The role of contextual modulations has been extensively studied in basic sensory and cognitive processes. However, little is known about their impact on social cognition, let alone their disruption in disorders compromising such a domain. In this chapter, we flesh out the social context network model (SCNM), a neuroscientific proposal devised to address the issue. In SCNM terms, social context effects rely on a fronto-temporo-insular network in charge of (a) updating context cues to make predictions, (b) consolidating context-target associative learning, and (c) coordinating internal and external milieus. First, we characterize various social cognition domains as context-dependent phenomena. Then, we review behavioral and neural evidence of social context impairments in behavioral variant frontotemporal dementia (bvFTD) and autism spectrum disorder (ASD), highlighting their relation with key SCNM hubs. Next, we show that other psychiatric and neurological conditions involve context-processing impairments following damage to the brain regions included in the model. Finally, we call for an ecological approach to social cognition assessment, moving beyond widespread abstract and decontextualized methods.
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http://dx.doi.org/10.1007/7854_2016_443 | DOI Listing |
BMC Health Serv Res
January 2025
Australian Centre for Health Services Innovation and Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia.
Background: Unwarranted clinical variation presents a major challenge in contemporary healthcare, indicating potential inequalities and inefficiencies, and unrealised potential for better outcomes. Despite an increasing focus on unwarranted clinical variation, and consideration of efforts to address this challenge, evidence-based strategies which achieve this are limited. Audit and feedback of healthcare processes (process auditing) and clinician engagement are important tools which may help to reduce unwarranted clinical variation, however their application in maternity care is yet to be thoroughly explored.
View Article and Find Full Text PDFBMC Psychiatry
January 2025
Division of Epidemiology and Social Sciences, Institute for Health and Equity, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
Background: During adolescence, a critical developmental phase, cognitive, psychological, and social states interact with the environment to influence behaviors like decision-making and social interactions. Depressive symptoms are more prevalent in adolescents than in other age groups which may affect socio-emotional and behavioral development including academic achievement. Here, we determined the association between depression symptom severity and behavioral impairment among adolescents enrolled in secondary schools of Eastern and Central Uganda.
View Article and Find Full Text PDFBMC Public Health
January 2025
Amsterdam UMC location Vrije Universiteit Amsterdam, Public and Occupational Health, De Boelelaan 1117, Amsterdam, the Netherlands.
Background: Developing interventions along with the population of interest using systems thinking is a promising method to address the underlying system dynamics of overweight. The purpose of this study is twofold: to gain insight into the perspectives of adolescents regarding: (1) the system dynamics of energy balance-related behaviours (EBRBs) (physical activity, screen use, sleep behaviour and dietary behaviour); and (2) underlying mechanisms and overarching drivers of unhealthy EBRBs.
Methods: We conducted Participatory Action Research (PAR) to map the system dynamics of EBRBs together with adolescents aged 10-14 years old living in a lower socioeconomic, ethnically diverse neighbourhood in Amsterdam East, the Netherlands.
Sci Rep
January 2025
Department of Psychology, Faculty of Behavioural and Social Sciences, University of Groningen, Grote Kruisstraat 2/1, 9712TS, Groningen, The Netherlands.
Recruits are exposed to high levels of psychological and physical stress during the special forces selection period, resulting in dropout rates of up to 80%. To identify who likely drops out, we assessed a group of 249 recruits, every week of the selection program, on their self-efficacy, motivation, experienced psychological and physical stress, and recovery. Using linear regression as well as state-of-the-art machine learning techniques, we aimed to build a model that could meaningfully predict dropout while remaining interpretable.
View Article and Find Full Text PDFBMJ Open
January 2025
The Third People's Hospital of Zhuhai, Zhuhai, Guangdong, China
Objectives: To explore the factors influencing medication adherence and the medication needs of patients with schizophrenia when living in a community in China.
Design: A qualitative study.
Setting: Community and psychiatric ward in Zhuhai city, Guangdong province.
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