Medvedev Oleg N, Cervin Matti, Barcaccia Barbara, Siegert Richard J, Roemer Anja, Krägeloh Christian U
University of Waikato, School of Psychology, Hillcrest, Hamilton, 3216 New Zealand.
Lund University, Lund, Sweden.
Mindfulness (N Y). 2021;12(4):911-922. doi: 10.1007/s12671-020-01555-8. Epub 2020 Nov 26.
Mindfulness, positive affect, and compassion may protect against psychological distress but there is lack of understanding about the ways in which these factors are linked to mental health. Network analysis is a statistical method used to investigate complex associations among constructs in a single network and is particularly suitable for this purpose. The aim of this study was to explore how mindfulness facets, affect, and compassion were linked to psychological distress using network analysis.
The sample ( = 400) included equal numbers from general and student populations who completed measures of five mindfulness facets, compassion, positive and negative affect, depression, anxiety, and stress. Network analysis was used to explore the direct associations between these variables.
Compassion was directly related to positive affect, which in turn was strongly and inversely related to depression and positively related to the observing and describing facets of mindfulness. The non-judgment facet of mindfulness was strongly and inversely related to negative affect, anxiety, and depression, while non-reactivity and acting with awareness were inversely associated with stress and anxiety, respectively. Strong associations were found between all distress variables.
The present network analysis highlights the strong link between compassion and positive affect and suggests that observing and describing the world through the lens of compassion may enhance resilience to depression. Taking a non-judging and non-reacting stance toward internal experience while acting with awareness may protect against psychological distress. Applicability of these findings can be examined in experimental studies aiming to prevent distress and enhance psychological well-being.
正念、积极情绪和同情心可能有助于预防心理困扰，但对于这些因素与心理健康的关联方式尚缺乏了解。网络分析是一种用于研究单一网络中各构念之间复杂关联的统计方法，特别适用于此目的。本研究旨在通过网络分析探索正念的各个方面、情绪和同情心与心理困扰之间的联系。
样本（n = 400）包括来自普通人群和学生群体的数量相等的个体，他们完成了关于正念的五个方面、同情心、积极和消极情绪、抑郁、焦虑和压力的测量。网络分析用于探索这些变量之间的直接关联。
同情心与积极情绪直接相关，积极情绪又与抑郁呈强烈的负相关，与正念的观察和描述方面呈正相关。正念的不评判方面与消极情绪、焦虑和抑郁呈强烈的负相关，而非反应性和有意识行动分别与压力和焦虑呈负相关。在所有困扰变量之间发现了强烈的关联。
本网络分析突出了同情心与积极情绪之间的紧密联系，并表明通过同情心的视角观察和描述世界可能增强对抑郁的恢复力。在有意识行动时，对内心体验采取不评判和不反应的立场可能预防心理困扰。这些发现的适用性可在旨在预防困扰和增强心理健康的实验研究中进行检验。
