Dyspnoea-12 and Multidimensional Dyspnea Profile: Systematic Review of Use and Properties
Bibliographic record
Abstract
CONTEXT: The Dyspnoea-12 (D-12) and Multidimensional Dyspnea Profile (MDP) were specifically developed for assessment of multiple sensations of breathlessness. OBJECTIVES: This systematic review aimed to identify the use and measurement properties of the D-12 and MDP across populations, settings and languages. METHODS: Electronic databases were searched for primary studies (2008-2020) reporting use of the D-12 or MDP in adults. Two independent reviewers completed screening and data extraction. Study and participant characteristics, instrument use, reported scores and minimal clinical important differences (MCID) were evaluated. Data on internal consistency (Cronbach's α) and test-retest reliability (intraclass correlation coefficient, ICC) were pooled using random effects models between settings and languages. RESULTS: A total 75 publications reported use of D-12 (n = 35), MDP (n = 37) or both (n = 3), reflecting 16 chronic conditions. Synthesis confirmed two factor structure, internal consistency (Cronbach's α mean, 95% CI: D-12 Total = 0.93, 0.91-0.94; MDP Immediate Perception [IP] = 0.88, 0.85-0.90; MDP Emotional Response [ER] = 0.86, 0.82-0.89) and 14 day test-rest reliability (ICC: D-12 Total = 0.91, 0.88-0.94; MDP IP = 0.85, 0.70-0.93; MDP ER = 0.84, 0.73-0.90) across settings and languages. MCID estimates for clinical interventions ranged between -3 and -6 points (D-12 Total) with small variability in scores over 2 weeks (D-12 Total 2.8 (95% CI: 2.0 to 3.7), MDP-A1 0.8 (0.6 to 1.1) and six months (D-12 Total 2.9 (2.0 to 3.7), MDP-A1 0.8 (0.6 to 1.1)). CONCLUSION: D-12 and MDP are widely used, reliable, valid and responsive across various chronic conditions, settings and languages, and could be considered standard instruments for measuring dimensions of breathlessness in international 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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".