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Record W4285495963 · doi:10.1111/jcpp.13667

Genetic and environmental influences on temperament development across the preschool period

2022· article· en· W4285495963 on OpenAlexaff
Chang Liu, Yao Zheng, Jody M. Ganiban, Kimberly J. Saudino

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2022
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Alberta
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNational Institute of Mental Health
KeywordsTemperamentNegative affectivityPsychologyDevelopmental psychologyPositive affectivityPersonalitySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Preschoolers' temperament characteristics are associated with children's long-term development. Such links underscore the importance of understanding factors that shape temperament during preschool. This is the first study to examine genetic and environmental sources of developmental growth in three temperament dimensions: surgency, negative affectivity, and effortful control, during the preschool period. METHODS: Biometric latent growth curve modeling was used to examine genetic, shared, and nonshared environmental contributions to the invariant level of and developmental growth in temperament, using a sample of 310 same-sex twin pairs (MZ = 123, DZ = 187) assessed at 3, 4, and 5 years of age. Temperament was assessed using primary caregiver's report on the Child Behavior Questionnaire-Short Form. RESULTS: All three temperament dimensions demonstrated linear increases from ages 3 to 5 years. The invariant levels of all three temperament dimensions were explained by genetic and nonshared environmental factors. Growth in surgency was fully explained by nonshared environmental factors, while growth in negative affectivity was mainly explained by genetic factors. Growth in effortful control was explained by genetic and nonshared environmental factors, although neither were significant due to large bootstrap standard errors. For negative affectivity and effortful control, the genetic factors that contributed to developmental growth were independent from those associated with their invariant levels. CONCLUSIONS: Collectively, these findings indicate that both genetic and nonshared environmental factors play important roles in the invariant levels of temperament. Findings also accord a critical role of children's nonshared environment in the development of surgency and to a lesser extent negative affectivity and effortful control. It is also notable that novel genetic effects contribute to developmental growth in negative affectivity and effortful control as children age, emphasizing the importance of integrating developmental models in genetic research.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.272
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2022
Admission routes1
Has abstractyes

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