Who is mentally healthy? Mental health profiles of Japanese social networking service users with a focus on LINE, Facebook, Twitter, and Instagram
Open accessAbstract
BACKGROUND: Both negative and positive associations between social networking service (SNS) usage and mental health have been suggested by previous studies; however, their differences by type of SNS and age remain unclear. We addressed this issue based on the frequency of traditional communication such as face-to-face and non-face-to-face communication (e.g., phone, email, and letters). METHODS: In total, 8,576 individuals participated, including 2,543 aged 18-39, 3,048 aged 40-64, and 2,985 aged over 65 years. They were asked to indicate their frequency of SNS usage, both for posting and checking, of LINE (a popular message application in Japan), Facebook, Twitter, and Instagram, with frequent usage defined as posting or checking more than a few times a week. To determine mental health status, WHO-5 (i.e., well-being), K6 (i.e., distress symptoms), and feelings of loneliness were assessed. Multiple and logistic regression analyses were adjusted for the frequency of traditional communication. To avoid type 1 error, a Bonferroni correction of p ≤ 0.002 was applied in the regression models (p = 0.05/18, a number of regression models). RESULTS: The most frequently used SNS across the three age groups was LINE; frequent usage (both posting and checking) among older adults was independently associated with better well-being. Frequent posting on Facebook was associated with better well-being in middle-aged adults. Young adults who frequently checked on Instagram showed a tendency toward better well-being and lower distress symptoms. On the contrary, frequent usage of Twitter was associated with distress symptoms or feelings of loneliness across all three age groups. CONCLUSIONS: We found generational and SNS-type-dependent negative and positive associations between SNS use and mental health, indicating the possible influences of SNS use and the importance of non-SNS communication.
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The only study that compared older and younger/middle-aged adults found generally more positive associations of active and passive social media uses for older adults.
“the only study that compared older and younger/middle-aged adults (Sakurai et al., 2021) found generally more positive associations of active and passive SMUs for older adults.”
From Are active and passive social media use related to mental health, wellbeing, and social support outcomes? A meta-analysis of 141 studies (2023) · cites this paper as Sakurai et al., 2021
The Results section (page not provided) compares young, middle-aged, and older adults and finds that both posting and checking on LINE are associated with better well-being in older adults. But the Discussion’s summary reports positive associations for different services in younger and middle-aged adults and no common positive association across generations; the Facebook discussion finds a positive association only for middle-aged adults. The paper therefore supports an older-adult finding for LINE, not generally more positive associations of active and passive social media use among older adults. (LLM, conf=0.86)
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Association Between Ego-Resilience and Social Isolation Among Urban Older People
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“Recently, the usefulness of digital tools was reported (Peng & Roth, 2022; Sakurai, Nemoto et al., 2021) to expand social interactions among older adults.”
BackgroundChen, Y., Yang, W., Zhang, X., & Wu, Y. (2025) · Health Communication · doi:10.1080/10410236.2025.2567514 · Cited by 3 · see citing works
“First, the measurement of SMU by Sakurai et al. (2021) and Qu et al. (2022) was restricted to the frequency and functionalities of a single platform (WeChat), without addressing the underlying purposes or motivations behind SMU.”
COVID-19 流行に伴う高齢者の行動と利用移動手段の変化
山内, さ., 島崎, 敢., 小嶋, 理., 米川, 隆., 武田, 夏., 新海, 裕., & 青木, 宏. (2021) · 自動車技術会論文集 · doi:10.11351/jsaeronbun.52.1143 · Cited by 2 · see citing works
Tanaka, Y., Iwata, Y., Oe, N., & Tadaka, E. (2024) · Social Sciences · doi:10.3390/socsci13020076 · Cited by 1 · see citing works
Kambara, K., Toya, A., Lee, S., Shimizu, H., Abe, K., Shigematsu, J., Zhang, Q., Abe, N., Hayase, R., Abe, N., et al. (2024) · Asian Journal Of Social Psychology · doi:10.1111/ajsp.12658 · Cited by 1 · see citing works
Increased Use of Asocial Technologies Is Associated with Reduced Well-being Among Older Adults
Anaraky, R. G., Schuster, A. M., Fossen, J. A. V., Nov, O., & Cotten, S. R. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713135 · Cited by 1 · see citing works
Health Promotion and Digital Tools: Analysis of Consumer Demands
Kouzuki, M. (2025) · Yonago acta medica · doi:10.33160/yam.2025.08.003 · Cited by 1 · see citing works
Zheng, T., Zheng, X., Xue, B., Xiao, S., Yang, L., Zhang, X., Chen, C., Li, X., Zhang, M., Liao, Y., et al. (2025) · BMC Public Health · doi:10.1186/s12889-025-24629-5 · Cited by 1 · see citing works
“Social media use competency significantly and negatively predicts depressive symptoms two years later, confirming hypothesis H2a and consistent with other findings [17, 46].”
