Cervical Cancer Beliefs and Pap Test Screening Practices Among Chinese American Immigrants
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To examine beliefs and Pap test utilization among Chinese American women, the largest Asian female population in the United States. RESEARCH APPROACH: Cross-sectional descriptive, correlational study. SETTING: Metropolitan areas of Portland, OR. PARTICIPANTS: 100 foreign-born Chinese women aged 40 years and older. METHODOLOGIC APPROACH: Three questionnaires were modified, translated, combined, and pretested. Participants completed the self-administered questionnaire in a group setting. MAIN RESEARCH VARIABLES: Utilization of Pap test screening, health beliefs, and cultural and sociodemographic variables. FINDINGS: Sixty-eight percent reported having a Pap test within the prior three years (adherence), and 84% reported ever having a Pap test. The odds of Pap test use and adherence decreased with increasing age. Women with insurance or a regular healthcare provider had better odds of Pap test use and adherence. Older age, older age when a participant moved to the United States, and increased modesty were negatively associated with ever having had a Pap test. CONCLUSIONS: Age and cultural beliefs influence Pap test use and adherence. The strength of provider recommendation and healthcare access as predictors suggest areas for interventions designed to increase screening for cervical cancer. INTERPRETATION: Nurses play a vital role in preventive health care, especially with the growing number of advanced practice nurses delivering primary care. Primary healthcare providers should be reminded of their influential role in increasing adherence to cancer screening. Further health policy action is necessary to extend screening coverage to those who do not have adequate health insurance.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".