<![CDATA[I’m alone but not lonely. U-shaped pattern of perceived loneliness during the COVID-19 pandemic in the UK and Greece]]>

2026-05-07T08:54:00Z https://api.figshare.com/v2/oai

oai:figshare.com:article/13251893 2020-11-18T13:25:46Z category_30418 category_30397 category_30409 category_30361 category_30364 portal_549 item_type_3 month_year_11_2020

10.5522/04/13251893.v1 https://figshare.com/articles/dataset/I_m_alone_but_not_lonely_U-shaped_pattern_of_perceived_loneliness_during_the_COVID-19_pandemic_in_the_UK_and_Greece/13251893 https://ndownloader.figshare.com/files/25519361 https://ndownloader.figshare.com/files/25519364 https://osf.io/fe8q7/ https://globalcovidstudy.com/ 10.5522/04/13251893 Bizzego, Andrea Andrea Bizzego 0000-0002-1586-8350 Carollo, Alessandro Alessandro Carollo Gabrieli, Giulio Giulio Gabrieli 0000-0002-9846-5767 Wong, Keri Ka-Yee Keri Ka-Yee Wong 0000-0002-2962-8438 Raine, Adrian Adrian Raine 0000-0002-3756-4307 Esposito, Gianluca Gianluca Esposito 0000-0002-9442-0254 <![CDATA[I’m alone but not lonely. U-shaped pattern of perceived loneliness during the COVID-19 pandemic in the UK and Greece]]> Other psychology not elsewhere classified Community psychology Social psychology Counselling psychology Health psychology Machine Learning COVID-19 Loneliness Mental Health UK Greece Lockdown Global Study Psychology not elsewhere classified Social and Community Psychology Health, Clinical and Counselling Psychology 2020-11-18 2023-05-30 Dataset 2020 University College London In the past months, many countries have adopted varying degrees of lockdown restrictions to control the spread of the COVID-19 virus. According to the existing literature, some consequences of lockdown restrictions on people’s lives are beginning to emerge. To inform policies for the current and/or future pandemics, particularly those involving lockdown restrictions, this study adopted a data-driven Machine Learning approach to uncover the short-term effects of lockdown on people’s physical and mental health. An online questionnaire launched on 17 April 2020 was completed by 2,276 people from 66 countries. Focusing on the UK sample (N=382), 10 aggregated variables representing participant’s living environment, physical and mental health were used to train a RandomForest model to predict the week of survey completion. Using an index of importance to identify the best predictor among the 10 variables, self perceived loneliness was identified as the most influential variable. Subsequent statistical analysis showed a significant U-shaped curve for loneliness levels, with a decrease during the 4th and 5th lockdown weeks. The same pattern was replicated in the Greek sample (N = 129). This suggests that for the very first period of time, the adopted lockdown measures affected people’s evaluation of their social support leading to a decreased sense of loneliness.

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