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Record W2041318321 · doi:10.1258/135763303771005234

Effective delivery of neonatal stabilization education using videoconferencing in Manitoba

2003· article· en· W2041318321 on OpenAlexaffabout
Liz Loewen, MM Seshia, Debbie Fraser Askin, Catherine Cronin, Stephanie Roberts

Bibliographic record

VenueJournal of Telemedicine and Telecare · 2003
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsSt. Boniface HospitalUniversity of ManitobaHealth Sciences CentreWinnipeg Regional Health Authority
Fundersnot available
KeywordsVideoconferencingModalitiesTest (biology)MedicineHealth professionalsPsychologyMedical educationNursingMultimediaHealth careComputer science

Abstract

fetched live from OpenAlex

We compared face-to-face and videoconference delivery of an education programme for health professionals on the subject of neonatal stabilization skills. A pre-test/post-test control group design was used to compare knowledge acquisition and satisfaction between the two modalities. There were no statistically significant differences between delivery modalities for knowledge acquisition. Both groups showed significant gains in knowledge when pre- and post-test scores were compared. Responses to most of the items in a survey of satisfaction with the course did not differ significantly between the two groups. Face-to-face participants expressed higher levels of comfort in interacting with the presenter, and those in the videoconference group were more willing to receive the course via videoconference in the future. Videoconferencing provided an effective and acceptable way of delivering neonatal stabilization skills.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.324
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations24
Published2003
Admission routes2
Has abstractyes

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