Cross-Cultural Adult ADHD Assessment in 42 Countries Using the Adult ADHD Self-Report Scale Screener
Bibliographic record
Abstract
OBJECTIVE: We analyzed adult ADHD symptoms in a cross-cultural context, including investigating the occurrence and potential correlates of adult ADHD and psychometric examination of the Adult ADHD Self-Report Scale (ASRS) Screener. METHOD: =12.57). RESULTS: The ASRS Screener demonstrated good reliability and validity, along with partial invariance across different languages, countries, and genders. The occurrence of being at risk for adult ADHD was relatively high (21.4% for women, 18.1% for men). The highest scores were obtained in the US, Canada, and other English-speaking Western countries, with significantly lower scores among East Asian and non-English-speaking European countries. Moreover, ADHD symptom severity and occurrence were especially high among gender-diverse individuals. Significant associations between adult ADHD symptoms and age, mental and sexual health, and socioeconomic status were observed. CONCLUSIONS: Present results show significant cross-cultural variability in adult ADHD occurrence as well as highlight important factors related to adult ADHD. Moreover, the importance of further research on adult ADHD in previously understudied populations (non-Western countries) and minority groups (gender-diverse individuals) is stressed. Lastly, the present analysis is consistent with previous evidence showing low specificity of adult ADHD screening instruments and contributes to the current discussion on accurate adult ADHD screening and diagnosis.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".