Treatment Patterns, Adherence, and Persistence in ADHD: A Canadian Perspective
Bibliographic record
Abstract
OBJECTIVE: To understand attention-deficit/hyperactivity disorder (ADHD) treatment patterns and estimate adherence and persistence in Quebec, Canada. DESIGN: This cross-sectional, retrospective prescription claims analysis used a random sample of 15 838 patients with ADHD from a Quebec database (Régie de l'assurance maladie du Québec [RAMQ]) to assess treatment patterns, adherence (1-year medication possession ratio in new users), and persistence (proportion persistent at 3, 6, and 12 months after index prescription). RESULTS: The mean patient age was 14 years; 72.6% were male. During the 5-year study period (2004-2009), 416 646 ADHD prescriptions were filled. Short-acting (SA) medications declined from 72.8% to 26.4% of all claims, while stimulant and nonstimulant long-acting (LA) medications increased from 27.2% to 73.6%. Approximately half of the patients used both SA and LA medications (either concomitantly or subsequently), and the others used only SA (30%) or LA (19%) drugs. Among patients using both, switching from SA to LA was the most frequent (27.9%) treatment pattern. More patients on LA methylphenidates (6.4%) compared with LA amphetamines (1.9%; P < 0.01) required augmentation with an SA drug. Fewer patients on SA stimulants (39.4%) were ≥ 80% adherent compared with LA stimulants (63%; P < 0.001) and LA nonstimulants (60.2%; P < 0.001). More patients on LA stimulants (81.1%) were persistent at 12 months compared with LA nonstimulants (61.7%; P < 0.001) and SA stimulants (59.6%; P < 0.001). Similar trends were observed at all time points measured. CONCLUSIONS: Switching from SA to LA medications and treatment augmentation are common in ADHD management, with implications for patient care and health care resource use. This analysis found poor adherence in ADHD treatment, although adherence and persistence were improved with LA stimulant formulations.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".