ArticleNPJ digital medicine2025
Determinants of depressive symptoms in multinational middle-aged and older adults.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning-based risk predictive models for depression in patients with diabetes: a systematic review and meta-analysis.Frontiers in endocrinology · 2026Pooled it
- The association between triglyceride glucose-frailty index and cardiometabolic multimorbidity among Chinese middle-aged and older adults: a national prospective cohort study.Cardiovascular diabetology · 2026Article
- Machine learning-based risk classification of depressive symptoms among patients with hearing loss: evidence from the Health and Retirement Study (HRS).Comprehensive psychoneuroendocrinology · 2026Article
- Comparison and validation of machine learning models to predict 5-year fall risk among community-dwelling older adults in China.BMC geriatrics · 2026Article
- Perceived health exposure to mega sporting event and depressive symptoms in older adults: the mediating roles of physical activity and loneliness.BMC psychiatry · 2026Article
- Activity-function transitions and interpretable machine learning for predicting incident depressive symptoms among ACE-exposed middle-aged and older adults: a multi-cohort study.Frontiers in public health · 2026Article
- Burden and factors associated with depression symptoms among older adults in Madinah, Saudi Arabia.Frontiers in public health · 2026Article
- Machine learning-based identification of anxiety symptoms in Chinese community-dwelling older adults: a comparative study of six algorithms with SHAP analysis and nomogram development.Frontiers in psychiatry · 2026Article
- Multidimensional Depressive Symptom Exposure and Incident Cognitive Decline: A Prospective Cohort Study.Depression and anxiety · 2026Article
- Cross-national predictive correlates of depressive symptoms among middle-aged and older adults with chronic conditions: an explainable machine learning analysis.Frontiers in psychiatry · 2026Article
- Multimorbidity is significantly associated with higher prevalence of depressive symptoms in middle-aged and older Chinese adults.Preventive medicine reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This study harnesses machine learning to dissect the complex socioeconomic determinants of depression risk among older adults across five international cohorts (HRS, ELSA, SHARE, CHARLS, MHAS). Evaluating six predictive algorithms, XGBoost demonstrated superior performance in four cohorts (AUC 0.7677-0.8771), while LightGBM excelled in ELSA (AUC 0.9011). SHAP analyses identified self-rated health as the predominant predictor, though key factors varied notably-gender was especially influential in MHAS. Stratified analyses by income and sex revealed marked heterogeneity: wealth, employment, digital inclusion, and marital status exerted greater influence in lower-income groups, with distinct gender-specific patterns. These findings highlight machine learning's capacity to reveal nuanced, context-dependent risk profiles beyond traditional models, emphasizing the need for tailored interventions that address the diverse vulnerabilities of aging populations, particularly those socioeconomically disadvantaged.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.