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采用潜在剖面分析评估 DSM-5 症状清单在筛查儿童自闭症谱系障碍中的效用。

Using latent profile analysis to evaluate the utility of a DSM-5 symptom checklist in screening children for autism spectrum disorder.

机构信息

Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA.

NeuroDevelopmental Science Center, Akron Children's Hospital, Akron, OH, USA.

出版信息

Clin Neuropsychol. 2022 Jul;36(5):874-898. doi: 10.1080/13854046.2021.1929495. Epub 2021 Jun 3.

Abstract

Currently available screening measures for Autism Spectrum Disorder (ASD) typically do not reflect DSM-5 diagnostic criteria and generally have weak positive predictive values. These factors result in missed opportunities for early intervention, delays in diagnosis, and contribute to inefficient usage of healthcare resources by inadequately discerning those in need of comprehensive assessment. This study examined a DSM-5 ASD symptom checklist to determine whether parent-report response patterns could accurately identify which children received an ASD diagnosis. Data were examined from 376 ASD evaluations in a three-year period. Latent profile analysis was used to determine if subgroups could be identified according to parent response patterns, and network analysis was implemented to examine the relationship among DSM-5 ASD criteria within each latent profile. A four-profile model was best supported based on fit indices and high probability classifications. The model was largely a product of how parents responded regarding their child's sensory behavior and minimally reflected other symptomatology. Subsequent network analyses by profile indicated weak coherence among DSM-5 symptoms within all profiles. Overall, direct assessment of DSM-5 criteria based on parent report did not add diagnostic value beyond that reflected in base rates. Although continued refinement of ASD screening tools is needed to improve accuracy of referrals for evaluations and reduce wait time for diagnosis, this study continues to support the need for behavioral observation and formal assessment by trained clinicians. Continued development of sensitive and specific screening tools, likely with embedded behavioral and/or objective observation, is needed.

摘要

目前用于自闭症谱系障碍 (ASD) 的筛查方法通常无法反映 DSM-5 诊断标准,且普遍具有较弱的阳性预测值。这些因素导致错失了早期干预的机会,延迟了诊断,并导致医疗资源利用效率低下,无法充分甄别需要全面评估的人群。本研究通过考察 DSM-5 ASD 症状检查表,以确定家长报告的反应模式是否可以准确识别出哪些儿童被诊断为 ASD。研究数据来自三年内 376 例 ASD 评估。潜在剖面分析用于确定是否可以根据家长的反应模式识别亚组,网络分析用于检查每个潜在剖面内 DSM-5 ASD 标准之间的关系。基于拟合指数和高概率分类,最佳支持四剖面模型。该模型主要是家长对孩子感官行为反应的产物,而对其他症状的反映则较少。根据剖面进行的后续网络分析表明,所有剖面内的 DSM-5 症状之间的一致性较弱。总体而言,基于家长报告的 DSM-5 标准的直接评估除了反映在基础比率之外,并没有增加诊断价值。尽管需要进一步改进 ASD 筛查工具以提高评估转介的准确性并减少诊断等待时间,但本研究仍支持行为观察和经过培训的临床医生进行正式评估的必要性。需要继续开发敏感和特异性的筛查工具,可能需要嵌入行为和/或客观观察。

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