Browsing by Author "Mun, Eun-Young"
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Item A bias correction method in meta-analysis of randomized clinical trials with no adjustments for zero-inflated outcomes(John Wiley & Sons, Inc., 2021-09-03) Zhou, Zhengyang; Xie, Minge; Huh, David; Mun, Eun-YoungMany clinical endpoint measures, such as the number of standard drinks consumed per week or the number of days that patients stayed in the hospital, are count data with excessive zeros. However, the zero-inflated nature of such outcomes is sometimes ignored in analyses of clinical trials. This leads to biased estimates of study-level intervention effect and, consequently, a biased estimate of the overall intervention effect in a meta-analysis. The current study proposes a novel statistical approach, the Zero-inflation Bias Correction (ZIBC) method, that can account for the bias introduced when using the Poisson regression model, despite a high rate of inflated zeros in the outcome distribution of a randomized clinical trial. This correction method only requires summary information from individual studies to correct intervention effect estimates as if they were appropriately estimated using the zero-inflated Poisson regression model, thus it is attractive for meta-analysis when individual participant-level data are not available in some studies. Simulation studies and real data analyses showed that the ZIBC method performed well in correcting zero-inflation bias in most situations.Item A cross-sectional study of latent tuberculosis infection, insurance coverage, and usual sources of health care among non-US-born persons in the United States(Wolters Kluwer Health, Inc., 2021-02-19) Annan, Esther; Stockbridge, Erica L.; Katz, Dolly; Mun, Eun-Young; Miller, Thaddeus L.ABSTRACT: More than 70% of tuberculosis (TB) cases diagnosed in the United States (US) occur in non-US-born persons, and this population has experienced less than half the recent incidence rate declines of US-born persons (1.5% vs 4.2%, respectively). The great majority of TB cases in non-US-born persons are attributable to reactivation of latent tuberculosis infection (LTBI). Strategies to expand LTBI-focused TB prevention may depend on LTBI positive non-US-born persons' access to, and ability to pay for, health care.To examine patterns of health insurance coverage and usual sources of health care among non-US-born persons with LTBI, and to estimate LTBI prevalence by insurance status and usual sources of health care.Self-reported health insurance and usual sources of care for non-US-born persons were analyzed in combination with markers for LTBI using 2011-2012 National Health and Nutrition Examination Survey (NHANES) data for 1793 sampled persons. A positive result on an interferon gamma release assay (IGRA), a blood test which measures immunological reactivity to Mycobacterium tuberculosis infection, was used as a proxy for LTBI. We calculated demographic category percentages by IGRA status, IGRA percentages by demographic category, and 95% confidence intervals for each percentage.Overall, 15.9% [95% confidence interval (CI) = 13.5, 18.7] of non-US-born persons were IGRA-positive. Of IGRA-positive non-US-born persons, 63.0% (95% CI = 55.4, 69.9) had insurance and 74.1% (95% CI = 69.2, 78.5) had a usual source of care. IGRA positivity was highest in persons with Medicare (29.1%; 95% CI: 20.9, 38.9).Our results suggest that targeted LTBI testing and treatment within the US private healthcare sector could reach a large majority of non-US-born individuals with LTBI. With non-US-born Medicare beneficiaries' high prevalence of LTBI and the high proportion of LTBI-positive non-US-born persons with private insurance, future TB prevention initiatives focused on these payer types are warranted.Item A Longitudinal Study Among Permanent Supportive Housing Residents: Increase in Social Support Co-Occurring with Decrease in Depressive Symptoms and Substance Use Problems(2021) Tan, Zhengqi; Mun, Eun-Young; Nguyen, Uyen-Sa; Walters, ScottPurpose: Social support is a well-known protective factor against depressive symptoms and substance use problems, but very few studies have examined its protective effects among residents of Permanent Supportive Housing (PSH), a housing program for people with a history of chronic homelessness. We examined whether perceived social support improves when provided with regular health coaching visits and whether improved social support is associated with reduced depressive symptoms and substance use problems among this underserved population. Methods:Participants were 653 adult PSH residents in North Texas (56% female; 57% Black; mean age: 51 years) who participated in a monthly health coaching program from 2014 to 2017. We assessed their health behaviors at baseline and three follow-up visits for up to 18 months. We used latent growth curve models to capture changes over time and parallel process growth models to examine the associations between the trajectories of social support and the trajectories of each health measure. Results:PSH residents showed improved social support, and decreased depressive symptoms and substance use problems over time. In addition, individuals with greater needs at baseline tended to improve faster, although their improvements