Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy.
Department of Psychology, University of North Texas, Denton, TX, USA.
Scand J Psychol. 2023 Dec;64(6):734-745. doi: 10.1111/sjop.12931. Epub 2023 May 26.
The Aberrant Salience Inventory (ASI) is a useful tool to measure salience abnormalities among the general population. There is strong clinical and scientific evidence that salience alteration is linked to psychosis. To the present day, no meta-analysis evaluating ASI's psychometric properties and screening potential has been published.
PubMed, Google Scholar, Scopus, and Embase were searched using terms including "psychosis," "schizophrenia," and "Aberrant Salience Inventory." Observational and experimental studies employing ASI on populations of non-psychotic controls and patients with psychosis were included. ASI scores and other demographic measures (age, gender, ethnicity) were extracted as outcomes. Individual patients' data (IPD) were collected. Exploratory factor analysis (EFA) was performed on the IPD.
Eight articles were finally included in the meta-analysis. ASI scores differ significantly between psychotic and non-psychotic populations; a novel three-factor model is proposed regarding subscales structure. Theoretical positive predictive values (PPVs) and negative predictive values (NPVs) were calculated and presented together with different cutoff points depending on preselected specific populations of interest.
PPV and NPV values reached levels adequate for ASI to be considered a viable screening tool for psychosis. The factor analysis highlights the presence of a novel subscale that was named "Unveiling experiences." Implications regarding the meaning of the new factor structure are discussed, as well as ASI's potential as a screening tool.
异常突显量表(ASI)是一种用于测量普通人群突显异常的有用工具。有强有力的临床和科学证据表明,突显改变与精神病有关。迄今为止,还没有发表过评估 ASI 心理测量特性和筛查潜力的荟萃分析。
使用包括“精神病”、“精神分裂症”和“异常突显量表”在内的术语在 PubMed、Google Scholar、Scopus 和 Embase 上进行了搜索。纳入了使用 ASI 对非精神病对照组和精神病患者人群进行的观察性和实验性研究。提取了 ASI 评分和其他人口统计学指标(年龄、性别、种族)作为结果。收集了个体患者的数据(IPD)。对 IPD 进行了探索性因素分析(EFA)。
最终有 8 篇文章纳入荟萃分析。AS 评分在精神病和非精神病人群之间存在显著差异;提出了一个新的三因素模型,用于子量表结构。计算了理论阳性预测值(PPV)和阴性预测值(NPV),并根据预先选择的特定感兴趣人群呈现了不同的截断值。
PPV 和 NPV 值达到了足以使 ASI 成为精神病筛查工具的水平。因子分析突出了存在一个新的子量表,该子量表被命名为“揭示体验”。讨论了新因子结构的意义以及 ASI 作为筛查工具的潜力。