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Record W4392469753 · doi:10.1017/s095457942400035x

Genetic and phenotypic evidence of the predictive validity of preschool parent reports of hyperactivity/impulsivity and inattention

2024· article· en· W4392469753 on OpenAlexaff
Ginette Dionne, Sara Mascheretti, Bei Feng, Hélène Paradis, Mara Brendgen, Frank Vitaro, Richard E. Tremblay, Michel Boivin

Bibliographic record

VenueDevelopment and Psychopathology · 2024
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalUniversité Laval
Fundersnot available
KeywordsImpulsivityHeritabilityPsychologyDevelopmental psychologyPredictive validityClinical psychologyGenetics

Abstract

fetched live from OpenAlex

Abstract To determine the validity of parent reports (PRs) of ADHD in preschoolers, we assessed hyperactivity/impulsivity (HI) and inattention (IN) in 1114 twins with PRs at 1.5, 2.5, 4, 5, 14, 15, and 17 years, and teacher-reports at 6, 7, 9, 10, and 12. We examined if preschool PRs (1) predict high HI/IN trajectories, and (2) capture genetic contributions to HI/IN into adolescence. Group-based trajectory analyses identified three 6–17 years trajectories for both HI and IN, including small groups with high HI ( N = 88, 10.4%, 77% boys) and IN ( N = 158, 17.3%, 75% boys). Controlling for sex, each unit of HI PRs starting at 1.5 years and at 4 years for IN, increased more than 2-fold the risk of belonging to the high trajectory, with incremental contributions (Odds Ratios = 2.5–4.5) at subsequent ages. Quantitative genetic analyses showed that genetic contributions underlying preschool PRs accounted for up to a quarter and a third of the heritability of later HI and IN, respectively. Genes underlying 1.5-year HI and 4-year IN contributed to 6 of 8 later HI and IN time-points and largely explained the corresponding phenotypic correlations. Results provide phenotypic and genetic evidence that preschool parent reports of HI and IN are valid means to predict developmental risk of ADHD.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.051
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.330
Teacher spread0.279 · 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 teacher head, 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
Published2024
Admission routes1
Has abstractyes

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