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Record W2168620164 · doi:10.1093/jpepsy/jsv067

Caregiver Emotional Availability, Caregiver Soothing Behaviors, and Infant Pain During Immunization

2015· article· en· W2168620164 on OpenAlexafffund
Nicole Atkinson, Hannah Gennis, Nicole Racine, Rebecca Pillai Riddell

Bibliographic record

VenueJournal of Pediatric Psychology · 2015
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsHospital for Sick ChildrenYork University
FundersOntario Ministry of Research and InnovationCanadian Institutes of Health Research
KeywordsMultivariate analysis of variancePsychologyAnalysis of varianceMultivariate analysisClinical psychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether caregivers with more extreme emotional availability scores enact different levels of soothing behaviors and whether infants of these caregivers differ in their pain scores across the first year of life. METHODS: Cross-sectional analyses (analyses of variance and multivariate analyses of variance) were conducted with parent-infant dyads at 2, 4, 6, and 12 months of age who had extreme caregiver emotional availability scores. Pain scores were examined using a minimum clinically significant difference. RESULTS: Infants with lower pain scores had caregivers who were in the high emotional availability group. This effect was most pronounced during the regulatory period at 2 months, and clinically significant differences in pain scores were found during the regulatory period at 12 months. Physical comforting and/or rocking were characteristic of caregivers with high emotional availability. CONCLUSION: This study suggests that caregiver emotional availability, in the extremes, do have clinically meaningful relationships with infant pain regulation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.027
GPT teacher head0.319
Teacher spread0.293 · 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

Citations24
Published2015
Admission routes2
Has abstractyes

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