Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Human Factors

Date Submitted: Dec 2, 2020
Date Accepted: Apr 22, 2021
Date Submitted to PubMed: Apr 29, 2021

The final, peer-reviewed published version of this preprint can be found here:

Age-Related Differences in Experiences With Social Distancing at the Onset of the COVID-19 Pandemic: A Computational and Content Analytic Investigation of Natural Language From a Social Media Survey

Moore RC, Lee AY, Hancock JT, Halley MC, Linos E

Age-Related Differences in Experiences With Social Distancing at the Onset of the COVID-19 Pandemic: A Computational and Content Analytic Investigation of Natural Language From a Social Media Survey

JMIR Hum Factors 2021;8(2):e26043

DOI: 10.2196/26043

PMID: 33914689

PMCID: 8191726

Age-Related Differences in Experiences with Social Distancing at the Onset of the COVID-19 Pandemic: A Computational and Content Analytic Investigation of Natural Language

  • Ryan C. Moore; 
  • Angela Y. Lee; 
  • Jeffrey T. Hancock; 
  • Meghan Colleen Halley; 
  • Eleni Linos

ABSTRACT

Background:

As COVID-19 poses different levels of threat to people of different ages, health communication regarding prevention measures such as social distancing and isolation may be strengthened by understanding the unique experiences of different age groups.

Objective:

The aim was to examine how people of different ages (1) experienced the impact of the COVID-19 pandemic and (2) their respective rates and reasons for compliance or non-compliance with social distancing and isolation health guidance.

Methods:

We fielded a survey on social media (N = 17,287) early in the pandemic to examine the emotional impact of COVID-19 and individuals’ rates and reasons for non-compliance with public health guidance, using computational and content analytic methods of linguistic analysis. The majority of our participants (76.5%) were from the United States.

Results:

Younger (18-31), middle-aged (32-44, 45-64), and older individuals (65+) significantly varied in how they described the impact of COVID-19 on their lives, including their emotional experience, self-focused attention and topical concerns. Younger individuals were more emotionally negative, self-focused, and less concerned with family, while middle aged people were other-focused and concerned with family. The oldest and most at-risk group was most concerned with health-related terms but were also lower in anxiety and higher in the use of emotionally positive terms than the other, less at-risk age groups. We also found relatively high rates of non-compliance with COVID-19 prevention measures, such as social distancing and self-isolation, with younger people being more likely to be non-compliant than older people. Among the 43% of respondents who did not fully comply with health orders, people differed substantially in the reasons they gave for non-compliance. The most common reason for non-compliance was not being able to afford missing work (57.3%). While work obligations proved challenging for participants across ages, younger people struggled more to find adequate space to self-isolate and manage their mental and physical health; middle-aged people faced more concerns regarding childcare; and older people perceived themselves as able to take sufficient precautions.

Conclusions:

Analysis of natural language can provide insight into rapidly developing public health challenges like the COVID-19 pandemic, uncovering individual differences in emotional experiences and health-related behaviors. In this case, our analyses revealed significant differences between different age groups in feelings about and responses to public health orders aimed to mitigate the spread of COVID-19. To improve public compliance with health orders as the pandemic continues, health communication strategies could be made more effective by being tailored to these age-related differences.


 Citation

Please cite as:

Moore RC, Lee AY, Hancock JT, Halley MC, Linos E

Age-Related Differences in Experiences With Social Distancing at the Onset of the COVID-19 Pandemic: A Computational and Content Analytic Investigation of Natural Language From a Social Media Survey

JMIR Hum Factors 2021;8(2):e26043

DOI: 10.2196/26043

PMID: 33914689

PMCID: 8191726

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.