Comparison of clinic models for patients with work-related asthma
Bibliographic record
Abstract
BACKGROUND: Work-related asthma (WRA) is a prevalent occupational lung disease that is associated with undesirable effects on psychological status, quality of life (QoL), workplace activity and socioeconomic status. Previous studies have also indicated that clinic structure may impact outcomes among patients with asthma. AIMS: To identify the impact of clinic structure on psychological status, QoL, workplace limitations and socioeconomic status of patients with WRA among two different tertiary clinic models. METHODS: We performed a cross-sectional analysis between two tertiary clinics: clinic 1 had a traditional referral base and clinical staffing while clinic 2 entirely comprised Worker's Compensation System referrals and included an occupational hygienist and a return-to-work coordinator. Beck Anxiety and Depression II Inventories (BAI and BDI-II), Marks' Asthma Quality of Life Questionnaire (M-AQLQ) and Work Limitation Questionnaire (WLQ) were used to assess outcomes for patients with WRA. RESULTS: Clinic 2 participants had a better psychological status across the four instruments compared with clinic 1 (for Beck 'Anxiety': P < 0.001 and 'Depression': P < 0.01, 'Mood' domain of M-AQLQ: NS and 'Mental Demands' domain of WLQ: P < 0.01). Clinic 2 had a greater proportion of participants with reduced income. CONCLUSIONS: Our study indicates that clinic structure may play a role in outcomes. Future research should examine this in larger sample sizes.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".