Patient‐Reported Outcome Measures for Pelvic Organ Prolapse: A Systematic Review Using the <scp>COnsensus</scp>‐Based Standards for the Selection of Health Measurement Instruments (<scp>COSMIN</scp>) Checklist
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcome measures (PROMs) are recommended to measure the impact of a health condition or intervention effectiveness as they aim to capture what is most meaningful to patients. Several PROMs are used to evaluate pelvic organ prolapse (POP)-related domains, yet the measurement properties of these instruments have not been fully explored with a rigorous analysis of the methodological quality and quality of evidence. OBJECTIVE: To conduct a systematic review reporting on the measurement properties of PROMs used for the assessment of POP-related domains in accordance with the COSMIN guidelines. SEARCH STRATEGY: Five databases were searched from inception to December 2023. SELECTION CRITERIA: Studies were eligible if they involved (1) at least one group of female adults diagnosed with or presenting with symptoms of POP; (2) a self-reported outcome measure (PROMs, questionnaires) to evaluate POP-related domains; and (3) at least one measurement property. DATA COLLECTION AND ANALYSIS: Methodological quality and measurement quality were assessed using the COSMIN risk of bias (ROB) checklist and the COSMIN criteria for good measurement properties. MAIN RESULTS: A total of 13 PROMs were included. The BIPOP had the lowest ROB for Content Validity. The POP-SS was the only PROM with sufficient evidence of adequate construct validity and responsiveness to be used in both surgical and conservative management settings. CONCLUSION: This original work identified a gap in evidence regarding the measurement qualities of identified PROMs used in the POP population.
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 | 0.025 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".