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Record W4410715738 · doi:10.3899/jrheum.2025-0390.o068

EXAMINING THE RELATIONSHIP BETWEEN SOCIODEMOGRAPHIC FACTORS AND MENTAL HEALTH IN CHILDHOOD-ONSET SYSTEMIC LUPUS ERYTHEMATOSUS

2025· article· en· W4410715738 on OpenAlexaffvenueabout
Jing Jin, Andrea Knight, Ashley Danguecan, Linda T. Hiraki, Deborah M. Levy, Jida Jaffan, Asha Jeyanathan, Lawrence C. Ng, Paris Moaf, Joanna Law, Angela Cortes, Sandra Williams‐Reid

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsMcMaster UniversitySunnybrook HospitalSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineMental healthLupus erythematosusSystemic diseaseConnective tissue diseaseSystemic lupus erythematosusImmunopathologyPediatricsPsychiatryImmunologyInternal medicineAutoimmune diseaseDiseaseAntibody

Abstract

fetched live from OpenAlex

O068 / #494 Topic:AS18 - Pediatric SLE ABSTRACT CONCURRENT SESSION 12: PEDIATRIC SLE – ADVANCES IN DISEASE OUTCOMES AND MENTAL HEALTH 24-05-2025 10:40 AM - 11:40 AM Background/Purpose Childhood-onset systemic lupus erythematosus (cSLE) is a chronic autoimmune disease with significant adverse impact on mental health. Furthermore, patients with cSLE often face health disparities due to marginalization involving individual-level race and ethnicity, household-level and neighborhood-level socioeconomic factors. We aimed to understand the impact of these multilevel sociodemographic factors for marginalization on mental health in youth with cSLE. Methods We conducted a retrospective cross-sectional cohort study of publicly insured cSLE patients (9-18 years) recruited from an outpatient lupus clinic in Ontario, Canada from October 2017-December 2023. All patients met ACR or SLICC criteria for SLE classification. The exposure of marginalization included measures for individual race and ethnicity, household low-income status, and neighborhood-level Ontario Marginalization Index (material resources, racialized and newcomer population dimensions). Mental health outcomes included the presence of clinically elevated anxiety symptoms, measured by the Screen for Childhood Anxiety Related Disorders (SCARED), and depression symptoms, measured by the Center for Epidemiologic Studies Depression Scale for Children (CES-DC) or Children’s Depression Inventory/Beck Depression Inventory (CDI/BDI). Logistic regression models examined associations between the marginalization exposure variables and the mental health outcomes, adjusting for age, sex, disease duration and activity. Results 100 cSLE patients were included. Marginalization characteristics are shown in Figure 1. 27% of the cohort lived in low-income households, and 52% lived in areas with the highest density of racialized and newcomer populations. Symptoms for anxiety were present in 43% and depression in 40%. Patients living in the most marginalized quintile of neighborhood material resources had higher odds of depressive symptoms compared to those in more material resourced neighborhoods (OR=4.2, 95% CI 1.2-13.9, p=0.02, Table 2). No other significant associations were observed for depressive symptoms, and no associations were found for anxiety symptoms. Figure 1: Shown are marginalization characteristics and mental health outcomes for the cSLE cohort (n=100). The “Other” race and ethnic category included individuals identifying as Indigenous, Middle Eastern, Southeast Asian, Latin American or multiethnicity. Table 2: Multivariable Logistic Regression Model for Association between Marginalization, Depression, and Anxiety Symptoms Conclusions In a publicly insured Canadian cohort of youth with cSLE, we found that those living in neighborhoods with the lowest material resources were at highest risk for depression symptoms. Further research into other social determinants of health is essential to improve mental health support for youth with cSLE from diverse socioeconomic backgrounds.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.321
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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