Computer adaptive testing strategies for the Edinburgh Postnatal Depression Scale (EPDS).

IF 3.2 3区 医学 Q2 PSYCHIATRY
Emily F Wong, Eynav E Accortt, Seung W Choi, Tiffani J Bright
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引用次数: 0

Abstract

Purpose: Perinatal mood and anxiety disorders (PMADs) include depressive and anxiety disorders during pregnancy or postpartum and can have significant consequences for the parent, child, and family. When severe, these conditions can lead to suicide. Despite numerous policy efforts to improve screening, education, and referral structures, disparities in PMAD diagnosis and treatment still exists, particularly among racial and ethnic minorities. Computer Adaptive Testing (CAT) has been shown to improve the efficiency of screening by significantly reducing test length. This study evaluates whether applying CAT to the Edinburgh Postnatal Depression Scale (EPDS) maintains diagnostic accuracy while ensuring these methods do not exacerbate racial disparities in PMAD screening outcomes.

Methods: Using real data simulation, we assessed three CAT-based short-form versions of the EPDS, derived from one-, two-, and three-factor item response theory models. We evaluated their diagnostic precision and examined potential racial disparities in false negative rates compared to the full-length EPDS.

Results: We demonstrate that estimated scores from three short versions of the EPDS administered through CAT-assuming one, two, and three-factor item response theory models-are more highly correlated with the full-length EPDS measure traditionally used to make clinical decisions (r's between 0.96 and 0.97) than the major depressive disorder subtest (CAT-MDD) from CAT-Mental Health (CAT-MH®) (r =.82), as previously reported. Importantly, the false negative rates of the CAT-implied diagnoses did not significantly vary between racial groups, indicating no evidence of racial bias in diagnostic accuracy.

Conclusion: The CAT-based versions of the EPDS offers a promising solution for improving the efficiency of PMAD screening without sacrificing diagnostic precision or exacerbating racial groups. By reducing evaluation time, these tools could facilitate more widespread and equitable screening, enabling earlier diagnosis and treatment of PMADs across diverse populations.

爱丁堡产后抑郁量表(EPDS)的计算机自适应测试策略。
目的:围产期情绪和焦虑障碍(PMADs)包括怀孕期间或产后的抑郁和焦虑障碍,可能对父母、孩子和家庭产生重大影响。严重时,这些情况可能导致自杀。尽管许多政策努力改善筛查、教育和转诊结构,但PMAD的诊断和治疗差距仍然存在,特别是在种族和少数民族之间。计算机自适应测试(CAT)已被证明可以通过显着减少测试长度来提高筛选效率。本研究评估了将CAT应用于爱丁堡产后抑郁量表(EPDS)是否能保持诊断准确性,同时确保这些方法不会加剧PMAD筛查结果的种族差异。方法:使用真实数据模拟,我们评估了三个基于cat的EPDS的简短版本,分别来自一因素,二因素和三因素项目反应理论模型。我们评估了他们的诊断精度,并检查了与全长EPDS相比假阴性率的潜在种族差异。结果:我们证明,如先前报道的那样,通过cat(假设一、二和三因素项目反应理论模型)实施的三个简短版本的EPDS的估计分数与传统上用于临床决策的全长EPDS测量(r在0.96和0.97之间)的相关性比cat -心理健康(CAT-MH®)的重度抑郁症子测试(CAT-MDD) (r = 0.82)更高。重要的是,ct暗示诊断的假阴性率在种族群体之间没有显著差异,表明在诊断准确性方面没有种族偏见的证据。结论:基于cat的EPDS为提高PMAD的筛查效率提供了一个有希望的解决方案,同时不会牺牲诊断精度或加剧种族差异。通过缩短评估时间,这些工具可以促进更广泛和公平的筛查,从而能够在不同人群中更早地诊断和治疗pmad。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Archives of Women's Mental Health
Archives of Women's Mental Health 医学-精神病学
CiteScore
8.00
自引率
4.40%
发文量
83
审稿时长
6-12 weeks
期刊介绍: Archives of Women’s Mental Health is the official journal of the International Association for Women''s Mental Health, Marcé Society and the North American Society for Psychosocial Obstetrics and Gynecology (NASPOG). The exchange of knowledge between psychiatrists and obstetrician-gynecologists is one of the major aims of the journal. Its international scope includes psychodynamics, social and biological aspects of all psychiatric and psychosomatic disorders in women. The editors especially welcome interdisciplinary studies, focussing on the interface between psychiatry, psychosomatics, obstetrics and gynecology. Archives of Women’s Mental Health publishes rigorously reviewed research papers, short communications, case reports, review articles, invited editorials, historical perspectives, book reviews, letters to the editor, as well as conference abstracts. Only contributions written in English will be accepted. The journal assists clinicians, teachers and researchers to incorporate knowledge of all aspects of women’s mental health into current and future clinical care and research.
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