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Record W2607356826 · doi:10.1097/jpn.0000000000000255

Pain Management During Newborn Screening

2017· article· en· W2607356826 on OpenAlexaff
Denise Harrison, Jessica Reszel, Bill Dagg, Cheryl Aubertin, Mariana Bueno, Sandra Dunn, Ann Fuller, JoAnn Harrold, Catherine Larocque, Stuart G. Nicholls, Margaret Sampson

Bibliographic record

VenueThe Journal of Perinatal & Neonatal Nursing · 2017
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsOntario Stroke NetworkOttawa HospitalChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsPsychological interventionMedicineOnline videoAnalyticsMultimediaNursing

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.298
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2017
Admission routes1
Has abstractyes

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