Diversity in pulmonary rehabilitation clinical trials: a systematic review of the literature
Bibliographic record
Abstract
Underrepresentation of minority groups in clinical trials may hinder the potential benefits of pulmonary rehabilitation (PR) programs for individuals with chronic obstructive pulmonary disease (COPD). The aim of this work was to determine whether participants in PR randomized control trials (RCTs) conducted in the U.S.A., Canada, the UK, and Australia are representative of ethnicity, sex, gender, and sociodemographic characteristics. A systematic search was performed for relevant literature from inception to December 2022. Titles and abstracts were screened before undergoing a full article review. Relevant data on reporting of age, sex, gender, ethnicity, and sociodemographic characteristics of participants was extracted. Thirty-six RCTs met the inclusion criteria. Only 6% of publications reported on ethnicity, with ≥90% of participants reported as ‘White.’ All 36 papers reported on age, with the mean between 60 and 69 years old. Thirty-five studies reported on sex (97%), with the majority (67%) reporting more male than female participants. There was no mention of different genders in any paper. Other sociodemographic factors were reported in 7 (19%) papers. Inclusivity and representation in clinical trials are essential to ensure that research findings are generalizable. Clinical trialists need to consider the demographics of today’s society during recruitment.
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 | 0.082 | 0.279 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".