ArticlePsychiatry research2021
Development and external validation of a risk calculator to predict internalising symptoms among Ugandan youths affected by HIV.
Article in Psychiatry research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Using Machine Learning to Predict Depression among Adolescents Living with HIV in Uganda.Global social welfare : research, policy & practice · 2026Article
- A synthesis of dimensions of wellbeing among adolescents and young people living with HIV from Sub-Saharan Africa for measurement in economic evaluation: a qualitative overview of reviews.Health and quality of life outcomes · 2026Review
- Does HIV-Related Stigma Depress Social Well-Being of Youths Affected by Parental HIV/AIDS?Frontiers in psychiatry · 2022Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
The aim of the study was to develop and externally validate a model to predict individualized risk of internalizing symptoms among AIDS-affected youths in low-resource settings in sub-Saharan Africa. Longitudinal data from 558 Ugandan adolescents orphaned by AIDS was used to develop our predictive model. Least Absolute Shrinkage and Selection Operator logistic regression was used to select the best subset of predictors using 10-fold cross-validation. External validation of the final model was conducted in a sample of 372 adolescents living with HIV in Uganda. Best predictors for internalizing symptoms were gender, family cohesion, social support, asset ownership, recent sexually transmitted infection (STI) diagnosis, physical health self-rating, and previous poor mental health; area under the curve (AUC) = 72.2; 95% CI = 67.9-76.5. For adolescents without history of internalizing symptoms, the AUC = 69.0, 95% CI = 63.4-74.6, and was best predicted by gender, drug use, social support, asset ownership, recent STI diagnosis, and physical health self-rating. Both models were well calibrated. External validation in adolescents living with HIV sample was similar, AUC = 69.7; 95% CI = 64.1-75.2. The model predicted internalizing symptoms among African AIDS-affected youth reasonably well and showed good generalizability. The model offers opportunities for the design of public health interventions addressing poor mental health among youth affected by HIV/AIDS.
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