Department of Behavioural Science and Health, Institute of Epidemiology & Health Care, University College London, London, UK.
Psychol Med. 2023 Jul;53(9):3943-3951. doi: 10.1017/S0033291722000605. Epub 2022 Mar 31.
The coronavirus disease 2019 (COVID-19) pandemic has brought about significant behavioural changes, one of which is increased time spent at home. This could have important public health implications. This study aimed to explore longitudinal patterns of 'home confinement' (defined as not leaving the house/garden) during the COVID-19 pandemic, and the associated predictors and mental health outcomes.
Data were from the UCL COVID-19 Social Study. The analytical sample consisted of 25 390 adults in England who were followed up for 17 months (March 2020-July 2021). Data were analysed using growth mixture models.
Our analyses identified three classes of growth trajectories, including one class showing a high level of persistent home confinement (the home-confined, 24.8%), one changing class with clear alignment with national containment measures (the adaptive, 32.0%), and one class with a persistently low level of confinement (the unconfined, 43.1%). A range of factors were associated with the class membership of home-confinement trajectories, such as age, gender, income, employment status, social relationships and health. The home-confined class had the highest number of depressive (diff = 1.34-1.68, < 0.001) and anxiety symptoms (diff = 0.84-1.05, < 0.001) at the end of the follow-up than the other two classes.
There was substantial heterogeneity in longitudinal patterns of home confinement during the COVID-19 pandemic. People with a persistent high level of confinement had the worst mental health outcomes, calling for special attention in mental health action plans, in particular targeted interventions for at-risk groups.
2019 年冠状病毒病(COVID-19)大流行带来了重大的行为变化,其中之一是在家中度过的时间增加。这可能对公共卫生具有重要意义。本研究旨在探索 COVID-19 大流行期间“居家隔离”(定义为不出门/花园)的纵向模式,以及相关的预测因素和心理健康结果。
数据来自 UCL COVID-19 社会研究。分析样本包括英格兰的 25390 名成年人,他们在 17 个月(2020 年 3 月至 2021 年 7 月)内接受了随访。使用增长混合模型进行数据分析。
我们的分析确定了三种增长轨迹类别,包括一个持续高度居家隔离的类别(居家隔离者,24.8%),一个与国家遏制措施明显一致的变化类别(适应性,32.0%),以及一个持续低度居家隔离的类别(未隔离者,43.1%)。一系列因素与居家隔离轨迹的类别成员有关,例如年龄、性别、收入、就业状况、社会关系和健康。与其他两个类别相比,居家隔离类别在随访结束时的抑郁症状(差异=1.34-1.68,<0.001)和焦虑症状(差异=0.84-1.05,<0.001)数量最多。
在 COVID-19 大流行期间,居家隔离的纵向模式存在很大的异质性。持续高度隔离的人心理健康状况最差,这需要在心理健康行动计划中特别关注,特别是针对高危人群的针对性干预。