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Using Computational Phenotyping to Identify Divergent Strategies for Effort Allocation Across the Psychosis Spectrum
Schizophrenia Bulletin ( IF 6.6 ) Pub Date : 2024-03-18 , DOI: 10.1093/schbul/sbae024
Alexis E Whitton 1 , Jessica A Cooper 2 , Jaisal T Merchant 3 , Michael T Treadway 2, 4 , Kathryn E Lewandowski 3, 5
Affiliation  

Background and Hypothesis Disturbances in effort-cost decision-making have been highlighted as a potential transdiagnostic process underpinning negative symptoms in individuals with schizophrenia. However, recent studies using computational phenotyping show that individuals employ a range of strategies to allocate effort, and use of different strategies is associated with unique clinical and cognitive characteristics. Building on prior work in schizophrenia, this study evaluated whether effort allocation strategies differed in individuals with distinct psychotic disorders. Study Design We applied computational modeling to effort-cost decision-making data obtained from individuals with psychotic disorders (n = 190) who performed the Effort Expenditure for Rewards Task. The sample included 91 individuals with schizophrenia/schizoaffective disorder, 90 individuals with psychotic bipolar disorder, and 52 controls. Study Results Different effort allocation strategies were observed both across and within different disorders. Relative to individuals with psychotic bipolar disorder, a greater proportion of individuals with schizophrenia/schizoaffective disorder did not use reward value or probability information to guide effort allocation. Furthermore, across disorders, different effort allocation strategies were associated with specific clinical and cognitive features. Those who did not use reward value or probability information to guide effort allocation had more severe positive and negative symptoms, and poorer cognitive and community functioning. In contrast, those who only used reward value information showed a trend toward more severe positive symptoms. Conclusions These findings indicate that similar deficits in effort-cost decision-making may arise from different computational mechanisms across the psychosis spectrum.

中文翻译:

使用计算表型来识别精神病谱系中努力分配的不同策略

背景和假设 努力成本决策的干扰已被强调为支撑精神分裂症患者阴性症状的潜在跨诊断过程。然而,最近使用计算表型分析的研究表明,个体采用一系列策略来分配努力,并且不同策略的使用与独特的临床和认知特征相关。这项研究以先前对精神分裂症的研究为基础,评估了患有不同精神障碍的个体的努力分配策略是否有所不同。研究设计 我们将计算模型应用于从执行奖励任务的努力支出的精神障碍患者 (n = 190) 获得的努力成本决策数据。样本包括 91 名精神分裂症/分裂情感障碍患者、90 名精神双相情感障碍患者和 52 名对照者。研究结果在不同的疾病之间和内部观察到不同的努力分配策略。相对于精神病性双相情感障碍患者,更大比例的精神分裂症/分裂情感性障碍患者不使用奖励值或概率信息来指导努力分配。此外,在各种疾病中,不同的努力分配策略与特定的临床和认知特征相关。那些不使用奖励值或概率信息来指导努力分配的人有更严重的阳性和阴性症状,以及较差的认知和社区功能。相比之下,那些只使用奖励值信息的人表现出更严重的阳性症状的趋势。结论 这些发现表明,在整个精神病谱系中,不同的计算机制可能会导致努力成本决策中的类似缺陷。
更新日期:2024-03-18
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