The impact of loneliness and social isolation during COVID-19 on cognition in older adults: a scoping review
Bibliographic record
Abstract
Background: The COVID-19 pandemic required implementation of public health measures to reduce the spread of SARS CoV-2. This resulted in social isolation and loneliness for many older adults. Loneliness and social isolation are associated with cognitive decline, however, the impact of this during COVID-19 has not been fully characterized. Objective: The aim of this scoping review was to explore the impact of social isolation and loneliness during COVID-19 on cognition in older adults. Eligibility criteria: Eligible studies occurred during the COVID-19 pandemic, enrolled older adults and reported longitudinal quantitative data on both loneliness (exposure) and cognition (outcome). Sources of evidence: A comprehensive search was conducted in CINAHL, Medline, PubMed, and Psychinfo databases (updated October 10, 2023). Charting methods: Studies were screened independently by two reviewers and study characteristics, including participant demographics, loneliness and cognition measurement tools, study objectives, methods and results were extracted. Results: The search yielded 415 results, and seven were included in the final data synthesis. All studies were conducted between 2019 and 2023. Six studies enrolled community-dwelling individuals while the remaining study was conducted in long-term care. In 6 studies, loneliness and/or social isolation was correlated with poorer cognitive function. In the seventh study, subjective memory worsened, while objective cognitive testing did not. Conclusion: Loneliness and social isolation during COVID-19 were correlated with cognitive decline in older adults. The long-term effect of these impacts remains to be shown. Future studies may focus on interventions to mitigate the effects of loneliness and social isolation during future pandemics.
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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 | 0.009 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".