Objectives: Modifiable lifestyle risk factors are of great interest in the prevention and management of Alzheimer's disease (AD). Loneliness and social networks may influence onset of AD, but little is known about this relationship in people with AD. The current study aimed to explore the relationship between loneliness and social networks (social measures) and cognitive and psychopathology decline (AD outcomes) in people with AD.
Methods: Ninety-three participants with mild to moderate AD were recruited from memory clinics, in a cross-sectional study. Social networks (measured by the Lubben Social Network Scale-6), feelings of loneliness (measured by De Jong Loneliness Scale), cognition (measured by the Standardized Mini-Mental State Examination), and psychopathology (measured by the Neuropsychiatric Inventory) were assessed in an interview setting. Two multiple regressions with bootstrap were conducted on cognition and psychopathology as outcome variables. Family and friends subsets of social networks and loneliness were entered as predictors and age, gender, and depression as covariates.
Results: The friendship subset of social networks was significantly related to cognition (independent of age, gender, depression, loneliness, and family subset of social network): B = 0.284, P = 0.01. Neither loneliness nor social networks predicted psychopathology (Ps > 0.05).
Conclusions: Maintaining or developing a close friendship network could be beneficial for cognition in people with AD. Alternatively, greater dementia severity may lead to fewer friends. More research on the direction of this relationship in people with AD is needed.
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http://dx.doi.org/10.1002/gps.5065 | DOI Listing |
R Soc Open Sci
January 2025
Mathematics Application Consortium for Science and Industry (MACSI), University of Limerick, Limerick, Ireland.
The analysis of social networks enables the understanding of social interactions, polarization of ideas and the spread of information, and therefore plays an important role in society. We use Twitter data-as it is a popular venue for the expression of opinion and dissemination of information-to identify opposing sides of a debate and, importantly, to observe how information spreads between these groups in our current polarized climate. To achieve this, we collected over 688 000 tweets from the Irish Abortion Referendum of 2018 to build a conversation network from users' mentions with sentiment-based homophily.
View Article and Find Full Text PDFFront Child Adolesc Psychiatry
March 2024
Military Population Health Directorate, Naval Health Research Center, San Diego, CA, United States.
Background: Adolescence is a particularly sensitive period of development for military-connected youth, given the socioemotional and physical changes that occur against the backdrop of the military career of their parent(s). Military-connected adolescents face unique stressors relative to their civilian counterparts, such as military relocations, parental absence due to deployments and trainings, and parental military-related physical and mental injury. These stressors may change family dynamics and disrupt social support networks, which can have lasting implications for adolescent health and well-being.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu India.
Autism spectrum disorder (ASD) is one of the complicated neurodevelopmental disorders that impacts the daily functioning and social interactions of individuals. It includes diverse symptoms and severity levels, making it challenging to diagnose and treat efficiently. Various deep learning (DL) based methods have been developed for diagnosing ASD, which rely heavily on behavioral assessment.
View Article and Find Full Text PDFBiomed Opt Express
January 2025
School of Psychology, Shenzhen University, Shenzhen, China.
Functional near-infrared spectroscopy (fNIRS) -based hyperscanning is a popular new technology in the field of social neuroscience research. In recent years, studying human social interaction from the perspective of inter-brain networks has received increasing attention. In the present study, we proposed a new approach named the hyper-brain independent component analysis (HB-ICA) for detecting the inter-brain networks from fNIRS-hyperscanning data.
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