Science mapping is a methodology that combines quantitative analysis, classification, and visualisation to identify the composition and inter-relationships between bibliographic objects. Although science mapping has proven useful in diverse fields, we are not aware of its application to self-compassion research, which we sought to rectify here. Specifically, we used bibliometric science mapping to identify the overarching structure of self-compassion research between 1999 and 2020.
We collected all articles using the search terms “self-compassion” and “self compassion” in the Web of Science database (N = 2185 articles). Keywords co-occurrence analysis, co-citation analysis, and network centrality analysis were used to describe the knowledge base and volume of self-compassion research.
Our analyses identified four general themes in the self-compassion literature: “mental health and well-being”, “clinical outcomes”, “self-perceptions”, and “physical health and family issues”. The first three themes are relatively well-consolidated and represent core areas of research on self-compassion, whereas the fourth theme is relatively less well-connected and more emergent within the broader corpus.
Our results, and the provision of interactive maps and extensive tables, should allow readers to examine connections between research clusters and areas, generate novel research ideas, and more fully understand the knowledge base of self-compassion research.