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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Moira Mckniff & Stephanie M. Simone & Tania Giovannetti, 2023. "Age, Loneliness, and Social Media Use in Adults during COVID-19: A Latent Profile Analysis," IJERPH, MDPI, vol. 20(11), pages 1-12, May.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:11:p:5969-:d:1157292
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    References listed on IDEAS

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    1. Kexin Yu & Shinyi Wu & Iris Chi & Deborah Carr, 2021. "Internet Use and Loneliness of Older Adults Over Time: The Mediating Effect of Social Contact [The relation between social network site usage and loneliness and mental health in community-dwelling ," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 76(3), pages 541-550.
    2. Tore Bonsaksen & Mariyana Schoultz & Hilde Thygesen & Mary Ruffolo & Daicia Price & Janni Leung & Amy Østertun Geirdal, 2021. "Loneliness and Its Associated Factors Nine Months after the COVID-19 Outbreak: A Cross-National Study," IJERPH, MDPI, vol. 18(6), pages 1-11, March.
    3. Venkatram Ramaswamy & Wayne S. Desarbo & David J. Reibstein & William T. Robinson, 1993. "An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data," Marketing Science, INFORMS, vol. 12(1), pages 103-124.
    4. Elena Rolandi & Roberta Vaccaro & Simona Abbondanza & Georgia Casanova & Laura Pettinato & Mauro Colombo & Antonio Guaita, 2020. "Loneliness and Social Engagement in Older Adults Based in Lombardy during the COVID-19 Lockdown: The Long-Term Effects of a Course on Social Networking Sites Use," IJERPH, MDPI, vol. 17(21), pages 1-12, October.
    5. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    6. Stanley Sclove, 1987. "Application of model-selection criteria to some problems in multivariate analysis," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 333-343, September.
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