AI Article Synopsis

  • Adverse childhood experiences (ACEs), such as abuse and household challenges, negatively impact lifelong health, and enhancing social support for affected individuals is essential for coping.
  • The study examined social networks using data from Reddit and Twitter, comparing those with and without ACE exposure, employing a neural network to classify ACE disclosures.
  • Findings revealed that individuals with ACEs had fewer overall followers but showed higher mutual following patterns and a tendency to connect with others who also experienced ACEs, suggesting a strategy for building resilience through shared experiences.

Article Abstract

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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265411PMC
http://dx.doi.org/10.2196/45171DOI Listing

Publication Analysis

Top Keywords

social networks
24
individuals aces
16
individuals
10
aces
10
web-based social
8
networks individuals
8
adverse childhood
8
childhood experiences
8
social
8
experienced aces
8

Similar Publications

Health-related quality of life in Chagas cardiomyopathy: Development of a theoretical model.

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 PDF

Background: 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.

View Article and Find Full Text PDF

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 PDF

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 PDF

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.

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!