Sydney School of Public Health, Prevention Research Collaboration, Charles Perkins Centre, The University of Sydney, Research and Education Network, Western Sydney Local Health District, Westmead Hospital, Corner Darcy & Hawkesbury Roads, Westmead, NSW, 2145, Australia.
Iverson Health Innovation Institute, Swinburne University of Technology, Melbourne, Australia.
Health Qual Life Outcomes. 2022 Mar 5;20(1):40. doi: 10.1186/s12955-022-01946-6.
Loneliness and social isolation are increasingly recognised as global public health threats, meaning that reliable and valid measures are needed to monitor these conditions at a population level. We aimed to determine if robust and practical scales could be derived for conditions such as loneliness and social isolation using items from a national survey.
We conducted psychometric analyses of ten items in two waves of the Household, Income and Labour Dynamics in Australia Survey, which included over 15,000 participants. We used the Hull method, exploratory structural equation modelling, and multidimensional item response theory analysis in a calibration sample to determine the number of factors and items within each factor. We cross-validated the factor structure using confirmatory factor analysis in a validation sample. We assessed construct validity by comparing the resulting sub-scales with measures for psychological distress and mental well-being.
Calibration and cross-validation consistently revealed a three-factor model, with sub-scales reflecting constructs of loneliness and social isolation. Sub-scales showed high reliability and measurement invariance across waves, gender, and age. Construct validity was supported by significant correlations between the sub-scales and measures of psychological distress and mental health. Individuals who met threshold criteria for loneliness and social isolation had consistently greater odds of being psychologically distressed and having poor mental health than those who did not.
These derived scales provide robust and practical measures of loneliness and social isolation for population-based research.
孤独和社会隔离日益被认为是全球公共卫生威胁,这意味着需要可靠和有效的措施来监测人群中的这些情况。我们旨在确定是否可以使用全国性调查中的项目来为孤独和社会隔离等情况得出可靠且实用的量表。
我们对澳大利亚家庭、收入和劳动力动态调查的两个波次中的 10 个项目进行了心理测量学分析,该调查共包括 15000 多名参与者。我们使用 Hull 方法、探索性结构方程建模和多维项目反应理论分析在校准样本中确定每个因素的因素和项目数量。我们在验证样本中使用验证性因子分析对因子结构进行了交叉验证。我们通过将得到的子量表与心理困扰和心理健康的衡量标准进行比较来评估结构效度。
校准和交叉验证一致显示出三因素模型,子量表反映了孤独和社会隔离的结构。子量表在各波次、性别和年龄之间具有较高的信度和测量不变性。子量表与心理困扰和心理健康衡量标准之间的显著相关性支持了结构效度。与没有达到孤独和社会隔离阈值标准的人相比,达到该标准的人在心理困扰和心理健康不佳方面的可能性始终更高。
这些衍生量表为基于人群的研究提供了可靠且实用的孤独和社会隔离衡量标准。