Personally Generated Quality of Life Outcomes in Adults With Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To explore quality of life (QOL) using the individualized Patient Generated Index (PGI) in young adults who were diagnosed with juvenile idiopathic arthritis (JIA) in childhood, and to examine associations between PGI ratings and standardized health-related outcome measures. METHODS: Patients (N = 79, mean age 25.1 [SD 4.2] yrs, 72% female) completed the PGI and the standardized measures: Health Assessment Questionnaire-Disability Index, 12-item Short Form Health Survey (SF-12; physical and mental health-related QOL [HRQOL]), Brief Pain Inventory (pain severity and interference), 5-item Hopkins Symptom Checklist, and visual analog scale for fatigue. Information on morning stiffness, medications, and demographics was also collected. Patients were compared to 79 matched controls. RESULTS: The most frequently nominated areas of importance for patients' personally generated QOL (assessed by PGI) were physical activity (n = 38, 48%), work/school (n = 31, 39%), fatigue (n = 29, 37%) and self-image (n = 26, 33%). Nomination of physical activity was associated with older age, morning stiffness, and more pain interference. Nomination of fatigue was associated with current use of disease-modifying antirheumatic drugs, whereas nomination of self-image was associated with polyarticular course JIA and pain interference. Nomination of work/school was not associated with other factors. Higher PGI scores (indicating better QOL) correlated positively with all SF-12 subscales except role emotional, and negatively with disability, pain severity, pain interference, and morning stiffness. Compared to controls, patients had more pain, poorer physical HRQOL, and less participation in full-time work or school. CONCLUSION: Physical activity, work/school, fatigue, and self-image were frequently nominated areas affecting QOL in young adults with JIA. The PGI included aspects of QOL not covered in standardized measures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".