Psychological Disorders of Patients With Allergic Rhinitis in Chengdu, China: Exploratory Research
Bibliographic record
Abstract
BACKGROUND: The number of patients with allergic rhinitis (AR) has exceeded 500 million worldwide due to the unstable curative effect that can easily produce mental and psychological disorders. However, most of the relevant existing literature is one-on-one retrospective analyses or targeted meta-analyses of AR with psychological disorders like irritability, depression, and anxiety, while "multi-hospital + interdisciplinary" multiple regression analyses are scarce. OBJECTIVE: This study aims to precisely identify the psychological disorders of patients with AR who were diagnosed and treated in the five most renowned hospitals in Chengdu, China over the past 5 years using 10 classification methods so as to attract attention and care from otolaryngologists. METHODS: The Symptom Checklist 90 (SCL-90) was used to group and score the mental state of 827 strictly screened patients with AR according to 9 classification criteria. The scores were then compared within groups. Intergroup comparisons were made between the study group and the Chinese norm, and the positive factors for psychological disorders were extracted. Four symptoms in the study group, that is, nasal itching, sneezing, clear discharge, and nasal congestion, were scored on a visual analog scale. Partial correlation analysis was performed between the extracted positive factors for psychological disorders and the symptom scores by the multiple regression statistical method. RESULTS: Among 827 patients, 124 (15%) had no mental health impairments, 176 (21.3%) had mild impairments, 474 (57.3%) had mild to moderate impairments, 41 (5%) had moderate to severe impairments, and 12 (1.4%) had severe impairments. The average score of the SCL-90 for all 827 patients was 2.64 (SD 0.25), which corresponded to mild to moderate mental health impairments. The 827 patients scored significantly higher for the 4 positive factors: depression, anxiety, psychosis, and other (sleep, diet). Depression was positively correlated with sneezing and clear discharge, anxiety was positively correlated with nasal itching and congestion, psychosis was positively correlated with nasal itching and sneezing, and other (sleep, diet) was positively correlated with clear discharge and nasal congestion. CONCLUSIONS: Patients with AR have mild to moderate mental health impairments, with women and those with abnormal BMI, aged ≥45 years, with a monthly salary <¥5110 (US $700), with a disease duration <13 years, residing in urban areas, with a high school or above education, or who are indoor laborers being at high risk and requiring more care, follow-up, and comprehensive therapy from otolaryngologists.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".