A Review of Canadian Diagnosed ADHD Prevalence and Incidence Estimates Published in the Past Decade
Bibliographic record
Abstract
(1) Background: ADHD is recognized as one of the most common neurodevelopmental disorders. The worldwide prevalence of ADHD is estimated at 5.3%; however, estimates vary as a function of a number of factors, including diagnostic methods, age, sex and geographical location. A review of studies is needed to clarify the epidemiology of ADHD in Canada. (2) Methods: A search strategy was created in PubMed and adapted for MEDLINE and PsycINFO. Papers were included if they examined diagnosed ADHD prevalence and/or incidence rates in any region of Canada, age group and gender. A snowball technique was used to identify additional papers from reference lists, and experts in the field were consulted. (3) Results: Ten papers included in this review reported on prevalence, and one reported on incidence. One study provided an overall prevalence estimate across provinces for adults of 2.9%, and one study provided an overall estimate across five provinces for children and youth of 8.6%. Across age groups (1 to 24 years), incidence estimates ranged from 0.4% to 1.2%, depending on province. Estimates varied by age, gender, province, region and time. (4) Conclusions: The overall Canadian ADHD prevalence estimate is similar to worldwide estimates for adults. Most studies reported on prevalence rather than incidence. Differences in estimates across provinces may reflect the varying number of practitioners available to diagnose and prescribe medication for ADHD across provinces. To achieve a more comprehensive understanding of the epidemiology of ADHD in Canada, a study is needed that includes all provinces and territories, and that considers estimates in relation to age, gender, ethnicity, geographical region, socioeconomic status and access to mental healthcare coverage. Incidence rates need further examination to be determined.
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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 | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.059 | 0.092 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".