Age, Loneliness, and Social Media Use in Adults during COVID-19: A Latent Profile Analysis

Moira Mckniff, Stephanie M. Simone and Tania Giovannetti ()
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Moira Mckniff: Department of Psychology and Neuroscience, Temple University, Philadelphia, PA 19122, USA
Stephanie M. Simone: Department of Psychology and Neuroscience, Temple University, Philadelphia, PA 19122, USA
Tania Giovannetti: Department of Psychology and Neuroscience, Temple University, Philadelphia, PA 19122, USA

IJERPH, 2023, vol. 20, issue 11, 1-12

Abstract: Loneliness has been linked to morbidity and mortality across the lifespan. Social media could reduce loneliness, though research on the relation between social media and loneliness has been inconclusive. This study used person-centered analyses to elucidate the inconsistencies in the literature and examine the possible role technology barriers played in the relation between social media use and loneliness during the COVID-19 pandemic. Participants ( n = 929; M age = 57.58 ± 17.33) responded to a series of online questions covering demographics, loneliness, technology barriers, and social media use (e.g., Facebook, Twitter, etc.) across a range of devices (e.g., computer, smartphone, etc.). A latent profile analysis was conducted to identify distinct profiles of social media use, loneliness patterns, and age. Results yielded five distinct profiles characterized that showed no systematic associations among age, social media use, and loneliness. Demographic characteristics and technology barriers also differed between profiles and were associated with loneliness. In conclusion, person-centered analyses demonstrated distinct groups of older and younger adults that differed on social media use and loneliness and may offer more fruitful insights over variable-centered approaches (e.g., regression/correlation). Technology barriers may be a viable target for reducing loneliness in adults.

Keywords: age; social media; loneliness; technology barriers; COVID-19 (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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