用普适性理论方法量化超高危精神病患者的精神病理学变化。

IF 3 Q2 PSYCHIATRY
Zohreh Doborjeh, Oleg N Medvedev, Maryam Doborjeh, Balkaran Singh, Alexander Sumich, Sugam Budhraja, Wilson Wen Bin Goh, Jimmy Lee, Margaret Williams, Edmund M-K Lai, Nikola Kasabov
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引用次数: 0

摘要

区分处于精神病超高风险(UHR)的年轻人的稳定和波动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,我们使用阳性和阴性症状量表 (PANSS) 对 159 名 UHR 进行了评估。通过估算三因素(积极、消极和一般)和五因素(积极、消极、认知、抑郁和敌对)症状模型的可靠性和通用性,运用通用性理论对 PANSS 进行了验证,并对稳定和波动特征进行了研究。PANSS 总量表(Gr = 0.85)显示,不同场合和样本人群的评分具有可接受的可靠性和普遍性。波动性症状(妄想、幻觉行为、缺乏自发性、谈话不流畅、情感退缩和躯体关注)随着时间的推移显示出很高的变异性,其中 50-68% 的变异由个体的短暂状态解释。相比之下,较为稳定的症状包括兴奋、关系不融洽、焦虑、内疚感、不合作和冲动控制能力差。PANSS 的 3 因子模型及其子量表在整个 UHR 人群和评估期间的评估得分均显示出稳健的可靠性和普适性(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可靠性和普遍性(G = 0.33-0.66)。经识别和调查,UHR 患者的波动症状更容易通过干预手段得到改善,这对预防和解决精神病问题具有重要意义。优先治疗波动症状可以提高干预效果,为临床试验提供更明确的重点。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性精神病模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A generalisability theory approach to quantifying changes in psychopathology among ultra-high-risk individuals for psychosis.

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.

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