slowed over time. Further, those who improved in social support tended to show reduced depressive symptoms (coefficient: –0.67, p< 0.01) and substance use problems (coefficient: –0.52, p< 0.01). Conclusions:This study suggests that increases in social support may positively impact depressive symptoms and substance use problems among PSH residents. Future housing programs could emphasize social support as an early component. Supported by Medicaid1115Waiver & R01AA019511.Item A Structural Equation Modeling Approach to Meta-analytic Mediation Analysis Using Individual Participant Data: Testing Protective Behavioral Strategies as a Mediator of Brief Motivational Intervention Effects on Alcohol-Related Problems(Springer Nature, 2021-11-12) Huh, David; Li, Xiaoyin; Zhou, Zhengyang; Walters, Scott T.; Baldwin, Scott A.; Tan, Zhengqi; Larimer, Mary E.; Mun, Eun-YoungThis paper introduces a meta-analytic mediation analysis approach for individual participant data (IPD) from multiple studies. Mediation analysis evaluates whether the effectiveness of an intervention on health outcomes occurs because of change in a key behavior targeted by the intervention. However, individual trials are often statistically underpowered to test mediation hypotheses. Existing approaches for evaluating mediation in the meta-analytic context are limited by their reliance on aggregate data; thus, findings may be confounded with study-level differences unrelated to the pathway of interest. To overcome the limitations of existing meta-analytic mediation approaches, we used a one-stage estimation approach using structural equation modeling (SEM) to combine IPD from multiple studies for mediation analysis. This approach (1) accounts for the clustering of participants within studies, (2) accommodates missing data via multiple imputation, and (3) allows valid inferences about the indirect (i.e., mediated) effects via bootstrapped confidence intervals. We used data (N = 3691 from 10 studies) from Project INTEGRATE (Mun et al. Psychology of Addictive Behaviors, 29, 34-48, 2015) to illustrate the SEM approach to meta-analytic mediation analysis by testing whether improvements in the use of protective behavioral strategies mediate the effectiveness of brief motivational interventions for alcohol-related problems among college students. To facilitate the application of the methodology, we provide annotated computer code in R and data for replication. At a substantive level, stand-alone personalized feedback interventions reduced alcohol-related problems via greater use of protective behavioral strategies; however, the net-mediated effect across strategies was small in size, on average.Item A treatise on independent component analysis in the presence of noise -- simulation and data applications in neuroimaging(2019-08) Mamun, Md Abdullah; Nandy, Rajesh R.; Aryal, Subhash; Mun, Eun-YoungThis doctoral thesis introduces a novel negentropy-based algorithm for model order selection in the presence of stationary colored Gaussian noise in the context of independent component analysis (ICA). Model order selection is a critical step in ICA because overestimation of model order selection may lead to splitting original source components, whereas underestimation may lead to loss of information. The existing order selection methods are prone to overestimation in the presence of colored Gaussian noise. The proposed negentropy-based order selection algorithm is aimed at overcoming this problem. This thesis provides a technical description of the method and reports the results from simulation experiments across a range of data conditions as well as real data applications. The new ICA estimation algorithm, noisyICA, extends the application of Hyvärinen's "fast fixed-point algorithm" for high dimensional data in the presence of white or stationary colored Gaussian noise. The first step of the algorithm is to reduce the dimension of observed data based on the proposed negentropy-based model order selection method. The next step of the noisyICA algorithm is to quasi-whiten data utilizing the noise covariance matrix, replacing the standard whitening procedure. Finally, the algorithm optimizes a contrast function based on Gaussian moments that removes biases due to Gaussian noise. Based on the simulation experiments, noisyICA performed well in comparison with fastICA in terms of bias reduction when estimating an ICA mixing matrix, and provided a reasonable and valid estimation of the ICA mixing matrix. The utility and feasibility of using the negentropy-based algorithm in model order selection is demonstrated in an analysis of two independent fMRI data sets. The first data set came from a task-related fMRI study that observed prescription opiate-dependent patients and healthy control subjects at resting state. The analysis of between-subjects and within-subject conditions demonstrated that the negentropy-based algorithm is consistent and robust to changes in data dimension. The second data analysis utilized the resting-state fMRI data from 25 patients with autism spectrum disorders (ASD). The performance of the negentropy-based algorithm was comparable to other commonly used methods. Finally, resting-state fMRI data from 10 ASD patients and 10 healthy control subjects were compared for brain region activation