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The development and validation of static and adaptive screeners to measure the severity of panic disorder, social anxiety disorder, and obsessive compulsive disorder

机译:静态和自适应筛选者的发展与验证,以衡量恐慌症,社交焦虑症和强迫症的严重程度

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Abstract A series of static and adaptive screeners for panic disorder, social anxiety disorder (SAD), and obsessive compulsive disorder (OCD) were developed and compared using data‐driven methods to facilitate the measurement of each disorder in community samples. Data comprised 3175 respondents for the development sample and 3755 respondents for the validation sample, recruited independently using Facebook advertising. Item Response Theory (IRT) was utilized to develop static continuous screeners and to simulate computerized adaptive algorithms. The screeners consisted of a small subset of items from each bank (79% reduction in items for panic disorder, 85% reduction in items for SAD, and 84% reduction in items for OCD) that provided similar scores ( r ?=?0.88–0.96). Both static and adaptive screeners were valid with respect to existing scales that purportedly measure similar constructs ( r ??0.70 for panic disorder, r ??0.76 for SAD, and r ??0.68 for OCD). The adaptive scales were able to maintain a higher level of precision in comparison to the static scales and evidenced slightly higher concordance with scores generated by the full item banks. The screeners for panic disorder, SAD, and OCD could be used as a flexible approach to measure and monitor the severity of psychopathology in tailored treatment protocols.
机译:摘要开发了一系列静态和自适应筛选者,用于恐慌症,社交焦虑症(悲伤)和强迫症(OCD),并使用数据驱动方法进行比较,以促进社区样本中每种病症的测量。数据包括3175名受访者,用于开发样本和3755名受访者的验证样本,独立使用Facebook广告招募。物品响应理论(IRT)用于开发静态连续筛选器并模拟计算机化自适应算法。筛选者由每个银行的一小部分物品组成(恐慌症的物品减少79%,悲伤的物品减少85%,而OCD的物品减少84%),提供了类似的得分(R?= 0.88 0.96)。静态和自适应筛选者对于据称旨在测量相似构建体的现有尺度(Rα&恐慌障碍,r = 0.76,悲伤,r = 0.68,OCD)。与静态尺度相比,自适应尺度能够保持更高的精度,并且可以通过完整项目库产生的分数来证明略微更高的一致性。恐慌症,悲伤和强迫症的筛选剂可作为测量和监测量身定制的治疗方案中精神病理学严重程度的灵活性方法。

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