Pap smear receipt among Vietnamese immigrants: the importance of health care factors
Bibliographic record
Abstract
OBJECTIVE: Recent US data indicate that women of Vietnamese descent have higher cervical cancer incidence rates than women of any other race/ethnicity, and lower levels of Pap testing than white, black, and Latina women. Our objective was to provide information about Pap testing barriers and facilitators that could be used to develop cervical cancer control intervention programs for Vietnamese American women. DESIGN: We conducted a cross-sectional, community-based survey of Vietnamese immigrants. Our study was conducted in metropolitan Seattle, Washington, DC. A total of 1532 Vietnamese American women participated in the study. Demographic, health care, and knowledge/belief items associated with previous cervical cancer screening participation (ever screened and screened according to interval screening guidelines) were examined. RESULTS: Eighty-one percentage of the respondents had been screened for cervical cancer in the previous three years. Recent Pap testing was strongly associated (p<0.001) with having a regular doctor, having a physical in the last year, previous physician recommendation for testing, and having asked a physician for testing. Women whose regular doctor was a Vietnamese man were no more likely to have received a recent Pap smear than those with no regular doctor. CONCLUSION: Our findings indicate that cervical cancer screening disparities between Vietnamese and other racial/ethnic groups are decreasing. Efforts to further increase Pap smear receipt in Vietnamese American communities should enable women without a source of health care to find a regular provider. Additionally, intervention programs should improve patient-provider communication by encouraging health care providers (especially male Vietnamese physicians serving women living in ethnic enclaves) to recommend Pap testing, as well as by empowering Vietnamese women to specifically ask their physicians for Pap testing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".