Loneliness is associated with increased morbidity and mortality. Deeper understanding of neurobiological mechanisms underlying loneliness is needed to identify potential intervention targets. We did not find any systematic review of neurobiology of loneliness. Using MEDLINE and PsycINFO online databases, we conducted a search for peer-reviewed publications examining loneliness and neurobiology. We identified 41 studies ( n = 16,771 participants) that had employed various methods including computer tomography (CT), structural magnetic resonance imaging (MRI), functional MRI (fMRI), electroencephalography (EEG), diffusion tensor imaging (DTI), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and post-mortem brain tissue RNA analysis or pathological analysis. Our synthesis of the published findings shows abnormal structure (gray matter volume or white matter integrity) and/or activity (response to pleasant versus stressful images in social versus nonsocial contexts) in the prefrontal cortex (especially medial and dorsolateral), insula (particularly anterior), amygdala, hippocampus, and posterior superior temporal cortex. The findings related to ventral striatum and cerebellum were mixed. fMRI studies reported links between loneliness and differential activation of attentional networks, visual networks, and default mode network. Loneliness was also related to biological markers associated with Alzheimer’s disease (e.g., amyloid and tau burden). Although the published investigations have limitations, this review suggests relationships of loneliness with altered structure and function in specific brain regions and networks. We found a notable overlap in the regions involved in loneliness and compassion, the two personality traits that are inversely correlated in previous studies. We have offered recommendations for future research studies of neurobiology of loneliness.
BackgroundMobile health (mHealth) offers a promising solution to the multitude of challenges the Vietnamese health system faces, but there is a scarcity of published information on mHealth in Vietnam.ObjectiveThe objectives of this scoping study were (1) to summarize the extent, range, and nature of mHealth initiatives in Vietnam and (2) to examine the opportunities and threats of mHealth utilization in the Vietnamese context.MethodsThis scoping study systematically identified and extracted relevant information from 20 past and current mHealth initiatives in Vietnam. The study includes multimodal information sources, including published literature, gray literature (ie, government reports and unpublished literature), conference presentations, Web-based documents, and key informant interviews.ResultsWe extracted information from 27 records from the electronic search and conducted 14 key informant interviews, allowing us to identify 20 mHealth initiatives in Vietnam. Most of the initiatives were primarily funded by external donors (n=15), while other initiatives were government funded (n=1) or self-funded (n=4). A majority of the initiatives targeted vulnerable and hard-to-reach populations (n=11), aimed to prevent the occurrence of disease (n=12), and used text messaging (short message service, SMS) as part of their intervention (n=14). The study revealed that Vietnamese mHealth implementation has been challenged by factors including features unique to the Vietnamese language (n=4) and sociocultural factors (n=3).ConclusionsThe largest threats to the popularity of mHealth initiatives are the absence of government policy, lack of government interest, heavy dependence on foreign funding, and lack of technological infrastructure. Finally, while current mHealth initiatives have already demonstrated promising opportunities for alternative models of funding, such as social entrepreneurship or private business models, sustainable mHealth initiatives outside of those funded by external donors have not yet been undertaken.
Depression is a serious, costly, and debilitating disorder that is understudied in rural women. Studies show that depression is associated with low social integration and support, but few studies investigate the relationship between depression and social network characteristics. This study examined the associations among women from three Ohio Appalachian counties enrolled in a health study, which aimed to collect information for a future social network smoking cessation intervention. An address-based sampling method was used to randomly select and recruit 404 women. A cross-sectional survey and interview were used to collect information about demographic, psychosocial, behavioral factors, and ego-centric social network characteristics, which are variables derived from an individual (ego) and her first degree contacts (alters). The CES-D scale assessed depressive symptoms. A multivariable logistic regression analysis described the association between these factors and participants with depression (defined as CES-D≥16). Higher network density, or greater number of relationships among alters divided by the total amount of alters, reduced the risk for depression (OR = 0.84, 95% confidence interval [CI] 0.73–0.95). Additionally, women with a high percentage of smoking alters were at greater risk for depression (OR = 1.19, 95% CI 1.02–1.39). Other factors associated with risk for depression included perceived stress score (OR = 1.34, 95% CI 1.24–1.45), loneliness score (OR = 1.37, 95% CI 1.05–1.80), and days with poor physical health (OR = 1.06, 95% CI 1.02–1.11). Findings suggest that psychosocial factors and social networks should be considered when addressing depression in clinical practice.
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