ADHD 青少年综合数据分析纵向（TIDAL）数据集：背景、方法和目的。
The ADHD teen integrative data analysis longitudinal (TIDAL) dataset: background, methodology, and aims.
机构信息
Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle Children's Research Insitute, 2001 8th Ave., Suite 400, Seattle, WA, 98117, USA.
Department of Psychiatry & Behavioral Health, Florida International University, 11200 SW 8th Street, Miami, FL, 33199, USA.
出版信息
BMC Psychiatry. 2020 Jul 8;20(1):359. doi: 10.1186/s12888-020-02734-6.
BACKGROUND
The Attention Deficit Hyperactivity Disorder (ADHD) Teen Integrative Data Analysis Longitudinal (TIDAL) dataset integrates data from four randomized trials.
METHOD
Participants with ADHD (N = 854; 72.5% male, 92.5% racial/ethnic minority, ages 10-17) were assessed three times across 12 months. Data includes parent, self, and teacher ratings, observations, and school records. The battery was harmonized using an Integrative Data Analysis (IDA) approach to form variables that assign unique values to all participants.
RESULTS
The data will be used to investigate: (1) profiles that organize the heterogeneous population into clinically meaningful subgroups, (2) whether these profiles predict treatment response, (3) heterogeneity in treatment response and variables that predict this response, (4) how treatment characteristics and adjunctive supports predict treatment response, and (5) mediators of treatment and whether these mechanisms are moderated by treatment characteristics.
CONCLUSIONS
The ADHD TIDAL Dataset will be openly shared with the field to maximize its utility.
背景
注意力缺陷多动障碍（ADHD）青少年综合数据分析纵向（TIDAL）数据集整合了四项随机试验的数据。
方法
854 名 ADHD 参与者（72.5%为男性，92.5%为种族/民族少数群体，年龄在 10-17 岁之间）在 12 个月内接受了三次评估。数据包括家长、自身和教师的评定、观察和学校记录。采用综合数据分析（IDA）方法对电池进行了协调，形成了为所有参与者分配唯一值的变量。
结果
该数据将用于研究：（1）将异质人群组织成具有临床意义的亚组的特征；（2）这些特征是否能预测治疗反应；（3）治疗反应的异质性和预测这种反应的变量；（4）治疗特点和辅助支持如何预测治疗反应；（5）治疗的中介因素，以及这些机制是否受治疗特点的调节。
结论
将公开分享 ADHD TIDAL 数据集，以最大限度地提高其效用。
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