Social networks in cardiovascular disease management.

Expert Rev Pharmacoecon Outcomes Res

University of Maryland School of Pharmacy, 220 Arch Street, 12th Floor Baltimore, MD 21201, USA.

Published: December 2010

Cardiovascular disease remains the leading cause of death in the USA. Social networks have a positive association with obesity, smoking cessation and weight loss. This article summarizes studies evaluating the impact of social networks on the management of cardiovascular disease. The 35 studies included in the article describe the impact of social networks on a decreased incidence of cardiovascular disease, depression and mortality. In addition, having a large-sized social network is also associated with better outcomes and improved health. The role of pharmacists is beginning to play an important role in the patient-centered medical home, which needs to be incorporated into social networks. The patient-centered medical home can serve as an adaptive source for social network evolvement.

Download full-text PDF

Source
http://dx.doi.org/10.1586/erp.10.68DOI Listing

Publication Analysis

Top Keywords

social networks
20
cardiovascular disease
16
management cardiovascular
8
impact social
8
social network
8
patient-centered medical
8
social
7
cardiovascular
4
networks cardiovascular
4
disease
4

Similar Publications

Spreading dynamics of information on online social networks.

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 PDF

Social determinants of health and health outcomes in older cancer survivors.

Curr 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 PDF

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.

View Article and Find Full Text PDF

Awareness, knowledge, and attitudes of the Belgian general population towards paternal perinatal depression: a descriptive cross-sectional study.

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 PDF

A systematic review of Machine Learning and Deep Learning approaches in Mexico: challenges and opportunities.

Front 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.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!