#postbabyhankypanky: An Empirically Based Knowledge Sharing Initiative About Sex and the Transition to Parenthood
Bibliographic record
Abstract
Despite the many sexual concerns experienced by new parents, and their reported desire for more information on this topic, both parents and healthcare providers remain reticent to broach the subject. The goal of this project was to disseminate evidence-based knowledge from our prior research in a way that was accessible, engaging, and would spark further interest and communication for both new parents and healthcare providers. We convened a multidisciplinary advisory group that also involved community parents who provided feedback at all phases of this project. We developed five brief YouTube videos, each featuring a core research finding. Following an empirically supported strategic knowledge translation plan, we disseminated the videos to our target audiences (i.e., expectant and new parents, healthcare providers, educators, and other stakeholders) using social media from February 2018 to November 2019. Data were collected using YouTube analytics and an online survey (convenience sample: N = 225 parents; N = 161 healthcare providers). From the date of the launch, the videos had a reach of 91,766 views from 14 countries, with viewers watching an average of 90% of a video. Overall, quantitative and qualitative survey results suggested that the videos were acceptable and appropriate, and respondents were more confident and comfortable discussing sexual issues (with their partner/with their patients) and would like more information about postpartum sexuality after watching the videos. YouTube videos are an acceptable and effective way to disseminate evidence aimed at raising awareness of factors affecting sexuality in the transition to parenthood.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".