Timeframe for Conversion to Psychosis From Individuals at Clinical High-Risk: A Quantile Regression

Author:

Zhang TianHong1ORCID,Wei YanYan1,Tang XiaoChen1,Xu LiHua1,Hu YeGang1,Liu HaiChun2,Wang ZiXuan3,Chen Tao45,Li ChunBo1,Wang JiJun167

Affiliation:

1. Department of Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention , Shanghai 200030 , PR China

2. Department of Automation, Shanghai Jiao Tong University , Shanghai 200240 , PR China

3. Department of Psychology, Shanghai Xinlianxin Psychological Counseling Center , Shanghai , PR China

4. Department of Big Data Research Lab, University of Waterloo , Ontario , Canada

5. Department of Labor and Worklife Program, Harvard University , Cambridge, MA , USA

6. Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science , Shanghai , PR China

7. Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University , Shanghai , PR China

Abstract

Abstract Background and Hypothesis The time taken for an individual who is at the clinical high-risk (CHR) stage to transition to full-blown psychosis may vary from months to years. This temporal aspect, known as the timeframe for conversion to psychosis (TCP), is a crucial but relatively underexplored dimension of psychosis development. Study Design The sample consisted of 145 individuals with CHR who completed a 5-year follow-up with a confirmed transition to psychosis within this period. Clinical variables along with functional variables such as the Global Assessment of Function (GAF) score at baseline (GAF baseline) and GAF-drop from the highest score in the past year. The TCP was defined as the duration from CHR identification to psychosis conversion. Participants were categorized into 3 groups based on TCP: “short” (≤6 months, ≤33.3%), “median” (7–17 months, 33.3%–66.6%), and “long” (≥18 months, ≥66.6%). The quantile regression analysis was applied. Study Results The overall sample had a median TCP of 11 months. Significant differences among the three TCP groups were observed, particularly in GAF-drop (χ2 = 8.806, P = .012), disorganized symptoms (χ2 = 7.071, P = .029), and general symptoms (χ2 = 6.586, P = .037). Greater disorganized symptoms (odds ratio [OR] = 0.824, P = .009) and GAF-drop (OR = 0.867, P = .011) were significantly associated with a shorter TCP, whereas greater general symptoms (OR = 1.198, P = .012) predicted a longer TCP. Quantile regression analysis demonstrated a positive association between TCP and GAF baseline above the 0.7 quantile and a negative association between TCP rank and GAF drop below the 0.5 quantile. Conclusions This study underscores the pivotal role of functional characteristics in shaping TCP among individuals with CHR, emphasizing the necessity for a comprehensive consideration of temporal aspects in early prevention efforts.

Funder

Ministry of Science and Technology of China, National Key R&D Program of China

National Natural Science Foundation of China

Clinical Research Plan of SHDC

Publisher

Oxford University Press (OUP)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3