Assessing the standard of care for child and adolescent attention-deficit hyperactivity disorder in Elgin County, Ontario: a pilot study.
Bibliographic record
Abstract
OBJECTIVE: To examine the current practice of rural family physicians in managing children with attention-deficit hyperactivity disorder (ADHD). DESIGN: Chart review of children and adolescents with a recorded diagnosis of ADHD. The data collected include the patient's age at diagnosis, the diagnosing physician, the number and type of presenting symptoms, whether the Diagnostic Statistical Manual, 4th ed (DSM-IV) criteria were met, pertinent treatment regimens, family history and comorbid conditions. Participating physicians were asked to complete a questionnaire. SETTING: Elgin County, Ontario. RESULTS: Thirty-six family physicians were contacted and 11 agreed to participate. Thirty-nine charts were reviewed. The average number of presenting symptoms was 2.9 for ADHD-inattentive subtype and 2.1 for ADHD-hyperactivity subtype. A diagnostic protocol was included in 20.5% of the charts. Of the 39 charts reviewed, 25.6% had sufficient information for the patients to meet the ADHD criteria. Family physicians diagnosed 5.1% of the cases, and the duration of time between referral to specialist and appointment was 47.2 weeks. CONCLUSIONS: Together the lack of symptom recording, the long duration between referrals, and the low percentage of family physicians diagnosing ADHD all suggest the need for developing diagnostic protocols for family physicians and increasing their knowledge of diagnosing and managing ADHD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".