A Design Construct of Developing Approaches to Measure Mental Health Conditions

  • Md Rafiqul Islam Department of Computer Science & Engineering Islamic University of Technology (IUT), Bangladesh Email: [email protected]
  • Shah Jahan Miah College of Business, Victoria University, Melbourne
  • Abu Raihan M. Kamal Department of Computer Science & Engineering Islamic University of Technology (IUT), Bangladesh Email: [email protected]
  • Oliver Burmeister Associate Prof of Info Systems SCHOOL OF COMPUTING & MATHEMATICS Charles Sturt University
Keywords: healthcare IS, design research, mental disorder, diagnosis, occupational stress, ICT professionals

Abstract

Mental health is an important determinant of communities’ well-being, influenced not only by individual attributes, but also by social and organisational environments in which people work and live. Despite studies examining mental health status among specific populations, few attempts are evident that focus on solution designs for detecting and measuring impact of mental health conditions. In this study, we develop a construct utilising design science research principles for outlining common vocabulary around the problem, and solution design relevant to a mental health management system. For the case of IT professionals, the developed construct is informed through a social-media based dataset containing more than 65,000 cells and 100 attributes potentially identifying influencing factors. Machine learning techniques are applied to the dataset to discover new findings for this specific group. It is anticipated that the analysis reported in this study would contribute in developing other electronic health management systems both for communities and healthcare professionals.

Author Biography

Shah Jahan Miah, College of Business, Victoria University, Melbourne
A/Prof of Infor Systems
Published
2019-02-12
How to Cite
Islam, M. R., Miah, S. J., Kamal, A. R. M., & Burmeister, O. (2019). A Design Construct of Developing Approaches to Measure Mental Health Conditions. Australasian Journal of Information Systems, 23. https://doi.org/10.3127/ajis.v23i0.1829
Section
Research on Health Information Systems