Sramek, Z., Lokuge, S., Sternat, T., Katzman, M. A., & Yatani, K. (2025) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3770713 · Cited by 1 · see citing works
“…should also be noted that prior work has used a variety of methods to collect data on participants’ smartphone use patterns and maladaptive behaviours, primarily self-report questionnaires such as the Smartphone Addiction Scale (e.g. [10, 93, 201]) or self-report usage time (e.g. [138, 193, 209]).”
Miyadera, R. (2021) · Journal of Rehabilitation Practices and Research · doi:10.33790/jrpr1100123 · Cited by 1 · see citing works
Sepas, A., El‐Hussuna, A., Atıcı, S. D., & Yang, W. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3956428 · Cited by 1 · see citing works
Miyaki, K., Kawamura, T., Takano, H., & Suzuki, K. H. (2022) · medRxiv · doi:10.1101/2022.02.26.22271302 · Cited by 1 · see citing works
“However, this does not directly contradict our current findings, as Japanese SNS consumption patterns tend to differ from those seen in other countries [20].”
ResultMiyadera, R., Furuta, T., Murayama, A., & Yamaguchi, T. (2022) · Journal of Rehabilitation Practices and Research · doi:10.33790/jrpr1100135
Do healthy older adults use SNS? Focus on LINE, Facebook, Twitter (now X), and Instagram
Tsukada, K., Takahashi, T., Shimizu, Y., Li, Y., Tsuchiya, T., Kawakubo, K., Sagara, T., Ito, K., Furuya, T., & Suzuki, H. (2024) · Archives of Gerontology and Geriatrics Plus · doi:10.1016/j.aggp.2024.100096
Hisata, Y., Nishida, S., Urayama, M., Sekine, H., Sugioka, T., Hirata, R., Katsuki, N. E., Tago, M., Ueda, Y., Amenomori, M., et al. (2025) · Journal of General and Family Medicine · doi:10.1002/jgf2.70024
“6 We defined a good SRH outcome as a score of 4 or more.”
Takizawa, Y. (2025) · Cyberpsychology Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2025-4-2
Qu, X., HOUSER, S., Zhang, J., Wen, J. S., & Zhang, W. (2022) · Figshare · doi:10.6084/m9.figshare.19634768
Nishinakagawa, M., Sakurai, R., Nemoto, Y., Matsunaga, H., Takebayashi, T., & Fujiwara, Y. (2024) · Figshare · doi:10.6084/m9.figshare.26599831
Godard, R., Draper, Z. A., Holtzman, S., & O’Connor, B. P. (2026) · Current Psychology · doi:10.1007/s12144-026-09064-y
“While a few studies have examined the differential impacts of active and passive use on different platforms (e.g., Sakurai et al., 2021), we are not aware of any that have compared levels of active and passive use (particularly on newer platforms, such as TikTok and BeReal).”
Zafar, A., Zia, A., Riaz, S., Babur, M., & Akram, S. (2026) · Archives of Gerontology and Geriatrics Plus · doi:10.1016/j.aggp.2026.100281
Instagram and Mental Health: Scoping Review with ☸SAIMSARA
SAIMSARA (2026) · SAIMSARA Journal · doi:10.62487/saimsara429bcd77
Yu, Q., Shi, D., Wang, H., Hu, X., Chen, F., Wang, Y., Jiang, M., Wang, X., & Wang, W. (2026) · Journal of Public Health Research · doi:10.1177/22799036261495154 · Cited by 2 · see citing works
Cheng, Y., & Gondo, Y. (2026) · Gerontology & Geriatrics Education · doi:10.1080/02701960.2026.2750168
- Authors
- Sakurai, R., Nemoto, Y., Mastunaga, H., & Fujiwara, Y.
- Affiliations
- Tokyo Metropolitan Institute of Gerontology (JP)
- National Center of Neurology and Psychiatry (JP)
- Corresponding author
- Sakurai, Ryota
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2021-03-03
- Volume
- 16
- Issue
- 3
- Pages
- e0246090
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC7928453
- OpenAlex
- W3134008627
- Cited by
- 57
- References
- 42
- Citations by year
- 2026: 6 · 2025: 10 · 2024: 16 · 2023: 7 · 2022: 13 · 2021: 5
- FWCI
- 14.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Japan Support Center for Suicide Countermeasures
- Japan Society for the Promotion of Science (the Grant-in-Aid for Challenging Exploratory Research)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Demography › Technology Use by Older Adults
- Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
- Keywords
- social networking services, mental health, lines, Facebook, Twitter, Instagram, well-being, distress symptoms, loneliness, age differences, generational differences, non-face-to-face communication, Japanese adults
- MeSH terms
- Online Social Networking, Adult, Age Factors, Aged, Female, Health Surveys, Humans, Japan, Loneliness, Male, Mental Health, Middle Aged, Prospective Studies, Logistic Models, Young Adult, Social Networking, Social Media
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