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Record W2883792085 · doi:10.1002/dev.21766

Executive function in teen and adult women: Association with maternal status and early adversity

2018· article· en· W2883792085 on OpenAlexaff
Mayra Linné Almanza-Sepúlveda, Elsie Chico, Andrea González, Geoffrey B. Hall, Meir Steiner, Alison S. Fleming

Bibliographic record

VenueDevelopmental Psychobiology · 2018
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsPsychologyAssociation (psychology)Executive functionsDevelopmental psychologyWorking memoryAdverse Childhood ExperiencesClinical psychologyCognitionPsychiatryMental health

Abstract

fetched live from OpenAlex

The aim of this study was to determine the impact of maternal age on executive function and the moderating effects of women's maternal status and early-life experiences. Four groups of women were assessed as a function of their age (teens vs. adults) and maternal status (mothers vs. nonmothers). Participants completed executive function tests, including Spatial Working Memory (SWM), Intra-Extra-Dimensional-Set-Shift (IED), and Stockings of Cambridge (SOC). Women also completed the Childhood Trauma Questionnaire to assess their experiences of early adversity. Results showed that for the IED-task, there were main effects of age and maternal status and an interaction between the two; adults performed better than teens, mothers performed better than nonmothers, and teen nonmothers performed the least well of all groups. For the SWM-task, adults performed better than teens. Our results indicate that although age is an important factor for proper executive functioning, different tasks are affected differently and other factors such as maternity and adverse childhood experiences moderate this functioning.

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)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.008
GPT teacher head0.248
Teacher spread0.240 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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