Documenting adherence to psychostimulants in children with ADHD.
Bibliographic record
Abstract
OBJECTIVE: This study evaluates the validity, inter-rater reliability, and stability over 3 months of a semi-structured telephone interview measuring adherence to stimulant treatment, the Stimulant Adherence Measure, against the Medication Event Monitoring System (MEMS). METHODS: Clinic-referred children (N=22, age 11.85 +/- 2.1 yrs) using psychostimulants for DSM-IV attention-deficit/hyperactivity disorder (ADHD) were eligible. Families used a MEMS device for the primary stimulant medication. Children and parents participated in a semi-structured telephone interview, the Stimulant Adherence Measure, for 3 consecutive months. Parent reports for previous 7 days and 28 days and child report for previous 7 days of medication use were compared to MEMS report. Inter-rater reliability and interview order were also examined. RESULTS: Nineteen children and parents completed (86%). Agreement between MEMS and parent report for previous 7 days at months 1, 2 and 3 (ICC=0.829, p<0.001; ICC=0.663, p<0.05; ICC=0.878, p<0.001 respectively) and for 28 days at months 1, 2 and 3 (ICC=0.793, p<0.001; ICC=0.907, p< 0.001; ICC=0.806, p<0.001 respectively) was good to excellent. Agreement between MEMS and child report for 7 days at months 1, 2 and 3 (ICC=0.773, p<0.001, ICC=0.542, p<0.05, ICC=0.606, p<0.05 respectively) was good. Inter-rater reliability was excellent (ICC=0.956, p<0.001). There was no interview order effect for parents (F=1.771, p>0.05) or children (F=1.621, p>0.05). CONCLUSION: The Stimulant Adherence Measure provides a valid and reliable method for determining stimulant medication use by children with 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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".