Determinants of loneliness in older immigrants: A scoping review
Bibliographic record
Abstract
Introduction: Older immigrants face several factors that increase their feeling of loneliness. Identifying determinants of loneliness is essential for designing relevant interventions that address to mitigate loneliness. Objective: This scoping review aimed to generate a list of factors and map those that are associated with older immigrants’ experience of loneliness. Methods: Arksey and O’Malley’s revised framework informed this scoping review. Various databases were searched to locate quantitative studies that were published in English between 2000 and 2023 that examined determinants of loneliness in older immigrants. In total, 23 studies were included. Extracted data (related to study characteristics, and results pertaining to the association of determinants with loneliness) were summarized using the vote counting method. Results: The results indicated that older immigrants experienced high levels of loneliness, which were associated with poor general and mental health. In addition, being married; having adequate income; large social network sizes, and frequent contacts with network members; participation in social activities; and a high sense of belonging to society; reduced older immigrants’ feeling of loneliness. Conclusion: Healthcare and social service providers can work with older immigrants to co-design interventions that target potentially modifiable determinants that address loneliness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".