Background: Adverse childhood experiences (ACEs), which include abuse and neglect and various household challenges such as exposure to intimate partner violence and substance use in the home, can have negative impacts on the lifelong health of affected individuals. Among various strategies for mitigating the adverse effects of ACEs is to enhance connectedness and social support for those who have experienced them. However, how the social networks of those who experienced ACEs differ from the social networks of those who did not is poorly understood.
Objective: In this study, we used Reddit and Twitter data to investigate and compare social networks between individuals with and without ACE exposure.
Methods: We first used a neural network classifier to identify the presence or absence of public ACE disclosures in social media posts. We then analyzed egocentric social networks comparing individuals with self-reported ACEs with those with no reported history.
Results: We found that, although individuals reporting ACEs had fewer total followers in web-based social networks, they had higher reciprocity in following behavior (ie, mutual following with other users), a higher tendency to follow and be followed by other individuals with ACEs, and a higher tendency to follow back individuals with ACEs rather than individuals without ACEs.
Conclusions: These results imply that individuals with ACEs may try to actively connect with others who have similar previous traumatic experiences as a positive connection and coping strategy. Supportive interpersonal connections on the web for individuals with ACEs appear to be a prevalent behavior and may be a way to enhance social connectedness and resilience in those who have experienced ACEs.
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http://dx.doi.org/10.2196/45171 | DOI Listing |
Trop Med Int Health
January 2025
Postgraduate Course in Reabilitação e Desempenho Funcional, Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM), Diamantina, Brazil.
Objective: Chagas disease can cause several complications, such as Chagas cardiomyopathy, the most severe clinical form of the disease. Chagas cardiomyopathy is complex and involves biological and psychosocial factors that can compromise health-related quality of life. However, it is necessary to establish interactions that significantly impact the health-related quality of life of this population.
View Article and Find Full Text PDFBackground: There is little evidence on the use or potential use of NHS repositories within the UK.
Methods: A mixed methods (quantitative/qualitative) study of two repositories: amber-the home of ambulance service research, and East Midlands Evidence Repository (EMER). A structured online questionnaire was distributed via the repository home page, and promoted via social media, email networks, and lists.
Peer support from social networks of gay, bisexual, and other men who have sex with men (GBMSM) has been recognised as a critical driver of engagement with HIV prevention. Using data from an online cross-sectional survey of 1,032 GBMSM aged 18 or over in Australia, a latent class analysis was conducted to categorise participants based on social support, LGBTQ + community involvement, and social engagement with gay men and LGBTQ + people. Comparisons between classes were assessed using multivariable multinomial logistic regression.
View Article and Find Full Text PDFJ Environ Manage
January 2025
School of Economics and Management, Beijing Jiaotong University, 100091, Beijing, China. Electronic address:
Chinese construction enterprises are at a pivotal point in their transition to sustainable development, with Environmental, Social, and Governance (ESG) emerging as a key driver. However, limited understanding of ESG mechanisms hampers effective management strategies. To address this challenge, this study constructs an ESG introduction mechanism framework based on Bayesian networks and machine learning algorithms.
View Article and Find Full Text PDFGeriatr Nurs
January 2025
School of Nursing, Fudan University, Shanghai 200032, China. Electronic address:
Objective: To explore the network structure of common geriatric syndromes and conditions in physically disabled older adults.
Methods: We chose fourteen common geriatric syndromes and conditions from the dataset and estimated networks with the partial correlation network method. We tested the stability and accuracy of the network using the package "bootnet" in R software.
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