Betty Walton
- Ph.D., MSW, LCSW
- Associate Research Professor
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IU Indianapolis
Contact
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(317) 274-8348
- beawalto@iu.edu
About
Betty Walton, Ph.D., LCSW, Associate Research Professor, Indiana University School of Social Work, Indianapolis, conducts translational research to support behavioral health services for children, youth, and adults. Over the past twenty-five years, she has helped build capacity for effective community based behavioral health services statewide, including the development of systems of care and wraparound services for youth and families with complex needs. Since 2010, Dr Walton and the IUSSW CANS/ANSA Research and Training Team (CARTT) have provided continuing education, coaching, and technical assistance to support the implementation of common assessment/outcome tools in public service systems (behavioral health specialized Medicaid programs, and child welfare). By collaborating with the state to implement individual and program outcome assessment measures/reports, CARTT also supports the routine use of practice-based data to inform planning and monitor progress at direct service, program, and system levels. Using statewide administrative data, related research has examined child mental health system development and recovery factors for children, youth, and adults with behavioral health disorders. Publications have been cited over 50 times.
Education
PhD
Emphasis/Major: Social Work Research2006 - Indiana University
Dissertation: Predictors of Improvement for Children Served in Developing Systems of Care
MSW
Emphasis/Major: Social Work1973 - The University of Iowa
BA
Emphasis/Major: Sociology1971 - University of Illinois
Research Interests
My research interests have evolved. Early translational research related to identifying behavioral health recovery factors for children/youth with complex behavioral health needs (system of care [SOC] development, fidelity to the wraparound model, and youth characteristics) supported the development and sustainability of high fidelity wraparound and support for system of care development statewide (Effland et al, 2011; Karikari et al., 2021). Annual wraparound program evaluations were enriched by combining assessment and Medicaid claims data to examine factors related to improved functioning.
Supporting the statewide implementation of holistic assessment, outcome management tools for children, youth, and adults statewide provided unique research opportunities. In collaboration with the state behavioral health authority and we examined the psychometric properties of the ANSA following its first use with adults with serious mental illness who participated in publicly funded treatment. A relationship between developing strengths and improved functioning for children and youth was demonstrated using longitudinal latent analyses (Hong et al., 2021; Hong et al., 2023).
A pandemic era study utilized Chi-squared automatic interaction detection (CHAID) to detect race-specific differences. Regardless of age, gender, or pandemic status, Asian Americans who received behavioral health services, struggled more with cultural-related factors compared to White and Black individuals. Intersections among behavioral or emotional needs (psychosis), life functioning needs (involvement in recovery, residential stability, decision making, medical/physical health), and strengths (job history, interpersonal, and spiritual) further differentiated the mental health functioning of Asian from White and Black Americans.
Subsequent studies have documented connections between the number of resolved needs, varying patterns of strengths, opioid use, geography (rural/urban residence), race and ethnicity, referral source, and service completion. The impact of spirituality/religion on outcomes was discussed at the 2023 American Public Health Association conference, and the mediating roles of strengths was presented at the 2024 Society of Social Work and Research Conference. Our research agenda includes merging Medicaid claims data with the integrated administrative data set to include the type and intensity of provided services in studies to inform practice and support recovery. To support this, a National Institute of Health (NIH) grant proposal is being developed by Dr. Saahoon Hong. Please see my NIH Biographical sketch for details.
Teaching Interests
My teaching interests include graduate education for doctoral research assistants and continuing education for behavioral health and social service professionals. For research assistants, hands-on involvement in research provides opportunities for individualized learning, knowledge application, and participatory research with federal, state, and local agencies, families, and youth. Former research assistants have completed independent studies, presented at national conferences, and/or published their work.
Cross-system, inter-disciplinary continuing education related to person-centered care utilizes a collaborative outcome management framework, assessment strategies and skills to inform decisions and monitor progress at multiple levels (direct service, supervision, program, and system).Through competency-based training, CARTT collaborates with the Center for Innovation in Population Health, College of Public Health, University of Kentucky to support trainers and local implementation coaches (supervisors and managers), program specialists (direct service social workers and other human service professionals) who utilize the Child and Adolescent Needs and Strengths (CANS) and Adult Needs and Strengths Assessment (ANSA) tools in practice. During 2020, our team transitioned from large in-person workshops to synrousnous online ZOOM workshops, while implementing an updated, standardized national curriculum. In 2021, we launched an asynchronous online overview course introducing the CANS, ANSAm and underlying philosophy via IU Expand. The course, revised in 2023, is a prerequisite for training/certification of new implementation coaches and a resource to already certified coaches and other stakeholders.
I have also enjoyed sharing our translational research in master and doctoral courses as a guest.
Awards and Honors
- TCOM Founders Award
2020 - Praed Foundation, University of Kentucky, Louisville, KY - Outcomes Champion, Systems of Care
2007 - Praed Foundation, Chicago, Illinois - Hero for Cross System Implementation, Individual Community Supporter
2006 - Mental Health America
Publications
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Hong, S., Walton, B. A., Kim, H.-W., Kaboi, M., Moynihan, S., & Rhee, T. G. (2023). Exploring disparities in behavioral heatlh service use in the early stages of the COVID-19 pandemic. International Journal of Behavioral Medicine, published online. https://doi.org/DOI: 10.1007/s12529-023-10192-z
Abstract
Background. Previous studies examined the impact of the COVID-19 pandemic on mental health, but few studies looked atassociations between the pandemic and state-funded behavioral health service utilization. We aimed to examine behavioralhealth service utilization during the early phase of COVID-19 among individuals with psychiatric disorders (PD), substanceuse disorders (SUD), and co-occurring disorders (COD).
