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Record W4414608834 · doi:10.1037/fam0001407

Two-year trajectories of psychopathology and differential parenting during COVID-19: A sibling study.

2025· article· en· W4414608834 on OpenAlexafffund
Imogen M. Sloss, Mark Wade, Heather Prime, Dillon T. Browne

Bibliographic record

VenueJournal of Family Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsYork UniversityUniversity of Toronto
FundersCanada Research ChairsSociety for Research in Child Development
KeywordsMental healthPsychopathologySiblingLongitudinal studyMultilevel modelChild psychopathologyChild and adolescent psychiatryDepressive symptomsDifferential (mechanical device)

Abstract

fetched live from OpenAlex

= 1,098; aged 5-19 years) across seven waves between May 2020 and September 2022. Three-level multilevel models investigated the trajectories of child mental health symptoms, and the variance in outcomes attributed to between-family, within-family, and within-individual differences. Significant proportions of variance in child mental health were attributed to family differences, individual differences, and change over time. On average, child mental health improved over time, although these trajectories were nonlinear. Higher family-level positive parenting practices and lower family-level negative parenting practices were associated with lower child mental health problems for both siblings. Children who were disfavored (received more negativity/less positivity compared to their sibling) had higher levels of mental health problems. Both family-wide and individual-level factors play a role in child mental health during periods of stress, emphasizing the importance of considering parenting and mental health across layers of family organization. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

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)0.002
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 score0.149
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.051
GPT teacher head0.412
Teacher spread0.361 · 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
Published2025
Admission routes2
Has abstractyes

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