Effect of symptoms expression difficulty and excessive physical perception on asthma control test results
Bibliographic record
Abstract
Introduction and Objective: Asthma is a chronic disease that airway inflammation is persistent, even if the symptoms are episodic. Asthma control test is a subjective test consisting of 5 questions, based on the patient9s self-reported respiratory symptoms. In this study, the relationship between asthma control, quality of life, body sensation and symptom expression adequacy was investigated in asthmatic patients. Method: ACT, SF-36 Quality of Life Scale, The Body Sensations Questionnaire (BSQ) and The Toronto Alexithymia Scale(TAS) were applied to the patients who were followed-up with the diagnosis of asthma. The scales were applied to each patient once and the relationship between each other was investigated. The BSQ is measures patients excessive perception of fear and symptoms. The TAS is a 20 item instrument that is one of the most commonly used measures of alexithymia. Alexithymia refers to people who have trouble identifying and describing emotions ; SF-36 was used to evaluate the quality of life. Results: 60 patients were included in the study. There was a significant relationship between ACT scoring and SF-36 quality of life scoring. The scales were calculated with pearson correlation coefficients. There was an inverse ratio between BSQ and ACT (p:0.011,r:-0.327). There was no significant correlation between ACT and TAS-20 (p:0,146, r:-0,190). Correlation table of ACT and BSQ with SF-36 is significant correlation was found. This shows us that the deterioration in the quality of life will cause an increase in symptoms and fears. It is thought that exaggerated symptoms will decrease the ACT scores and cause more drug use. However, more studies are needed on this subject.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".