HPV Knowledge and Attitudes Among American Indian and Alaska Native Health and STEM Conference Attendees
Bibliographic record
Abstract
American Indian and Alaska Native women had approximately twice the incidence of cervical cancer as white women. Preventive measures for cervical cancer rely on screening and HPV vaccination. However, vaccine series completion and catch-up vaccinations for eligible adults are low across all racial/ethnic groups. Therefore, the aim of this study was to identify gaps in knowledge and evaluate the attitudes toward HPV and the vaccine among AIANs with various levels of training in the STEM and health-related fields. A survey was used to collect data from audience members at two national conferences geared towards American Indian and Alaska Natives in health and STEM fields in September 2017. A vignette study was administered via a live electronic poll to test knowledge (true/false questions), attitudes, and to collect demographic information. Respondents self-identified as primarily American Indian and Alaska Native (74%), pursuing or completed a graduate degree (67%), and female (85%). Most respondents (86%) were aware of HPV-associated cancer in men. However, most (48-90%) answered incorrectly to detailed true/false statements about HPV and available vaccines. After educational information was provided, opinions collected via vignettes highlighted mainly positive attitudes toward vaccination; specifically, that vaccines are safe and all eligible community members should be vaccinated (75% and 84%, respectively). We observed that our respondents with higher educational attainment still lacked accurate knowledge pertaining to HPV and the vaccine. Overall, continued education about HPV and the vaccine is needed across all levels of education including American Indian and Alaska Native community members and health professionals.
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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 | 0.000 | 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) | 0.000 | 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".