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Developmental pathways linking childhood and adolescent internalizing, externalizing, academic competence, and adolescent depression

2016· article· en· W2411232482 on OpenAlexafffundabout
Murray Weeks, George B. Ploubidis, John Cairney, T. Cameron Wild, Kiyuri Naicker, Ian Colman

Bibliographic record

VenueJournal of Adolescence · 2016
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of AlbertaMcMaster UniversityUniversity of Ottawa
FundersEconomic and Social Research CouncilCanadian Institutes of Health ResearchHospital for Sick ChildrenCanada Research ChairsSick Kids Foundation
KeywordsPsychologyDevelopmental psychologyLongitudinal studyExternalizationAdolescent developmentDepressive symptomsLatent growth modelingCompetence (human resources)Early childhoodPath analysis (statistics)Clinical psychologyAnxietyPsychiatryMedicine

Abstract

fetched live from OpenAlex

This study examined longitudinal pathways through three domains of adaptation from ages 4-5 to 14-15 (internalizing problems, externalizing problems, and academic competence) towards depressive symptoms at age 16-17. Participants were 6425 Canadian children followed bi-annually as part of the National Longitudinal Study of Children and Youth. Within-domain (i.e., stability) effects were moderate in strength. We found longitudinal cross-domain effects across one time point (i.e., one-lag cascades) between internalizing and externalizing in early childhood (positive associations), and between academic competence and externalizing in later childhood and adolescence (negative associations). We also found cascade effects over multiple time points (i.e., multi-lag cascades); lower academic competence at age 4-5 and greater internalizing at age 6-7 predicted greater age 12-13 externalizing, and greater age 6-7 externalizing predicted greater age 16-17 depression. Important pathways towards adolescent depression include a stability path through childhood and adolescent internalizing, as well as a number of potential paths involving all domains of adaptation, highlighting the multifactorial nature of adolescent depression.

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 score0.455
Threshold uncertainty score0.904

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.026
GPT teacher head0.274
Teacher spread0.248 · 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

Citations94
Published2016
Admission routes3
Has abstractyes

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