The Role of Information and Communication Technologies in Social Participation of Older Adults: A Scoping Review
Bibliographic record
Abstract
IMPORTANCE: Social participation is essential for healthy aging, supporting older adults' health and well-being. Although information and communication technologies (ICTs) offer promising opportunities, a focused summary of the literature on ICT use for social participation, a distinct aspect of digital engagement, has been lacking. OBJECTIVE: To summarize existing literature on ICT use for social participation among older adults and identify gaps by examining study characteristics, ICT classifications, and associated health variables. DATA SOURCES: PsycINFO, MEDLINE, Embase, and CINAHL were searched for quantitative, nonexperimental studies published from 2016 through 2024. STUDY SELECTION AND DATA COLLECTION: The authors followed the Joanna Briggs Institute scoping review methodology. FINDINGS: Of 9,795 screened articles, 85 met the inclusion criteria. The number of relevant publications has increased over time, with nearly half (47.1%) related to the COVID-19 pandemic. Modes of interaction included social media (72.4%), email (64.5%), text messaging (60.5%), and video calls (53.9%). Most studies assessed communication frequency with family and friends (72.9%), whereas fewer explored meeting new people online (7.1%) or the quality of online participation (5.9%). Social well-being (56.5%) and mental health (43.4%) were the most frequently examined health variables. CONCLUSIONS AND RELEVANCE: The growing body of research highlights ICTs' role in social participation in later life but reveals key gaps. Research on underrepresented populations, ICTs' potential for expanding social networks, and the quality of online participation remains limited. Inconsistent measurement practices hinder ability to draw conclusions. These gaps point to critical opportunities for future occupational therapy research and practice. Plain-Language Summary: Staying socially connected is important for older adults' health, well-being, and overall quality of life. This review explored how older adults use digital technologies, such as video calls, email, text messaging, and social media, to stay in touch and participate socially. Interest in these technologies has grown in recent years, especially during the COVID-19 pandemic. Most research focused on communication with family and friends; fewer studies examined forming new relationships online or the quality of online interactions. Digital tools can reduce loneliness and support participation, particularly when in-person contact is limited. However, more research is needed to understand usage patterns and the adoption of these tools in daily life, especially among underrepresented groups. This knowledge can help occupational therapy practitioners better support older adults in using technology to promote meaningful social connections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".