The role of health information technology in improving awareness of HPV and HPV vaccine among U.S. adults: Insights from the health information national trends survey.
Bibliographic record
Abstract
10535 Background: Despite advances in cancer prevention and wide-spread availability of Human papilloma virus (HPV) vaccines, US adults continue to have suboptimal HPV vaccination uptake with less than 50% vaccinated. Strategies aimed at enhancing HPV-related awareness are considered one of the most effective ways to improve HPV vaccine adoption and potentially eliminate HPV-related cancers. Health information technology (HIT) may influence HPV-related awareness and subsequently drive vaccine adoption. This study assessed the impact of HIT utilization on HPV and HPV vaccine awareness. Methods: Data was obtained from Health Information National Trends Survey (HINTS 5 cycles 1 and 2). Cross-sectional sample of 6,522 individuals aged 18 years or more was analyzed. The independent variables were use of smartphone, computer, or electronic means to (i) look up health information, (ii) fill a prescription online, (iii) communicate with a doctor or doctor’s office, (iv) look up test results of and (v) track health care charges. The dependent variables were HPV and HPV vaccine awareness. Chi-square analysis was used to evaluate group differences, and a multiple logistic regression was used to analyze the association between HIT utilization and HPV-related awareness controlling for sociodemographic and health-related factors. Results: Of the total sample, awareness of HPV and HPV vaccine was 62.7% and 61.8% respectively. In adjusted multivariable logistic regression analysis, those who utilized a smartphone, computer, or electronic means to look up health information (aOR 2.23; 95% CI 1.68 – 2.97, p < 0.001), communicate with healthcare provider (aOR 1.53; 95% CI 1.23 – 1.91, p < 0.001), look up test results (aOR 1.67; 95% CI 1.35 – 2.08, p < 0.001), and track health care charges (aOR 1.61; 95% CI 1.26 – 2.05, p < 0.001), were more likely to endorse HPV awareness than those who did not. Similar positive associations were observed for HIT utilization and HPV vaccine awareness. Conclusions: Our findings showed a positive association between HIT utilization and HPV-related awareness. Amid a background of sub-optimal HPV vaccination and explosion in technology, these results emphasize the potential for the role of HIT in preventive medicine. Strategies that integrate HIT into vaccine interventions and communications should be encouraged as a medium to expand HPV awareness and vaccine coverage.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".