I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece

Objectives: 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 yet the evolution of such conse...

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Main Authors: Carollo, Alessandro, Bizzego, Andrea, Gabrieli, Giulio, Wong, Keri Ka-Yee, Raine, Adrian, Esposito, Gianluca
Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/164039
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spelling sg-ntu-dr.10356-1640392023-03-05T15:33:42Z I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece Carollo, Alessandro Bizzego, Andrea Gabrieli, Giulio Wong, Keri Ka-Yee Raine, Adrian Esposito, Gianluca Lee Kong Chian School of Medicine (LKCMedicine) School of Social Sciences Social sciences::Psychology Science::Medicine Machine Learning COVID-19 Objectives: 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 yet the evolution of such consequences in relation to the time spent in lockdown is understudied. To inform policies involving lockdown restrictions, this study adopted a data-driven Machine Learning approach to uncover the short-term time-related effects of lockdown on people’s physical and mental health. Study design: An online questionnaire was launched on 17 April 2020, distributed through convenience sampling and was self-completed by 2,276 people from 66 different countries. Methods: Focusing on the UK sample (N = 325), 12 aggregated variables representing the participant’s living environment, physical and mental health were used to train a RandomForest model to estimate the week of survey completion. Results: Using an index of importance, Self-Perceived Loneliness was identified as the most influential variable for estimating the time spent in lockdown. A significant U-shaped curve emerged for loneliness levels, with lower scores reported by participants who took part in the study during the 6th lockdown week (p = 0.009). The same pattern was replicated in the Greek sample (N = 137) for week 4 (p = 0.012) and 6 (p = 0.009) of lockdown. Conclusions: From the trained Machine Learning model and the subsequent statistical analysis, Self-Perceived Loneliness varied across time in lockdown in the UK and Greek populations, with lower symptoms reported during the 4th and 6th lockdown weeks. This supports the dissociation between social support and loneliness, and suggests that social support strategies could be effective even in times of social isolation. Nanyang Technological University Published version This research is supported by Nanyang Technological University (Singapore) under the NAP-SUG grant to GE. 2023-01-03T06:08:23Z 2023-01-03T06:08:23Z 2021 Journal Article Carollo, A., Bizzego, A., Gabrieli, G., Wong, K. K., Raine, A. & Esposito, G. (2021). I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece. Public Health in Practice, 2, 100219-. https://dx.doi.org/10.1016/j.puhip.2021.100219 2666-5352 https://hdl.handle.net/10356/164039 10.1016/j.puhip.2021.100219 34870253 2-s2.0-85120310856 2 100219 en Public Health in Practice © 2021 The Authors. Published by Elsevier Ltd on behalf of The Royal Society for Public Health. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Social sciences::Psychology
Science::Medicine
Machine Learning
COVID-19
spellingShingle Social sciences::Psychology
Science::Medicine
Machine Learning
COVID-19
Carollo, Alessandro
Bizzego, Andrea
Gabrieli, Giulio
Wong, Keri Ka-Yee
Raine, Adrian
Esposito, Gianluca
I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece
description Objectives: 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 yet the evolution of such consequences in relation to the time spent in lockdown is understudied. To inform policies involving lockdown restrictions, this study adopted a data-driven Machine Learning approach to uncover the short-term time-related effects of lockdown on people’s physical and mental health. Study design: An online questionnaire was launched on 17 April 2020, distributed through convenience sampling and was self-completed by 2,276 people from 66 different countries. Methods: Focusing on the UK sample (N = 325), 12 aggregated variables representing the participant’s living environment, physical and mental health were used to train a RandomForest model to estimate the week of survey completion. Results: Using an index of importance, Self-Perceived Loneliness was identified as the most influential variable for estimating the time spent in lockdown. A significant U-shaped curve emerged for loneliness levels, with lower scores reported by participants who took part in the study during the 6th lockdown week (p = 0.009). The same pattern was replicated in the Greek sample (N = 137) for week 4 (p = 0.012) and 6 (p = 0.009) of lockdown. Conclusions: From the trained Machine Learning model and the subsequent statistical analysis, Self-Perceived Loneliness varied across time in lockdown in the UK and Greek populations, with lower symptoms reported during the 4th and 6th lockdown weeks. This supports the dissociation between social support and loneliness, and suggests that social support strategies could be effective even in times of social isolation.
author2 Lee Kong Chian School of Medicine (LKCMedicine)
author_facet Lee Kong Chian School of Medicine (LKCMedicine)
Carollo, Alessandro
Bizzego, Andrea
Gabrieli, Giulio
Wong, Keri Ka-Yee
Raine, Adrian
Esposito, Gianluca
format Article
author Carollo, Alessandro
Bizzego, Andrea
Gabrieli, Giulio
Wong, Keri Ka-Yee
Raine, Adrian
Esposito, Gianluca
author_sort Carollo, Alessandro
title I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece
title_short I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece
title_full I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece
title_fullStr I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece
title_full_unstemmed I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece
title_sort i'm alone but not lonely. u-shaped pattern of self-perceived loneliness during the covid-19 pandemic in the uk and greece
publishDate 2023
url https://hdl.handle.net/10356/164039
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