An Empirical Evaluation of Social Support and Psychological Well-being in Older Chinese and Korean Immigrants
Bibliographic record
Abstract
OBJECTIVES: To examine, among older Chinese and Korean immigrants: (1) the concept and measurement of perceived social support; (2) levels of social support and psychological well-being by living arrangement; and (3) whether social support is positively related to psychological well-being. DESIGN: A convenience sample of 200 self-identified Chinese and Koreans, aged 65 years and older, were interviewed. Psychometric analysis was conducted to examine the reliability and validity of a new social support measure. Bivariate and multivariate analyses were used to examine the relationship between social support and psychological well-being. RESULTS: Factor analysis revealed a four-factor solution of social support and adequate psychometrics of all social support scales was found. Multivariate results suggest that Koreans have more depression than Chinese (p < 0.01). Those who lived with their spouse and adult children had lower overall psychological well-being (p < 0.05) and lower positive affect (p < 0.05) compared to those who lived alone. Having more emotional/companionship support significantly (p < 0.001) contributed to better overall psychological well-being, having less depression and higher positive affect. CONCLUSIONS: A new multidimensional social support measure for use with older Chinese and Koreans could be useful upon further validation. These results suggest that older Chinese and Koreans' psychological well-being may be negatively affected when they live with their adult children. More depression in Koreans may be related to difficulties in expanding their social network beyond Korean-speaking people.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".