Gründahl Marthe, Weiß Martin, Maier Lisa, Hewig Johannes, Deckert Jürgen, Hein Grit
Translational Social Neuroscience Unit, Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University of Würzburg, Würzburg, Germany.
Institute of Psychology, Department of Psychology I: Differential Psychology, Personality Psychology and Psychological Diagnostics, University of Würzburg, Würzburg, Germany.
Front Psychiatry. 2022 Apr 5;13:798596. doi: 10.3389/fpsyt.2022.798596. eCollection 2022.
A variety of factors contribute to the degree to which a person feels lonely and socially isolated. These factors may be particularly relevant in contexts requiring social distancing, e.g., during the COVID-19 pandemic or in states of immunodeficiency. We present the Loneliness and Isolation during Social Distancing (LISD) Scale. Extending existing measures, the LISD scale measures both state and trait aspects of loneliness and isolation, including indicators of social connectedness and support. In addition, it reliably predicts individual differences in anxiety and depression. Data were collected online from two independent samples in a social distancing context (the COVID-19 pandemic). Factorial validation was based on exploratory factor analysis (EFA; Sample 1, = 244) and confirmatory factor analysis (CFA; Sample 2, = 304). Multiple regression analyses were used to assess how the LISD scale predicts state anxiety and depression. The LISD scale showed satisfactory fit in both samples. Its two state factors indicate being as well as , while its three trait factors reflect general , and . Our results imply strong predictive power of the LISD scale for state anxiety and depression, explaining 33 and 51% of variance, respectively. Anxiety and depression scores were particularly predicted by low dispositional and by currently being more . In turn, being was related to being less (state) as well as having lower in general (trait). We provide a novel scale which distinguishes between acute and general dimensions of loneliness and social isolation while also predicting mental health. The LISD scale could be a valuable and economic addition to the assessment of mental health factors impacted by social distancing.
多种因素导致一个人感到孤独和社会孤立的程度。这些因素在需要保持社交距离的情况下可能尤为相关，例如在新冠疫情期间或免疫缺陷状态下。我们提出了社交距离期间的孤独与孤立（LISD）量表。LISD量表在现有测量方法的基础上进行了扩展，测量了孤独和孤立的状态和特质方面，包括社会联系和支持的指标。此外，它还能可靠地预测焦虑和抑郁的个体差异。数据是在社交距离背景下（新冠疫情）从两个独立样本在线收集的。因素验证基于探索性因素分析（EFA；样本1，n = 244）和验证性因素分析（CFA；样本2，n = 304）。多元回归分析用于评估LISD量表如何预测状态焦虑和抑郁。LISD量表在两个样本中均显示出良好的拟合度。它的两个状态因素表明处于[具体状态1]以及[具体状态2]，而它的三个特质因素反映了一般的[特质1]、[特质2]和[特质3]。我们的结果表明LISD量表对状态焦虑和抑郁具有很强的预测能力，分别解释了33%和51%的方差。焦虑和抑郁得分尤其由低倾向性的[具体特质]以及当前更多地处于[具体状态]所预测。反过来，处于[具体状态]与较少处于[另一具体状态]（状态）以及总体上具有较低的[另一特质]（特质）相关。我们提供了一个新颖的量表，它区分了孤独和社会孤立的急性和一般维度，同时还能预测心理健康。LISD量表可能是对受社交距离影响的心理健康因素评估的一个有价值且经济的补充。
