Prevalence of attention-deficit hyperactivity disorder in children, adolescents and adults in the Middle East and North Africa region: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: To systematically estimate the overall prevalence of attention-deficit hyperactivity disorder (ADHD) in children, adolescents and adults across the Middle East and North Africa (MENA) region. DESIGN: Systematic review and meta-analysis conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. DATA SOURCES: Medline and Scopus databases were comprehensively and systematically searched between 1990 and February 2023. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included all cross-sectional or cohort studies that diagnosed ADHD using validated diagnostic tools (eg, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria, ADHD rating scales and ADHD diagnostic interview) or non-validated tools (eg, brain imaging techniques, computerised cognitive tests and quantitative electroencephalography). DATA EXTRACTION AND SYNTHESIS: Two reviewers performed the data extraction independently using standardised data collection sheet. Newcastle-Ottawa Scale was used to assess the quality of the included studies. Individualised and pooled event rate and upper and lower limit at 95% CI were calculated according to the ADHD cases and the total sample size using a random-effect model. The subgroup prevalence analyses according to ADHD subtypes, gender, MENA country and age were also performed. RESULTS: A total of 63 articles met the inclusion criteria involving 849 902 participants. The overall prevalence of ADHD was 10.3% (95% CI 0.081 to 0.129). The prevalence rate ranged from 1.3% (Yemen) to 22.2% (Iran). Subgroup analyses showed that the prevalence in adults was 13.5 and 10.1 in children and adolescents. Males exhibited significantly higher prevalence compared with females as these were 11.1% and 7%, respectively. Attention-deficit subtype was significantly the most prevalent (46.7%) compared with hyperactivity/impulsivity (33.7%) and combined types (20.6%). CONCLUSION: The overall prevalence of ADHD was high in the MENA region. It is crucial to allocate more attention and resources towards the prevention and treatment of ADHD in children, adolescents and adults within the region.
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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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.033 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".