Understanding technology use during the pandemic through the lens of age-friendly cities and communities: an international, multi-centre study

Marston, Hannah; Prabhu, Vishnunarayan Girishan and Ivan, Loredana (2025). Understanding technology use during the pandemic through the lens of age-friendly cities and communities: an international, multi-centre study. COVID, 5(7)

DOI: https://doi.org/10.3390/covid5010007

URL: https://www.mdpi.com/2673-8112/5/1/7

Abstract

Research on age-friendly cities and communities (AFCC) has primarily taken a qualitative approach. This article extends insights from a quantitative perspective to understand the international perspectives of community living and well-being during the COVID-19 pandemic. Employing an intersectional approach, this online survey aimed to understand human behaviour within AFCC. This article contextualises the digital practices and the impact of technology experienced through the age-friendly city lens of adults aged 18–50+ years living in different types of communities. Using an original dataset collected from 2020 to 2021 across 11 sites and in 13 languages, the study gathered responses from a sample size of 3422 participants. Findings indicate that adults aged 50+ years reported significantly lower loneliness scores, and higher well-being scores compared to adults aged below 40. Factors including gender, education level, and marital and employment status were found to impact loneliness and well-being significantly. From a community perspective, individuals living in rural areas and small towns reported significantly lower loneliness scores and higher well-being scores than those living in metros and cities. These findings contribute to the ongoing discourse in AFCC and have the potential to aid policy responses intended to reduce loneliness and improve well-being through public health and pandemic preparedness planning.

Viewing alternatives

Download history

Metrics

Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions

Item Actions

Export

About