using group ICA. Brain activation (vision, default mode, and basal ganglia) was better represented for the healthy control subjects than the ASD patients. In sum, noisyICA as an alternative to the existing ICA estimation algorithms is promising based on the simulation analyses. In comparison with fastICA algorithm, noisyICA reduces bias in estimating the mixing matrix of independent components for high dimensional data that contain Gaussian noise.Item A Tutorial on Cognitive Diagnosis Modeling for Characterizing Mental Health Symptom Profiles Using Existing Item Responses(Springer Nature, 2022-02-04) Tan, Zhengqi; de la Torre, Jimmy; Ma, Wenchao; Huh, David; Larimer, Mary E.; Mun, Eun-YoungIn research applications, mental health problems such as alcohol-related problems and depression are commonly assessed and evaluated using scale scores or latent trait scores derived from factor analysis or item response theory models. This tutorial paper demonstrates the use of cognitive diagnosis models (CDMs) as an alternative approach to characterizing mental health problems of young adults when item-level data are available. Existing measurement approaches focus on estimating the general severity of a given mental health problem at the scale level as a unidimensional construct without accounting for other symptoms of related mental health problems. The prevailing approaches may ignore clinically meaningful presentations of related symptoms at the item level. The current study illustrates CDMs using item-level data from college students (40 items from 719 respondents; 34.6% men, 83.9% White, and 16.3% first-year students). Specifically, we evaluated the constellation of four postulated domains (i.e., alcohol-related problems, anxiety, hostility, and depression) as a set of attribute profiles using CDMs. After accounting for the impact of each attribute (i.e., postulated domain) on the estimates of attribute profiles, the results demonstrated that when items or attributes have limited information, CDMs can utilize item-level information in the associated attributes to generate potentially meaningful estimates and profiles, compared to analyzing each attribute independently. We introduce a novel visual inspection aid, the lens plot, for quantifying this gain. CDMs may be a useful analytical tool to capture respondents' risk and resilience for prevention research.Item An application of Markov chain Monte Carlo (MCMC) methods in alcohol research: item parameter recovery for the Protective Behavioral Strategies Survey(2020) De La Torre, Jimmy; Mun, Eun-Young; Tan, ZhengqiPurpose: This study was motivated by the measurement challenges of Project INTEGRATE, a large-scale synthesis study of aggregate data and individual participant data (IPD) from brief alcohol intervention trials for young adults. Methods: The present study utilized Markov chain Monte Carlo (MCMC) methods to help address the measurement challenges using the Protective Behavioral Strategies Survey. We aimed to recover item parameters for a two-parameter logistic item response theory (2PL-IRT) model. We tested the viability and feasibility of the custom-developed MCMC algorithm in R under study conditions that varied the number of items (J=5, 10, 20 and 40) and sample size (N=300, 500 and 1000). For each condition, 25 replications were conducted. We evaluated the accuracy of parameter recovery based on the mean bias and root mean square error (RMSE). Results: The MCMC algorithm for the 2-PL IRT model adequately recovered item parameters: for J=5 items and N=300, the bias and RMSE of the item discrimination parameter were -.039 and .073, respectively; and of the item severity parameter were .033 and .065, respectively. As the number of items and sample size increased, both item parameters were more accurately estimated. Conclusions: We presented the outcomes of MCMC methods for a 2PL-IRT model in the recovery of item parameters as the first step toward obtaining commensurate latent trait scores for participants from multiple studies and ensuring the same data interpretation across multiple studies for IPD meta-analysis or integrative data analysis.Item An epidemic model for non-first-order transmission kinetics(PLOS, 2021-03-11) Mun, Eun-Young; Geng, FengCompartmental models in epidemiology characterize the spread of an infectious disease by formulating ordinary differential equations to quantify the rate of disease progression through subpopulations defined by the Susceptible-Infectious-Removed (SIR) scheme. The classic rate law central to the SIR compartmental models assumes that the rate of transmission is first order regarding the infectious agent. The current study demonstrates that this assumption does not always hold and provides a theoretical rationale for a more general rate law, inspired by mixed-order chemical reaction kinetics, leading to a modified mathematical model for non-first-order kinetics. Using observed data from 127 countries during the initial phase of the COVID-19 pandemic, we demonstrated that the modified epidemic model is more realistic than the classic, first-order-kinetics based model. We discuss two coefficients associated with the modified epidemic model: transmission rate constant k and transmission reaction order n. While k finds utility in evaluating