THE COMBINED EFFECTS OF LONELINESS AND SOCIAL ISOLATION ON MENTAL HEALTH IN A NATIONAL SAMPLE OF OLDER ADULTS
Bibliographic record
Abstract
Abstract Social connections are important to maintain health across adulthood. Loneliness and social isolation are global issues and are linked to negative mental health outcomes worldwide, especially among older adults. Past research focuses primarily on loneliness and isolation separately, though many older people experience them simultaneously. Also, there is a paucity of research examining mechanisms through which combinations of loneliness/isolation result in poor mental health. My first objective examined how combined loneliness/isolation affect psychological distress among a group of older adults, and how grouping this sample into four groups of loneliness (yes/no) and isolation (yes/no) may help identify which group(s) are at the greatest risk for distress. My second objective explored perceived social support and relationship satisfaction as mediators of the effects of combined loneliness/solation on distress. I addressed these objectives with a cross-sectional national sample of 2,745 Canadian older adults, aged 55 to 101 years, who completed self-report measures of loneliness, social isolation, social support, relationship satisfaction, perceived physical health, and psychological distress. Those experiencing greater combined loneliness/isolation also experienced higher levels of distress. For lonely older adults, experiencing isolation simultaneously predicted clinically significant distress, but this was not true for those who were not lonely. Participants who were both lonely/isolated had the poorest mental health because they were less satisfied with their relationships, but not because they had less perceived social support. The present study has the potential to expand what we know about pathways through which combinations of loneliness/isolation may lead to poor mental health in older adults.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".