A substantial literature has found that religiosity is positively related to individuals' civic engagement and informal helping behavior. Concurrently, social networks as sources of information and encouragement have been suggested as the mechanism underlying phenomena including successful job searches, improved health and greater subjective well-being. In this paper we use data from the Portraits of American Life Study (PALS) to examine whether religiously based social networks explain the well-established relationship between religion and civic engagement. We test potential mechanisms including beliefs, affiliation, and social networks, and we find that having a strong network of religious friends explains the effect of church attendance for several civic and neighborly outcomes. We suggest this phenomenon may exist in other, non-religious, spheres that also produce strong friendship networks.
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http://dx.doi.org/10.1016/j.ssresearch.2012.09.011 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Department of Statistics and Data Science, College of Science, Southern University of Science and Technology, Shenzhen 518055, China.
Social media is profoundly changing our society with its unprecedented spreading power. Due to the complexity of human behaviors and the diversity of massive messages, the information-spreading dynamics are complicated, and the reported mechanisms are different and even controversial. Based on data from mainstream social media platforms, including WeChat, Weibo, and Twitter, cumulatively encompassing a total of 7.
View Article and Find Full Text PDFCurr Opin Support Palliat Care
January 2025
Department of Medical Social Science, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Purpose Of The Review: Today, two-thirds of all cancer survivors are at least 65 years old. Older cancer survivors have complex care needs, and addressing their social determinants of health (SDoH) is critical for improving and managing survivorship outcomes for this uniquely vulnerable population, yet research specifically examining these associations remains limited and emergent. To this end, we describe the emergent body of evidence on the associations between SDoH domains and older cancer survivors' outcomes.
View Article and Find Full Text PDFFront Psychol
January 2025
Guangdong Polytechnic of Science and Trade, Guangzhou, China.
Introduction: The present study examines the role of social network diversity in fostering cultural sustainability among Chinese social media users.
Methods: Utilizing a quantitative methodological approach, data was gathered from a sample of 1,200 active users across various Chinese social media platforms. Participants completed surveys assessing the diversity of their cultural interactions on these platforms, their levels of cultural empathy, cultural adaptability, and the sustainability of cultural practices.
Front Psychiatry
January 2025
Department of Public Health, Biostatistics and Medical Informatics Research Group, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB), Brussels, Belgium.
Background: Paternal perinatal depression affects 10% of fathers, implying a significant burden on families and public health. A better insight into the population's health literacy could guide professionals and policymakers in addressing these men and making better use of existing healthcare options. It is also crucial for caregivers, as they play a vital role in identifying symptoms, encouraging help-seeking, and reducing stigma.
View Article and Find Full Text PDFFront Artif Intell
January 2025
CONAHCYT-Instituto Potosino de Investigación Científica y Tecnológica, A.C. División de Geociencias Aplicadas, San Luis Potosí, Mexico.
This systematic review provides a state-of-art of Artificial Intelligence (AI) models such as Machine Learning (ML) and Deep Learning (DL) development and its applications in Mexico in diverse fields. These models are recognized as powerful tools in many fields due to their capability to carry out several tasks such as forecasting, image classification, recognition, natural language processing, machine translation, etc. This review article aimed to provide comprehensive information on the Machine Learning and Deep Learning algorithms applied in Mexico.
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