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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, METHODS, RESULTS. Meshes: Adolescent, Cross-Sectional Studies, Depressive Disorder, Developing Countries, Female, Health Surveys, Humans, Male, Psychometrics, Reproducibility of Results, Surveys and Questionnaires, Young Adult, Zimbabwe.
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Does one size fit all : psychometric properties of the Shona Symptom Questionnaire ( SSQ ) among adolescents and young adults in Zimbabwe? Context: Depression is a major contributor to the global burden of disease. Onset commonly occurs during the adolescent period. Understanding how depression tools are functioning among adolescents has been relatively overlooked. Using cross-sectional survey data among a sample of 2768 adolescents (aged 15-19) and 2027 young adults (aged 20-24) living in Zimbabwe this paper calibrated the Shona Symptom Questionnaire (SSQ) against the Self Report Questionnaire (SRQ-20) and examined the performance indices of the SSQ based on various cut points for classification. Using a multivariate logistic regression model we isolated particular characteristics to test their association with the odds of being misclassified as non-depressed by the SSQ. A modified cut point of five or more substantially increases the depression estimates for both age groups. The prevalence of depression increased from 3.5% to 13.2% among adolescents and from 5.1% to 16.2% among young adults based on these revisions. Adolescents who were orphaned or ever had sex had significantly a greater odd of being misclassified. When retested using the modified cut point of five or greater, associations with misclassification disappeared.
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Scales were not administered separately or in their entirety but rather overlapping items were only asked once, utilizing exclusively SRQ-20 phrasing rather than the culturally-emic language in the SSQ. Final Decision: no