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Record W2995422925 · doi:10.1177/0844562119894184

Maternal Prenatal Anxiety and Children’s Externalizing and Internalizing Behavioral Problems: The Moderating Roles of Maternal-Child Attachment Security and Child Sex

2019· article· en· W2995422925 on OpenAlexafffundvenueabout
Elena Ali, Nicole Létourneau, Karen Benzies, Henry Ntanda, Deborah Dewey, Tavis S. Campbell, Gerry Giesbrecht

Bibliographic record

VenueCanadian Journal of Nursing Research · 2019
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsAnxietyPsychologyClinical psychologyAssociation (psychology)Developmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Prenatal anxiety is associated with child behavioral problems. Prenatal anxiety is predictive of postnatal anxiety which can interfere with the security of maternal-child attachment and further raise the risk of child behavior problems. Secure maternal-child attachment is essential for optimal emotional health. Sex influences the type of behavior problem experienced. There is a gap in understanding whether attachment security and the sex of the child can moderate association between prenatal anxiety and children's behavioral problems. PURPOSE: To examine the association between prenatal anxiety and child behavioral problems and to test the moderating effects of attachment security and child sex on the association between prenatal anxiety and child behavioral problems. METHODS: Secondary analysis of data from 182 mothers and their children, enrolled in the Alberta Pregnancy Outcomes and Nutrition Study using Hayes' (2013) conditional process modeling. RESULTS: = 0.01) behaviors only in children with an insecure style of attachment. Child sex did not moderate the association between prenatal anxiety and children's behavioral problems. CONCLUSIONS: Attachment security moderated the association between prenatal anxiety and children's externalizing and internalizing behavioral problems.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.725

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 integrity0.0000.001
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 head0.036
GPT teacher head0.360
Teacher spread0.324 · 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

Citations16
Published2019
Admission routes4
Has abstractyes

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