The minimal important difference of the hospital anxiety and depression scale in patients with chronic obstructive pulmonary disease
Bibliographic record
Abstract
BACKGROUND: Interpretation of the Hospital Anxiety and Depression Scale (HADS), commonly used to assess anxiety and depression in COPD patients, is unclear. Since its minimal important difference has never been established, our aim was to determine it using several approaches. METHODS: 88 COPD patients with FEV1 </= 50% predicted completed the HADS and other patient-important outcome measures before and after an inpatient respiratory rehabilitation. For the anchor-based approach we determined the correlation between the HADS and the anchors that have an established minimal important difference (Chronic Respiratory Questionnaire [CRQ] and Feeling Thermometer). If correlations were >/= 0.5 we performed linear regression analyses to predict the minimal important difference from the anchors. As distribution-based approach we used the Effect Size approach. RESULTS: Based on CRQ emotional function and mastery domain as well as on total scores, the minimal important difference was 1.41 (95% CI 1.18-1.63) and 1.57 (1.37-1.76) for the HADS anxiety score and 1.68 (1.48-1.87) and 1.60 (1.38-1.82) for the HADS total score. Correlations of the HADS depression score and CRQ domain and Feeling Thermometer scores were < 0.5. Based on the Effect Size approach the MID of the HADS anxiety and depression score was 1.32 and 1.40, respectively. CONCLUSION: The minimal important difference of the HADS is around 1.5 in COPD patients corresponding to a change from baseline of around 20%. It can be used for the planning and interpretation of trials.
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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 | 0.013 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".