MétaCan
Menu
← Back to cohort
Record W2947451554 · doi:10.1093/pch/pxz066.092

93 Risk and protective factors for self-regulation at school entry

2019· article· en· W2947451554 on OpenAlexaffabout
Erin Hetherington, Sheila McDonald, Nicole Racine, Suzanne Tough

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsLogistic regressionProtective factorPsychological interventionCohortMedicineLongitudinal studyDemographyPsychologyEarly childhoodClinical psychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Self-regulation, defined as the ability to manage emotions, regulate behaviors, and focus attention, are developed early in childhood and provide the underpinnings for social, emotional, academic, and behavioural well-being in childhood. Early identification of factors associated with poor-self regulation can help inform interventions to promote school readiness. What factors are associated with poor self-regulation among children at age 5? A total of 1688 women participating in a longitudinal pregnancy cohort study in a Canadian city completed questionnaires from pregnancy up to when their children were five years of age. Self-regulation was measured at age 5 by maternal report on the Behavioural Assessment Scale for Children-2 (BASC-2). Children who scored “at risk” on the attention, executive function or emotion control subscales were considered to be at risk for poor self-regulation. Risk and protective factors included maternal and child characteristics, maternal mental health, and family environment, measured at age 3. Multivariable logistic regression models were used to estimate adjusted odd ratios (AOR) for poor self regulation. Twenty-one percent of children had lower self-regulation skills, and this was higher among boys (24%) compared to girls (19%). Risk factors for poor self-regulation included lower family income (AOR 1.45 95% CI 1.07, 1.95), mothers with a history of adverse childhood experiences (AOR 1.53, 95%CI 1.08, 2.14), and mothers with lower emotional stability (AOR 2.16 95% CI 1.57, 2.97). Protective factors included high levels of social support (0.65, 95%CI 0.47, 0.88). Several parenting styles were assessed, and only children of mothers who engaged in more hostile parenting behaviours were more likely to have poor self-regulation skills at age five (AOR: 3.00 95%CI: 2.21, 4.06). Children who watched more than 1 hour of television per day had a 1.35 increased odds (95% CI: 1.04, 1.73) of poor self-regulation. Children are at risk of lower self-regulation due to both family circumstances (lower income) as well as maternal experiences and emotional instability. Hostile parenting puts children at particular risk for poor self-regulation and strategies that support alternate parenting approaches could be beneficial. Finally, monitoring and managing screen time may allow children to engage in other opportunities that foster self-regulation skills.

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)0.003
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 score0.183
Threshold uncertainty score0.364

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.011
GPT teacher head0.267
Teacher spread0.257 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuePaediatrics & Child Health→Same topicChild and Adolescent Psychosocial and Emotional Development→French-language works237,207→