Methodological workflow for deriving internet use trajectories using SHARE data
Keywords:
internet use trajectories;, methodological workflow;, SHARE;, longitudinal data
Abstract
Abstract: This paper examines how internet use among older adults evolves over time based on longitudinal data from the Survey of Health, Ageing and Retirement in Europe (SHARE). The contribution of the study is the introduced transparent and replicable workflow for identifying internet use trajectories using a latent-class mixed model framework, offering a practical approach for future research in this area. The analysis of the SHARE dataset reveals distinct internet use trajectories, including consistent usage, consistent non-usage, and increasing and decreasing probabilities of internet usage over time. The proposed methodological workflow enables robust and reproducible trajectory analysis and supports future research on digital inclusion among ageing groups.References
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2. Bergmann, M., Kneip, T., De Luca, G. & Scherpenzeel, A., 2019. Survey participation in the Survey of Health, Ageing and Retirement in Europe (SHARE), Wave 1-7.. s.l.:SHARE-ERIC.
3. Börsch-Supan, A. et al., 2013. Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE).. International Journal of Epidemiology.
4. Eurostat, 2025. Digitalisation in Europe – 2025 edition, s.l.: s.n.
5. Gomes, A. & Dias, J. G., 2024. Digital Divide in the European Union: A Typology of EU Citizens. Social Indicators Research.
6. Gordon, N. P. & Crouch, E., 2019. Digital Information Technology Use and Patient Preferences for Internet-Based Health Education Modalities: Cross-Sectional Survey Study of Middle-Aged and Older Adults With Chronic Health Conditions. JMIR Aging.
7. Heponiemi, T. et al., 2023. Predicting Internet Use and Digital Competence Among Older Adults Using Performance Tests of Visual, Physical, and Cognitive Functioning: Longitudinal Population-Based Study. Journal of Medical Internet Research.
8. Herle, M. et al., 2020. Identifying typical trajectories in longitudinal data: modelling strategies and interpretations.. European Journal of Epidemiology.
9. Kamin, S. T., Beyer, A. & Lang, F. R., 2020. Social support is associated with technology use in old age. Zeitschrift für Gerontologie und Geriatrie.
10. Kamin, S. T. & Lang, F. R., 2018. Internet Use and Cognitive Functioning in Late Adulthood: Longitudinal Findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).
11. Kebede, A. S., Ozolins, L.-L., Holst, H. & Galvin, K., 2022. Digital Engagement of Older Adults: Scoping Review. Journal of Medical Internet Research.
12. König, R. & Seifert, A., 2020. From Online to Offline and Vice Versa: Change in Internet Use in Later Life Across Europe. Frontiers in Sociology.
13. Laird, N. M. & Ware, J. H., 1982. Random-Effects Models for Longitudinal Data. Biometrics.
14. Li, M. et al., 2025. Eleven-Year Trajectories of Internet Usage Time and Depression Scores Among Middle-Aged and Older Adults in China: Latent Class Mixed Model Analysis. Journal of Medical Internet Research.
15. Mariano, J., Marques, S., Ramos, M. R. & de Vries, H., 2021. Internet Use by Middle-Aged and Older Adults: Longitudinal Relationships With Functional Ability, Social Support, and Self-Perceptions of Aging. Psychology and Aging.
16. Matthews, K., Nazroo, J. & Marshall, A., 2019. Digital inclusion in later life: cohort changes in internet use over a ten-year period in England.. Ageing and Society.
17. Proust-Lima, C., Philipps, V. & Lique, B., 2017. Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm.. Journal of Statistical Software.
18. Ryoo, J. H. et al., 2018. Longitudinal Model Building Using Latent Transition Analysis: An Example Using School Bullying Data. Frontiers in Psychology.
19. SHARE-ERIC, 2024a. Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 5 Version 9.0.0, s.l.: s.n.
20. SHARE-ERIC, 2024b. Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 6. Release version: 9.0.0., s.l.: s.n.
21. SHARE-ERIC, 2024c. Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 8. Release version: 9.0.0., s.l.: s.n.
22. SHARE-ERIC, 2024d. Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 9. Release version: 9.0.0., s.l.: s.n.
23. Szabo, A., Allen, J., Stephens, C. & Alpass, F., 2019. Longitudinal Analysis of the Relationship Between Purposes of Internet Use and Well-being Among Older Adults. The Gerontologist.
24. van der Nest, G., Passos, V. L., Candel, M. J. & van Breukelen, G. J., 2020. An overview of mixture modelling for latent evolutions in longitudinal data: Modelling approaches, fit statistics and software. Advances in Life Course Research.
25. Wale, A. et al., 2025. Effectiveness of Interventions for Addressing Digital Exclusion in Older Adults in the Social Care Domain: Rapid Review. JMIR Aging.
Published
2026-06-30
How to Cite
Vasileva, P. (2026). Methodological workflow for deriving internet use trajectories using SHARE data. Vanguard Scientific Instruments in Management, 22(1), 105-119. Retrieved from https://www.vsim-journal.info/index.php?journal=vsim&page=article&op=view&path[]=593
Section
Articles
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