the effectiveness of control measures due to its responsiveness to external factors, n is more closely related to the intrinsic properties of the epidemic agent, including reproductive ability. The rate law for the modified compartmental SIR model is generally applicable to mixed-kinetics disease transmission with heterogeneous transmission mechanisms. By analyzing early-stage epidemic data, this modified epidemic model may be instrumental in providing timely insight into a new epidemic and developing control measures at the beginning of an outbreak.Item Detecting Alcohol Consumption Among Homeless Individuals Using Ecological Momentary Assessment, Transdermal Sensors, And Timeline Follow Back Methods(2020) Li, Xiaoyin; Mun, Eun-Young; Businelle, Michael; Lineberry, Shelby; Tan, Zhengqi; Walters,ScottPurpose: The present study examined the extent to which self-reported measures of alcohol use from ecological momentary assessment (EMA) among homeless drinkers corresponded with estimates from a transdermal alcohol sensor (SCRAM) and self-reported timeline follow-back (TLFB) recall measures. Methods: Participants were 63 homeless adults who were receiving services at a homeless shelter in Dallas, TX. Participants' alcohol consumption data were collected via EMA, SCRAM sensor, and a TLFB recall measure at the 4-week follow-up. For each assessment approach, we created two daily alcohol use variables: any use (1= alcohol use positive or 0 = alcohol use negative) and alcohol use quantity. We analyzed data using multilevel models, calculated intraclass correlation coefficients for inter-rater agreement, and estimated pairwise correlations and means across all three assessment methods. Results: Across the three assessment methods, the intraclass correlation coefficient for inter-rater agreement was 0.81 for any alcohol use and 0.76 for alcohol use quantity, indicating excellent agreement. Furthermore, the EMA assessed the quantity of alcohol used was highly correlated with SCRAM peak transdermal alcohol concentration estimate, whereas TLFB had low to modest correlations with EMA and SCRAM measures of alcohol use quantity. Conclusions: Compared with a transdermal alcohol measure, EMA is a valid measure of alcohol use among homeless drinkers. Given the substantial day-to-day variation in alcohol consumption and the ease of EMA compared to biological measures, EMA-based measures of alcohol consumption may be an important tool for clinical research, especially among underserved populations.Item Do Brief Alcohol Interventions Reduce Driving After Drinking Among College Students? A Two-step Meta-analysis of Individual Participant Data(Oxford University Press, 2021-02-16) Mun, Eun-Young; Li, Xiaoyin; Lineberry, Shelby; Tan, Zhengqi; Huh, David; Walters, Scott T.; Zhou, Zhengyang; Larimer, Mary E.; in Collaboration with Project, Integrate TeamAIMS: College students who drink are at an increased risk of driving after drinking and alcohol-involved traffic accidents and deaths. Furthermore, the persistence of driving after drinking over time underscores a need for effective interventions to prevent future drunk driving in adulthood. The present study examined whether brief alcohol interventions (BAIs) for college students reduce driving after drinking. METHODS: A two-step meta-analysis of individual participant data (IPD) was conducted using a combined sample of 6801 college students from 15 randomized controlled trials (38% male, 72% White and 58% first-year students). BAIs included individually delivered Motivational Interviewing with Personalized Feedback (MI + PF), Group Motivational Interviewing (GMI), and stand-alone Personalized Feedback (PF) interventions. Two outcome variables, driving after two+/three+ drinks and driving after four+/five+ drinks, were checked, harmonized and analyzed separately for each study and then combined for meta-analysis and meta-regression analysis. RESULTS: BAIs lowered the risk of driving after four+/five+ drinks (19% difference in the odds of driving after drinking favoring BAIs vs. control), but not the risk of driving after two+/three+ drinks (9% difference). Subsequent subgroup analysis indicated that the MI + PF intervention was comparatively better than PF or GMI. CONCLUSIONS: BAIs provide a harm reduction approach to college drinking. Hence, it is encouraging that BAIs reduce the risk of driving after heavy drinking among college students. However, there may be opportunities to enhance the intervention content and timing to be more relevant for driving after drinking and improve the outcome assessment and reporting to demonstrate its effect.Item Do brief motivational interventions increase motivation for change in drinking among college students? A meta-analysis of individual participant data(2022-08) Tan, Zhengqi; Mun, Eun-Young; Walters, Scott T.; Zhou, Zhengyang; Huh, David; Nandy, Rajesh R.Brief Motivational Interventions (BMIs) have been identified as one of the most effective individually focused alcohol intervention strategies for college students in the United States. Despite the central role of motivation for change in BMIs, whether BMIs increase motivation for change has rarely been investigated. The current study conducted a meta-analysis of individual participant data (IPD; 15 studies, N = 5,903) from