user, user and WPM, and gender and WPM. Our research investigates 33 users; a voice activated medical tracking application and a mobile healthcare fieldwork environment. The field study suggests that VAMTA can be applied to either an emergency medical services or preventative care setting. We illustrate that the user's gender and computer experience has a significant impact (p < 0.05) on the use of voice interface as an input to a medical database of patient signs and symptoms. WPM and the interaction of gender and WPM show a weak impact (p < 0.10) on system performance.