MétaCan
Menu
Back to cohort
Record W3159682307 · doi:10.1177/2167702621993887

Growth in Self-Regulation Over the Course of Adolescence Mediates the Effects of Foster Care on Psychopathology in Previously Institutionalized Children: A Randomized Clinical Trial

2021· article· en· W3159682307 on OpenAlexaff
Cora Mukerji, Mark Wade, Nathan A. Fox, Charles H. Zeanah, Charles A. Nelson

Bibliographic record

VenueClinical Psychological Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsUniversity of Toronto
FundersNational Institute of Mental HealthBinder Family FoundationJohn D. and Catherine T. MacArthur Foundation
KeywordsPsychopathologyPsychosocialFoster carePsychologyInstitutionalisationRandomized controlled trialDevelopmental psychologyClinical psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Children reared in institutions experience severe psychosocial deprivation, with lasting consequences for social and emotional development. This study evaluated growth trajectories of self-regulation from ages 8 to 16 among institutionally-reared children randomized to foster care (foster care group; FCG) or to remain in institutional care (care as usual group; CAUG), compared to a never-institutionalized group (NIG). We then tested a developmental pathway by which growth in self-regulation reduces general psychopathology at 16 for FCG versus CAUG. FCG experienced modest growth in self-regulation over adolescence and "caught up" to NIG by age 16. The beneficial effect of foster care on psychopathology operated through growth in self-regulation; part of this effect was further mediated by reduced peer difficulties for FCG. Findings reveal that the effects of foster care on self-regulation emerge over adolescence and that growth in self-regulation is a mechanism by which foster care mitigates the impact of institutionalization on psychopathology.

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)0.002
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.040
GPT teacher head0.444
Teacher spread0.403 · 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 designRandomized trial
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

Citations12
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueClinical Psychological ScienceSame topicChild Welfare and AdoptionFrench-language works237,207