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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Browsing Publications -- Scott T. Walters by Subject "Female"
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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 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.Item 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-YoungAdults 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.