Impact of a 12-minute educational video prior to initial consultation in a Mature Women’s Health and Menopause Clinic
Bibliographic record
Abstract
OBJECTIVES: Assess acceptability of a 12-minute educational video before menopause clinic consultation and evaluate its impact on knowledge and treatment certainty. METHODS: This was a pre-post intervention study among new patients with vasomotor symptoms (VMS) referred to a menopause clinic in Toronto, Canada. Participants completed electronic questionnaires before and after viewing a 12-minute online video covering menopause facts and VMS treatments. Participants' demographic information and referring provider type were recorded. A 19-item true/false knowledge quiz and validated Decision Conflict Scale (DCS) were administered before and after viewing the video along with a validated Acceptability questionnaire after the video. Demographic information and acceptability were summarized descriptively and independent samples t tests compared knowledge and DCS total and subscores before and after viewing the education module. Multivariable analysis was used to identify factors associated with achieving treatment certainty. RESULTS: Seventy-one participants completed pre- and postintervention questionnaires. Mean age was 51.4 ± 6.0 years and most were White (58/71, 81.7%), had a university degree (24/71, 63.3%) and household income >$90,000 (53/71, 74.6%). After the video, there was significant increase in knowledge score (12.7 ± 2.1 vs. 16.9 ± 1.8, P < 0.001) and decrease in all DCS scores (total and five subscores) compared with preintervention scores (P < 0.001). Acceptability was high with 62/71 (87.3%) respondents indicating the tool was useful. Findings were independent of level of education, household income, and referring physician type. CONCLUSION: In a study of predominantly university-educated White women, a 12-minute education module on menopause and VMS treatment was acceptable, there was improved knowledge and decision certainty about VMS treatment.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".