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Record W4402087816 · doi:10.1007/s10578-024-01752-9

Prospective Associations of Maternal Depressive Symptoms and Emotion Dysregulation with Children’s Internalizing Problems: The Moderating Role of Fathers

2024· article· en· W4402087816 on OpenAlexaff
Yihui Gong, Xin Feng, Meingold Hiu-ming Chan, Natasha Slesnick

Bibliographic record

VenueChild Psychiatry & Human Development · 2024
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of British Columbia
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsPsychologyAnxietyDepressive symptomsClinical psychologyLongitudinal studyDepression (economics)Developmental psychologyEmotional dysregulationPsychiatryMedicine

Abstract

fetched live from OpenAlex

Parents, including fathers, contribute to the early development of internalizing symptoms, which is observable and prevalent among young children. This longitudinal study examined the moderating role of paternal depressive symptoms/emotion dysregulation in the prospective associations between maternal depressive symptoms/emotion dysregulation and children's internalizing problems (depressive and anxiety symptoms). Ninety-four preschoolers and their mothers and fathers participated. Parents completed online questionnaires when their children were four years old and one year later. Results indicated that higher paternal depressive symptoms were associated with an increase, while lower paternal symptoms were associated with a decrease, in the negative impact of maternal emotion dysregulation on children's later depressive, but not anxiety, symptoms. We also tested the moderating role of paternal emotion dysregulation, these pathways were not significant. The findings enhance our understanding of the interaction between maternal and paternal psychological characteristics in contributing to children's anxiety and depressive symptoms.

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)0.000
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 score0.082
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.252
Teacher spread0.242 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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