Comparing written and verbal delivery of a treatment regimen to women with overactive bladder: a randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: Overactive bladder is a common condition among aging women requiring a multifaceted treatment approach, which is usually communicated by physician to the patient in the clinic setting. The objective of this two-center, randomized controlled trial was to determine if a transcribed list of six management strategies for overactive bladder improves immediate and delayed retention of these recommendations compared with a traditional verbal discussion. METHODS: Between March, 2015 and February, 2019, women newly diagnosed with overactive bladder were randomized to either the intervention group, where they received a transcribed list of six treatment recommendations, or to the control group, where the same six recommendations were communicated verbally by their physician. Participants in both groups were asked to recall treatment recommendations immediately after their appointment and 2 weeks later. A score out of 6 was assigned at each time point based on the number of recommendations participants could list. Scores at each point of recall were compared between groups. RESULTS: Seventy-two women were recruited and randomized to either the written instruction (n = 34) or verbal discussion group (n = 38). Immediate total retention score was significantly better for women who received the transcribed list compared with those receiving verbal communication (P = 0.002). There was no difference in 2-week total information retention scores between groups. CONCLUSIONS: A written list of recommendations is a quality improvement initiative that can improve overactive bladder participants' immediate retention of a suggested treatment regimen, but lacks impact 2 weeks later.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".