关键词: ADHD BCS70 IRT data mining

Mesh : Attention Deficit Disorder with Hyperactivity / diagnosis psychology Child Data Mining / methods Diagnostic and Statistical Manual of Mental Disorders Female Humans Male Psychiatric Status Rating Scales Psychometrics Reproducibility of Results Retrospective Studies United Kingdom

来  源:   DOI:10.1002/mpr.1753   PDF(Sci-hub)   PDF(Pubmed)

Abstract:
To facilitate future outcome studies, we aimed to develop a robust and replicable method for estimating a categorical and dimensional measure of Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) attention deficit hyperactivity disorder (ADHD) in the 1970 British Cohort Study (BCS70).
Following a data mining framework, we mapped DSM-5 ADHD symptoms to age 10 BCS70 data (N = 11,426) and derived a 16-item scale (α = 0.85). Mapping was validated by an expert panel. A categorical subgroup was derived (n = 594, 5.2%), and a zero-inflated item response theory (IRT) mixture model fitted to estimate a dimensional measure.
Subgroup composition was comparable with other ADHD samples. Relative risk ratios (ADHD/not ADHD) included boys = 1.38, unemployed fathers = 2.07, below average reading = 2.58, and depressed parent = 3.73. Our estimated measures correlated with two derived reference scales: Strengths and Difficulties Questionnaire hyperactivity (r = 0.74) and a Rutter/Conners-based scale (r = 0.81), supporting construct validity. IRT model items (symptoms) had moderate to high discrimination (0.90-2.81) and provided maximum information at average to moderate theta levels of ADHD (0.5-1.75).
We extended previous work to identify ADHD in BCS70, derived scales from existing data, modeled ADHD items with IRT, and adjusted for a zero-inflated distribution. Psychometric properties were promising, and this work will enable future studies of causal mechanisms in ADHD.
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