Editorial: Women in science: Pulmonary rehabilitation
Bibliographic record
Abstract
Pulmonary rehabilitationWorldwide, less than 30% of the workforce in research and development are women (1).Within the field of healthcare, however, female representation (74%) has made substantial gains (2).This is in line with data (2021) from the European Respiratory Society (ERS), showing a higher number of female members (69%) in comparison to male members within the "Allied Respiratory Professionals" Assembly, including amongst others lung function technologist, physiotherapists, nurses and psychologists.This is also visible in the Assembly's early career member category (less than 40 years of age), where women (68%) are also more represented.This increasing representativeness of the female gender is also seen in leadership roles, as five out of 10 (50%) most influenceable researchers (based on the number of publications in the last decade) in the field of pulmonary rehabilitation (PR) are female (3).The current topic on "Women in Science: Pulmonary Rehabilitation" celebrates the increasing representativeness and leadership of females in this research area.It intends to provide a stage for researchers who identify as a woman to present their research within the field of PR.In this topic collection, published research is clustered in two areas that can be considered hot topics in the latest years, namely regarding the settings where PR can be delivered and its role in the treatment of symptoms and extrapulmonary features. Pulmonary rehabilitation settingEvidence of the effects of PR on people with chronic obstructive pulmonary disease (COPD) is unequivocal and its implementation is advocated in guidelines worldwide (4).Still, patients' access to and completion of PR is low, with 8% to 50% of patients referred to PR never attending, and from those who attend, 10% to 32% not completing it (5).The most common barriers to accessing PR include geographic distance, difficulty in commuting and disruption of daily life routine (6).Increasing the variety of settings in which PR is delivered has been suggested to improve accessibility (4), but research in this area is taking its first steps.This research topic includes a rapid review and a randomized controlled trial (RCT) exploring the effects of home-based and community-based PR programs on health outcomes in people with COPD.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.018 | 0.020 |
| Insufficient payload (model declined to judge) | 0.037 | 0.032 |
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".