What facilitates the acceptance of technology to promote social participation in later life? A systematic review
Bibliographic record
Abstract
BACKGROUND: Social participation is an important aspect of health and well-being across the lifespan, but older adults might encounter some barriers, which has been highlighted in the current Covid-19 pandemic situation, where technology has become the primary way to maintain contact with family and friends. In fact, technology can serve both as a facilitator and barrier to social participation in later life, and this issue needs to be further understood. AIM: To identify the barriers and facilitators encountered by older adults in using technology to promote social participation. METHODS: A systematic review was conducted. Studies were included if they were peer-reviewed, written in English or French, included participants 50 years or older, included technology to promote social participation, and reported potential barriers or facilitators regarding such technologies. Four databases were included: MEDLINE, CINAHL, PsychINFO and, ERIC. Each study was reviewed by two independent reviewers. The quality of the study was appraised using the Crowe Critical Appraisal Tool. RESULTS: Seventeen studies were included in this report. Four main themes emerged from the data: perceived benefits of the technology, self-confidence and knowledge about using the technology efficiently and safely, affordability of the technology, and ability of the technology to adapt to the physical and cognitive declines in later life. CONCLUSION: These findings can help health care professionals to make better decisions when deciding to recommend technology for their older clients.IMPLICATIONS FOR REHABILITATIONAcceptance of technology to promote social participation in later life is a multi-complex process. There is no "one size fits all" approach, a person-centered intervention must be used.When introducing new technologies, using an adapted/tailored training approach could potentially increase self-efficacy in using technology.Rehabilitation professionals' misconceptions concerning the use of technology in later life can be a barrier to acceptance. It's important to be aware of our own believes and attitudes in this context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".