Methods. Using the last Adult Needs and Strengths Assessment (ANSA) completed in 2019 and 2020 in a Midwestern state,a column proportion test and Poisson regression model examined the associations of the pandemic year, age, gender, race/ethnicity, diagnostic type, and behavioral health needs.
Results. Between 2019 and 2020, the number of adults newly involved in behavioral health services increased from 11,882 to 17,385.The number of total actionable items (TAI) differed by gender and age group. Adults who were Black or American Indian were morelikely to have a significantly higher number of needs that interfered with functioning (β = 0.08; CI [0.06, 0.09]), (β = 0.16; CI [0.08,0.23]), respectively, than White peers. Individuals with COD showed the highest number of needs (β = 0.27; CI [0.26, 0.28]) whencompared to the needs of individuals with psychiatric disorders, after controlling for year, age, gender, and race/ethnicity.
Conclusions. Additional research is needed to better understand the intersections of age, gender identity, race/ethnicity,the complexity of needs, and useful strengths. The involvement of practitioners, service organizations, researchers, andpolicymakers will be required to provide accessible, effective behavioral health services with cultural and developmentaladaptations to support recovery. -
Hong, S., Walton, B. A., Kim, H.-W., & Rhee, T. G. (2023). Predicting the Behavioral Health Needs of Asian Americans in Public Mental Health Treatment: A Classification Tree Approach. Administration and Policy in Mental Health and Mental Health Services Research. Published. https://doi.org/https://doi.org/10.1007/s10488-023-01266-x
Abstract Given the fact that experiencing pandemic-related hardship and racial discrimination worsen Asian Americans’ mental health, this study aimed to identify unique characteristics of behavioral health needs among Asian Americans (N = 544) compared to White Americans (N = 78,704) and Black Americans (N = 11,252) who received publicly funded behavioral health services in Indiana before and during the COVID-19 pandemic. We used 2019–2020 Adults Needs and Strengths Assessment (ANSA) data for adults eligible for Medicaid or funding from the state behavioral health agency. Chi-squared automatic interaction detection (CHAID) was used to detect race-specific differences among demographic variables, the pandemic status, and ANSA items. Results indicated that, regardless of age, gender, or pandemic status, Asian Americans who received behavioral health services, struggled more with cultural-related factors compared to White and Black individuals. Within this context, intersections among behavioral/emotional needs (psychosis), life functioning needs (involvement in recovery, residential stability, decision making, medical/physical health), and strengths (job history, interpersonal, and spiritual) further differentiated the mental health functioning of Asian from White and Black Americans. Classification tree algorithms offer a promising approach to detecting complex behavioral health challenges and strengths of populations based on race, ethnicity, or other characteristics. -
Hong, S., Walton, B. A., Kim, H.-W., Lee, S., & Rhee, T. G. (2021). Longitudinal Patterns of Strengths among Youth with Psychiatric Disorders: A Latent Profile Transition Analysis. Child Psychiatry & Human Development, 54, 1-8. https://doi.org/https://www.doi.org/10.1007/s10578-021-01217-3
Abstract
A better understanding of variability in the strengths of youth with psychiatric disorders is critical as a strength-based approach can lead to recovery. This study aimed to identify subgroups of strengths among youth with mental disorders and determine whether subgroups changes were associated with mental health recovery. Youth with mental disorders (N = 2228) from a statewide database were identified in the state fiscal year of 2019. Using the latent profile analysis and latent transition analysis, we identified three strength profiles (i.e., essential, usable, and buildable). Over 90% of youth sustained or developed strengths over time. Positive transitions were associated with mental health recovery, symptom reduction, and personal recovery. Buildable strengths supported youth’s personal recovery independent of improving mental health needs. The findings suggest that subgroups of strengths may be a promising source for planning and tracking youth’s progress and guiding clinicians to more efficiently allocate community-based resources. -
Karikari, I., Walton, B. A., Bishop, C., & Evans, P. (2021). State-Community System of Care Development: an Exploratory Longitudinal Review . The Journal of Behavioral Health Services and Research, 48(2), 240-258. https://doi.org/https://doi.org/10..1007/s11414-020-09702-8
In response to unmet mental health needs of children and youth, the system of care (SOC) value-based philosophy evolved into a framework to support equitable access to services. This longitudinal study explored the use of a standardized system of care instrument, the System of Care Implementation Survey (SOCIS), to inform planning and to monitor state and local SOC development in one mid-western state. Results measured state and local system development across fifteen related factors. Over time, system development remained at a mid-level, with an emerging foundation based on collaboration, endorsed SOC values, family involvement, individualized treatment, governance, and leadership. Significant fluctuations appeared in factors as systems worked through restructuring and clarifying implementation processes. Further research is suggested to better understand the complexities of SOC development in order to support effective behavioral health services and supports for children, youth, and families.
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Walton, B., Walton, B. A., & Walton, B. (2020). Addressing Specialization and Time to Enhance Adult Learning: Workshop Participants’ Perceptions. Professional Development: The International Journal of Continuing Social Work Education, 23(1), 15-26.
