Self-administration and interviewer-administration of the German Chronic Respiratory Questionnaire: instrument development and assessment of validity and reliability in two randomised studies
Bibliographic record
Abstract
BACKGROUND: Assessment of health-related quality of life (HRQL) is important in patients with chronic obstructive pulmonary disease (COPD). Despite the high prevalence of COPD in Germany, Switzerland and Austria there is no validated disease-specific instrument available. The objective of this study was to translate the Chronic Respiratory Questionnaire (CRQ), one of the most widely used respiratory HRQL questionnaires, into German, develop an interviewer- and self-administered version including both standardised and individualised dyspnoea questions, and validate these versions in two randomised studies. METHODS: We recruited three groups of patients with COPD in Switzerland, Germany and Austria. The 44 patients of the first group completed the CRQ during pilot testing to adapt the CRQ to German-speaking patients. We then recruited 80 patients participating in pulmonary rehabilitation programs to assess internal consistency reliability and cross-sectional validity of the CRQ. The third group consisted of 38 patients with stable COPD without an intervention to assess test-retest reliability. To compare the interviewer- and self-administered versions, we randomised patients in groups 2 and 3 to the interviewer- or self-administered CRQ. Patients completed both the standardised and individualised dyspnoea questions. RESULTS: For both administration formats and all domains, we found good internal consistency reliability (Crohnbach's alpha between 0.73 and 0.89). Cross-sectional validity tended to be better for the standardised compared to the individualised dyspnoea questions and cross-sectional validity was slightly better for the self-administered format. Test-retest reliability was good for both the interviewer-administered CRQ (intraclass correlation coefficients for different domains between 0.81 and 0.95) and the self-administered format (intraclass correlation coefficients between 0.78 and 0.86). Lower within-person variability was responsible for the higher test-retest reliability of the interviewer-administered format while between person variability was similar for both formats. CONCLUSIONS: Investigators in German-speaking countries can choose between valid and reliable self-and interviewer-administered CRQ formats.
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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 | 0.153 | 0.213 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".