Publications -- Scott T. Walters

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12503/31520

This collection is limited to articles published under the terms of a creative commons license or other open access publishing agreement since 2016. It is not intended as a complete list of the author's works.

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Now showing 1 - 6 of 6

Understanding cancer genetic risk assessment motivations in a remote tailored risk communication and navigation intervention randomized controlled trial
(Informa UK Limited, trading as Taylor & Francis Group, 2022-12-16) Le Compte, Circe G.; Lu, Shou-En; Ani, Julianne; McDougall, Jean; Walters, Scott T.; Toppmeyer, Deborah; Boyce, Tawny W.; Stroup, Antoinette; Paddock, Lisa; Grumet, Sherry; Lin, Yong; Heidt, Emily; Kinney, Anita Y.
BACKGROUND: National guidelines recommend cancer genetic risk assessment (CGRA) (i.e. genetic counseling prior to genetic testing) for women at increased risk for hereditary breast and ovarian cancer (HBOC). Less than one-half of eligible women obtain CGRA, leaving thousands of women and their family members without access to potentially life-saving cancer prevention interventions. PURPOSE: The Genetic Risk Assessment for Cancer Education and Empowerment Project (GRACE) addressed this translational gap, testing the efficacy of a tailored counseling and navigation (TCN) intervention vs. a targeted print brochure vs. usual care on CGRA intentions. Selected behavioral variables were theorized to mediate CGRA intentions. METHODS: Breast and ovarian cancer survivors meeting criteria for guideline-based CGRA were recruited from three state cancer registries (N = 654), completed a baseline survey, and were randomized. TCN and targeted print arms received the brochure; TCN also participated in a tailored, telephone-based decision coaching and navigation session grounded in the Extended Parallel Process Model and Ottawa Decision Support Framework. Participants completed a one-month assessment. Logistic regression was used to compare the rate of CGRA intentions. CGRA intentions and theorized mediator scores (continuous level variables) were calculated using mixed model analysis. RESULTS: CGRA intentions increased for TCN (53.2%) vs. targeted print (26.7%) (OR = 3.129; 95% CI: 2.028, 4.827, p < .0001) and TCN vs. usual care (23.1%) (OR = 3.778, CI: 2.422, 5.894, p < .0001). Perceived risk (p = 0.023) and self-efficacy (p = 0.035) mediated CGRA intentions in TCN. CONCLUSIONS: Improvements in CGRA intentions and theorized mediators support the use of a tailored communication intervention among women at increased HBOC risk. (Clinicaltrials.gov: NCT03326713.)Trial registration: ClinicalTrials.gov identifier: NCT03326713.
Using machine learning to identify predictors of imminent drinking and create tailored messages for at-risk drinkers experiencing homelessness
(Elsevier Inc., 2021-04-20) Walters, Scott T.; Businelle, Michael S.; Suchting, Robert; Li, Xiaoyin; Hebert, Emily T.; Mun, Eun-Young
Adults experiencing homelessness are more likely to have an alcohol use disorder compared to adults in the general population. Although shelter-based treatments are common, completion rates tend to be poor, suggesting a need for more effective approaches that are tailored to this understudied and underserved population. One barrier to developing more effective treatments is the limited knowledge of the triggers of alcohol use among homeless adults. This paper describes the use of ecological momentary assessment (EMA) to identify predictors of "imminent drinking" (i.e., drinking within the next 4 h), among a sample of adults experiencing homelessness and receiving health services at a homeless shelter. A total of 78 mostly male (84.6%) adults experiencing homelessness (mean age = 46.6) who reported hazardous drinking completed up to five EMAs per day over 4 weeks (a total of 4557 completed EMAs). The study used machine learning techniques to create a drinking risk algorithm that predicted 82% of imminent drinking episodes within 4 h of the first drink of the day, and correctly identified 76% of nondrinking episodes. The algorithm included the following 7 predictors of imminent drinking: urge to drink, having alcohol easily available, feeling confident that alcohol would improve mood, feeling depressed, lower commitment to being alcohol free, not interacting with someone drinking alcohol, and being indoors. The research team used the results to develop intervention content (e.g., brief tailored messages) that will be delivered when imminent drinking is detected in an upcoming intervention phase. Specifically, we created three theoretically grounded message tracks focused on urge/craving, social/availability, and negative affect/mood, which are further tailored to a participant's current drinking goal (i.e., stay sober, drink less, no goal) to support positive change. To our knowledge, this is the first study to develop tailored intervention messages based on likelihood of imminent drinking, current drinking triggers, and drinking goals among adults experiencing homelessness.
Serious mental illness and negative substance use consequences among adults on probation
(BioMed Central Ltd., 2018-03-22) Rossheim, Matthew E.; Livingston, Melvin D.; Lerch, Jennifer A.; Taxman, Faye S.; Walters, Scott T.
BACKGROUND: Adults on probation are at greater risk of both using substances and having a mental disorder compared to the general population. Several theories explain the relationship between substance use and poor mental health. However, the interaction between substance use, mental health, and substance-related consequences is not well understood. A better understanding of this relationship may help treatment programs become more responsive to people with serious mental illness (SMI). METHOD: The current study used interview data from 313 adults on probation who reported recent substance use. We examined associations between SMI risk, substance use, and substance use consequences. RESULTS: A substantial proportion of the sample (37.5%) screened at risk of having a SMI. Adjusting for type and amount of substance use, those who screened at risk of having a SMI reported more negative substance use consequences. Significant interaction effects were observed between use of alcohol or opiates and SMI risk. Alcohol use was associated with more negative substance use consequences among those at risk of SMI, while opiate use was associated with more consequences among those not at risk. CONCLUSIONS: Programs are sorely needed to identify and treat adults with comorbid substance use and mental health symptoms, particularly for adults in the justice system. Clinicians should carefully consider how mental health may interact with substance use to exacerbate consequences.
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-Young
This 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.
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.
Use of a Health Advocacy Model for Survivors of Interpersonal Violence
(MDPI, 2020-12-02) Grace, Jessica; Walters, Scott T.; Gallegos, Irene; Thompson, Erika L.; Spence, Emily E.
This article examines the implementation of a health advocacy model designed for survivors of interpersonal violence (IPV) in a metropolitan area of North Texas. Using a framework influenced by motivational interviewing, solution-focused therapy, and trauma-informed care, this program engaged IPV survivors in creating health and safety goals. Goal attainment scaling was used to track progress after each health advocacy encounter. Clients could set their own goals for healthcare, self-care, and safety. The program served 419 clients and 648 goals were set by clients at the first visit. Among all goals, 89% selected goals focused on healthcare, with 47% of those selecting obtaining health insurance or coverage as a need. These results demonstrate the need for an enhanced healthcare response for this population. The remaining goals selected were self-care (7%) and safety (3%). The design of the health advocacy intervention shows promise towards filling the gaps between IPV and healthcare service delivery systems.

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