Spouse depression and disease course among persons with rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVE: To examine the role of spouse mood in the disability and disease course of persons with rheumatoid arthritis (PWRA). METHODS: A total of 133 married PWRA completed questionnaires, including the Rheumatoid Arthritis Disease Activity Index and the Disabilities of the Arm, Shoulder, and Hand, assessing PWRA arthritis disease activity and disability, respectively, at 2 time points 1 year apart. In addition, both PWRA and their spouses completed the Center for Epidemiologic Studies Depression Scale, a standardized community measure of depression at both time points. RESULTS: Multiple regression analysis revealed spouse depressive symptoms at initial assessment to be predictive of followup PWRA disability and disease activity, even after controlling for initial levels of PWRA depression, disability, disease activity, age, number of years married, education, disease duration, and employment. Specifically, higher levels of spouse depression predicted worse disease course over a 1-year period for PWRA, as indicated by higher reports of subsequent PWRA disability and disease activity. CONCLUSION: Our findings highlight the key role played by the spouse in PWRA disease course, and point to the importance of including the spouse in clinical interventions. Implications for theory, research, and treatment are discussed with a focus on examining pathways through which spouse depressive symptoms may affect PWRA disease course and disability.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".