Stresses and Disability in Depression across Gender
Author(s) -
Sharmishtha Deshpande,
Bhalchandra Kalmegh,
Poonam Patil,
Madhav R. Ghate,
Sanjeev Sarmukaddam,
Vasudeo Paralikar
Publication year - 2014
Publication title -
depression research and treatment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.738
H-Index - 27
eISSN - 2090-133X
pISSN - 2090-1321
DOI - 10.1155/2014/735307
Subject(s) - algorithm , depression (economics) , suicidal ideation , medicine , machine learning , poison control , injury prevention , computer science , economics , environmental health , macroeconomics
Depression, though generally episodic, results in lasting disability, distress, and burden. Rising prevalence of depression and suicide in the context of epidemiological transition demands more attention to social dimensions like gender related stresses, dysfunction, and their role in outcome of depression. Cross-sectional and follow-up assessment of men and women with depression at a psychiatric tertiary centre was undertaken to compare their illness characteristics including suicidal ideation, stresses, and functioning on GAF, SOFAS, and GARF scales ( N = 107). We reassessed the patients on HDRS-17 after 6 weeks of treatment. Paired t -test and chi-square test of significance were used to compare the two groups, both before and after treatment. Interpersonal and marital stresses were reported more commonly by women ( P < 0.001) and financial stresses by men ( P < 0.001) though relational functioning was equally impaired in both. Women had suffered stresses for significantly longer duration ( P = 0.0038). Men had more impairment in social and occupational functioning compared to females ( P = 0.0062). History of suicide attempts was significantly associated with more severe depression and lower levels of functioning in case of females with untreated depression. Significant cross-gender differences in stresses, their duration, and types of dysfunction mandate focusing on these aspects over and above the criterion-based diagnosis.
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