Impact of Health Literacy on Patient-Reported Outcomes in Benign Gynecology: A Systematic Review
Bibliographic record
Abstract
The objective of this study was to systematically review the relationship between low health literacy and patient-reported outcomes in patients with benign gynecologic conditions. In this specific population, we also sought to determine the current reported prevalence of low health literacy, examine demographic characteristics that may be related to low health literacy, and collate any health literacy interventions described in the literature. A systematic search of MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase, The Cochrane Library, Web of Science, PubMed, and clinicaltrials.gov was performed on July 12, 2021, and repeated on October 13, 2023, for terms related to health literacy, specific health literacy measures, and benign gynecologic conditions. There were language or publication period restrictions. Inclusion required primary literature to report associations between health literacy and patient-reported outcomes, using validated tools to quantitatively measure each, in adult women with benign gynecologic conditions. Title screening, abstract screening, and full-text review were conducted with Covidence software (Melbourne, Australia) assisting with the review process. Of the 18,701 studies returned using our search strategy, 25 were selected for full-text review. Of these, no studies met inclusion criteria and reported an association between health literacy and patient-reported outcomes. This study identified a large gap in the literature. Future work should be directed at evaluating the association between health literacy and patient-reported outcomes in benign gynecology to inform patient-centered interventions and care provision.
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 | 0.017 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".