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Record W3119966560 · doi:10.1017/s2040174420001348

Caregiving adversity during infancy and preschool cognitive function: adaptations to context?

2021· article· en· W3119966560 on OpenAlexaff

Bibliographic record

VenueJournal of Developmental Origins of Health and Disease · 2021
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsSocioemotional selectivity theoryCognitionFlexibility (engineering)Psychological interventionCognitive developmentCognitive flexibilitySocial cognitionCognitive skill

Abstract

fetched live from OpenAlex

From a conditional adaptation vantage point, early life caregiving adversity likely enhances aspects of cognition needed to manage interpersonal threats. Yet, research examining early life care and offspring cognition predominantly relies upon experiments including affectively neutral stimuli, with findings generally interpreted as "early-life caregiving adversity is, de facto, 'bad' for cognitive performance." Here, in a Southeast Asian sample, we examined observed maternal sensitivity in infancy and cognitive performance 3 years later as preschoolers took part in three tasks, each involving both a socioemotional (SE) and non-socioemotional (NSE) version: relational memory (n = 236), cognitive flexibility (n = 203), and inhibitory control (n = 255). Results indicate the relation between early life caregiving adversity and memory performance significantly differs (Wald test = 7.67, (1), P = 0.006) depending on the SE versus NSE context, with maternal sensitivity in infancy highly predictive of worse memory for SE stimuli, and amongst girls, also predictive of better memory when NSE stimuli are used. Results concerning inhibitory control, as well as cognitive flexibility in girls, also tentatively suggest the importance of considering the SE nature of stimuli when assessing relations between the caregiving environment and cognitive performance. As not all approaches to missing data yielded similar results, implications for statistical approaches are elaborated. We conclude by considering how an adaptation-to-context framework approach may aid in designing pedagogical strategies and well-being interventions that harness pre-existing cognitive strengths.

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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.021
GPT teacher head0.296
Teacher spread0.276 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of Developmental Origins of Health and DiseaseSame topicChild Abuse and TraumaFrench-language works237,207