COVID-19 experiences of social isolation and loneliness among older adults in Africa: a scoping review
Bibliographic record
Abstract
Objective: Social isolation and loneliness (SI/L) are considered critical public health issues. The primary objective of this scoping review is to document the experience of SI/L among older adults in Africa during the COVID-19 pandemic, given research gaps in this area. We identified the reasons for SI/L, the effects of SI/L, SI/L coping strategies, and research and policy gaps in SI/L experiences among older adults in Africa during COVID-19. Methods: Six databases (PubMed, Scopus, CINAHL, APA PsycINFO, Web of Science, and Ageline) were used to identify studies reporting the experiences of SI/L among older adults in Africa during the COVID-19 lockdown. We adopted the Joanna Briggs Institute (JBI) methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Results: Social isolation and loneliness due to COVID-19 in Africa affected older adults' mental, communal, spiritual, financial, and physical health. The use of technology was vital, as was the role of social networks within the family, community, religious groups, and government. Methodological challenges include the risk of selective survival bias, sampling biases, and limited inductive value due to context. Also, lack of large-scale mixed methods longitudinal studies to capture the experiences of older adults during COVID-19. There were essential policy gaps for African mental health support services, media programs, and community care service integration targeting older adults in the era of the COVID-19 lockdown. Discussion: Like in other countries, COVID-19 lockdown policies and the lockdown restrictions primarily caused the experience of SI/L among older adults in Africa. In African countries, they resulted in a severance of older adults from the cultural structure of care for older adults and their familial support systems. Weak government intervention, personal situations, challenges regarding technology, and detachment from daily activities, disproportionately affected older adults in Africa.
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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 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".