Understanding the impact of the COVID-19-related lockdown in university workers. Identifying groups through cluster analysis

OBJECTIVE: To analyse the COVID-19-related lockdown impact on University workers, to identify groups based on this information, and to study the factors associated with each group. STUDY DESIGN: Cross-sectional study. METHODS: A survey was conducted 3.5 weeks after COVID-19-related lockdown in University workers in Spain. Sociodemographic variables, housing, work, health conditions, levels of anxiety, stress and depression (DASS-21), and social support (MSPSS) were collected. A cluster analysis was performed to identify groups depending on the impact of the lockdown. Differences between groups were tested using Chi-square and Mann-Whitney-U tests, and associated factors with binary logistic regression. RESULTS: We identified two groups of workers. “G1: Consequences in the daily life routine” was mainly composed of men, Research and Teaching Personnel (RTP) with more stable professional categories, higher income level, and bigger houses than people in G2. Participants in “G2: Concerns for the current and future well-being” presented worse intensity of pain than before the lockdown, more anxiety, depression, stress and less social support than people in G1. ASP (Administration and Services Personnel) had more risk of belonging to G2 than RTP (OR = 5.863). A higher number of people living at home decreased the risk of being in G2 (OR = 0.439). People with lower pain intensity had less risk of being in G2 (OR = 0.014), and this risk decreased as friends support increased (OR = 0.833). CONCLUSIONS: In G1, the consequences were immediately reflected in the stress resulting from changes in their daily work routine. In G2, the concerns were related to their professional future, with worse mental health, greater intensity of pain and less social support.