Interdisciplinary workshops trained and supported supervisors and coaches to implement common assessment tools in practice across social service sectors. By applying adult learning, learning transfer, and situated learning theories, this qualitative study elicited perceptions of trainers and trainees to identify improvement training and technical assistance strategies. Ten semi-structured interviews were completed. Using thematic analysis, six themes emerged (specialization, time, engagement/interest, content, marketing, and technology). Specialized training for experienced adults helped match new knowledge and skills to practice. Addressing time constraints of busy professionals required consideration of participants’ availability and training duration. Consistent with applied theories, suggestions for improvement included interactive training, small group discussions, realistic examples or vignettes, and helping participants comprehend the importance of the content. The creative use of technology, pre-training need assessment, reflexive practice, and supportive organizational factors can be helpful to advance continuing education in social service professions. Utilization of suggestions to modify workshops improved engagement and the transfer of knowledge to practice.
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Walton, B. A., & Kim, H.-W. (2018). Refining a Recovery Measure for Adults with Behavioral Health Challenges: An Exploratory Factor Analysis. Journal of Social Service Research, 44(2), 249-265. https://doi.org/ 10.1080/01488376.2018.1442897
Increasingly, social workers and behavioral health practitioners use assessment instruments to support service planning and to monitor progress. Following statewide implementation of the Adult Needs and Strengths Assessment (ANSA) to identify behavioral health symptoms, related functional challenges, risks, and strengths, this validation study explored the underlying structure of the instrument. An exploratory factor analysis used routinely collected information for Midwestern adults with diagnosed behavioral health disorders who participated in community-based services (N D 46,013). Five factors with adequate to good internal consistency (a D 0.733¡0.880) emerged: personal recovery, trauma and stress related problems, substance use risks, self-sufficiency, and cultural-linguistic considerations. Validation of the ANSA supports use of the instrument to engage individuals and families, to plan services, to monitor progress, and to conduct research. Implications for social work education, supervision, and practice include the importance of understanding culture, holistic assessment, and services supporting personal recovery for individuals living with mental illness or substance use disorders. Confirmation of findings requires additional research. The article was published online in March 2018 and then appeared in the next published journal edition.
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Quiroga, C. V., & Walton, B. A. (2014). Needs and Strengths Associated With Acute Suicidal Ideation and Behavior in a Sample of Adolescents in Mental Health Treatment: Youth and Family Correlates. Residential Treatment for Children and Youth, 31(3), 171-187. View Publication For Needs and Strengths Associated With Acute Suicidal Ideation and Behavior in a Sample of Adolescents in Mental Health Treatment: Youth and Family Correlates
This study examined a comprehensive set of adolescent and family needs and strengths associated with acute suicidal ideation and/or behavior among youth using mental health services in
Indiana (U.S.). Youth (n = 3292) were assessed with the Child and Adolescent Needs and Strengths questionnaire. Findings revealed that mental health issues (depression, psychosis) were the most
important cofactors of acute suicidal ideation and/or behavior, followed by high-risk behaviors and psychosocial adjustment (nonsuicidal self-injury, harmful behavior, aggression, sleep disruption),
and strengths (optimism). Family and caregiver needs
were not significant predictors after controlling for other variables. Prevention and outpatient treatment among adolescents should encompass a wide array of individual needs and strengths. -
Moore, M., & Walton, B. A. (2013). Improving the Mental Health Functioning of Youth in Rural Communities. Contemporary Rural Social Work, 5, 85-103.
Disparities in mental health outcomes for youth are often found between rural and urban areas. As part of an overarching question about under what circumstances and for whom, the wraparound process is beneficial (Suter & Bruns, 2009), this study specifically examined whether high fidelity to the wraparound model helped bridge the gap between outcomes in urban and rural areas for youth with complex behavioral health challenges. Youth participating in Indiana’s Community Alternatives to Psychiatric Residential Treatment Facilities Medicaid demonstration grant between 2008 and 2011 (n = 811) resided in urban (n = 615) or rural (n = 196) communities. Logistic regression examined treatment and contextual predictors of improvement in the mental health functioning of youth. High fidelity to the wraparound model and higher levels of initial behavioral health symptoms predicted improvement in mental health outcomes, with a small, but significant effect size (R2 = .129). Geography, demographic characteristics, initial risk behaviors, nor functional needs were significant predictors of change. Effectively implementing the wraparound process is a feasible strategy to reduce disparities in behavioral health outcomes for youth with complex needs in rural communities.
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Effland, V., Walton, B. A., & McIntyre, J. (2011). Connecting the dots: Stages of implementation, wraparound fidelity, and youth outcomes. Journal of Child & Family Studies, 50(2), 736-746. https://doi.org/10.1007/s10826-011-9541-5
Several necessary system and organizational support conditions for wraparound have been identified (Walker et al. 2003). Yet, the relationship between these necessary system level conditions and wraparound fidelity has only recently begun to be examined. Similarly, few studies have included a measure of wraparound fidelity when examining the relationship between wraparound implementation and youth outcomes. The statewide implementation of a wraparound demonstration grant offers the opportunity to explore these relationships and to identify factors that predict improvement in functioning for youth receiving wraparound. Findings suggest that significant relationships exist between (1) the stage of development of necessary support conditions for wraparound and wraparound fidelity and (2) wraparound fidelity and improvement in youth outcomes. Specific elements of wraparound (i.e., outcomes based and community based) and baseline needs and strengths (e.g., high levels of anxiety and conduct issues, poor functioning at home and in school, judgment, and risks) were found to predict a reduction in youth needs. Other unexpected relationships between youth outcomes and the cultural competence element of wraparound and being multi-racial were also discovered. These findings reinforce the importance of supporting high fidelity wraparound for youth and their families in a recovery focused behavioral health system.
