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Case definition in epidemiologic studies of AD/HD
Slavica K Katusic1, William J Barbaresi, Robert C Colligan
1Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. katusic.slavica@mayo.edu
Annals of Epidemiology
|June 22, 2005
Summary
A new five-step method for identifying attention-deficit/hyperactivity disorder (AD/HD) in population studies found that using multiple data sources identified more cases than relying solely on DSM-IV criteria.
Area of Science:
- Epidemiology
- Child Psychiatry
- Developmental Psychology
Background:
- Attention-deficit/hyperactivity disorder (AD/HD) diagnosis in large populations presents challenges.
- Accurate case identification is crucial for epidemiological research and understanding disorder prevalence.
Purpose of the Study:
- To propose and evaluate a novel five-step, multimodal procedure for defining and identifying AD/HD cases in population-based epidemiologic studies.
- To assess the utility of combining various data sources beyond standard diagnostic criteria.
Main Methods:
- A birth cohort (1976-1982) was screened using school/medical records, a diagnostic index, and psychiatric records.
- A five-step process involved initial screening, followed by applying research criteria using DSM-IV, questionnaire, and clinical diagnosis data.
- Validity was assessed by comparing outcomes (treatment, substance abuse, school, comorbidities) between cases meeting and not meeting DSM-IV criteria.
Main Results:
- Out of 5718 subjects, 379 met the research criteria for AD/HD.
- Cases not meeting DSM-IV criteria (N=151) showed distinct characteristics: more inattentive symptoms, older age, and less substance abuse/comorbidities.
- No significant differences were found in gender, treatment, school outcomes, or diagnosing professional between groups.
Conclusions:
- Solely applying DSM-IV criteria would have missed 151 potential AD/HD cases.
- This study highlights the critical importance of integrating multiple information sources and data combinations for robust case definition and identification in epidemiological research.