意大利语版 16 项前驱症状问卷(PQ-16)及其在寻求帮助的超高危人群和普通人群中的心理测量特征。

IF 2.1 4区 医学 Q3 PSYCHIATRY
Alberto Parabiaghi, Alessandro Alberto Rossi, Anna Castelnovo, Lorenzo del Fabro, Stefania Mannarini, Mauro Emilio Percudani, for the CCM2013 Project team (corporate authorship)
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引用次数: 0

摘要

背景:人们越来越关注精神病的早期阶段以及有症状的前驱状态的识别,因此开发了越来越多的筛查工具。由 16 个项目组成的前驱状态问卷(PQ-16)是全球范围内用于这一目的的自填式工具。然而,迄今为止,PQ-16 的基本心理测量特性尚未得到深入研究。本研究旨在考察意大利版 PQ-16 (iPQ-16)在求助者和普通人群中的结构效度、测量不变性、可靠性和其他心理测量特性:方法:对在六个社区心理健康服务机构就诊的 449 名年轻门诊患者和在教育环境中注册的 318 名对照组参与者进行了 iPQ-16 测试。进行了确认性因子分析(CFAs)、求助群体与普通人群样本之间的测量不变量(MI)、收敛效度、重测信度、内部一致性和患病率分析。最后,还通过与 CAARMS 诊断结果相对应的接收方操作特征曲线(ROC)对所采用的 PQ-16 临界值的有效性进行了测试:CFA证实了iPQ-16的单因素结构,并达到了标度MI。iPQ-16显示出较高的内部一致性、测试-再测试可靠性、收敛有效性和可接受的诊断准确性。ROC分析表明,得分≥4为最佳临界值:iPQ-16是一份有效、可靠的问卷,可用于评估意大利门诊患者和普通学生的高心理风险。iPQ-16具有良好的心理测量特性,易于在临床和研究中用作UHR筛查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Italian version of the 16-item Prodromal Questionnaire (PQ-16) and its psychometric features in help-seeking ultra-high-risk subjects and in the general population

The Italian version of the 16-item Prodromal Questionnaire (PQ-16) and its psychometric features in help-seeking ultra-high-risk subjects and in the general population

Background

Increasing attention to the early stages of psychosis and the identification of symptomatic prodromal states have led to the development of a growing number of screening tools. The 16-item version of the Prodromal Questionnaire (PQ-16) is a worldwide used self-administered tool for this purpose. However, to date, fundamental psychometric properties of PQ-16 were not thoroughly investigated. This study aimed to examine the structural validity, measurement invariance, reliability and other psychometrical properties of the Italian version of the PQ-16 (iPQ-16) in help-seeking individuals and in the general population.

Methods

The iPQ-16 was administered to 449 young outpatients attending six community mental health services and to 318 control participants enrolled in educational environment. Confirmatory factor analyses (CFAs), measurement invariance (MI) between the help-seeking group and the general population sample, convergent validity, test–retest reliability, internal consistency, and prevalence analyses were performed. Lastly, the validity of the adopted PQ-16 cut-offs through Receiver Operating Characteristic (ROC) curves plotted against CAARMS diagnoses was also tested.

Results

CFAs confirmed the single-factor structure for the iPQ-16 and scalar MI was reached. The iPQ-16 showed high internal consistency, test–retest reliability, convergent validity, and acceptable diagnostic accuracy. ROC analysis suggested a score of ≥4 as best cut-off.

Conclusions

The iPQ-16 represents a valid and reliable questionnaire for the assessment of high mental risk in both Italian outpatients and general student population. It has good psychometric properties and is easy to implement as UHR screening for clinical as well as research purposes.

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来源期刊
Early Intervention in Psychiatry
Early Intervention in Psychiatry 医学-精神病学
CiteScore
4.80
自引率
5.00%
发文量
112
审稿时长
6-12 weeks
期刊介绍: Early Intervention in Psychiatry publishes original research articles and reviews dealing with the early recognition, diagnosis and treatment across the full range of mental and substance use disorders, as well as the underlying epidemiological, biological, psychological and social mechanisms that influence the onset and early course of these disorders. The journal provides comprehensive coverage of early intervention for the full range of psychiatric disorders and mental health problems, including schizophrenia and other psychoses, mood and anxiety disorders, substance use disorders, eating disorders and personality disorders. Papers in any of the following fields are considered: diagnostic issues, psychopathology, clinical epidemiology, biological mechanisms, treatments and other forms of intervention, clinical trials, health services and economic research and mental health policy. Special features are also published, including hypotheses, controversies and snapshots of innovative service models.
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