Components of a Digital Storytelling Intervention for Human Papillomavirus and Cancer Prevention Among LGBTQ+ Individuals: Formative Mixed Methods Inquiry
Bibliographic record
Abstract
Background: Human papillomavirus (HPV) is one of the most prevalent sexually transmitted infections in the United States; however, vaccination uptake falls far below the goal of 80% of the population set forth by Healthy People 2030. Specifically, within the LGBTQ+ (lesbian, gay, bisexual, transgender, queer/questioning) population, HPV vaccination adherence remains a complex issue. Due to the widespread use of technology within the young adult population, digital health tools such as digital storytelling (DST) have been promoted as an effective way to increase vaccination uptake. Objective: The purpose of this study was to conduct a formative inquiry into (1) what components should be considered for inclusion in an HPV documentary tailored for sexual and gender minority populations and (2) what dissemination channels would be more effective and impact the uptake and completion of the HPV vaccine among sexual and gender minority populations. Additionally, this study aims to provide insight into perceived HPV risk and its implications on the HPV vaccine uptake within the LGBTQ+ population. Methods: A mixed methods study was conducted between January 2021 and September 2021 in Atlanta, Georgia. Intake surveys were distributed to individuals identifying as members of the LGBTQ+ community to examine demographic characteristics, barriers to vaccine adherence, and current HPV vaccination status. Perceived HPV risk was assessed using 5 statements on a 1 to 7 Likert scale. Key informant interviews were conducted via Zoom with participants who completed the intake surveys and consented to be interviewed. Transcripts were coded and analyzed using the constant comparison method for emergent themes surrounding components of effective DST campaigns. Results: Forty-seven individuals completed the intake survey and interview. A total of 13 out of 47 (27.7%) of participants indicated that they were not sure when provided with the statement "I am likely to get HPV", whereas 12 out of 47 (29.8%) participants strongly disagreed with the statement "I am at high risk for getting HPV" and 13 out of 47 (27.7%) participants indicated that they were not sure when presented with the statement "HPV would be a serious threat to the quality of my life." A total of 14 out of 47 (29.8%) participants responded that they were not sure to the statement "HPV would be a severe threat to my health" and 13 out of 47 (27.7%) participants strongly agreed that "HPV would be a severe threat to my sex life." Qualitative analysis indicated a high level of stigma experienced in interactions between the LGBTQ+ population and private practitioners. Major barriers to vaccination hesitancy were concerns about age, perceived reduced risk, and lack of provider recommendation. Participant interviews revealed that "Real Outcomes," and "Accurate Representation" were the main components that should be considered for inclusion in an HPV documentary tailored for sexual and gender minority populations. Conclusions: Creation of a DST intervention within the LGBTQ+ population should include information surrounding the real outcomes of HPV and accurate representation.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".