98%
921
2 minutes
20
Background: A critical facet of motivation is effort-based decision making, which refers to the mental processes involved in deciding whether a potential reward is worth the effort. To advance understanding of how individuals with schizophrenia and major depressive disorder utilize cost-benefit information to guide choice behavior, this study aimed to characterize individual differences in the computations associated with effort-based decision making.
Methods: One hundred forty-five participants (51 with schizophrenia, 43 with depression, and 51 healthy control participants) completed the Effort Expenditure for Rewards Task, with mixed effects modeling conducted to estimate the predictors of decision making. These model-derived, subject-specific coefficients were then clustered using k-means to test for the presence of discrete transdiagnostic subgroups with different profiles of reward, probability, and cost information utilization during effort-based decision making.
Results: An optimal 2-cluster solution was identified, with no significant differences in the distribution of diagnostic groups between clusters. Cluster 1 (n = 76) was characterized by overall lower information utilization during decision making than cluster 2 (n = 61). Participants in this low information utilization cluster were also significantly older and more cognitively impaired, and their utilization of reward, probability, and cost was significantly correlated with clinical amotivation, depressive symptoms, and cognitive functioning.
Conclusions: Our findings revealed meaningful individual differences among participants with schizophrenia, depression, and healthy control participants in their utilization of cost-benefit information in the context of effortful decision making. These findings may provide insight into different processes associated with aberrant choice behavior and may potentially guide the identification of more individualized treatment targets for effort-based motivation deficits across disorders.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.bpsc.2023.05.009 | DOI Listing |
Diagn Interv Radiol
September 2025
LMU University Hospital, LMU Munich, Department of Radiology, Munich, Germany.
Purpose: Computed tomography fluoroscopy (CTF)-guided biopsy is an established technique for sampling pulmonary lesions, particularly with the growing prevalence of lung nodule screening programs. This study investigated procedural and lesion-related factors affecting success and complication rates in routine CTF-guided lung core-needle biopsies at a tertiary center.
Methods: Consecutive patients undergoing percutaneous CTF-guided lung biopsies over a 10-year period (2007-2016) were retrospectively analyzed.
Background: Advancements in healthcare have significantly improved the prospect of patients with CHD, with over 97% now surviving adulthood. This growing population requires lifelong care and support to manage their condition. Digital health innovations, such as the "Ask Me Anything" (AMA) tool, aim to empower patients and improve collaboration with clinicians.
View Article and Find Full Text PDFThis study examines Mexico's fertility transition (1930-2015) and how socioeconomic status (SES), geography, and indigeneity shaped reproductive behaviors. Using net fertility-the number of surviving children under five-we assess how prestige bias (adopting high-status fertility norms) and conformism bias (aligning with local norms) influenced change across distinct population groups. We introduce the time, space, and population model to analyze the combined effects of macrostructural forces, spatial diffusion, and individual decision-making.
View Article and Find Full Text PDFPeriodontol 2000
September 2025
Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Oral cancer is a major global health burden, ranking sixth in prevalence, with oral squamous cell carcinoma (OSCC) being the most common type. Importantly, OSCC is often diagnosed at late stages, underscoring the need for innovative methods for early detection. The oral microbiome, an active microbial community within the oral cavity, holds promise as a biomarker for the prediction and progression of cancer.
View Article and Find Full Text PDFAnn Palliat Med
September 2025
Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.