: Theoretical models in informal dementia care have been developed to understand how risk and protective factors interact to cause caregiver's distress. The development of psychological network analysis provides a rich complement to our current models, as explores how different variables (or nodes) are associated using graph theories. : The present study explored the use of network analysis using data from 125 informal caregivers of their partner with dementia (PwD). The included variables were recipient's dependency, self-efficacy, conflict within the family, dyadic adjustment, and caregiver's distress. : The analysis suggests a complex network of interacting variables. The core variable was not the caregiver's distress but rather their dyadic adjustment with their PwD. Variables were associated with caregiver distress through a large array of direct and indirect pathways and were associated with each other in the form of an asymmetric spider's web.: The results show the complex interplay of variables in a psychological network. The central role of distress suggests a complex and dynamic role, notably through a bidirectional influence with quality of interactions. In the same way, quality of interactions appeared as one of the strongest nodes, its connectivity suggesting a crucial role to consider in our models and interventions.
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http://dx.doi.org/10.1080/13607863.2022.2134294 | DOI Listing |
Physiol Rev
January 2025
Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland.
Physical activity is a meaningful part of life, which starts before birth and lasts until death. There are many health benefits to be derived from physical activity, hence, regular engagement is recommended on a weekly basis. However, these recommendations are often not met.
View Article and Find Full Text PDFPLoS One
January 2025
School of Behavioral Sciences, The Academic College of Tel Aviv-Yafo, Tel Aviv, Israel.
Background: Occupational burnout, resulting from long-term exposure to work-related stressors, is a significant risk factor for both physical and mental health of employees. Most research on burnout focuses on routine situations, with less attention given to its causes and manifestations during prolonged national crises such as war. According to the Conservation of Resources theory, wartime conditions are associated with a loss of resources, leading to accelerated burnout.
View Article and Find Full Text PDFPsychiatry Clin Neurosci
January 2025
Shanghai Artificial Intelligence Laboratory, Shanghai, China.
Large language models (LLMs) have gained significant attention for their capabilities in natural language understanding and generation. However, their widespread adoption potentially raises public mental health concerns, including issues related to inequity, stigma, dependence, medical risks, and security threats. This review aims to offer a perspective within the actor-network framework, exploring the technical architectures, linguistic dynamics, and psychological effects underlying human-LLMs interactions.
View Article and Find Full Text PDFJ Res Adolesc
March 2025
Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
The Nordic countries are among the most digitally advanced societies in the world. Past research suggests that both social support offline and interaction online are linked to adolescent psychological adjustment. However, less is known regarding the complex implications of distinctive sources of social support offline and online interaction for a broader range of indices of adolescent psychosocial well-being, including its contemporary forms such as social media addiction.
View Article and Find Full Text PDFNeurosurg Rev
January 2025
Department of Neurological Surgery, University of Virginia, Charlottesville, VA, USA.
Postoperative facial nerve (FN) dysfunction is associated with a significant impact on the quality of life of patients and can result in psychological stress and disorders such as depression and social isolation. Preoperative prediction of FN outcomes can play a critical role in vestibular schwannomas (VSs) patient care. Several studies have developed machine learning (ML)-based models in predicting FN outcomes following resection of VS.
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