University of Alberta, Edmonton, Canada.
Chokka Center for Integrative Health, Edmonton, AB, Canada.
J Atten Disord. 2023 Feb;27(3):324-331. doi: 10.1177/10870547221136228. Epub 2022 Nov 11.
Screening for adult Attention-Deficit/Hyperactivity Disorder (ADHD) and differentiating ADHD from comorbid mental health disorders remains to be clinically challenging. A screening tool for ADHD and comorbid mental health disorders is essential, as most adult ADHD is comorbid with several mental health disorders. The current pilot study enrolled 955 consecutive patients attending a tertiary mental health center in Canada and who completed EarlyDetect assessment, with 45.2% of patients diagnosed with ADHD. The best ADHD classification model using composite scoring achieved a balanced accuracy of 0.788, showing a 2.1% increase compared to standalone ADHD screening, detecting four more patients with ADHD per 100 patients. The classification model including ADHD with comorbidity was also successful (balanced accuracy = 0.712). The results suggest the novel screening method can improve ADHD detection accuracy and inform the risk of ADHD with comorbidity, and may further inform specific comorbidity including MDD and BD.
筛查成人注意缺陷多动障碍（ADHD）并将其与共患精神健康障碍区分开来仍然具有临床挑战性。需要一种用于 ADHD 和共患精神健康障碍的筛查工具，因为大多数成人 ADHD 都与几种精神健康障碍共患。本研究纳入了在加拿大一家三级精神卫生中心就诊的 955 例连续患者，并完成了早期检测评估，其中 45.2%的患者被诊断为 ADHD。使用综合评分的最佳 ADHD 分类模型达到了 0.788 的平衡准确性，与单独的 ADHD 筛查相比提高了 2.1%，每 100 名患者多检测出 4 名 ADHD 患者。包括 ADHD 共病的分类模型也取得了成功（平衡准确性=0.712）。结果表明，这种新的筛查方法可以提高 ADHD 的检测准确性，并提示 ADHD 共病的风险，还可能进一步提示包括 MDD 和 BD 在内的特定共病。
