ArticleFrontiers in public health2026
Structural determinants of depressive symptoms among refugees and host communities in South Sudan: evidence from explainable machine learning.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- AI-Based Approaches to Refugee Mental Health Care: Systematic Integrative Review.Journal of medical Internet research · 2026Pooled it
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2 authors.
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Abstract
Background: Depressive symptoms in displacement settings are often framed as consequences of refugee status, which can obscure the shared structural conditions emphasized in the Social Determinants of Health (SDoH) framework that shape mental health for refugees and host communities and limit the identification of practical intervention targets. This study examines the relative contribution of health, socioeconomic, protection, and contextual factors to depressive symptom severity among adults living in displacement-affected settings in South Sudan. Methods: We analyzed nationally representative data from 3,055 adults (2,066 refugees, mean displacement duration 11.15 years; 989 host community members) from the 2023 Forced Displacement Survey. Depressive symptom severity was measured using the PHQ-9. We compared Elastic Net regression, Random Forests, and Extreme Gradient Boosting (XGBoost) using 10 × 5 nested cross-validation. The best-performing model was interpreted using SHapley Additive exPlanations (SHAP) to estimate the marginal contribution of each predictor in PHQ units. Results: Mean depressive symptom severity was low to moderate overall ( Conclusion: Depressive symptoms in South Sudan appear to be structured primarily by health, material hardship, and protection-related gradients rather than refugee status
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