Stimulant Use Associated With Psychosocial Factors, HIV Risk, and Concurrent Hazardous Alcohol Use Among US Adults: Exploratory Cross-Sectional Questionnaire Study
Notice bibliographique
Résumé
BACKGROUND: Stimulant use is a major public health problem that contributes to morbidity and mortality among men who have sex with men (MSM) in the United States. To reduce the harms associated with stimulant use, there is a need to identify the factors associated with stimulant use to inform interventions. Additionally, there is a need to use large crowdsourcing platforms like Amazon Mechanical Turk (MTurk) to engage more individuals who use substances across the United States. OBJECTIVE: We identified the correlates of stimulant use among people who use alcohol or stimulants in the United States recruited using MTurk. METHODS: Participants who were aged ≥18 years in the United States and reported alcohol or stimulant (ie, cocaine, crack cocaine, and methamphetamine) use were deemed eligible and recruited via the web platform MTurk. Participants completed a baseline survey, which assessed sociodemographics, psychosocial (ie, depression, affect, self-esteem, and stress) factors, substance use, and sexual behaviors. Data were collected and analyzed with STATA (version 17; StataCorp). Stratifying by MSM status, bivariate and multivariable logistic regression models were built in STATA to examine the correlates of stimulant use. Multivariable models controlled for age, race, health insurance, and relationship status. RESULTS: Of 272 participants, 201 (73.9%) identified as male, 134 (49.2%) were MSM, 52 (19.1%) were from racial and ethnic minoritized communities, and 158 (58%) were in a relationship. The mean age was 36.10 (SD 10.3) years. A total of 40 (14.7%) participants reported stimulant use in the past 6 months. Factors significantly associated with stimulant use were being MSM (adjusted odds ratio [aOR] 4.61, 95% CI 1.97-10.81), a higher Alcohol Use Disorders Identification Test-Concise score (aOR 1.24, 95% CI 1.08-1.42), more intense cravings for alcohol in the past 24 hours (aOR 1.03, 95% CI 1.01-1.04), a higher depression score (aOR 1.06, 95% CI 1.01-1.12), a greater number of male partners in the last 6 months (aOR 1.32, 95% CI 1.08-1.61), a greater number of female partners in the last 6 months (aOR 1.42, 95% CI 1.04-1.92), and being diagnosed with a sexually transmitted infection (eg, syphilis, gonorrhea, chlamydia, herpes simplex virus, human papillomavirus, and other) in the last 6 months (aOR 14.61, 95% CI 3.45-61.87). Additionally, there was a significant additive interaction between MSM status and negative affect, such that the impact of negative affect on stimulant use was significantly greater among MSM compared with non-MSM (relative excess risk due to interaction 0.085, 95% CI 0.037-0.13). CONCLUSIONS: Interventions that address stimulant use should use evidence-based approaches that reduce negative affect, depression, and cravings for alcohol. Additionally, interventions should be customized for MSM populations.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 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 | 0,002 | 0,002 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».