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Record W4413878334 · doi:10.3899/jrheum.2025-0375

Individual and Socioecological Resilience in Childhood-Onset Systemic Lupus Erythematosus: Associations With Patient Characteristics and Psychosocial Patient-Reported Outcomes

2025· article· en· W4413878334 on OpenAlexaffvenueabout
Isabella Zaffino, Louise Boulard, Ashley Danguecan, Asha Jeyanathan, Lawrence C. Ng, Sandra Williams‐Reid, Angela Cortes, Deborah M. Levy, Linda T. Hiraki, Andrea Knight

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of TorontoInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick ChildrenMental Health Research Canada
Fundersnot available
KeywordsMedicinePsychosocialPsychological resilienceLupus erythematosusResilience (materials science)Systemic lupus erythematosusConnective tissue diseaseImmunologyPsychiatryAutoimmune diseaseInternal medicineDiseaseAntibodyPsychotherapist

Abstract

fetched live from OpenAlex

Objective This study investigates individual and socioecological resilience and its relationship with sociodemographic and disease characteristics, as well as psychosocial patient-reported outcome measures (PROMs) in childhood-onset systemic lupus erythematosus (cSLE). Methods We conducted a cross-sectional study of patients with cSLE, ages 11-22 years, at a Canadian tertiary center from October 2021 to July 2024. The 10-item Connor-Davidson Resilience Scale (CD-RISC-10) assessed individual resilience. The Child and Youth Resilience Measure–Revised (CYRM-R) assessed socioecological resilience. Linear regression models examined associations between resilience with sociodemographic (eg, health literacy, adverse childhood experiences [ACEs]) and disease factors (eg, age of onset, duration, disease activity). Pearson correlations determined relationships between resilience and patient-reported depressive and anxiety symptoms, executive functioning, pain interference, and fatigue. Results Of 49 participants, the mean score for individual psychological resilience was 26.0 (SD 7.1; CD-RISC-10), and the mean score for socioecological resilience was 73.4 (SD 9.1; CYRM-R). Higher resilience on CD-RISC-10 (β 0.99, 95% CI 0.45-1.55, P < 0.01) and CYRM-R (β 0.84, 95% CI 0.13-1.55, P = 0.02) was associated with better health literacy on the communication subscale. Lower CYRM-R scores were associated with higher number of ACEs (β −1.02, 95% CI −1.88 to −0.17; P = 0.02). For PROMs, lower scores for both individual and socioecological resilience correlated with worse depressive symptoms ( r −0.44, P = 0.003 for CD-RISC-10; r −0.55, P = 0.001 for CYRM-R) and executive functioning ( r −0.49, P = 0.002 for CD-RISC-10; r −0.56, P = 0.002 for CYRM-R). Conclusion Greater resilience was associated with fewer ACEs and better health-related communication, patient-reported mental health, and executive functioning. Findings highlight the importance of fostering resilience to improve outcomes in youth with cSLE.

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)0.004
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.014
GPT teacher head0.289
Teacher spread0.275 · 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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