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, I. K., Walton, B. A., Ludeker-Seibert, K., & Riley, K. Examining the emergence of a learning collaborative: A framework to support complex program implementation. Social Science. Accepted.
To address unmet behavioral health needs of children and youth, the system of care (SOC) philosophy was developed and evolved into a framework to support community-based coordinated networks that provide an array of effective services and supports. There is a limited elaboration of the actual implementation processes and intricacies of SOC development, particularly, in terms of the roles of local SOC coordinators. Limited published research has addressed the necessary knowledge and roles of local coordinators, and the theoretical underpinnings and structure of their learning, skill development, and capacity building.
Utilizing an archival approach and reflexive thematic analysis, this qualitative study examined records of three forums involving 50 local SOC coordinators(11% male, 89% female, 93% white, ages between 27 and 66 years) between 2017 and 2018.
The analysis revealed varying levels of experience, knowledge, and skills, and uncovered several SOC development strategies utilized by coordinators. The study illustrates the inception of a learning collaborative that served a a bridge and implementation driver for SOC development and socio-professional support for local coordinators.
The findings provide an empirical base and emerging framework for SOC coordinator training and professional development. The value of learning collaboratives in facilitating exposure to a diverse knowledge base and the importance of fostering supportive spaces for coordinators as they strive to develop SOCs are evident. Incorporating supportive learning collaboratives for local change agents could be a dynamic strategy to support the effective implementation of system-wide changes or enhancements in behavioral health services.
Presentations
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Hong, S., Walton, B. A., & Kim, H.-W. (2024). The mediating roles of psycho-social strengths to substance use disorder treatment completion. Society of Social Work and Rearch, Washington , DC United States.
Introduction: Research on substance use disorder (SUD) treatment dropout has highlighted the adverse impact it can have on clients, including legal and financial issues, relapse, and unfavorable physical and behavioral health conditions. Previous research has identified the factors associated with higher completion rates for adults with SUD, such as the type of substance, education, employment status, health insurance, and referral source. However, little research has examined the interrelationships, including direct and indirect/mediation effects, among legal system involvement, psycho-social factors related to person-level strengths, improvement in behavioral health needs, and SUD treatment completion. Therefore, the main purpose of this study is to examine direct and indirect effects among measured variables, latent variables, and their underlying structures of SUD treatment completion.
Methods: Using a statewide sample from one Midwestern state, we identified 3,627 young adults (aged 18-25; 83.2% Whites; 4.7% Hispanic; 62.5% lived in urban areas) receiving publicly funded behavioral health services. Thirty percent of young adults were referred by the court/justice system. We compared the treatment completion of these young adults to those who were referred by sources other than the court/justice system, including individual/self-referral, referral from Child Welfare/Department of Child Services, Health Care, and other community referrals. In addition, thirty-three percent of young adults used opioids as a primary, secondary, or tertiary substance in SFY 2021.
We conducted a logistic regression model to examine the unique associations of gender, race/ethnicity, urban/rural residence, psycho-social strengths, court/justice system involvement, opioid use disorder, behavioral health needs improvement, and SUD treatment completion. We then applied structural equation modeling (SEM) to detect the mediating role of psycho-social strengths in behavioral health needs improvement that led to SUD treatment completion.
Results: Using MLE in AMOS 28, the logistic regression model identified unique associations of legal system involvement, strengths, and improvement in behavioral health needs with SUD treatment completion. The SEM estimation terminated normally within the default convergent criterion (Chi-square = 95.203, df = 12, p = 0.000; RMSEA = 0.044, CI = (0.036, 0.052); CFI = 0.97; TLI = 0.923), and these model fit values exceed the criteria recommended by Hu and Bentler (1999), confirming that positive attributes in strengths mediate the effect of court/justice involvement and improvement in behavioral health needs that lead to SUD treatment completion.
While there were significant differences in completing SUD treatment between White and Black participants, the SEM model confirms that legal system involvement and the mediating role of strengths were critically important in detecting improvement in behavioral health needs and SUD treatment completion, regardless of race. Psycho-social factors related to strengths include social connectedness, optimism, job history, and resilience.
Based on these results, implications for counseling practice and future research are discussed.
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Walton, B. A., & Hong, S. (2024). Exploring cultural identity from a strengths perspective: Implications for social work practice. University of Southern Indiana School of Social Work, Evansville, IN United States.
Following a brief discussion of the strengths perspective’s benefits in recovery (Hong et al., 2021; Rapp & Sullivan, 2014; Rapp & Goscha, 2012), we will explore cultural identity as a strength. Reflecting membership in and support from a social group with specific values, practices and norms (Heersmink, 2021), cultural identity includes, but is not limited to, age, generation, religion/spirituality, gender identity and expression, race and ethnicity, language, profession, class, nationality, rural/urban residence (Heersmink, 2021; Harris et al., 2024). Therapeutic approaches have evolved to a multi-cultural approach, focused on professional development and cultural humility. As social workers, being aware of one’s own cultural identity and curious about/respectful of others’ is consistent with ethical principles (NASW, 2021), enhances relationships, and supports effective practice. In this interactive workshop, participants will have the opportunity to discuss the role of strengths in recovery, explore their own multi-cultural identity, and discuss how cultural identity is related to social work practice.
