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https://hdl.handle.net/10356/164039
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DC Field | Value | Language |
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dc.contributor.author | Carollo, Alessandro | en_US |
dc.contributor.author | Bizzego, Andrea | en_US |
dc.contributor.author | Gabrieli, Giulio | en_US |
dc.contributor.author | Wong, Keri Ka-Yee | en_US |
dc.contributor.author | Raine, Adrian | en_US |
dc.contributor.author | Esposito, Gianluca | en_US |
dc.date.accessioned | 2023-01-03T06:08:23Z | - |
dc.date.available | 2023-01-03T06:08:23Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | 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 | en_US |
dc.identifier.issn | 2666-5352 | en_US |
dc.identifier.uri | https://hdl.handle.net/10356/164039 | - |
dc.description.abstract | 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. | en_US |
dc.description.sponsorship | Nanyang Technological University | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Public Health in Practice | en_US |
dc.rights | © 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/). | en_US |
dc.subject | Social sciences::Psychology | en_US |
dc.subject | Science::Medicine | en_US |
dc.title | I'm alone but not lonely. U-shaped pattern of self-perceived loneliness during the COVID-19 pandemic in the UK and Greece | en_US |
dc.type | Journal Article | en |
dc.contributor.school | Lee Kong Chian School of Medicine (LKCMedicine) | en_US |
dc.contributor.school | School of Social Sciences | en_US |
dc.identifier.doi | 10.1016/j.puhip.2021.100219 | - |
dc.description.version | Published version | en_US |
dc.identifier.pmid | 34870253 | - |
dc.identifier.scopus | 2-s2.0-85120310856 | - |
dc.identifier.volume | 2 | en_US |
dc.identifier.spage | 100219 | en_US |
dc.subject.keywords | Machine Learning | en_US |
dc.subject.keywords | COVID-19 | en_US |
dc.description.acknowledgement | This research is supported by Nanyang Technological University (Singapore) under the NAP-SUG grant to GE. | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | LKCMedicine Journal Articles SSS Journal Articles |
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File | Description | Size | Format | |
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1-s2.0-S2666535221001440-main.pdf | 1.63 MB | Adobe PDF | View/Open |
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