Medications for alcohol use disorder (MAUD) and opioid use disorder (MOUD) are underutilized evidence-based treatments. While patients often receive treatment in multiple medical treatment settings, it is unknown whether certain treatment settings or combinations of settings are associated with increased receipt of MAUD or MOUD. Data from the cross-sectional 2019 National Survey on Drug Use and Health were used to identify treatment settings where adult respondents received any past year alcohol treatment (n = 476, 33% female) or, separately, opioid treatment (n = 337, 38% female).
View Article and Find Full Text PDFBackground: Although studies are increasingly adopting online protocols, few such studies in the addiction field have comprehensively described their data review procedures and successes in detecting low-quality/fraudulent data. The current study describes data collection protocols and outcomes of a large, longitudinal study (the PAL Study 2021) that implemented online design elements to study individuals seeking peer support for an alcohol use disorder.
Methods: In 2021, the PAL Study collaborated with mutual-help group (MHG) partners and recovery-related organizations to recruit individuals attending a 12-step group, Women for Sobriety (WFS), LifeRing Secular Recovery, and/or SMART Recovery for an alcohol problem in-person and/or online in the prior 30 days.
Introduction: Although attending substance use-focused mutual-help meetings online may reduce attendance barriers, associations of attendance mode with group participation and outcomes are unknown. Using longitudinal data from mutual-help group attendees, this study, after identifying differences in baseline characteristics by attendance mode, examined associations of attendance mode with mutual-help participation (number of meetings attended, involvement) and outcomes (alcohol abstinence, heavy drinking, alcohol problems).
Methods: The Peer Alternatives for Addiction Study 2021 Cohort sampled attendees of 12-step groups (e.
Alcohol Clin Exp Res (Hoboken)
February 2024
Background: Untreated alcohol use disorder (AUD) can have negative outcomes, including premature death. Completing specialty treatment for AUD can improve economic and educational outcomes. However, there are large racial and ethnic disparities in treatment completion, and how these disparities vary intersectionally (e.
View Article and Find Full Text PDFBackground: We investigate whether living in a state that expanded Medicaid eligibility is associated with receiving alcohol screening and brief counseling among nonelderly, low-income adults and a subgroup with chronic health conditions caused or exacerbated by alcohol use.
Method: Data are from the 2017 and 2019 Behavioral Risk Factor Surveillance System (N = 15,743 low-income adults; n = 7062 with a chronic condition). We used propensity score-weighted, covariate-adjusted, modified Poisson regression to estimate associations between residence in a Medicaid-expansion state and receipt of alcohol screening and brief counseling.
The purpose of this study was to identify patterns of tobacco uptake and other substance use, from early to late adolescence. We used weighted latent class analysis, conducted separately for 7, 9, and 11 graders, to assess patterns of susceptibility, ever and current use of combustible tobacco and e-cigarettes, and other substance use (ie, current alcohol, binge drinking, and marijuana). Data were from Wave 3 of the Texas Adolescent Tobacco and Marketing Surveillance System (n = 2733; N = 461,069), collected in fall 2015.
View Article and Find Full Text PDFBackground: Outcome expectations are an important determinant of health behavior, according to Social Cognitive Theory; yet recent literature has not examined the relationship between outcome expectations and tobacco product use (e.g., use of cigarettes, cigars, hookah, e-cigarettes, or smokeless tobacco).
View Article and Find Full Text PDFIntroduction: Research shows that adolescents who are overweight or obese may be at greater risk of cigarette smoking, and that this relationship may vary by gender. However, this relationship is understudied for electronic cigarettes (e-cigarettes). Given the high rate of adolescent obesity and the rise in e-cigarette use in adolescents, this relationship should be investigated.
View Article and Find Full Text PDFObjectives: To provide a full methodological description of the design of the wave I and II (6-month follow-up) surveys of the Texas Adolescent Tobacco and Marketing Surveillance System (TATAMS), a longitudinal surveillance study of 6, 8, and 10 grade students who attended schools in Bexar, Dallas, Tarrant, Harris, or Travis counties, where the 4 largest cities in Texas (San Antonio, Dallas, Fort Worth, Houston, and Austin, respectively) are located.
Methods: TATAMS used a complex probability design, yielding representative estimates of these students in these counties during the 2014-2015 academic year. Weighted prevalence of the use of tobacco products, drugs and alcohol in wave I, and the percent of: (i) bias, (ii) relative bias, and (iii) relative bias ratio, between waves I and II are estimated.
J Adolesc Health
September 2017
Purpose: Little is known about the nature and extent of adolescents' exposure to tobacco- and e-cigarette-related communications on social media. In this study, we describe the prevalence and correlates of youth exposure and engagement with tobacco- and e-cigarette-related social media.
Methods: Data are from the baseline survey of the Texas Adolescent Tobacco and Marketing Surveillance system, a cross-sectional sample of sixth, eighth, and 10th graders (n = 3907, N = 461,097).
Objectives: Given the increasing trend in use of electronic cigarettes ("e-cigarettes") among youth, it is crucial to understand how these products are perceived and how these perceptions are associated with their decision whether or not to use them.
Methods: This is a cross-sectional analysis of data from a rapid response surveillance system of 6th, 8th and 10th grade students' tobacco use behaviors (sample [n] = 3704 from a population of students [N] = 434,601). We used weighted logistic regression models to investigate the relationship between perceptions of harm and addictiveness and e-cigarette use, including the use of flavored and non-flavored e-cigarettes.
Background: Although children of lower socio-economic status (SES) in the United States have generally been found to be at greater risk for obesity, the SES-obesity association varies when stratified by racial/ethnic groups-with no consistent association found for African American and Hispanic children. Research on contextual and setting-related factors may provide further insights into ethnic and SES disparities in obesity. We examined whether obesity levels among central Texas 8th grade students (n=2682) vary by school-level economic disadvantage across individual-level family SES and racial/ethnicity groups.
View Article and Find Full Text PDFBackground: Research suggests that physical activity breaks (ABs) during class increase students' physical activity levels and provide an academic benefit. This study evaluates a 3-year intervention aimed at encouraging teacher AB use.
Methods: Thirty central Texas middle schools were assigned to 1 of 3 conditions: training-only (Basic), training plus facilitator support (Basic Plus), and training/facilitator support and a social marketing campaign (Basic Plus SM).
The Central Texas Coordinated Approach To Child Health (CATCH) Middle School Project is a 3.5-year school-based project aimed at promoting physical activity (PA), healthy eating, and obesity prevention among public middle school students in Texas. This article describes the CATCH intervention model and presents baseline findings from spring 2009.
View Article and Find Full Text PDFBackground: Marathon Kids® (MK) is a community and school-based program that promotes running, walking, and healthy eating in elementary school children. This study assessed the impact of MK on self-reported physical activity (PA), fruit and vegetable consumption (FVC), and related psycho-social factors in a sample of low-income, 4th- and 5th-grade students in Texas (n = 511). Intervention strategies included structured school running time, behavioral tracking, celebratory events, and rewards.
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