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Hong, S., Walton, B. A., & Kim, H.-W. (2023). The impact of faith-driven substance use disorder treatment on treatment completion success. American Public Health Association, Atlanta , GA United States.
Background
§Previous research has explored various individual, environmental, and treatment-related factors associated with SUD treatment completion, including age, gender, race/ethnicity, employment status, social support, motivation for treatment, and treatment type. §Additionally, characteristics of the treatment setting, such as evidence-based practices and barriers to treatment, can affect completion rates. §However, research evaluating the impact of a faith-driven approach on SUD treatment completion is limited.
Study Aims
This study aimed to examine the intersections of faith, psycho-social factors, and SUD treatment outcomes in community-based outpatient settings.
Methods
Study Sample. Using a statewide sample in one Midwestern state, we identified 2,909 young adults (aged 18-25) who participated in publicly funded outpatient-based substance use treatments. They completed the Adult Needs and Strength Assessment (ANSA) and National Outcome Measures (NOMS), which track individual-level behavioral health needs, strengths, and psycho-social factors, in State Fiscal Year 2021.
Faith refers to the individual’s experience of receiving comfort and support from religious or spiritual involvement using an item named spiritual/religious strengths in ANSA.
Measures. ANSA is a comprehensive assessment of psychological and social factors designed to support decision-making and monitor functional change and strength development (Lyons, 2022; Hong et al., 2023a). NOMS tool includes questions about housing stability, education, employment, criminal justice status, and the primary/secondary/tertiary substance
Analysis
The Chi-square Automatic Interaction Detection (CHAID) was employed to examine intersections of faith, psycho-social factors, and SUD treatment completion. Specific variables include gender, race/ethnicity, types of substances used, behavioral health-related strengths items, and other demographic information. And the data were divided into a training set and a testing set, using an 80% and 20% split, respectively.
Findings
The CHAID analysis depicts the intersections of faith, natural supports, volunteering, job experience, talents/interests, education, resourcefulness, optimism, resilience, type of substance, and Total Actionable Items Improvement Rates (TAI). Faith was associated with positive psycho-social factors.§No intersections of faith, gender, race/ethnicity, and justice system involvement. §The prevalence rates of individuals with faith were significantly different between non-opioid use disorders and opioid use disorders. Faith exhibited a negative association with TAI, the most significant predictor of SUD service completion.
Conclusions
A notable gap exists in the current literature concerning faith-based clinical strategies to enhance SUD treatment outcomes in publicly-funded behavioral health services. §Additional research is necessary to develop and implement faith-based SUD treatments or interventions that align with the behavioral health needs of individuals with SUD, ultimately increasing the likelihood of successful outcomes of SUD treatment.
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Lipsey, A. D., Hong, S., Walton, B. A., & Kim, H.-W. (2023). A Machine Learning-Informed Young Adults Substance Use Treatment Outcomes by Race and Ethnicity. College of Public Health, University of Kentucky, Lexington, KY United States.
Background
Race and ethnicity have been found to impact substance use disorder (SUD) recovery, plus age, employment status, type of substance, and referral source. Generally, socioeconomic factors moderated these trends. However, knowledge gaps remain to inform and improve treatment completion rates and outcomes for people of color. §This study builds on related, and recent strengths-based studies to consider the role of protective factors (strengths) on SUD treatment completion and outcomes.
Study aims to enhance the knowledge and understanding of the racial/ethnic disparities in SUD treatment outcomes with the application of machine learning (ML) methods.
Inclusion & Exclusion Criteria
The inclusion criteria were: 1) Studies published in English; 2) Studies involved substance use treatment as the major outcome measures; 3) Studies used ML for feature extraction and selection; 4) Studies came from PubMed database. The exclusion criteria were: 1) Studies used only White participants; 2) Studies used regression models as statistical models, instead of extended regression models in ML; 3) Studies used factor analysis as statistical models, rather than dimensionality reduction models in ML; 4) Review articles; and 5) Studies measured only Tobacco usage.
Systematic Review Process
The review of the literature published in PubMed was conducted, using the synonyms of "Substance-Related Disorders,” "Machine Learning," "Racial Groups," and "treatments.” Search results yielded 27 articles. An additional 6 articles were added via the snowball method. Of those 33 articles, 17 didn’t relate specifically to our topic, so review includes 16 articles though 2 were not retrieved.
Conclusions
* Racial and ethnic disparity in SUD treatment outcomes continues.
* Research on SUD treatment completion consistently highlights the negative consequences linked to treatment dropout, encompassing legal and financial challenges, relapse, and adverse physical and mental health outcomes.
* During the pandemic years, it has also noted a significant increase in both SUD treatment admissions and dropout rates.
* A notable gap exists in the current literature concerning evidence-based clinical strategies aimed at mitigating SUD treatment dropout in publicly-funded behavioral health services.
* These strategies involve informed clinical decisions guided by machine learning-driven algorithms, utilizing real-time behavioral health assessments and diverse cross-system individual-level data.
*Further research is needed to develop and implement a tool that aids behavioral health practitioners in making clinical determinations that ultimately bolster the probability of successful completion of SUD treatment.
