ArticleSchizophrenia bulletin2024
Using Computational Phenotyping to Identify Divergent Strategies for Effort Allocation Across the Psychosis Spectrum.
Article in Schizophrenia bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Nociceptin orphanin F/Q Pathways are dysregulated by stress and modulate reward responsiveness and motivated behavior across species.Molecular psychiatry · 2026Article
- Understanding Effort-Cost Decision-Making Mechanisms in Mood and Psychotic Disorders: A Computational Modeling Approach Across Physical and Cognitive Effort Paradigms.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Article
- Effort and substance use: differentiating tobacco use through reinforcement learning of effort based decision making.Journal of computational neuroscience · 2026Article
- Shared and distinct features of common effort-based decision-making paradigms and their relation to brain structure and neuropsychiatric conditions: An integrated narrative review.Cognitive, affective & behavioral neuroscience · 2026Review
- Effort and Substance Use: Differentiating Tobacco Use Through Reinforcement Learning of Effort Based Decision Making.Research square · 2026Article
- Increased Sensitivity to Effort and Perception of Effort in People with Schizophrenia.Schizophrenia bulletin · 2025Article
- Beyond reward learning deficits: Exploration-exploitation instability reveals computational heterogeneity in value-based decision making in early psychosis.medRxiv : the preprint server for health sciences · 2025Article
- Using the grip strength effort task to measure reward processing dysfunction in schizophrenia and major depressive disorder.Neuroscience applied · 2025Article
- Increasing the Construct Validity of Computational Phenotypes of Mental Illness Through Active Inference and Brain Imaging.Brain sciences · 2024Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
background and hypothesisDisturbances 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
designWe 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
resultsDifferent 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.
conclusionsThese findings indicate that similar deficits in effort-cost decision-making may arise from different computational mechanisms across the psychosis spectrum.
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