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Heterogeneous Associations Between Frequent Virtual Communication and Loneliness Among Older Adults: Observational
Daisuke Kato1,2,3,4, Ichiro Kawachi5, Katsunori Kondo2,6
1Takemi Program in International Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
Journal of Medical Internet Research
|August 7, 2026
Summary
Frequent virtual communication modestly reduced loneliness in older Japanese adults. The association varied across individual profiles, suggesting personalized digital interventions could be beneficial.
Area of Science:
- Gerontology
- Public Health
- Digital Communication
Background:
- Loneliness is a significant public health issue for older adults.
- Evidence on virtual communication's impact on loneliness is mixed.
- Understanding variations in this association across different older adult profiles is limited.
Purpose of the Study:
- To examine the association between frequent virtual communication and loneliness in Japanese older adults.
- To explore if this association differs based on baseline individual characteristics.
Main Methods:
- Observational analysis of 4807 Japanese adults aged 65+ from the 2019-2022 Japan Gerontological Evaluation Study.
- Frequent virtual communication defined as internet/email use ≥2-3 times/week for social contact.
- Targeted maximum likelihood estimation and generalized random forest used to analyze associations and heterogeneity.
Main Results:
- Frequent virtual communication was associated with a modest decrease in loneliness scores (difference -0.136).
- Exploratory analyses indicated heterogeneity in the association across baseline profiles.
- The association remained significant and in the same direction in supplementary analyses, including adjustment for baseline loneliness.
Conclusions:
- Frequent virtual communication is linked to lower loneliness in older Japanese adults.
- The association shows potential heterogeneity across different individual profiles.
- Findings should be interpreted cautiously due to retrospective reporting and observational design; causal inference is not supported.
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