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Browsing by Author "Walton, Betty"
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Item Behavioral Health Needs of Older Adults Living in Poverty: Machine Learning-Based Predictive Models(2023-01-13) Hong, Saahoon; Yi, Eun-Hye G.; Walton, Betty; Kim, Hea-WonTo develop contextually sensitive and effective services for older adults in poverty, this study aimed to identify the characteristics and patterns of older adults’ BH service needs, compared to those of middle-aged adults. The findings suggest that employment is the most important predictor for classifying older adults with behavioral health needs, followed by adjustment to trauma, independent living, legal system involvement, sleep, disability, transportation, social skills, and self-care. Interestingly, gender and race were not significantly important in classifying behavioral health needs between middle-aged and older adult groups. The older adults who had non-actionable ratings on employment and actionable ratings on the legal system (current JS involvement), middle-aged adults were more likely to struggle with anxiety than older adults. The older adults with non-actionable ratings on employment, legal system, and adjustment to trauma, non-disabled older adults were more likely to present behavioral health needs on medical/physical, anxiety, independent living, recreational, and sleep.Item Collaborate, Review Data and Change; Repeat(2022-09-27) Walton, Betty; Wendy, HarroldContext. The ANSA and TCOM framework, in conjunction with related information, can support data-informed policy planning and funding initiatives. One state’s collaborative data-informed recovery strategies provide an example. The concept of recovery from mental health and substance use disorders evolved from a deficit focus to include functional and personal recovery. Through a collaborative process SAMHSA, the federal behavior health authority, developed recovery’s working definition: “a process of change through which individuals improve their health and wellness, live a self- directed life, and strive to reach their full potential” in four dimensions (Health - overcoming or managing one’s diseases or symptoms, Home – a stable and safe place to live, Purpose - meaningful daily activities, and Community - relationships and social networks that provide support, friendship, love, and hope. Recently, SAMHSA acknowledged that the 2012 framework needs to evolve and issued a Recovery Challenge to community-based organizations to highlight innovative recovery strategies and practices. The challenge requires active, meaningful involvement of individuals with lived experience. Recovery and TCOM frameworks were cross walked to support training and to inform the state’s recovery support strategies. One strategy was to create a Recovery Support Workgroup (RSW) comprised of a dozen state agencies and community stakeholders. More than 51% of RSW members have lived experience with mental health and/or substance use. This group makes data-informed recommendations to state’s Mental Health and Addiction Planning and Advisory Council. Following a statewide 2019 gap analysis, which identified recovery support needs, the RSW created subgroups to address five recovery support needs: Personal support networks, Peer support services, Hobbies and interests, Prevention and wellness, and Safe and affordable housing. Data Collection Methodology. Multiple data sources informed the subgroups’ efforts: a consumer satisfaction survey, social determinants of health survey a Lived Experience Survey distributed through recovery groups, Medicaid claims diagnoses, recovery data collected at recovery organizations, and ANSA data. All data were associated with recovery dimensions: Health, Home, Community and Purpose. For ANSA data, the process required collaboration among the state’s data management, recovery support services, and the IU CANS/ANSA technical assistance teams. Enhancing ANSA Outcome Management Reports. Outcome Management reports, available to the state team, providers, and the IU CANS/ANSA team, were modified to inform the RSW subgroups by formatting reports by recovery dimensions and additional concerns. Building on existing reports (Resolved Actionable Needs, and item level metrics (Actionable, Continuing, Clinical Progress, Newly Identified, and Worsening), three new recovery focused reports were developed. Sharing and using the data. This collaborative, data-informed recovery initiative has received national attention. A variety of strategies to disseminate and to use the results for planning and managing change will be discussed: What has worked? What has been challenging? What has not work? What are the implications for quality improvement, program evaluation, and research?Item Deliberate Self-Harm in Young Children(2020-08) Lewis, Lisa McConnell; Adamek, Margaret E.; Vernon, Robert; Aalsma, Matthew C.; Walton, BettyWhile deliberate self-harm (DSH) in adolescents and adults has been established as a reliable predictor of future suicidal behavior and attempts, whether the same is true for younger children has rarely been studied. Two separate articles will address issues regarding intentional self-injury in young children. The first identified describes the demographic profile of young children who engage in NSSI and evaluated whether predictors of adolescent NSSI are also associated with NSSI in children. The second manuscript analyzed NSSI behaviors to see if they can be correctly predicted from knowledge of a child's history of maltreatment to identify which trauma variables are central in prediction of NSSI status. A Chi-square and logistic regression were run on data from 16,271 records of children ages 5-9 years who received services from the IDMHA in 2018. NSSI was significantly (p < .000) associated with trauma history (x2 = 75.54, df = 1), anxiety (x2 = 107.59, df = 1), depression (x2 = 217.011, df = 1), suicide risk (x2= 993, df = 1), and impulsivity (x2 = 122.49, df = 1. Presence of a caregiver mental health problem (x2 =38.29, df = 1), age (x2 = 14.18, df = 4), being male (x2 = 11.59, df = 1), and being Caucasian (x2 = 23.29, df = 6) at p < .05. Regression results indicated the overall model of seven predictors (sexual abuse [OR 1.14], physical abuse [OR 1.26], emotional abuse [OR1.3], neglect [OR .895], medical trauma [OR 1.34], exposure to natural disaster [OR 1.81] and victim of a crime [1.14] was statistically reliable in distinguishing between children who self-injure and those who do not. [-2 Log Likelihood = 6228.78, x2(6) = 105.416, p < .000]. NSSI does occur in preadolescent children and while there is some indication that the risk factors and co-variates are like those of adolescents, there are some differences which need further study. Training clinicians to inquire about self-injury during assessment of younger children is a simple step. The variables of age and sex throughout development as well as identifying protective as well as risk factors with children should be studied.Item Managing Recovery with Adults Involved in Behavioral Health and Criminal Justice Systems(2022-09-21) Hong, Saahoon; Walton, BettyYoung adults with mental health needs experience increased criminal behaviors, peaking at 16-25 years. In addition, the lack of support for young adults' behavioral health needs increases the likelihood of further involvement in the justice system. This study aimed to predict dual behavioral health and justice system involvement for adults participating in publicly funded treatment and support services needs. Policy implications were also discussed.Item Recovery from Problem Gambling: A Machine Learning Approach(2022-07-29) Hong, Saahoon; Walton, Betty; Kim, Hea-WonThe primary purpose of this study was to examine and identify intersections of the first wave of the COViD-19 pandemic, behavioral health needs/strengths, demographic characteristics, and recovery from problem gambling. By analyzing Adult Needs and Strengths Assessment (ANSA) datasets, we identified critical factors associated with improvement from problem gambling. In addition, we discussed risk factors that led to the continued struggling with problem gambling.Item Young Adults with the Mental Health and Criminal Justice System Involvement: A Preliminary Study(2023-01-15) Hong, Saahoon; Walton, Betty; Kim, Hea-Won; Moynihan, StephanieThis study examined the intersection of characteristics, behavioral health needs, and strengths for young adults with dual involvement in the mental health and criminal justice systems. Findings predicted dual system involvement with the following ANSA items: 1) substance use; 2) gender; 3) depression; 4) anxiety; 5) volunteering (strength); 6) developmental; 7) impulse control; 8) residential stability; 9) parental/caregiver role, and 10) anger control. The most significant predictor associated with the dual system involvement, differentiating from the non-dual system involvement, was substance use followed by gender and depression. More young men than young women had substance use needs. Young adults with dual system involvement presented higher rates of actionable ratings on depression and impulse control than their counterparts.