Project INTEGRATE (Mun et al., 2015) to examine whether BMIs increase motivation for change in drinking. Different measures and responses used in the original trials were harmonized across studies, and effect size estimates were derived from a model that adjusted for baseline motivation and demographic variables for each study (step 1) and subsequently combined in a random-effects meta-analysis model (step 2). After adjustment for baseline levels of motivation level and demographic variables, the intervention effects of BMIs on motivation for change was not statistically significant (standard mean difference [SMD]: 0.026, 95% CI: [-0.001, 0.053], p = .06, k = 19). Subsequent metaregression analyses among BMI subtypes indicated that the intervention effect did not differ between individually delivered motivational interviewing with personalized feedback (MI+PF), stand-alone personalized feedback (PF), and group-based motivational interviewing (GMI). Among all BMI subtypes, only GMI had a statistically significant intervention effect on motivation compared to controls (SMD: 0.055, 95% CI: [0.007, 0.103], p = .025, k = 5). Within the first three months post-intervention, there was a decrease in SMD of 0.05 (95% CI: [0.01, 0.08]) in motivation per month. However, no statistically significant difference in the intervention effects was found between studies with short-term vs. long-term follow-up. Although the results from the current study do not support the hypothesis that BMIs improve motivation for change, the evidence as a whole suggests ways in which motivation may be improved following intervention and can be tested in future studies.Item Do Brief Motivational Interventions Reduce Drinking and Driving among College Students? A Meta-analysis of Individual Participant Data(2020) Mun, Eun-Young; Zhou, Zhengyang; Walters, Scott; Li, Xiaoyin; Tan, Zhengqi; Lineberry, ShelbyPurpose, Alcohol-impaired driving (AID) is a serious public health concern in the United States. Although often targeted in brief motivational interventions (BMIs), AID has rarely been examined as a primary outcome in trials. This study examined the effectiveness of BMIs on AID for college students using a two-step meta-analysis of individual participant data. Methods, The data came from Project INTEGRATE, a large-scale synthesis study of individual participant data from BMIs and other individual-focused interventions designed to reduce heavy drinking and related problems among college students. A total of 15 trials assessed AID at baseline and the most immediate follow-up within 12 months post intervention (N=9,992; 58.3% female; 71.8% White; 54.6% 1st-year). Two outcomes were driving shortly after consuming 2+ drinks (25 comparisons), and consuming 4+ drinks (21 comparisons), which were coded to 1 (yes) or 0 (no). We separately analyzed these outcomes in random-effects meta-analysis models using "metafor" for R. Results, Overall, there were no statistically significant intervention effects on AID. The pooled log odds ratios of the combined trials were -0.03 (95% CI: -0.15, 0.09) for driving shortly after consuming 2+ drinks, and -0.10 (95% CI: -0.26, 0.07) for driving shortly after consuming 4+ drinks. Conclusions, Although BMIs are efficacious for reducing drinking and alcohol-related negative consequences, the findings from this meta-analysis indicate that they have little to no effects on AID among college students. Given the public health implications of AID, more focused intervention efforts are needed.Item Does abstaining from alcohol in high school moderate intervention effects for college students? Implications for tiered intervention strategies(Frontiers Media S.A., 2022-12-20) Tan, Lin; Friedman, Zachary; Zhou, Zhengyang; Huh, David; White, Helene R.; Mun, Eun-YoungBrief motivational intervention (BMI) and personalized feedback intervention (PFI) are individual-focused brief alcohol intervention approaches that have been proven efficacious for reducing alcohol use among college students and young adults. Although the efficacy of these two intervention approaches has been well established, little is known about the factors that may modify their effects on alcohol outcomes. In particular, high school drinking may be a risk factor for continued and heightened use of alcohol in college, and thus may influence the outcomes of BMI and PFI. The purpose of this study was to investigate whether high school drinking was associated with different intervention outcomes among students who received PFI compared to those who received BMI. We conducted moderation analyses examining 348 mandated students (60.1% male; 73.3% White; and 61.5% first-year student) who were randomly assigned to either a BMI or a PFI and whose alcohol consumption was assessed at 4-month and 15-month follow-ups. Results from marginalized zero-inflated Poisson models showed that high school drinking moderated the effects of PFI and BMI at the 4-month follow-up but not at the 15-month follow-up. Specifically, students who reported no drinking in their senior year of high school consumed a 49% higher mean number of drinks after receiving BMI than PFI at the 4-month follow-up. The results suggest that alcohol consumption in high school may be informative when screening and allocating students to appropriate