The Experiences and Determinants of Sleep Problems of Immigrant and Canadian-Born Older Adults—Analysis of Canadian Longitudinal Study on Aging Baseline Data
Bibliographic record
Abstract
BACKGROUND: Although prevalent, limited knowledge is available on the experience of sleep problems (i.e., disturbance in sleep latency and in sleep maintenance) and their determinants in immigrant older adults. PURPOSE: To compare immigrant and Canadian-born older adults' experiences of: 1) sleep problems, 2) determinants of sleep problems, categorized into precipitating and perpetuating factors, and 3) determinants most significantly contributing to each sleep problem. METHODS: Baseline data obtained by the comprehensive cohort of the Canadian Longitudinal Study on Aging were analyzed. Participants 55+ years of age and with complete data on their country of birth comprised the sample, with 18,245 Canadian-born and 4,257 immigrant older adults. Single or multiple items were used to assess the precipitating (chronic condition, sleep disorders, pain, depressive symptoms, psychological distress, education, marital and socio-economic status) and perpetuating (smoking, alcohol consumption, physical activity) factors. Chi-square test and independent sample t-test were used in the comparison and multiple regression was applied to determine the most significant determinant of each sleep problem in each group of older adults. RESULTS: Despite differences in a few determinants of sleep problems, the set of factors contributing to disturbance in sleep latency and maintenance was comparable for Canadian-born and immigrant older adults, and included: having a sleep disorder and high level of depressive symptoms and psychological distress. CONCLUSION: The findings highlight the importance of public health campaigns to increase older adults' awareness of sleep problems, the factors that may contribute to disturbance in sleep, and strategies to prevent and/or manage sleep problems.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".