Understanding older adults ' use of social technology and the factors influencing use
Open accessAbstract
Having access and skills to use social technology,i.e.social internet use, social media and social applications, are considered as being vital to online social connection. Whilst evidence exists around facilitators and barriers to general technology use, evidence is limited with regards to the motivators, skills and tangible offline benefits older technology users experience with social technology. Therefore, this study used a qualitative, exploratory method to understand older adults’ experiences of using social technology to connect with others. Semi-structured interviews were conducted with 20 older adults (65+ years) across England, Scotland and Wales. Despite having access to social technology for social connection, and using this technology regularly, multiple barriers impacted motivators and skills for use, namely perceived self-efficacy and fear, the culture of online communication, absence of social capital and physical functioning. Some of these barriers of social technology use are reminiscent of barriers of wider technology use and emphasise the importance of addressing these barriers for digital exclusion, as well as social connection. However, some of these barriers were specific to social technology use and should be considered when providing guidance or interventions to increase older adults’ online social connection. Social connection was a clear tangible outcome to social technology use, and individuals discussed the benefits of using social technology, particularly visual communication tools, for online connection.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The ability and confidence in using technology remain essential predictors of technology participation among older adults.
“The ability and confidence in using technology remain essential predictors of technology participation among older adults. 50”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 60 · Cited by 143
Research works printed but not linked: 20
- Age UK (2018) Digital Inclusion Evidence Review. London: Age UK.
- Bergström A (2017) Digital equality and the uptake of digital applications among seniors of different age. Nordicom Review 38, 79-91.
- Burholt V, Winter B, Aartsen M, Constantinou C, Dahlberg L, Feliciano V, De Jong Gierveld J, van Regenmortel SV and Waldegrave C (2020) A critical review and development of a conceptual model of exclusion from social relations for older people. European Journal of Ageing 17, 3-19.
- Coelho J, Rito F and Duarte C (2017) 'You, me & TV' -fighting social isolation of older adults with Facebook, TV and multimodality. International Journal of Human-Computer Studies 98, 38-50.
- Cornejo R, Tentori M and Favela J (2013) Enriching in-person encounters through social media: a study on family connectedness for the elderly. International Journal of Human-Computer Studies 71, 889-899.
- Cotten SR, Anderson WA and McCullough BM (2013) Impact of internet use on loneliness and contact with others among older adults: cross-sectional analysis. Journal of Medical Internet Research 15, e39.
- Creswell JW, Plano Clark VL, Gutmann ML and Hanson WE (2003) Advanced mixed methods research designs. In Tashakkori A and Teddlie C (eds), Handbook of Mixed Methods in Social and Behavioral Research. Thousand Oaks, CA: Sage, pp. 209-240.
- Gilleard C and Higgs P (2008) Internet use and the digital divide in the English Longitudinal Study of Ageing. European Journal of Ageing 5, 233-239.
- Gracia E and Herrero J (2009) Internet use and self-rated health among older people: a national survey. Journal of Medical Internet Research 11, e49.
- Harley DA, Kurniawan SH, Fitzpatrick G and Vetere F (2009) Age matters: bridging the generation gap through technology-mediated interaction. Extended Abstracts on Human Factors in Computing Systems, pp. 4799-4802.
- Marino S (2015) Making space, making place: digital togetherness and the redefinition of migrant identities online. Social Media + Society 1. Available at https://doi.org/10.1177/2056305115622479. · DOI
- Morris MG, Venkatesh V and Ackerman PL (2005) Gender and age differences in employee decisions about new technology: an extension to the theory of planned behavior. IEEE Transactions on Engineering Management 52, 69-84.
- Wellman B and Haythornwaite C (eds), The Internet in Everyday Life. Malden, MA: Blackwell, pp. 215-243.
- Pennington CR, Heim D, Levy AR and Larkin DT (2016) Twenty years of stereotype threat research: a review of psychological mediators. PLOS ONE 11, e0146487.
- Tsai JM, Cheng MJ, Tsai HH, Hung SW and Chen YL (2019) Acceptance and resistance of telehealth: the perspective of dual-factor concepts in technology adoption. International Journal of Information Management 49, 34-44.
- Van Deursen AJ and Helsper EJ (2015) The third-level digital divide: who benefits most from being online? In Robinson L, Cotten SR and Schulz J (eds), Communication and Information Technologies Annual. Bingley, UK: Emerald Group Publishing, pp. 29-52.
- White H, McConnell E, Clipp E, Bynum L, Teague C, Navas L, Craven S and Halbrecht H (1999) Surfing the net in later life: a review of the literature and pilot study of computer use and quality of life. Journal of Applied Gerontology 18, 358-378.
- Winstead V, Anderson WA, Yost EA, Cotten SR, Warr A and Berkowsky RW (2013) You can teach an old dog new tricks: a qualitative analysis of how residents of senior living communities may use the web to overcome spatial and social barriers. Journal of Applied Gerontology 32, 540-560.
- Wright DW and Hill TJ (2009) Prescription for trouble: Medicare Part D and patterns of computer and internet access among the elderly. Journal of Aging & Social Policy 21, 172-186.
- Yoon H, Jang Y, Vaughan PW and Garcia M (2020) Older adults' Internet use for health information: digital divide by race/ethnicity and socioeconomic status. Journal of Applied Gerontology 39, 105-110.
- Authors
- Wilson, G., Gates, J. R., Vijaykumar, S., & Morgan, D. J.
- Affiliations
- Northumbria University (GB)
- Swansea University (GB)
- Corresponding author
- Wilson, Gemma
- Venue
- Ageing and Society
- Publisher
- Cambridge University Press (CUP)
- Published
- 2021-04-20
- Volume
- 43
- Issue
- 1
- Pages
- 222-245
- ISSN
- 0144-686X (ISSN-L)
- 1469-1779
- OpenAlex
- W3156686426
- Cited by
- 143
- References
- 60
- Citations by year
- 2026: 33 · 2025: 53 · 2024: 34 · 2023: 14 · 2022: 7 · 2021: 2
- FWCI
- 22.45
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Ageing and Society (publishedVersion, cc-by)
- Northumbria Research Link (Northumbria University) (acceptedVersion)
- Cronfa (Swansea University) (submittedVersion, cc-by)
- Funders
- Leverhulme Trust
- British Academy
- Medical Research Council (MR/K02325X/1)
- Topics
- Social Sciences › Demography › Technology Use by Older Adults
- Health Sciences › Health Professions › General Health Professions › Aging, Elder Care, and Social Issues
- Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
- Keywords
- older adults, social technology, social media use, online relationships, digital exclusion, technology adoption barriers, self-efficacy, technology anxiety, social capital, physical function, visual communication tools, technological competence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review