Negative Symptom Trajectories in Individuals at Clinical High Risk for Psychosis: Differences Based on Deficit Syndrome, Persistence, and Transition Status.

Schizophrenia bulletin open(2023)

引用 0|浏览16
暂无评分
摘要
Background and Hypothesis:Negative symptom trajectory in clinical high risk (CHR) for psychosis is ill defined. This study aimed to better characterize longitudinal patterns of change in negative symptoms, moderators of change, and differences in trajectories according to clinical subgroups. We hypothesized that negative symptom course will be nonlinear in CHR. Clinical subgroups known to be more severe variants of psychotic illness-deficit syndrome (DS), persistent negative syndrome (PNS), and acute psychosis onset-were expected to show more severe baseline symptoms, slower rates of change, and less stable rates of symptom resolution. Study Design:Linear, curvilinear, and stepwise growth curve models, with and without moderators, were fitted to negative symptom ratings from the NAPLS-3 CHR dataset (N = 699) and within clinical subgroups. Study Results:Negative symptoms followed a downward curvilinear trend, with marked improvement 0-6 months that subsequently stabilized (6-24 months), particularly among those with lower IQ and functioning. Clinical subgroups had higher baseline ratings, but distinct symptom courses; DS vs non-DS: more rapid initial improvement, similar stability of improvements; PNS vs non-PNS: similar rates of initial improvement and stability; transition vs no transition: slower rate of initial improvement, with greater stability of this rate. Conclusions:Continuous, frequent monitoring of negative symptoms in CHR is justified by 2 important study implications: (1) The initial 6 months of CHR program enrollment may be a key window for improving negative symptoms as less improvement is likely afterwards, (2) Early identification of clinical subgroups may inform distinct negative symptom trajectories and treatment needs.
更多
查看译文
关键词
psychosis,negative symptom trajectories,deficit syndrome
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要