alcohol interventions to meet their different needs.Item Ecological Momentary Assessment of Alcohol Consumption and Its Concordance with Transdermal Alcohol Detection and Timeline Follow-Back Self-report Among Adults Experiencing Homelessness(John Wiley & Sons, Inc., 2021-03-03) Mun, Eun-Young; Li, Xiaoyin; Businelle, Michael S.; Hebert, Emily T.; Tan, Zhengqi; Barnett, Nancy P.; Walters, Scott T.BACKGROUND: Studies of alcohol use presume valid assessment measures. To evaluate this presumption, we examined the concordance of alcohol use as measured by ecological momentary assessment (EMA) self-reports, transdermal alcohol concentration readings via the Secure Continuous Remote Alcohol Monitor (SCRAM), and retrospective self-reports via the Timeline Follow-Back (TLFB) among adults experiencing homelessness. METHODS: Forty-nine adults who reported alcohol misuse (mean age = 47, SD = 9; 57% Black; 82% men) were recruited from a homeless shelter. For 4 weeks, alcohol use was assessed: (i) 5 times or more per day by EMA, (ii) every 30 minutes by a SCRAM device worn on the ankle, and (iii) by TLFB for the past month at the end of the study period. There were 1,389 days of observations of alcohol use and alcohol use intensity for 49 participants. RESULTS: EMA and SCRAM alcohol use data agreed on 73% of days, with an interrater agreement Kappa = 0.46. A multilevel analysis of concordance of 3 measures for alcohol use yielded statistically significant correlations of 0.40 (day level) and 0.63 (person level) between EMA and SCRAM. Alcohol use was detected on 49, 38, and 33% of days by EMA, SCRAM, and TLFB, respectively. For alcohol use intensity, EMA and SCRAM resulted in statistically significant correlations of 0.46 (day level) and 0.78 (person level). The concordance of TLFB with either EMA or SCRAM was weak, especially at the day level. CONCLUSIONS: This is the first study to examine concordance of alcohol use estimates using EMA, SCRAM, and TLFB methods in adults experiencing homelessness. EMA is a valid approach to quantifying alcohol use, especially given its relatively low cost, low participant burden, and ease of use. Furthermore, any stigma associated with wearing the SCRAM or reporting alcohol use in person may be attenuated by using EMA, which may be appealing for use in studies of stigmatized and underserved populations.Item Illicit Substance Use Among a Sample of Subsidized Housing Residents: Concordance, Longitudinal Trends, and Quality of Life(2019-05) Rendon, Alexis; Walters, Scott T.; Spence-Almaguer, Emily; Mun, Eun-Young; Livingston, Melvin D.; Suzuki, SumihiroThis three-paper model dissertation investigates issues related to self-reported substance use. Self-report is a less invasive and expensive method of collecting substance use behavior when compared to a toxicological test, but the self-report method has been shown to be unreliable in some populations. We found that self-report missed some use captured by a saliva toxicological test administered to a subsidized housing population enrolled in a technology-assisted health coaching program. Concordance was highest among marijuana users and increased over time. Higher rates of concordance were found when the recall window was expanded from a restricted biological recall window to match the toxicological test to the full 90 day window of the Timeline Follow-Back. Participants who reported using substances more frequently reported having more problems related to their substance use. We also found that both substance use problems and the frequency of consumption of a combined Other category of substances, including cocaine, amphetamine, methamphetamine, opiates, prescription pills, or phencyclidine were predictive of lower quality of life. This dissertation validates previous literature indicating that self-report is a fair to moderately good measure of actual substance use behavior in vulnerable populations that may intentionally or unintentionally misreport their substance use. Programs limited to self-reported measures may consider widening their recall windows to increase accuracy of self-report.Item Increases in social support co-occur with decreases in depressive symptoms and substance use problems among adults in permanent supportive housing: an 18-month longitudinal study(BioMed Central Ltd., 2021-01-06) Tan, Zhengqi; Mun, Eun-Young; Nguyen, Uyen-Sa D.T.; Walters, Scott T.BACKGROUND: Social support is a well-known protective factor against depressive symptoms and substance use problems, but very few studies have examined its protective effects among residents of permanent supportive housing (PSH), a housing program for people with a history of chronic homelessness. We utilized unconditional latent growth curve models (LGCMs) and parallel process growth models to describe univariate trajectories of social support, depressive symptoms, and substance use problems and to examine their longitudinal associations in a large sample of adults residing in PSH. METHODS: Participants were 653 adult PSH residents in North Texas (56% female; 57% Black; mean age: 51 years) who participated in a monthly health coaching program from 2014 to 2017. Their health behaviors were assessed at baseline and tracked every six months at three follow-up visits. RESULTS: Unconditional LGCMs indicated