HPV vaccine-related articles shared on Facebook from 2019 to 2021: Did COVID make a difference?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
HPV vaccination is recommended for children beginning at age 9 to prevent several types of cancer. Many parents turn to Facebook for health information. This study describes changes in HPV vaccine-related articles shared on Facebook amidst the COVID-19 pandemic. HPV-related articles shared on Facebook (2019–2021) were collected using Buzzsumo, a social media analytics tool and analyzed using content analysis. Articles were categorized by valence, misinformation, evidence types, persuasive tactics, and framing. We quantified these data and tested for difference by article year. Of the 138 included articles, 51% had positive valence towards the vaccine and 36% had negative valence. In 2021, there was a significant increase in positive messaging (72% vs. 44% in 2019/2020; p < 0.01) and misinformation decreased from 50% in 2019 to 24% in 2021 (p = 0.04). Persuasive strategies were more common in 2019 than in later years. Despite decreased engagement in 2021, more positive HPV vaccine messaging was observed, although a quarter of articles still contained misinformation. Our results can inform strategies for communicating with parents about the HPV vaccine. Our study is the first to analyze HPV-related articles linked on Facebook and to assess for differences during the pandemic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.006 | 0.002 |
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 it