Impact of COVID-19 restrictions on newly occurring loneliness in older people – a prospective study in a memory clinic population
Bibliographic record
Abstract
Abstract The COVID-19 pandemic was associated with high burden and numerous negative consequences for older people. Social isolation and loneliness are major and prevalent health problems impacting well-being and quality of life and may have increased due to pandemic-related restrictions. The present study investigate the impact of the COVID-19 pandemic on loneliness in people visiting a memory clinic between March 2020 and September 2022. We conducted a prospective, single-center, questionnaire-based observational follow-up study to assess potential predictors of newly occurring, pandemic-related loneliness. Next to a newly developed COVID-19 questionnaire, a comprehensive neuropsychological test battery, the Neuropsychiatric Inventory and the Geriatric Depression Scale were used. In total 426 people (mean age: 76.48 years, 12.9% cognitively intact, 33.1% diagnosed with Mild Cognitive Impairment, 49.8% diagnosed with dementia, and 4.2% diagnosed with depression) completed the COVID-19 questionnaire at baseline and 166 at follow-up. Newly occurring loneliness was indicated by 22.3% of baseline participants and by 24.1% of follow-up participants. Results of logistic regression analysis showed that living alone (OR 5.452) and having less contact with friends (OR 2.771) were most predictive of the occurrence of loneliness. The use of digital communication media as an alternative strategy for social interaction was lowest in dementia patients (6–13%). In conclusion, personal contacts and a close friendship network appear to be more decisive to prevent loneliness in older people than does the use of digital communication media. However, promoting an intensified use of digital communication media may be useful to counteract loneliness, especially in dementia patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".