Pain Management During Newborn Screening
Bibliographic record
Abstract
To assess the reach, acceptability, and effect of the BSweet2Babies video showing breast-feeding, skin-to-skin care, and sucrose during blood sampling on intention to recommend the video or advocate for use of the interventions. In July 2014, the video and an electronic survey were produced and posted. After 1 year, the online viewer survey responses and YouTube analytics were analyzed. One year after posting, the BSweet2Babies video had 10 879 views from 125 countries and 187 (1.7%) viewers completed the survey. Most respondents were aware of the analgesic effects of breast-feeding, skin-to-skin care, and sucrose. Nearly all respondents (n = 158, 92%) found the BSweet2Babies video to be a helpful resource and 146 (84%) answered that they would recommend the video to others. After viewing the video, 183 (98%) respondents answered that they would advocate for 1 or more of the interventions. The BSweet2Babies video showing effective pain treatment during blood sampling had a large reach but a very small response rate for the survey. Therefore, analysis of acceptability and effect on intention to recommend the video and advocate for the interventions depicted are limited. Further research is warranted to explore how to best evaluate videos delivered through social media and to determine the effect of the video to promote knowledge translation into clinical practice.
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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 | 0.002 | 0.016 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".