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Hyperactivity‐inattention symptoms in childhood and suicidal behaviors in adolescence: the Youth Gazel Cohort

2008· article· en· W2035181727 on OpenAlexaff
Cédric Galéra, M.-P. Bouvard, Gaëlle Encrenaz, Antoine Messiah, Éric Fombonne

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2008
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsPsychopathologyPoison controlSuicide preventionPsychologyInjury preventionPsychiatryPopulationCohortClinical psychologySuicide attemptSuicidal behaviorHuman factors and ergonomicsMedicineMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: Although a link has been suggested between attention deficit/hyperactivity disorder (ADHD) and completed suicide, little is known about the association with suicidal behaviors in community settings. This study addresses the relationship between childhood hyperactivity-inattention symptoms (HI-s) and subsequent suicidal behaviors. METHOD: Nine hundred sixteen subjects aged 7-18 were recruited from the general population and surveyed in 1991 and 1999. Parent and adolescent self-reports provided psychopathology and suicidal behavior pattern measures. Multivariate modeling was used to evaluate the effects of childhood HI-s and other risk factors on adolescent suicidal behaviors. RESULTS: In males, HI-s independently accounted for the risk of lifetime suicide plans/attempts (OR=3.25, P = 0.02) and adolescent 12-month prevalence rates of suicide plans/attempts (OR=5.46, P = 0.03). In females, HI-s did not independently heighten the likelihood of suicidal behaviors. CONCLUSION: This survey suggests a possible specific link between HI-s and suicide plans/attempts in males.

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)0.001
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 score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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

Citations60
Published2008
Admission routes1
Has abstractyes

Explore more

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