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Hong, S., Walton, B. A., Kim, H.-W., & Moynihan, S. (2023). Combining ANSA with Other Administrative Data to Predict Treatment Completion for Young Adults Who Use Opioids: A CHAID Analysis. College of Public Health, University of Kentucky, Lexington, KY United States.
Despite efforts, the opioid use crisis continues, with about 3% of the US adult population misusing opioids (SAMHSA, 2022). Service systems are using data to identify risks (Brandt, 2020). Research has operationally defined progress as service completion and/or improved functioning. However, few related studies have utilized assessment information. To better understand outpatient treatment completion for young adults who use opioids, we added protective factors that could lead to successful treatment completion.
Using a statewide sample in one midwestern state, we identified 2,286 young adults (aged 18-25) who used opioids as a primary, secondary, or tertiary substance in SFY 2021. We compared the treatment completion of these young adults to young adults who used problem substances other than opioid use (N=6,714) that, included alcohol, cocaine, marijuana, methamphetamine, benzodiazepines, or other drugs.
All analyses were conducted with IBM SPSS Modeler and SPSS Statistics. The chi-square automatic interaction detection (CHAID) approach was used to predict treatment completion. The independent variables were ANSA strengths, National Outcome Measures, TEDS, and demographic data. Preliminary findings found association patterns of treatment completion with resourcefulness, optimism, social connectedness, community involvement, family strengths, source of referral, natural supports, talents/interests, job history, and employment status.
During the session, participants will be engaged by using a digital app (e.g., kahoot.com) to identify ANSA strengths and other factors that could be related to treatment completion. In addition to being introduced to CHAID decision tree analysis and findings, they will be engaged in discussing the implication of the findings for direct practice, program development, and policy. Their views on the likely relationship between treatment completion and improved functioning will be solicited. We will encourage feedback about the analytical approach.
Disclosure: The study was funded by an Indiana University Challenge SUD Grant and the Indiana Division of Mental Health and Addiction.
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Hong, S., Walton, B. A., YI, E.-H. G., & Kim, H.-W. (2023). Behavioral Health Needs of Middle-aged and Older Adults Living in Poverty: Machine Learning-Based Predictive Models. Socieity for Social Work and Research (SSWR), Pheonix, United States.
Abstract
Background. Growing evidence revealed behavioral health (BH) service needs for older adults (WHO, 2020; Webb, 2020; Novotney, 2019). However, the BH service needs and use of older adults living under 200% of poverty (42%; Cubanski et al., 2021) remained understudied. To develop contextually sensitive and effective services for older adults living in poverty, this study aimed to identify the characteristics and patterns of older adults’ BH service needs compared to those of middle-aged adults.
Methodology. This study used one Midwestern state’s 2019 publicly funded BH administrative data. A sample of adults aged 55 and older got involved in the publicly funded statewide behavioral health services (total N=8,071; middle-aged adults [aged 55 to 64]: N= 6,313, older adults [aged 65 to 74]: N=1,758). A balance node provided by SPSS Modeler was used to correct imbalances between the two groups (aged 55 to 64 [N= 6,313] and aged 65 to 74 [N=6,307]). Adult Needs and Strengths Assessments (ANSA; Lyons, 2009) were completed to facilitate care planning and to monitor outcomes in State Fiscal Year 2019 and initial assessments were completed within three years (2017 thru 2019). A chi-square automatic interaction detection (CHAID) model was used to detect the relationship between Behavioral Health needs (BH) and age group. The CHAID analysis divided data into training (80% out of the balanced sample) and testing (20%) datasets to test the model.
Findings. Findings can be interpreted by consider the significance of specific variables and intersectionality patterns characterizing older adults and individuals 55 to 64 with behavioral health needs. Employment needs, the most statistically important predictor may reflect retirement status. Although CHAID trees appears branches out from employment to criminal justice involvement, trauma adjustment emerged as the second most important factor predicting the age group. For example, for individuals without employment or legal issues, the presence/absence of trauma related needs framed complex patterns of functional/health needs for 52% of the sample. In the presence of trauma related needs, caregiver’s involvement in care needs were associated with physical health issues, disability, ability to care for themselves and make decisions were more likely for older adult (14% of the sample). In the absence of trauma, having a disability and social functioning status characterized 17% of the sample. Middle-aged adults were more likely to experience anxiety.
Discussion. Although the predictors were not new, different patterns of intersecting behavioral and physical health, functional conditions have practice, policy, and research implications. Instead of considering older adult behavioral health care as similar for all individuals, the need for trauma-informed integrated health care and specialized services for older individuals involved in the criminal justice system is supported. Additional research, using both machine learning and traditional approaches, is needed to better understand middle-aged and older adults’ needs, strengths, and to improve social services supporting well-being and addressing needs.
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Hong, S., Walton, B. A., & Kim, H.-W. (2023). Young Adults with Mental Health and Criminial Justice System Involvement. SSWR, Phoenix, AR United States.
Abstract
Context. In 2020, 9.7% of young adults (18-25) experienced serious mental illness; 17% had a major depressive disorder and 12.2% had co-occurring mental health and substance use disorders (SUD; Delphin-Rittmon, 2021). In 2021, although 25% of young adults endorsed substance use disorders, they were less least likely to receive treatment (SAMHSA, 2022). Young adults with mental health needs experience increased criminal behaviors, peaking between ages 16 and 25 (Stoltenberg & D ’Alessio, 2007; Pullmann, 2010). The lack of support for young adults’ behavioral health needs has been related to further involvement in the justice system. McAra and McVie (2010) support diversion from the justice system.
