MétaCan
Menu
Back to cohort
Record W4413118143 · doi:10.1093/rheumatology/keaf374

Anxiety symptoms and associated factors in the Scleroderma Patient-centered Intervention Network (SPIN) cohort: a cross-sectional study

2025· article· en· W4413118143 on OpenAlexafffundabout
Sabrina Provencher, Marie‐Eve Carrier, Gabrielle Virgili-Gervais, Meira Golberg, Richard S. Henry, Linda Kwakkenbos, Catherine Fortuné, Amy Gietzen, Karen Gottesman, Geneviève Guillot, Amanda Lawrie-Jones, Maureen Sauvé, Susan J. Bartlett, Laura K. Hummers, Vanessa L. Malcarne, Maureen D. Mayes, Michelle Richard, James Stempel, Robyn K. Wojeck, Andrea Benedetti, Brett D. Thombs

Bibliographic record

VenueLara D. Veeken · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsAtlantic School of TheologyMcGill University Health CentreMcGill UniversityJewish General Hospital
FundersLady Davis Institute for Medical ResearchCanadian Institutes of Health ResearchScleroderma AtlanticScleroderma Association of British ColumbiaScleroderma VictoriaScleroderma Society of OntarioJewish General HospitalFonds de Recherche du Québec - SantéArthritis SocietyFondation de l'Hôpital général juifMcGill University
KeywordsMedicineCohortAnxietyPopulationDemographyConfidence intervalBody mass indexStandard scoreCohort studyInternal medicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: We (1) compared anxiety symptom levels in a multinational SSc cohort to a general population normative sample and (2) evaluated sociodemographic, lifestyle and SSc disease factors associated with symptoms. METHODS: Scleroderma Patient-centered Intervention Network Cohort participants completed the Patient-Reported Outcomes Measurement Information System (PROMIS) Version 2 4a Anxiety domain upon enrolment. PROMIS domain scores use T-scores (mean = 50, S.D. = 10) calibrated to a United States normative sample. We compared T-scores to the PROMIS United States normative sample and, in SSc, assessed associations of sociodemographic, lifestyle and physician-reported disease-related variables with multivariable linear regression. RESULTS: Among 2463 participants with SSc, mean anxiety symptom T-score (52.6, S.D. = 10.0, 95% CI 52.2, 53.0) was ∼1/3 S.D. higher than the United States general population mean of 50 (S.D. = 10), though within normal limits. Higher T-scores were associated with younger age (1.07 T-score points per 10 years, 95% CI 0.74, 1.40), female sex (1.81, 95% CI 0.63, 3.00), non-married status (0.99, 95% CI 0.14, 1.84), race or ethnicity other than White (1.79, 95% CI 0.72, 2.85), living in Canada (1.70, 95% CI 0.61, 2.79), the United Kingdom (1.53, 95% CI 0.06, 2.99) or France (2.01, 95% CI 0.98, 3.03) (vs the United States), higher BMI (0.11, 95% CI 0.03, 0.17), less time since non-Raynaud's symptom onset (0.82 per 10 years, 95% CI 0.40, 1.30), gastrointestinal involvement (2.70, 95% CI 1.52, 3.88), moderate small joint contractures (1.24, 95% CI 0.10, 2.38), the absence of interstitial lung disease (0.93, 95% CI -1.79, -0.07) and Sjögren disease (1.67, 95% CI 0.17, 3.17). Interstitial lung disease was not statistically significant when accounting for an interaction with country. Anxiety was also associated with pruritus and pain intensity in a sensitivity analysis that included variables with possible bi-directional pathways with anxiety. CONCLUSION: Anxiety symptoms were somewhat elevated among individuals with SSc and associated with multiple sociodemographic and disease factors.

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)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.289
Teacher spread0.270 · 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

Citations2
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueLara D. VeekenSame topicSystemic Sclerosis and Related DiseasesFrench-language works237,207