Health Literacy and Disease Understanding Among Aging Women With Pelvic Floor Disorders
Bibliographic record
Abstract
OBJECTIVES: Few studies on health literacy and disease understanding among women with pelvic floor disorders have been published. We conducted a pilot study to explore the relationship between disease understanding and health literacy, age, and diagnosis type among women with urinary incontinence and pelvic organ prolapse. METHODS: The study subjects were recruited from urology and urogynecology specialty clinics based on a chief complaint suggestive of urinary incontinence or pelvic prolapse. Subjects completed questionnaires to assess symptom severity, and health literacy was measured using the Test of Functional Health Literacy in Adults. Patient-physician interactions were audiotaped during the office visit. Immediately afterward, patients were asked to describe diagnoses and treatments discussed by the physician and record them on a checklist, with follow-up phone call, where the same checklist was administered 2 to 3 days later. RESULTS: A total of 36 women with pelvic floor disorders, aged 42 to 94 years, were enrolled. We found that health literacy scores decreased with increasing age. However, all patients had low percentage recall of their pelvic floor diagnoses and poor understanding of their pelvic floor condition despite high health literacy scores. Patients with pelvic prolapse seemed to have worse recall and disease understanding than patients with urinary incontinence. CONCLUSIONS: High health literacy as assessed by the Test of Functional Health Literacy in Adults may not correlate with patients' ability to comprehend complex functional conditions such as pelvic floor disorders. Lack of understanding may lead to unrealistic treatment expectations, inability to give informed consent for treatment, and dissatisfaction with care. Better methods to improve disease understanding are needed.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".