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Record W2294451219 · doi:10.1093/pch/21.2.74

The impact of an educational intervention on knowledge about infant crying and abusive head trauma

2016· article· en· W2294451219 on OpenAlexaff
Amy Ornstein, Eleanor Fitzpatrick, Jill Hatchette, Christy Woolcott, Linda Dodds

Bibliographic record

VenuePaediatrics & Child Health · 2016
Typearticle
Languageen
FieldMedicine
TopicChild Abuse and Related Trauma
Canadian institutionsDalhousie UniversityIzaak Walton Killam Health Centre
Fundersnot available
KeywordsCryingHead traumaShaken baby syndromeIntervention (counseling)MedicineHead (geology)PediatricsInfant cryingPsychologyChild abuseMedical emergencyPsychiatrySurgeryInjury preventionPoison control

Abstract

fetched live from OpenAlex

BACKGROUND: Infants follow a predictable trajectory of increased early crying. Frustration with crying is reported to be a trigger for abusive head trauma (AHT). OBJECTIVE: To evaluate the impact of postpartum delivery of the educational program, the Period of PURPLE Crying (PURPLE), in a group of first-time mothers. The primary objective was to determine whether there was a change in knowledge about infant crying and shaking after exposure to PURPLE. Factors associated with change in knowledge were also examined. METHOD: A total of 93 participants were recruited over a four-month period at a tertiary care hospital in Nova Scotia. Pre- and postintervention data were collected. RESULTS: Knowledge about infant crying increased significantly after program delivery (P=0.001). Low baseline crying knowledge was a significant predictor of increased knowledge about infant crying (P≤0.01). There was an insignificant decrease in shaking knowledge (P=0.5), which may have been the consequence of high baseline knowledge. CONCLUSION: An educational program for new parents appears to be warranted, especially with respect to improving knowledge about infant crying. This may have a positive benefit in AHT prevention. Additional studies are required to evaluate the impact of the program on other caregivers and on rates of AHT.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.015
GPT teacher head0.348
Teacher spread0.332 · 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 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

Citations13
Published2016
Admission routes1
Has abstractyes

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