Abstract
Understanding digital exclusion in older adults during the COVID-19 pandemic could help tailor responses to future outbreaks. This cohort study used data from older adults aged 60+ years in England who participated in wave nine (2018/2019) of the main English Longitudinal Study of Ageing (ELSA) survey, and/or wave one of the ELSA COVID-19 sub-study (June/July 2020). Using latent class analysis and latent transition analysis, we aimed to identify distinct subgroups of older adults characterised by different patterns of internet use pre- and intra-pandemic, explore the extent to which individuals remained in the same subgroup or transitioned to a different subgroup during the COVID-19 pandemic, and examine longitudinal associations of socio-economic factors (education, occupational class, and wealth) with latent class membership. Preliminary tests showed that the types of internet activities differed between men and women; therefore, subsequent analyses were stratified by biological sex. Three clusters (low, medium, and high) were identified in male participants at both timepoints. Among female participants, three clusters were distinguished pre-pandemic and two (low versus high) during the pandemic. The latent classes were characterised by participants’ breadth of internet use. Higher education, occupational class, and wealth were associated with greater odds of membership in the medium and/or high classes, versus the low class, in men and women. A high degree of stability in latent class membership was observed over time. However, men experienced a stark decrease in online health information-seeking. Our results highlight that inequality regarding the range of functional and social opportunities provided by the internet prevailed during the pandemic. Policymakers should ensure that digital access and upskilling initiatives are equitable for all.
Original language | English |
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Article number | e0303061 |
Journal | PLoS ONE |
Volume | 19 |
Issue number | 5 |
Early online date | 9 May 2024 |
DOIs | |
Publication status | Published - 9 May 2024 |
Data Availability Statement
Data Availability: The data underlying the results presented in the study (SN 5050 and SN 8688) are available from the UK Data Service (https://ukdataservice.ac.uk/). Details on how to access the data, including the conditions of use, can be found on the ELSA website (https://www.elsa-project.ac.uk/accessing-elsa-data) and the UK Data Service website. The syntax files to replicate the analyses presented in this paper are openly available from GitHub, at https://github.com/OliviaMalkowski/Inequalities-Internet-COVID-19.git.Funding
This work was supported by an Economic and Social Research Council (https://www.ukri.org/councils/esrc/) funded studentship through the South West Doctoral Training Partnership [grant number ES/P000630/1 to O.S. M.]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Funders | Funder number |
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Economic and Social Research Council | |
South West Doctoral Training Partnership | ES/P000630/1 |