Studying the Epidemiology of Attention-Deficit Hyperactivity Disorder: Screening Method and Pilot Results
Bibliographic record
Abstract
OBJECTIVE: As part of a larger epidemiologic study of risk factors for attention-deficit hyperactivity disorder (ADHD), this pilot study combined parent and teacher information to estimate ADHD prevalence among elementary school children in a North Carolina county. The methods developed for this study and the pitfalls we encountered illustrate the challenges involved in conducting population-based studies of ADHD. METHODS: We employed 2-stage screening using DSM-IV criteria. Teachers completed behaviour-rating scales for all children. We then administered a structured telephone interview to parents of potential cases. We screened 362 of 424 (85%) children in grades 1 to 5 in 4 schools. RESULTS: According to parent reports, 43 children (12%) had previously been diagnosed with ADHD by a health professional. Thirty-four children (9%) were taking ADHD medication. Forty-six children (12.7%) met study case criteria for ADHD, based on combined teacher and parent reports. Of the 46 cases, 18 (39%) had not been previously identified. Eight previously diagnosed children, however, did not meet case criteria. After we adjusted for nonresponse, the estimated prevalence was 16% (95%CI, 12% to 20%). CONCLUSIONS: These data suggest that the DSM-IV prevalence of ADHD has been substantially underestimated, although the true prevalence in this population may be less than the 16% estimated here. Population-based studies of ADHD are feasible and may provide important information about practice and treatment patterns in community settings, as well as a broader understanding of the etiology and life course of this common disorder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".