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一种用于量化精神病超高风险个体精神病理学变化的概化理论方法。

A generalisability theory approach to quantifying changes in psychopathology among ultra-high-risk individuals for psychosis.

作者信息

Doborjeh Zohreh, N Medvedev Oleg, Doborjeh Maryam, Singh Balkaran, Sumich Alexander, Budhraja Sugam, Goh Wilson Wen Bin, Lee Jimmy, Williams Margaret, M-K Lai Edmund, Kasabov Nikola

机构信息

Knowledge Engineering and Discovery Research Institute, School of Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.

School of Population Health, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.

出版信息

Schizophrenia (Heidelb). 2024 Oct 4;10(1):87. doi: 10.1038/s41537-024-00503-y.

Abstract

Distinguishing stable and fluctuating psychopathological features in young individuals at Ultra High Risk (UHR) for psychosis is challenging, but critical for building robust, accurate, early clinical detection and prevention capabilities. Over a 24-month period, 159 UHR individuals were assessed using the Positive and Negative Symptom Scale (PANSS). Generalisability Theory was used to validate the PANSS with this population and to investigate stable and fluctuating features, by estimating the reliability and generalisability of three factor (Positive, Negative, and General) and five factor (Positive, Negative, Cognitive, Depression, and Hostility) symptom models. Acceptable reliability and generalisability of scores across occasions and sample population were demonstrated by the total PANSS scale (Gr = 0.85). Fluctuating symptoms (delusions, hallucinatory behaviour, lack of spontaneity, flow in conversation, emotional withdrawal, and somatic concern) showed high variability over time, with 50-68% of the variance explained by individual transient states. In contrast, more stable symptoms included excitement, poor rapport, anxiety, guilt feeling, uncooperativeness, and poor impulse control. The 3-factor model of PANSS and its subscales showed robust reliability and generalisability of their assessment scores across the UHR population and evaluation periods (G = 0.77-0.93), offering a suitable means to assess psychosis risk. Certain subscales within the 5-factor PANSS model showed comparatively lower reliability and generalisability (G = 0.33-0.66). The identified and investigated fluctuating symptoms in UHR individuals are more amendable by means of intervention, which could have significant implications for preventing and addressing psychosis. Prioritising the treatment of fluctuating symptoms could enhance intervention efficacy, offering a sharper focus in clinical trials. At the same time, using more reliable total scale and 3 subscales can contribute to more accurate assessment of enduring psychosis patterns in clinical and experimental settings.

摘要

区分处于精神病超高风险(UHR)的年轻人的稳定和波动的精神病理特征具有挑战性,但对于建立强大、准确的早期临床检测和预防能力至关重要。在24个月的时间里,使用阳性和阴性症状量表(PANSS)对159名UHR个体进行了评估。采用概化理论对该人群的PANSS进行验证,并通过估计三因素(阳性、阴性和一般)和五因素(阳性、阴性、认知、抑郁和敌意)症状模型的信度和概化性来研究稳定和波动特征。PANSS总量表显示,各场合和样本人群得分的信度和概化性可接受(Gr = 0.85)。波动症状(妄想、幻觉行为、缺乏自发性、言语流畅性、情感退缩和躯体关注)随时间变化差异很大,个体瞬时状态可解释50 - 68%的方差。相比之下,更稳定的症状包括兴奋、关系不协调、焦虑、内疚感、不合作和冲动控制差。PANSS的三因素模型及其分量表在UHR人群和评估期内显示出其评估得分具有较强的信度和概化性(G = 0.77 - 0.93),为评估精神病风险提供了合适的方法。五因素PANSS模型中的某些分量表显示出相对较低的信度和概化性(G = 0.33 - 0.66)。在UHR个体中识别和研究的波动症状更易于通过干预得到改善,这可能对预防和治疗精神病具有重要意义。优先治疗波动症状可提高干预效果,并在临床试验中提供更明确的重点。同时,使用更可靠的总量表和3个分量表有助于在临床和实验环境中更准确地评估持久的精神病模式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69f2/11452639/391f1186e64e/41537_2024_503_Fig1_HTML.jpg

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