Growing old in Canada: physical and psychological well-being among elderly Chinese immigrants
Bibliographic record
Abstract
OBJECTIVE: Immigrants are a vital component of the current and future ethnic aging population in Canada. This study was undertaken to explore the health status of elderly Chinese immigrants in a western Canadian city and to identify the major determinants of their physical and psychological well-being. METHOD: Using a 50% random sample of elderly Chinese residing in three residential complexes occupied exclusively by individuals of ethnic Chinese origin located in downtown Calgary, a total of 147 Chinese seniors were interviewed in their homes by trained, bilingual interviewers using a structured questionnaire that covered a wide range of topics including health status, social network, living arrangements, use of health-related services, and socio-demographic information. DATA ANALYSIS: Descriptive and inferential analyses were conducted using the Statistical Package for the Social Sciences. A principal component factor analysis using varimax rotation was performed to explore the underlying factorial structure of the seven items measuring well-being. The internal consistency of all scales used was assessed by Cronbach's alpha reliability test. Two multiple ordinary least-squares (OLS) regression models were constructed to identify the major determinants of respondents' physical and psychological well-being. RESULTS: The findings revealed that a majority of the participants described their physical health as good or very good. Results of multiple OLS regression analysis demonstrated that education, country of origin, use of medications, physical mobility, and perceived financial needs were significantly associated with physical well-being, whereas sex, marital status, length of residence, education, and physical mobility were significantly related to psychological well-being. CONCLUSION: Healthcare professionals, service providers, and policy-makers need to understand the significant impact of the various socio-demographic and background variables that contribute to the well-being of community-dwelling Chinese elderly immigrants. The provision of culturally sensitive and linguistically appropriate healthcare, social, and medical services is needed for the growing older Chinese population. Future studies should compare the health status of foreign-born Chinese seniors with those who were native-born, as well those co-residing with adult children.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".