Objectives

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.

Methods

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.

Results

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.

Conclusions

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.

中文翻译：

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自怜研究的文献计量学评论：科学映射文献，1999 年至 2020 年

目标

科学制图是一种结合定量分析、分类和可视化来识别书目对象之间的组成和相互关系的方法。尽管科学制图已被证明在不同领域很有用，但我们不知道它在自我同情研究中的应用，我们试图在此纠正。具体来说，我们使用文献计量科学映射来确定 1999 年至 2020 年间自我同情研究的总体结构。

方法

我们使用 Web of Science 数据库中的搜索词“自我同情”和“自我同情”收集了所有文章（N  = 2185 篇文章）。关键词共现分析、共引分析和网络中心性分析被用来描述自我同情研究的知识库和数量。

结果

我们的分析确定了自我同情文献中的四个一般主题：“心理健康和幸福”、“临床结果”、“自我认知”和“身体健康和家庭问题”。前三个主题相对完整，代表了自我慈悲研究的核心领域，而第四个主题的联系相对较少，并且在更广泛的语料库中更为突出。

结论

我们的结果，以及提供的交互式地图和广泛的表格，应该让读者能够检查研究集群和领域之间的联系，产生新颖的研究思路，并更全面地了解自我同情研究的知识基础。