Low Risk Perception of Harm From Substance Use and Sexual Behaviors Among Online Help–Seeking Sexual and Gender Minoritized People in San Francisco, California: Cross-Sectional Survey
Notice bibliographique
Résumé
BACKGROUND: Substance use and HIV epidemics have disproportionately affected sexual and gender minoritized (SGM) communities, with heightened risks among men who have sex with men (MSM) and transgender women of color due to intersecting challenges like poverty, mental health issues, and discrimination. Despite overall declines in substance use and sexual risk behaviors in the general population, these issues persist within SGM communities, exacerbated by stigma and systemic barriers to care. Digital health interventions have emerged as promising tools to address these disparities, offering accessible and stigma-reducing alternatives to traditional care, particularly effective among younger individuals and in underserved areas. OBJECTIVE: This study seeks to examine the social correlates of substance use and sexual risk perception among an online sample of help-seeking MSM and transgender women in San Francisco, California. METHODS: We recruited 409 help-seeking MSM and transgender women by using social media advertisements on Facebook, Instagram, and Grindr in 2022-2024. Participants provided informed consent and completed a baseline assessment. RESULTS: Utilization of testing resources for HIV and hepatitis was high among the participants (401/409, 98.04% and 360/409, 88.02%, respectively). Knowledge of HIV or other sexually transmitted infection health services was also high (379/409, 92.67%). Fewer participants (264/409, 64.55%) were knowledgeable about substance use-related services. Although many participants reported that using substances posed a high risk of harm, some perceived engaging in condomless sex, using prescription opioid drugs without a prescription, and using substances during sex as low risk (122/409, 29.83%, 41/409, 10.02%, and 60/409, 14.67%, respectively). Participants who reported experiencing unstable housing were more likely to report perceiving sharing needles (adjusted odds ratio [aOR] 7.20, 95% CI 1.99-27.80) and nonprescription opioid use (aOR 4.02, 95% CI 1.08-14.90) as low risk. Participants who reported an income below the federal poverty level were more likely to report perceiving sharing needles (aOR 6.35, 95% CI 1.84-23.40), prescription opioid use (aOR 2.89, 95% CI 1.32-6.18), and substance use during sex (aOR 2.29, 95% CI 1.14-4.48) as low risk. Participants who have not been tested for hepatitis in the past have 3.31 times the odds of perceiving prescription opioid use as low risk compared to counterparts who have been tested for hepatitis before (95% CI 1.36-7.68). CONCLUSIONS: This study underscores the importance of social determinants in shaping low risk perception of the harm associated with substance use behaviors among online help-seeking SGM people in San Francisco. These systemic inequities structure participants' perceptions, access, and utilization of preventive and public health services. Our findings identify critical opportunities for outreach and preventative efforts needed to serve vulnerable populations.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».