In the state of Indiana, the third highest referral source for adult behavioral health services was the criminal justice system. However, little is known about individuals’ needs, challenges, and successes after young adults with behavioral health needs become involved in the justice system.
Research Questions
1 .What critical factors were critical in predicting dual behavioral health and justice system involvement for adults participating in publicly funded treatment and support services?
2. To what extent dual-system involvement was associated with behavioral health outcomes (TAI Reduction Rate)?
Methods. Using administrative data, young adults with dual involvement in publicly funded behavioral health treatment and the criminal justice system were identified by a legal basis of referral for treatment (National Outcome Measure) and current or a history of legal system involvement (Adult Needs and Strengths Assessment [ANSA, Lyons, 2009}). Data analyses included Data mining Approach: Chi-squared Automatic Interaction Detection (CHAID) & Classification and Regression Trees (CRT and Hierarchical Linear Regression with Dummy Codes.
Findings. In the CHAID analysis, the most important predictors of dual system involvement of young adults were anxiety, substance use, being male, depression, family income, resourcefulness, non-suicidal self-injurious behavior, eating disturbance, social functioning, and job history. The rate of recovery (decreased needs) was significantly related to being male, Black, or Hispanic, and to current or past justice system involvement.
Conclusions. Anxiety and Substance Use (SUD) were the top two strongest predictors of characterizing dual system involvement. Individuals with current dual system involvement experienced lower rates of clinical improvement (maybe because of hard to meet the unique needs of these adults or much more complicated needs). Further analysis is needed to better understand to support the recovery of young adults with dual system involvement.
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Walton, B. A. (2023). Data-Informed Social Work Practice from a Recovery Perspective. University of Southern Indiana , Evansville, IN United States.
Learning Objectives
Participants will be able to identify three principles or dimensions related to behavioral health recovery.
Participants will discuss how available information (data) is used in social work practice.
Participants will examine the implications of a practice-based program evaluation for direct practice, program management, and community support.
Abstract
Data-informed decisions utilize data as a second opinion, whereas data-driven decisions rely on data alone to decide the next step. Since many decisions are complex, considering the values underlying the data is important to make informed decisions. n behavior health recovery, a process of change during which individuals improve their health and wellness to reach their full potential, underlying principles focus on health, home, purpose, and community. Ten principles guide recovery: hope, person-driven, occurs through many pathways, holistic, supported by peers and allies, by addressing trauma, relationships, and networks, culturally based and influenced, involves individual, family, and community strengths and responsibility, and based on respect. Social determinants of health (SDH) and mental illness interact to increase risks.
In a social work conference workshop, from a recovery perspective, professional and lay participants explored how available data could be utilized in planning services, monitoring progress, managing services, and improving individual’s outcomes. Routinely used assessment data can be examined to monitor progress for individuals or groups of people. To identify and address outcome disparities by age, gender, race, ethnicity and/or geography, group reports can be disaggregated for specific subgroups. Program evaluation and information from external sources can also inform services, programs, and policies (e.g., National Survey on Drug Use and Health, research related to service access, SDH, and disparities).
Lastly, we reviewed a statewide practice-based program evaluation for adults (n = 12,614), who had completed behavioral health services. A hierarchical linear regression considered individual characteristics, interventions, involvement in recovery, and strengths as predictors of recovery. Recovery was defined as the rate of personal change (number of ever identified needs that interfered with functioning divided by number of resolved needs. After reviewing different reporting strategies, participants discussed the study’s implications for practice, program management, and community support. Participants utilized worksheets to take notes and complete small group activities.
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Walton, B., Walton, B. A., & Kim, H.-W. (2022). The intersection of gambling addiction recovery and mental illness: A machine learning approach. Society for Social Work and Research, Washington, DC.
Context. Given that a variety of gaming activities (i.e., casinos, TV and instant scratch lotteries, sports bettings) are growing, COVID-19 related stress is presenting a severe threat to worsen addictive behaviors (Håkansson’s et al., 2020). Since certain forms of gambling, like internet-based and other forms of gambling activities, could remain unchangeably available to these adults in the COVID-19 related confinement, special attention to the gambling addiction as consequences of the COVID-19 pandemic is needed. In this regard, the purpose of this study is to examine and identify intersectionality for gambling addiction recovery with mental health needs in a behavioral health system.
Methods. The sample of adults aged 18 and above who participated in Midwestern state-funded mental health and addiction services in 2019 and 2020 was selected. Their initial and most recent assessments among adults with the need for gambling addition treatment at the initial assessment were analyzed for the study (N=654). All participants were taken the Adult Needs and Strengths Assessment (ANSA; Lyons, 2009) as the last assessment in either 2019 or 2020, including six domains: (1) strengths, (2) life functioning, (3) cultural factors, (4) caregiver needs, and resources, (5) behavioral health needs, and (6) risk behaviors. This study focused on the ANSA 57 items and four demographic information (i.e., age, gender, race/ethnicity, calendar year). Each ANSA item was rated on a four-point scale, ranging from 0 (non-actionable) to 3 (immediate action required). These ratings were changed into non-actionable (0) and actionable (1) and were examined by a machine learning decision tree model, chi-square automatic interaction detection (CHAID).
