Uso de questionários para avaliar a multidimensionalidade e a qualidade de vida do fibromiálgico
Bibliographic record
Abstract
UNLABELLED: Fibromyalgia syndrome (FMS) is a painful condition of unknown etiology, highly prevalent, and associated with other conditions, which causes great impact on daily life and quality of life. OBJECTIVE: To assess, due to the multifactorial character of the FMS, the discriminating power of instruments used to identify good indicators of self-assessment and self-knowledge. PATIENTS AND METHODS: This is a descriptive, exploratory, comparative, cross-sectional study with quantitative approach, and sample comprising a treatment group (T), diagnosed with FMS (n = 63) and a control group (C), undergoing interconsultation at the Pain Outpatient Clinic (n = 75). The following instruments were used: Fibromyalgia Impact Questionnaire (FIQ); visual analogue scale (VAS); McGill Pain Questionnaire; and the Post-Sleep Inventory (PSI). To evaluate the quality of life, Medical Outcomes Study 12-item Short-Form Health Survey (SF-12) was used. RESULTS: In the two groups, female gender predominated. The mean age of the sample was 42.3 ± 4.3 years, 45% were married, and the average schooling was 8 ± 3.5 years. The mean duration of pain was 3.2 years, and a mean time of two years were required for the clinical diagnosis of FMS in group T. Group T had higher levels of pain, anxiety, and depression, worse quality of sleep, less flexibility, and worse quality of life, although some of these symptoms were also present in group C. CONCLUSIONS: All instruments had good discriminating power (P < 0.05), especially FIQ, VAS and PSI, whose areas under the ROC curve were greater.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".