Components of a Digital Storytelling Intervention for Human Papillomavirus and Cancer Prevention Among LGBTQ+ Individuals: Formative Mixed Methods Inquiry
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».