Bibliographic record
Abstract
OBJECTIVES: This study aims to evaluate psychological disorders such as impulsivity, alexithymia, depression, and anxiety and to analyze the relationship between psychiatric disorders and disease activity, fatigue and quality of life in ankylosing spondylitis (AS) patients. PATIENTS AND METHODS: Between May 2016 and January 2017, a total of 70 AS patients (30 females, 40 males; mean age 42.9±10.5 years; range, 22 to 70 years) and 56 healthy controls (27 females; 29 males; mean age 44.8±13.0 years; range, 21 to 70 years) were included. Demographic characteristic, laboratory analyses, disease activity, quality of life, functionality, fatigue, and psychological disorders were assessed. The Ankylosing Spondylitis Disease Activity Score (ASDAS), Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Metrology Index (BASMI), Nottingham Health Profile (NHP) and Ankylosing Spondylitis Quality of Life (ASQOL), Fatigue Severity Scale (FSS), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Toronto Alexithymia Scale (TAS-20), Eating Attitude Test (EAT), and Barratt Impulsiveness Scale-11 (BIS-11) were used. Significant predictors for anxiety, depression and impulsiveness were evaluated using multivariate analyses. RESULTS: The BDI (13.88±8.99; 9.78±8.34), BAI (14.58±10.02; 10.53±8.99), and non-planning impulsivity (26.00±4.57; 24.28±3.77) scores were higher in the AS group than controls (p=0.01; p=0.01; p=0.02 respectively). Non-planning impulsivity was correlated with fatigue, social isolation, and depression (p=0.03; p=0.01; p=0.01 respectively). Multivariate analyses showed that fatigue scores were positively associated with non- planning impulsiveness. CONCLUSION: Impulsivity may be one of the psychiatric disorders associated with AS, such as the more commonly known anxiety and depression. Fatigue is considered as a critical target for increased impulsivity.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".