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Psychometric evaluation of the Major Depression Inventory among young people living in Coastal Kenya

Background: The lack of reliable, valid and adequately standardized measures of mental illnesses in sub-Saharan Africa is a key challenge for epidemiological studies on mental health.  We evaluated the psychometric properties and feasibility of using a computerized version of the Major Depression In...

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Detalles Bibliográficos
Autores principales: Otiende, Mark, Abubakar, Amina, Mochamah, George, Walumbe, David, Nyundo, Christopher, Doyle, Aoife M, Ross, David A, Newton, Charles R, Bauni, Evasius
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5968359/
https://www.ncbi.nlm.nih.gov/pubmed/29862324
http://dx.doi.org/10.12688/wellcomeopenres.12620.1
Descripción
Sumario:Background: The lack of reliable, valid and adequately standardized measures of mental illnesses in sub-Saharan Africa is a key challenge for epidemiological studies on mental health.  We evaluated the psychometric properties and feasibility of using a computerized version of the Major Depression Inventory (MDI) in an epidemiological study in rural Kenya. Methods: We surveyed 1496 participants aged 13-24 years in Kilifi County, on the Kenyan coast. The MDI was administered using a computer-assisted system, available in three languages. Internal consistency was evaluated using both Cronbach’s alpha and the Omega Coefficient. Confirmatory factor analysis was performed to evaluate the factorial structure of the MDI. Results:  Internal consistency using both Cronbach’s Alpha (α= 0.83) and the Omega Coefficient (0.82; 95% confidence interval 0.81- 0.83) was above acceptable thresholds. Confirmatory factor analysis indicated a good fit of the data to a unidimensional model of MDI (χ (2) (33, N = 1409) = 178.52 p < 0.001, TLI = 0.947, CFI = 0.961, and Root Mean Square Error of Approximation, RMSEA = .056), and this was confirmed using Item Response Models (Loevinger’s H coefficient 0.38) that proved the MDI was a unidimensional scale. Equivalence evaluation indicated invariance across sex and age groups. In our population, 3.6% of the youth presented with scores suggesting major depression using the ICD-10 scoring algorithm, and 8.7% presented with total scores indicating presence of depression (mild, moderate or severe).  Females and older youth were at the highest risk of depression. Conclusions: The MDI has good psychometric properties.  Given its brevity, relative ease of usage and ability to identify at-risk youth, it may be useful for epidemiological studies of depression in Africa.  Studies to establish clinical thresholds for depression are recommended. The high prevalence of depressive symptoms suggests that depression may be an important public health problem in this population group.