Reinwarth Anna C, Ernst Mareike, Gerstorf Denis, Brähler Elmar, Wild Philipp S, Münzel Thomas, König Jochem, Lackner Karl J, Pfeiffer Norbert, Beutel Manfred E
Department of Psychiatry and Psychotherapy, University Medical Centre of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Department of Psychosomatic Medicine and Psychotherapy, University Medical Centre of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Sci Rep. 2025 May 23;15(1):17889. doi: 10.1038/s41598-025-00678-z.
Most research on adults' vulnerability to loneliness during the pandemic has been of limited quality. This study aimed to overcome previous limitations by examining loneliness trajectories in German adults from a population-based cohort during the pandemic using face-to-face assessment, identifying risk factors and highlighting those particularly relevant to older adults. Analyses included two measurement points before and two during the pandemic, combining data from the population-based Gutenberg Health Study and COVID-19 Study (N = 7001; baseline: M = 51.72, SD = 10.04). Growth mixture models identified distinct loneliness trajectories. Factors associated with these trajectories were tested by a multinomial logistic regression model including sociodemographic, individual, and pandemic-related predictors and interactions with age. Overall, mean loneliness increased. Three distinct classes were identified: No Loneliness (59.3%), Onset (23.3%), and Temporary Increase (17.4%). In comparison to No Loneliness, Onset was associated with reduction in social contact during the pandemic and Temporary Increase with sex, high school degree, pre-pandemic depression symptoms, pandemic-related stressors and social support. No unique risk factors for older adults were found. Interventions that strengthen one's adaptability to (acute) stressors and promote social resources with special attention to women may be a promising way to prevent loneliness during the pandemic.
大多数关于成年人在疫情期间易患孤独感的研究质量有限。本研究旨在克服先前的局限性，通过在疫情期间使用面对面评估对德国成年人群体队列中的孤独轨迹进行研究，识别风险因素，并突出那些与老年人特别相关的因素。分析包括疫情前的两个测量点和疫情期间的两个测量点，结合了基于人群的古登堡健康研究和新冠疫情研究的数据（N = 7001；基线：M = 51.72，标准差 = 10.04）。生长混合模型确定了不同的孤独轨迹。通过多项逻辑回归模型对与这些轨迹相关的因素进行了测试，该模型包括社会人口统计学、个体和与疫情相关的预测因素以及与年龄的相互作用。总体而言，平均孤独感有所增加。确定了三个不同的类别：无孤独感（59.3%）、开始出现孤独感（23.3%）和暂时增加（17.4%）。与无孤独感相比，开始出现孤独感与疫情期间社交接触的减少有关，暂时增加与性别、高中学历、疫情前的抑郁症状、与疫情相关的压力源和社会支持有关。未发现老年人的独特风险因素。加强一个人对（急性）压力源的适应能力并促进社会资源，特别关注女性，可能是在疫情期间预防孤独感的一种有前途的方法。