that over time, social support increased, whereas depressive symptoms and substance use problems decreased. However, their rates of change slowed over time. Further, in parallel process growth models, we found that at baseline, individuals with greater social support tended to have less severe depressive symptoms and substance use problems (coefficients: - 0.67, p < 0.01; - 0.52, p < 0.01, respectively). Individuals with a faster increase in social support tended to have steeper rates of reduction in both depressive symptoms (coefficient: - 0.99, p < 0.01) and substance use problems (coefficient: - 0.98, p < 0.01), respectively. CONCLUSIONS: This study suggests that plausibly, increases in social support, though slowing over time, still positively impact depressive symptoms and substance use problems among PSH residents. Future PSH programs could emphasize social support as an early component as it may contribute to clients' overall health.Item Longitudinal Associations of Social Support with Depression and Substance Use Problems among Permanent Supportive Housing Residents(2020) Walters, Scott; Mun, Eun-Young; Tan, ZhengqiPurpose: Social support is a well-known protective factor against depression and substance use problems, but very few studies have examined its protective effects among Permanent Supportive Housing (PSH) residents. We utilized unconditional latent growth curve (LGC) models and parallel process growth (PPG) models to describe trajectories of social support, depression, and substance use problems, and to examine their longitudinal associations in a large sample of adults residing in PSH. Methods: Participants were 653 adult PSH residents (56% female; 57% Black, 35% White, 8% others; mean age: 51 years). Health behaviors were assessed at baseline and every 6 months during a 2-year longitudinal study, which was conducted in Fort Worth, TX from 2014 to 2017. Results: Unconditional LGC models indicated that over time, social support increased whereas depressive symptoms and substance use problems decreased. However, their rate of change all slowed over time. Further, in PPG models, at baseline, greater social support was linked to less severe depression and substance use problems (coefficients: -0.21, p< 0.01; -0.06, p< 0.01, respectively). Linear slopes of social support and depression were negatively associated (coefficient: -0.01, p=0.01), indicating that faster rates of increase in social support were associated with steeper rates of reduction in depression. Linear slopes of social support and substance use problems were positively linked but statistically insignificant (coefficient: 0.01, p=0.63). Conclusions: This study suggests that increases in social support may positively impact depression and substance use problems among PSH residents, but when their positive trajectory slows, boosters may be needed.Item Opportunities for Tuberculosis Prevention in Private Sector Healthcare: Health Insurance and Usual Sources of Healthcare in Foreign-Born Persons with Latent Tuberculosis Infection(2019-03-05) Stockbridge, Erica L.; Miller, Thaddeus; Mun, Eun-Young; Annan, EstherOpportunities for Tuberculosis Prevention in Private Sector Healthcare: Health Insurance and Usual Sources of Healthcare in Foreign-Born Persons with Latent Tuberculosis Infection E. Annan 1, E. L. Stockbridge 2, T. L. Miller 2, E.Y. Mun2 1Department of Biostatistics & Epidemiology, University of North Texas Health Science Center, Fort Worth, TX, United States. 2 Department of Health Behavior & Health Systems, University of North Texas Health Science Center, Fort Worth, TX, United States. Abstract Background: Preventing TB in the foreign-born US population is a priority, as over two-thirds of active TB cases in the US occur among foreign-born persons. With 90% of incident active TB cases among foreign-born persons stemming from reactivation of latent TB infections (LTBI), there is a need to increase targeted LTBI testing and treatment in foreign-born persons. It may be feasible to conduct these activities within the US private healthcare sector, but LTBI-positive foreign-born persons' use of healthcare and ability to pay for care will facilitate or impede such a strategy. These characteristics are not well-described in current literature. Aims: (1) Estimate LTBI prevalence among foreign-born individuals by health insurance status and usual source of healthcare (USHC); and (2) examine patterns of insurance coverage and USHC among foreign-born persons with LTBI. Methods: We analyzed 2011-12 National Health and Nutrition Examination Survey (NHANES) self-reported health insurance and USHC data for foreign-born individuals in combination with markers for LTBI. The sample was restricted to civilian, noninstitutionalized, foreign-born persons ages 6 years or older with interferon gamma release assay (IGRA) results and self-reported insurance and USHC data (N=1,793). We used Stata /SE 15.1 to conduct analyses and adjust for complex sampling design. Results: Overall, 15.9% of our sample were LTBI-positive. Of LTBI-positive persons, 37.0% had some form of insurance and 76.9% had a USHC. LTBI prevalence was highest in persons who used a clinic or health center as a USHC (17.3%), but 44.6% of persons with LTBI use a physician’s office or HMO as a USHC. Insured