An eHealth Intervention for Promoting COVID-19 Knowledge and Protective Behaviors and Reducing Pandemic Distress Among Sexual and Gender Minorities: Protocol for a Randomized Controlled Trial (#SafeHandsSafeHearts) (Preprint)
Notice bibliographique
Résumé
BACKGROUND Existing data on COVID-19 disparities among vulnerable populations portend excess risk for lesbian, gay, bisexual, transgender (LGBT) and other persons outside of heteronormative and cisgender identities (ie, LGBT+). Owing to adverse social determinants of health, including pervasive HIV and sexual stigma, harassment, violence, barriers in access to health care, and existing health and mental health disparities, sexual and gender minorities in India and Thailand are at disproportionate risk for SARS-CoV-2 infection and severe disease. Despite global health disparities among LGBT+ populations, there is a lack of coordinated, community-engaged interventions to address the expected excess burden of COVID-19 and public health–recommended protective measures. OBJECTIVE We will implement a randomized controlled trial (RCT) to evaluate the effectiveness of a brief, peer-delivered eHealth intervention to increase COVID-19 knowledge and public health–recommended protective behaviors, and reduce psychological distress among LGBT+ people residing in Bangkok, Thailand, and Mumbai, India. Subsequent to the RCT, we will conduct exit interviews with purposively sampled subgroups, including those with no intervention effect. METHODS SafeHandsSafeHearts is a 2-site, parallel waitlist-controlled RCT to test the efficacy of a 3-session, peer counselor–delivered eHealth intervention based on motivational interviewing and psychoeducation. The study methods, online infrastructure, and content were pilot-tested with LGBT+ individuals in Toronto, Canada, before adaptation and rollout in the other contexts. The primary outcomes are COVID-19 knowledge (index based on US Centers for Disease Control and Prevention [CDC] items), protective behaviors (index based on World Health Organization and US CDC guidelines), depression (Patient Health Questionnaire-2), and anxiety (Generalized Anxiety Disorder-2). Secondary outcomes include loneliness, COVID-19 stress, and intended care-seeking. We will enroll 310 participants in each city aged 18 years and older. One-third of the participants will be cisgender gay, bisexual, and other men who have sex with men; one-third will be cisgender lesbian, bisexual, and other women who have sex with women; and one-third will be transfeminine, transmasculine, and gender nonbinary people. Participants will be equally stratified in the immediate intervention and waitlist control groups. Participants are mainly recruited from online social media accounts of community-based partner organizations. They can access the intervention on a computer, tablet, or mobile phone. SafeHandsSafeHearts involves 3 sessions delivered weekly over 3 successive weeks. Exit interviews will be conducted online with 3 subgroups (n=12 per group, n=36 in each city) of purposively selected participants to be informed by RCT outcomes and focal populations of concern. RESULTS The RCT was funded in 2020. The trials started recruitment as of August 1, 2021, and all RCT data collection will likely be completed by January 31, 2022. CONCLUSIONS The SafeHandsSafeHearts RCT will provide evidence about the effectiveness of a brief, peer-delivered eHealth intervention developed for LGBT+ populations amid the COVID-19 pandemic. If the intervention proves effective, it will provide a basis for future scale-up in India and Thailand, and other low- and middle-income countries. CLINICALTRIAL ClinicalTrials.gov NCT04870723; https://clinicaltrials.gov/ct2/show/NCT04870723 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/34381
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 | 0,021 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,009 | 0,006 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,160 | 0,018 |
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 ».