Measurement Properties and Interpretability of the Chronic Respiratory Disease Questionnaire (CRQ)
Bibliographic record
Abstract
The chronic respiratory questionnaire, available as an interviewer and a self-administered instrument, includes 20 items across four domains: dyspnea (5 items), fatigue (4 items), emotional function (7 items), and mastery (4 items). When completing this instrument, patients rate their experience on a 7-point scale ranging from 1 (maximum impairment) to 7 (no impairment). The Chronic Respiratory Questionnaire has demonstrated excellent measurement properties for both discriminative and evaluative purposes and served as a model in numerous methodological studies in chronic airflow limitation and patients with chronic obstructive pulmonary disease. We performed a systematic review of the literature on the chronic respiratory questionnaire to summarize the key qualities of the chronic respiratory questionnaire and to appraise the work regarding the minimal important difference of the chronic respiratory questionnaire. This paper includes a revision of our initial definition of the minimal important difference and a methodological framework for using anchor based approaches to establish the minimal important difference pioneered by Jaeschke and colleagues. Other approaches to evaluate the minimal important difference include distribution-based methods and panel-based methods. Investigators have used all of these approaches to establish the minimal important difference for the chronic respiratory questionnaire and the results are in general agreement with the minimal important difference of 0.5 for the mean domain scores of the chronic respiratory questionnaire. As a result of this literature review and discussion at the workshop, we established several research objectives. These objectives include the exploration of presentation of quality of life information and prospective anchor-based approaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".