Predictors of time to first symptomatic recovery of major depressive disordered patients: a case study at Jimma University Medical Center

Author:

Asefa Ketema Zerihun,Bedada Tadele Degefa,Fufa Jaleta Abdisa,Gari Firomsa Shewa,Gelcho Gurmessa Nugussu,Akessa Geremew Muleta

Abstract

Abstract Background Major Depressive Disorder is one of the most common mental disorders, and it is the main cause of disability worldwide with a prevalence ranging from 7 to 21%. Objective The goal of this study was to predict the time it took for patients with severe depressive disorders at Jimma University Medical Center to experience their initial symptomatic recovery. Study design The researchers utilized a prospective study design. Methods Patients with major depressive disorder were followed up on at Jimma University Medical Center from September 2018 to August 2020 for this study. The Gamma and Inverse Gaussian frailty distributions were employed with Weibull, Log-logistic, and Log-normal as baseline hazard functions. Akaike Information Criteria were used to choose the best model for describing the data. Results This study comprised 366 patients, with 54.1% of them experiencing their first symptomatic recovery from a severe depressive disorder. The median time from the onset of symptoms to symptomatic recovery was 7 months. In the study area, there was a clustering effect in terms of time to first symptomatic recovery from major depressive disorder. According to the Log-normal Inverse-Gaussian frailty model, marital status, chewing khat, educational status, work status, substance addiction, and other co-variables were significant predictors of major depressive disorder (p-value < 0.05). Conclusion The best model for describing the time to the first symptomatic recovery of major depressive disorder is the log-normal Inverse-Gaussian frailty model. Being educated and working considerably were the variables that reduces the time to first symptomatic recovery from major depressive disorder; whereas being divorced, chewing khat, substance abused and other co-factors were the variables that significantly extends the time to first symptomatic recovery.

Publisher

Springer Science and Business Media LLC

Subject

Psychiatry and Mental health

Reference58 articles.

1. Depression WH. Other common mental disorders: global health estimates. Geneva: World Health Organization. 2017. p. 24.

2. Kessler RC, Bromet EJ. The epidemiology of depression across cultures. Annu Rev Public Health. 2013;18(34):119–38.

3. Dewey C. A stunning map of depression rates around the world: The Washington Post; 2013. p. 7.

4. Ezzati M, Vander Hoorn S, Lopez AD, Danaei G, Rodgers A, Mathers CD, Murray CJ. Comparative quantification of mortality and burden of disease attributable to selected risk factors. Glob Burden Dis Risk Factors. 2006;1(2):241–396.

5. Tomlinson M, Grimsrud AT, Stein DJ, Williams DR, Myer L. The epidemiology of major depression in South Africa: results from the South African Stress and Health study: mental health. S Afr Med J. 2009;99(5):368–73.

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