Cognitive Behavioral Therapy for Youth With Childhood‐Onset Lupus: A Randomized Clinical Trial
Bibliographic record
Abstract
Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐Onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist. We expected that TEACH would be considered feasible and acceptable based on recruitment and retention rates. We also examined the effect of TEACH on youths’ depressive, fatigue, and pain symptoms compared to medical treatment as usual (TAU). Methods A pilot two‐arm longitudinal randomized controlled clinical trial was conducted. Adolescents (12–17 years) and young adults (18–22 years) with childhood‐onset systemic lupus erythematosus and elevated depressive, fatigue, and/or pain symptoms were recruited from six pediatric rheumatology sites across the United States and Canada from August 2020 to March 2023. Participants were randomized 1:1 to TEACH and TAU or TAU alone and reported symptom data at baseline and eight weeks later. Results Of the 200 youth approached, 97 consented to participate (48.5% recruitment). Among 64 eligible participants, 32 were randomized to TEACH and TAU and 32 to TAU alone. Retention was high (92.2%). At postassessment, the intervention group demonstrated reductions in depressive (C emm 7.88, 95% confidence interval 3.20–12.60; 14%) and fatigue (C emm 3.91, 95% confidence interval 0.44–7.39; 7%) symptoms but not pain (C emm 0.89, 95% confidence interval −0.06 to 1.84). Conclusion This remotely delivered cognitive behavioral intervention tailored to youth with lupus was feasible and associated with reduced depressive and fatigue symptoms compared with medical TAU. Further increasing accessibility by implementing TEACH in medical settings may improve uptake and patient outcomes. image
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".