Department of Psychology, Utah State University, 2810 Old Main Hill, Logan, UT, 84322, USA.
Department of Psychiatry and Behavioral Sciences, University of Minnesota, 2450 Riverside Ave, F227, Minneapolis, MN, 55454, USA.
Qual Life Res. 2019 Nov;28(11):2909-2917. doi: 10.1007/s11136-019-02232-7. Epub 2019 Jun 14.
The current study aimed to examine how patterns of interpersonal relational contexts (e.g., face-to-face or technology-based) and processes (e.g., initiated or accepted) relate to depressive symptomology and life satisfaction.
Participants were recruited through Amazon's Mechanical Turk (n = 962 adults [52.1% female; aged 18-78; 16.4% Non-White]). Quota sampling was used to closely match the sample demographics to that of the United States Census data. Latent class analyses (LCA) identified classes of interpersonal relations using the Multidimensional Interpersonal Relations Scale. Next, participants' responses on the Beck Depression Inventory and Satisfaction With Life Scale were examined to evaluate differences in depressive symptoms and life satisfaction across classes.
LCA results supported a 4-class model, in which classes were characterized by patterns of relational contexts and processes: Class 1 (50.6%) engagement across all contexts (e.g., face-to-face) and processes (e.g., initiated); Class 2 (12.7%) engagement across all contexts and processes except Facebook; Class 3 (24.0%) engagement in all contexts and only passive processes; and Class 4 (12.7%) engagement in only technology-based contexts and passive processes. Membership in Classes 1 and 2 was associated with lower depressive symptomology and higher life satisfaction as compared to Classes 3 and 4.
The findings suggest that patterns of relations differentially relate to depressive symptoms and life satisfaction. The findings suggest that multicontextual (e.g., face-to-face and technology-based) and reciprocal relationships with friends (e.g., initiating and accepting connections) may play an important role in the association between interpersonal relations with life satisfaction and depressive symptoms.
本研究旨在探讨人际关系的模式（例如，面对面或基于技术的）和过程（例如，主动发起或被动接受）如何与抑郁症状和生活满意度相关。
通过 Amazon 的 Mechanical Turk（n=962 名成年人[女性占 52.1%；年龄 18-78 岁；16.4%非白人]）招募参与者。配额抽样用于使样本人口统计学特征与美国人口普查数据密切匹配。潜在类别分析（LCA）使用多维人际关系量表来确定人际关系的类别。接下来，检查参与者在贝克抑郁量表和生活满意度量表上的反应，以评估不同人际关系类别之间的抑郁症状和生活满意度差异。
LCA 结果支持 4 类模型，其中类别的特点是人际关系的模式：类 1（50.6%）在所有情境（例如面对面）和过程（例如主动发起）中都有参与；类 2（12.7%）在所有情境和过程中都有参与，但不包括 Facebook；类 3（24.0%）在所有情境中都有参与，但只有被动过程；类 4（12.7%）仅在基于技术的情境中且只有被动过程。与类 3 和类 4 相比，类 1 和类 2 的成员与较低的抑郁症状和较高的生活满意度相关。
研究结果表明，人际关系模式与抑郁症状和生活满意度存在差异。研究结果表明，与朋友的多情境（例如面对面和基于技术的）和互惠关系（例如主动发起和接受联系）可能在人际关系与生活满意度和抑郁症状之间的关联中发挥重要作用。
