Measuring Dyspnea and Perceived Exertion in Healthy Adults and with Respiratory Disease: New Pictorial Scales
Bibliographic record
Abstract
BACKGROUND: Dyspnea or perceived exertion during exercise is most commonly measured using Borg or visual analog scales, created for use in adults. In contrast, pictorial scales have been promoted for children due to skepticism concerning applicability of the said scales in pediatrics. We sought to validate our newly created, pictorial Dalhousie Dyspnea and Perceived Exertion Scales in adult populations and compare ratings with the Borg scale. METHODS: Dyspnea and perceived exertion ratings obtained with both modified Borg CR-10 and Dalhousie scales during maximal cycle exercise were compared in 24 healthy adults and 17 with various pulmonary disorders. Scale ratings for perceived exertion were plotted against work while ratings for dyspnea were plotted against ventilation using previously developed alternative models to simple power law. Goodness of fit was determined by lowest root-mean-square error or by corrected Akaike information criterion. RESULTS: Pictorial ratings of dyspnea and perceived exertion measured by both scale ratings rose as expected with increasing exercise intensity, and individual trajectories obtained by either scale were virtually superimposable in 90 % of subjects. In general, the lowest root-mean-square error or corrected Akaike information criterion was found with models which incorporated a time delay, defined as the fraction of maximum work or ventilation at which point a clear increase in ratings above resting level was reported. CONCLUSIONS: The Dalhousie Dyspnea and Exertion Scales offer an equally good alternative to the Borg scale for measuring dyspnea and perceived exertion in adults.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".