Anxiety and Social Support Are Associated with Loneliness among Adults with Disabilities and Older Adults with No Self-Reported Disabilities 10 Months Post COVID-19 Restrictions
Bibliographic record
Abstract
With increased physical restrictions during the coronavirus disease 2019 (COVID-19) pandemic, many individuals, especially older adults and individuals with disabilities, experienced increased feelings of loneliness. This study aimed to identify factors associated with loneliness among older adults and people with disabilities residing in British Columbia (BC), Canada 10 months following COVID-19 physical restrictions. Participants included a total of 70 adults consisting of older adults (>65 years of age) without any self-reported disabilities and adults (aged 19 or above) with disabilities (e.g., stroke, spinal cord injury, etc.). Participants completed standardized self-report measures of their levels of anxiety, depression, social support, mobility, and loneliness. We used hierarchical linear regression to determine the association of age, sex, disability status, anxiety, depression, social support, and mobility with loneliness. Participants reported general low levels of loneliness, anxiety, and depression and an overall high level of perceived social support. Most participants reported living with others. Our analysis showed a positive association between anxiety and loneliness (β = 0.340, p = 0.011) and a negative association between social support and loneliness (β = −0.315, p = 0.006). There was no association between depression and loneliness (β = 0.210, p = 0.116) as well as between mobility and loneliness (β = −0.005, p = 0.968). These findings suggest that anxiety and social support have been significantly associated with loneliness in older adults and people with disabilities during the COVID-19 pandemic. Increased efforts to reduce anxiety and improve social support in clinical and community settings may be helpful in reducing loneliness in older adults and people with disabilities during the COVID-19 pandemic.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".