According to its evolutionary conceptualization, loneliness is considered an internal signal (i.e., social pain) that alerts its experiencers to a threat to social relationships and promotes relationship restoration. Although this conceptualization seems plausible, it needs to be reconciled with seemingly inconsistent findings. First, loneliness is often defined as perceived social isolation, which does not necessarily correspond with objective isolation. The discrepancy between objective and subjective social isolation implies that loneliness is not an accurate signal of social isolation. Second, social pain is associated with not only prosocial behaviors but also aggressive behaviors, which are detrimental to social relationships. Third, chronic loneliness is associated with a wide range of health problems, which seems incongruent with the notion of loneliness as an adaptation. This review addresses each of these three issues and argues that the evolutionary conceptualization of loneliness can integrate these apparent contractions.

Psychological research has advanced considerably with the advent of noninvasive brain imaging techniques, which have been further enhanced by recent developments in neuroscientific analysis methods. These advancements have enabled scientists to assess similarities and dissimilarities in neural activity between individuals, thereby establishing neuroscientific approaches as powerful tools for elucidating the characteristics of dyadic and group relationships. In this paper, we introduce the features of cutting-edge neuroimaging analysis techniques and explore the emerging relationship between shared reality and social connections. We specifically argue from the perspective of neural homophily that similarity in how individuals perceive the world is crucial for the formation and maintenance of social connections. Furthermore, we offer a novel perspective on the mechanisms by which individuals may become socially isolated and experience loneliness, suggesting that these processes are driven by a lack of shared reality. Finally, we outline future directions, highlighting new questions expected to be addressed through technological advancements, and propose pathways to deepen our understanding of social connections.

Social isolation and loneliness among women during pregnancy and child-rearing have become more apparent because of the effects of the coronavirus disease 2019 (COVID-19) pandemic and other social factors. Social isolation and loneliness among women during the perinatal and child-rearing periods pose a risk of serious problems such as suicide and child abuse. In this scenario, information and communication technology (ICT) is attracting attention as a method of resolving social isolation and loneliness. ICT enables people located far apart to communicate. In recent years, technologies based on artificial intelligence and virtual reality have been increasingly utilized to support people. This study examined a wide range of psychological approaches to address social isolation and loneliness by using ICT. It also explored the potential of using ICT to support women during the perinatal and child-rearing periods. Moreover, this study investigated the possible dangers of ICT in promoting social isolation and loneliness.

Social isolation and loneliness are social factors that can affect health. These factors are called “social determinants of health” (“SDH”). Several studies have demonstrated that SDH influences health status, leading to health disparities between groups from different social backgrounds. Measures to address health disparities include a high-risk approach, which targets individuals with high health risks and is aimed at secondary prevention of diseases; a population approach, which aims to reduce the health risks of the entire population; and different types of population approaches that focus on reducing health disparities by targeting specific groups. By applying machine learning and accounting for differences in heterogeneity between subgroups within the target population, novel interventions have been proposed to address health disparities. To reduce health disparities through SDH initiatives, planning projects on existing evidence, evaluating their effectiveness and impact, and generating new evidence are necessary. The linkage and accumulation of data between databases and large-scale surveys should also be promoted. Therefore, a database with uniform national medical, health, and living environment information must be created.