Loneliness and intersectionality: A progressive conditional approach

Yang, Keming

Abstract

Both loneliness and intersectionality have become well established areas of academic research since the 1970s and 1980s. Nevertheless, only very recently some meaningful connections were made between the two, although researchers have paid attention to the interactive effects of two or more socio-demographic attributes on loneliness. For intersectionality, much of academic research is invested in establishing it as a theoretical approach in tackling social injustice, whilst how it should be studied empirically remains a major challenge. In contrast, research on loneliness has been predominantly empirical, and the small number of studies on loneliness from the intersectional perspective have adopted different research methodologies. This paper proposes and illustrates an approach loyal to the fundamental principles of intersectionality and simple to conduct in empirical investigations at the same time. First, it focuses exclusively on intersectional cross-classifications rather than both the main and the interactional effects; second, it demands a rationale of starting from one attribute and then moving on to include an additional attribute at a time; third, it examines the intersectional cross-classifications and their relationships with the interested outcome systematically without transforming the data in set memberships. The approach is illustrated with analyses of the data collected in Great Britain in the seventh round (2014/15) of European Social Survey. Young people (under 30) of ethnic minority and born inside Great Britain suffered from the highest percentage of frequent loneliness (15%), whilst their counterparts born outside the country enjoyed the lowest rate. Among the middle-aged, ethnicity determined how vulnerable they were to frequent loneliness. For older people (60+) born outside Great Britain, regardless of ethnicity, the percentage of frequent loneliness was 10%.

Citation

Yang, K. (2023). Loneliness and intersectionality: A progressive conditional approach. Current Research in Behavioural Sciences, 5, Article 100122. https://doi.org/10.1016/j.crbeha.2023.100122

• Journal Article Type: Article
• Acceptance Date: May 23, 2023
• Online Publication Date: Jul 5, 2023
• Publication Date: 2023
• Deposit Date: Oct 23, 2023
• Publicly Available Date: Oct 23, 2023
• Journal: Current Research in Behavioral Sciences
• Print ISSN: 2666-5182
• Electronic ISSN: 2666-5182
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 5
• Article Number: 100122
• DOI: https://doi.org/10.1016/j.crbeha.2023.100122
• Keywords: Psychology (miscellaneous); Behavioral Neuroscience
• Public URL: https://durham-repository.worktribe.com/output/1815052