persons had a slightly higher prevalence of LTBI than uninsured persons (16.2% and 15.3%, respectively). While LTBI prevalence was highest in persons with Medicare, persons with LTBI were most likely to be uninsured (37.0%) or have private insurance (33.1%). In total, 56.7% of persons with LTBI had both health insurance and a USHC, while 20.2% had neither insurance nor a USHC. Conclusion: Both health insurance and USHC were common within foreign-born individuals with LTBI residing in the US. Although different strategies are needed to address LTBI within the vulnerable population of foreign-born persons without health insurance or USHC, our results suggest that targeted LTBI testing and treatment within the US private healthcare sector could reach the majority of foreign-born individuals with LTBI.Item Project INTEGRATE: A Comprehensive and Systematic Meta-analysis Study of Brief Alcohol Interventions for Young Adults(2019-03-05) Li, Xiaoyin; Zhou, Zhengyang; Walters, Scott; Mun, Eun-YoungPurpose: Project INTEGRATE is a large synthesis study of alcohol intervention trials, which has been supported by the National Institute on Alcohol Abuse and Alcoholism since 2010. This multi-site, interdisciplinary project involves experts from a wide range of disciplinary fields (e.g., psychology, sociology, public health, statistics) who come together to help promote public health. Currently, we are conducting a comprehensive meta-analysis to examine the comparative effectiveness of brief alcohol interventions (BAI) for adolescents and young adults (aged 11-25). Through a previous systematic review and data request, we have compiled aggregate data (AD) from 189 studies and individual participant data (IPD) from 24 studies. We are currently reviewing full-text articles from 2013 through 2018 to update AD and IPD. Methods/Results: To examine the efficacy and mechanisms of BAIs on alcohol outcomes, our work has extended network meta-analysis models and multivariate random-effects meta-analysis models. Using a multilevel Bayesian hurdle model, we demonstrated how IPD from heterogeneous clinical trials with abundant structural and empirical zeros can be modeled in one step analysis. To validly compare individuals across time and studies, we have developed scoring approaches to harmonize and advance item response theory (IRT) models using Markov chain Monte Carlo studies. The goal of our methodological work is to develop tools to provide better clarity for the field by maximizing available data that are most granular and comprehensive. Thus far, we found that an in-person brief motivational intervention (BMI) is efficacious for reducing alcohol-related problems, and the benefit is sustained through 12 months post-intervention. We also found that the implementation and content of intervention makes a difference. When BMIs were highly personalized to participants, it was more beneficial to have a higher number of intervention components; conversely, when interventions have more general content, it was better to cover fewer components. Conclusions: Project INTEGRATE is developing innovative approaches to synthesizing information that will provide more robust, large-scale evidence of what works well, for whom, and how. The model-based inference derived from this complex synthesis of all available data will provide more contextualized and mechanism-based answers to major stakeholders.Item Protective behavioral strategies are more helpful for avoiding alcohol-related problems for college drinkers who drink less(2020) Li, Xiaoyin; Walters, Scott; Mun, Eun-YoungPurpose: Many health providers recommend that college students should use protective behavioral strategies (PBS) (e.g., setting drinking limits) to reduce negative consequences. This recommendation is derived from previous research showing that PBS can help reduce alcohol-related harm. However, more research is needed to determine whether PBS are equally protective across different demographic groups when college drinkers increase their alcohol consumption. This study examined race, gender, and alcohol use level as moderators of the association between PBS and alcohol-related problems among college students. Methods: A total of 12,011 participants (87.7% White, 61% Women) from 12 studies were selected from Project INTEGRATE that combined individual participant data from 24 intervention studies for college students. Complex samples hierarchical regressions were conducted using Mplus. Alcohol use, alcohol-related problems, and PBS use were continuous variables that were measured or estimated in latent variable modeling. Results: Moderation analyses suggested that the protective association between PBS and alcohol-related problems was greater for those who drank less. This moderated effect did not differ across men and women or across racial groups. Conclusions: Greater use of PBS may not always be beneficial for lowering alcohol problems, especially among heavier drinkers or during heavy drinking situations. College drinking prevention programs should ensure that students are aware of the limits of PBS as a harm reduction strategy for alcohol problems. Findings from this study provide evidence for public health efforts to reduce alcohol use "across the board" in addition to promoting PBS among student drinkers.