Title: A web-based system for early detection of symptom of depression

Authors: Bhairavi D. Pandya; Dinesh P. Mital; Shankar Srinivasan; Syed Haque

Addresses: Department of Health Informatics, School of Health Related Professions, University of Medicine and Dentistry of New Jersey, 65 Bergan Street Newark, NJ 07107-3001, USA ' Department of Health Informatics, School of Health Related Professions, University of Medicine and Dentistry of New Jersey, 65 Bergan Street Newark, NJ 07107-3001, USA ' Department of Health Informatics, School of Health Related Professions, University of Medicine and Dentistry of New Jersey, 65 Bergan Street Newark, NJ 07107-3001, USA ' Department of Health Informatics, School of Health Related Professions, University of Medicine and Dentistry of New Jersey, 65 Bergan Street Newark, NJ 07107-3001, USA

Abstract: According to the World Health Organization, depression affects about 121 million people worldwide. The Centers for Disease Control report in the USA an estimated 10% of the population will be affected by depression in a given year. We developed the patient data management system (PDMS) to determine if a web-based system can be effectively utilised for the early detection of depressive symptoms. There were 394 participants in the study, 65.5% (N = 258) were female and 34.5% (N = 136) were male. In summary, 89.9% of the population (N = 354) was not depicting any depression symptoms according to CES-D score. The frequency of positive depression screening (indicated by a CED-S score of > 16) was observed in 10.16% (N = 40) of the total population. There was a significant effect of gender on higher CES-D score at p < .05 level for the subjects in the study [F (1,392) = 11.34, p = .001].

Keywords: depression screening; web-based systems; depression detection; depressive symptoms; internet screening; gender.

DOI: 10.1504/IJMEI.2014.058534

International Journal of Medical Engineering and Informatics, 2014 Vol.6 No.1, pp.65 - 73

Published online: 24 May 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article