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Record W3012544919 · doi:10.3389/frym.2020.00031

Using Games to Train Doctors and Nurses to Save Babies at Birth

2020· article· en· W3012544919 on OpenAlexafffund
Simran K. Ghoman, Georg M. Schmölzer

Bibliographic record

VenueFrontiers for Young Minds · 2020
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
FundersUniversity of AlbertaChildren's Hospital FoundationStollery Children’s Hospital FoundationWomen and Children's Health Research InstituteChildren's Health Research InstituteHeart and Stroke Foundation of Canada
KeywordsNeonatal resuscitationCryingMedicineResuscitationBreathingNursingNeonatal nursingMedical emergencyPediatricsEmergency medicineAnesthesiaPsychiatry

Abstract

fetched live from OpenAlex

For parents, the sound of their newborn baby crying is a wonderful sign that the baby is healthy and breathing. However, millions of babies each year are born sick and depend on doctors and nurses to help them start breathing. Helping a baby breathe is called neonatal resuscitation. It is important that doctors and nurses practice performing the correct steps of neonatal resuscitation so that they are ready when a newborn baby needs their help. We created the boardgame RETAIN for doctors and nurses to play, to train their neonatal resuscitation knowledge and skills. We discovered that doctors and nurses significantly improved their knowledge of neonatal resuscitation after playing RETAIN. Building on this discovery, we may be able to use RETAIN to help doctors and nurses all around the world be better prepared to save babies at birth.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.000
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 head0.131
GPT teacher head0.391
Teacher spread0.260 · 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 designNot applicable
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

Citations0
Published2020
Admission routes2
Has abstractyes

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