A risk calculator to predict adult attention-deficit/hyperactivity disorder: generation and external validation in three birth cohorts and one clinical sample
Arthur Caye; Jessica Agnew‐Blais; Louise Arseneault; Helen Gonçalves; Christian Kieling; K. Langley; Ana Maria B. Menezes; Terrie E. Moffitt · 2019 · Epidemiology and Psychiatric Sciences
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
AIM: Few personalised medicine investigations have been conducted for mental health. We aimed to generate and validate a risk tool that predicts adult attention-deficit/hyperactivity disorder (ADHD). METHODS: Using logistic regression models, we generated a risk tool in a representative population cohort (ALSPAC - UK, 5113 participants, followed from birth to age 17) using childhood clinical and sociodemographic data with internal validation. Predictors included sex, socioeconomic status, single-parent family, ADHD symptoms, comorbid disruptive disorders, childhood maltreatment, ADHD symptoms,
Abstract by Arthur Caye; Jessica Agnew‐Blais; Louise Arseneault; Helen Gonçalves; Christian Kieling; K. Langley; Ana Maria B. Menezes; Terrie E. Moffitt, Epidemiology and Psychiatric Sciences (2019) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1017/s2045796019000283
