Mental Health Care Use and Associated Factors in Systemic Sclerosis: A Scleroderma <scp>Patient‐Centered</scp> Intervention Network Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Systemic sclerosis (SSc) has significant psychosocial implications. We aimed to evaluate the proportion of participants in a large international SSc cohort who used mental health services in a 3-month period and to evaluate demographic, psychological, and disease-specific factors associated with use. METHODS: Baseline data of participants enrolled in the Scleroderma Patient-Centered Intervention Network Cohort were analyzed. We determined the proportion that used mental health services and the source of services in the 3 months prior to enrollment. Multivariable logistic regression was used to identify variables associated with service use. RESULTS: Of the 2319 participants included in the analysis, 417 (18%) used mental health services in the 3 months prior to enrollment. General practitioners were the most common mental health service providers (59%), followed by psychologists (25%) and psychiatrists (19%). In multivariable analysis, mental health service use was independently associated with higher education (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.03-1.11), smoking (OR 1.06, 95% CI 1.02-1.11), being retired (OR 0.60, 95% CI 0.38-0.93), having limited SSc (OR 1.39, 95% CI 1.02-1.89), and having higher anxiety symptom scores (OR 1.04, 95% CI 1.03-1.06) and lower self-efficacy scores (OR 0.90, 95% CI 0.83-0.97). Variables not significantly associated included age, race, disease manifestations, depression symptom scores, and body image distress. CONCLUSION: About 18% of participants in a large international cohort received mental health services in a 3-month period, of whom the majority received these services from a general practitioner.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".