EP31.13: Impact of educational videos on gynecologic patients' clinical experience: a knowledge translation quality initiative
Bibliographic record
Abstract
The primary objective is to evaluate the impact of educational videos on patients' understanding of their gynecology appointment which includes an ultrasound scan. Secondary objectives are to evaluate the effect of the educational videos on patients' anxiety level associated with the appointment and patients' acceptability of the videos. This is a pre-post intervention study among new patients (18-50 years old) with pelvic pain issues visiting Endometriosis Clinic at McMaster University for a consultation including an ultrasound scan. Participants completed electronic questionnaires before and after viewing two 7-minute online videos. A 12-item true/false knowledge quiz and a 20-question Spielberger's state–trait anxiety inventory (STAI) questionnaire were administered before and after viewing the videos. Ottawa acceptability questionnaire was also administered after watching the videos. A total of 13 patients were recruited. Patients' knowledge scores significantly increased after watching the videos (6.9 ± 1.8 vs. 8.6 ± 2.0, P-value = 0.02). There was a significant decrease in patients' anxiety levels after watching the videos (48.3 ± 4.6 vs. 45.1 ± 4.5, P-value = 0.006). Lastly, acceptability was high with 13/13 respondents (100%) indicating that educational videos were useful, and the amount of information provided was “just right” (100%) and “balanced” (92.3%). The educational videos were acceptable, improved patients' appointment knowledge, and decreased their anxiety. To the best of our knowledge, this is the first study on developing and evaluating educational videos specific to patients with pelvic pain issues with low health literacy.
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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 | 0.029 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".