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使用多项式回归重新审视 ADHD 相关的自我报告问题。

Reexamining ADHD-Related Self-Reporting Problems Using Polynomial Regression.

机构信息

1 Florida International University, Miami, FL, USA.

出版信息

Assessment. 2019 Mar;26(2):305-314. doi: 10.1177/1073191117693349. Epub 2017 Feb 15.

Abstract

Individuals with attention deficit hyperactivity disorder (ADHD) underreport symptoms compared with informants and objective measures. This study applied enhanced statistical methodology (polynomial regression) to the study of ADHD self-reporting to clarify what contributes to symptom underreporting by adolescents with ADHD ( N = 107; ages = 11-15 years). Polynomial regression models were conducted to test competing hypotheses about the nature of self-reporting problems. Traditional difference score models were nested within polynomial regression models to examine how modeling strategy influences results. Sixty-six percent of the sample substantially underreported symptoms compared with parents and 23.6% denied all symptoms. Polynomial regression models provided no evidence that the size of the discrepancy between parent and adolescent symptom reports possessed meaningful linear associations with any of the hypothesized predictors. Nested models indicated that the difference score approach led to very poor model fit and increased risk for Type I errors when examining underreporting among youth with ADHD. This finding suggests that past evaluations using a difference score approach should be replicated using polynomial regression to ensure that significant effects do not represent statistical artifact.

摘要

患有注意缺陷多动障碍(ADHD)的个体与知情人和客观测量相比,报告的症状较少。本研究应用增强的统计方法(多项式回归)来研究 ADHD 的自我报告,以澄清 ADHD 青少年(N=107;年龄=11-15 岁)报告症状较少的原因。进行多项式回归模型以测试关于自我报告问题性质的竞争假设。传统的差异分数模型嵌套在多项式回归模型中,以检查建模策略如何影响结果。与父母相比,66%的样本大量少报症状,而 23.6%的样本否认所有症状。多项式回归模型没有提供证据表明父母和青少年症状报告之间差异的大小与任何假设的预测因素具有有意义的线性关联。嵌套模型表明,当检查 ADHD 青少年的漏报情况时,差异分数方法导致模型拟合不佳,并且 Type I 错误的风险增加。这一发现表明,过去使用差异分数方法进行的评估应使用多项式回归进行复制,以确保显著效果不代表统计假象。

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