Research on Older Persons’ Access and Use of Technology in the Arab Region: Critical Overview and Future Directions
Bibliographic record
Abstract
This paper presents the findings of a scoping review that maps exploratory evidence and gaps in research on information and communication technology (ICT) access and use among older persons in the Arab region. This review is part of a larger project that studies ICT access and use and related challenges faced by older adults in Qatar. A search was conducted in eleven scientific databases and search engines covering empirical studies published in English and Arabic between January 2016 and June 2021. Eleven studies were retrieved in the final corpus. A thematic analysis alongside the PRISMA for scoping reviews (PRISMA-ScR) was used to retrieve the findings. Our analysis identifies smartphones and social media applications for communication and information sharing as the most accessed and used technologies by older persons in the region. Moreover, our review highlighted the importance of the sociocultural factors in shaping ICT access and use by older persons in the region. The functional limitations of older persons in interaction with certain technology factors such as usability, functionality, and accessibility were also highlighted as major challenges inhibiting ICT access and use by this population segment. This scoping review provides a comprehensive overview of ICT access and use, and the factors affecting them among older persons in the Arab region. It highlights the scarcity of research on the subject in the region. It also stresses the fact that there is a need for more research on older persons and their caregivers in the context of the Arab world. More culturally appropriate need-based and adapted technologies are also recommended. Our review is a comprehensive source for researchers and technology developers interested in targeting and engaging older adults in the Arab region.
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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 | 0.023 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".