PROTECTING THE HEALTH OF VIETNAMESE REFUGEES BY LOCAL HEALTH PROFESSIONALS AND UNIVERSITY STUDENTS
Bibliographic record
Abstract
Abstract Nearly 50 years after the fall of Saigon (1975), studies continue to show the high prevalence of physical (ADL, IADL), mental (depressive symptoms), and cognitive (dementia) disabilities in older Vietnamese refugees. Adverse lifelong experiences in Vietnam and host countries may have impacted these results. Some refugees who arrived during their youth became health professionals while their children attend universities, predominantly enrolled in pre-health courses. Leveraging their bilingual/bicultural and health background, they have hosted free health fairs for their monolingual older Vietnamese for the past 16 years in Houston, Texas, the 2nd largest Vietnamese-populated city in the nation. Despite the high prevalence of dementia, no free cognitive healthcare has been provided. The purpose of the study is to report the collaborative efforts to fill the gap using the Cultural Exchange Model (CEM) and improve dementia literacy. The CEM teaches that to create knowledge, two constituencies need to merge within the Community. One arm of Vietnamese stakeholders (older adults, medical doctors) already exists. We formed another arm, Cognitive Health Initiative (CHAIN): 28 bilingual/bicultural Vietnamese university students, who were trained in Montreal Cognitive Assessment (MoCA). During 2023, we jointly attended 11 health fairs with Vietnamese medical professionals and offered 337 MoCA in Vietnamese and English. The results showed that older Vietnamese (≥65) scored the lowest (22.4/30) among participants (White=24.8; Black=23.9; Hispanic=23.3). Utilizing existing, underlying resilience and the unique affinity among local Vietnamese health professionals, our next steps include continuing to offer a “Memory Booth” by local Vietnamese pre-health students, thereby strengthening intergenerational relationships.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".