Results. Findings presented the interaction with substance use, impulse control, resiliency, education, sexuality, caregiver involvement in care, sleep, employment, residential stability, and resourcefulness for the gambling recovery. The most significant predictor for gambling addiction recovery was substance use. Specifically, it means that white adults were more likely to present the gambling addiction recovery when they stayed clean from substance use and did not struggle with impulse control than their peers. In contrast, the current needs for substance use treatment, impulse control, and caregiver involvement in care were the major predictors that were preventing gambling addiction recovery. These predictors emerged as the most critical variables intersected with gambling addiction recovery upon repeated constructions of the decision tree. The overall accuracy, a percentage of correct predictions for the machine learning model, was 76.9%.
Conclusion and Implications. The findings suggest that staying clean from substance use and impulse control were primary predictors that led to gambling addiction recovery. The machine learning-based gambling addiction recovery model could be a promising approach to detect the intersection of race/ethnicity and behavioral health challenges and their recovery. It could eventually be a basis for the development of a gambling addiction recovery model for adults with needs for gambling addiction treatment at the initial assessment. Further research is also needed to explore the relationship between the identified intersection and other mental health illnesses. Such a relationship study will support the development of an efficient mental health and gambling recovery model.
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Walton, B. A. (2022). Program Evaluation: Examples, Considerations, and Implications. IUSSW, Indianapolis, IN United States.
With a group of macro gradulate student, I shared our team’s collaborative work with the state mental health and addiction authority to evaluate programs. Different types of program evaluations were shared and implications for practice/policy discussed.
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Hong, S., Walton, B. A., & Kim, H.-W. (2022). Recovery from problem gambling: A machine learning approach. SEOW, Indianapolis, IN United States.
Recovery from Problem Gambling: Intersection with Mental Illness, Strengths, COViD-19, Gender, Age, & Race
Method. Problem gambling (PG) was identified for 654 adults who entered behavioral health services in 2019 or 2020. We tracked whether PG improved or not during the year. Demographic and assessment data were from DARMHA, the Indiana Division of Mental Health & Addiction database. The assessment instrument was the Adult Needs and Strengths Assessment (ANSA; Lyons, 2009). A machine learning approach using decision trees predicted recovery from PG.
Results. Upon repeated decision tree constructions, improvement from PG was associated with substance use disorder (SUD), impulse control, education, race (white/non-white), resourcefulness, age, depression, anxiety, volunteering, and gender (male/female).
The most significant predictor for improvement from PG was SUD. Among adults without SUD (n=251), 72.5% recovered. For adults with SUD, only 37.8% recovered. Individuals without SUD were more likely to recover from gambling addiction when they were resourceful, older (over 36 years old), and White. In contrast, individuals with SUD, less than a high school education, and impulse control challenges were less likely to recover from problem gambling.
Model’s accuracy. The overall model accuracy was .798, which indicated that the model distinguished well between individuals improving from or sustaining PG.
Implications
Practice. The study highlights the importance of completing a holistic assessment with individuals that have PG. Identifying and concurrently addressing co-occurring disorders (SUD, impulse control, depression) could increase the likelihood of recovery. Adapting services to engage and support younger adults, people of color, and women in the recovery process is also suggested.
Research. The machine learning-based gambling addiction recovery model could be a promising approach to detect the intersection of race/ethnicity, behavioral health challenges, and improvement from problem gambling or other specific disorders. Further is needed to evaluate the effectiveness of concurrently addressing PG, behavioral health disorders, and adapting services to improve outcomes for diverse populations.
Policy. The results suggest that policy makers support evidence-based and best PG practices that concurrently address other behavior health needs and provide equitable treatment.
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Walton, B. A. (2022). Systems of Care. IUSSW, Indianapolis, IN United States.
Invited presentation regarding systems of care covered the origins, philosophy, practice model, and implementation across Indiana. Information about how to get involved locally or at the state level was provided.
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Walton, B. A. (2022). Supporting Behavioral Health Recovery for Adults in Rural Communities. School of Social Work at Stephen F. Austin State University, NACOGDOCHES, TX.
Context. In 2020, 21% of adults experienced mental illness; 5.6% experienced severe mental illness (SMI). Over 29% had mental illness or a substance use disorder (SUD); 2.2% had SMI and SUD (SAMHSA, 2021). Having SMI and SUD has been related to disparate service access (Priester et al., 2016). Social determinants of health (SDOH) may increase mental health risks, and serious mental illness increases the likelihood of poverty and other SDOH (Braveman et al., 2011; American…, 2019). Recovery includes independence and symptom reduction, emphasizing independence (Davidson et al., 2008; Insel, 2022; Lambden et al, 2018). Outcome disparities have been documented related to race, ethnicity, gender and geography (Andrykowski et al., 2014; Eack & Newheill, 2012; WHO, n. d.). It is time to move beyond identifying disparities to monitoring and addressing them. Related research questions: What factors predicted recovery? What are the implications for practice in rural communities?
Method. Using SFY21 administrative data from a Midwestern state, the sample (n = 6458) of treated adults with complex behavioral health needs ranged from 18 to 85 (mean age = 37.18; 52% female; 76.6% non-Hispanic white). Adult Needs and Strength Assessment (ANSA; Lyons, 2009) identified useable strengths and needs that interfered with functioning in four domains (Life Functioning, Behavioral/Emotional, Risks, and Cultural Factors). Including demographic and NOMS data added gender, age, race/ethnicity, educational level, and rural residence (identified by zip code [Hirsch, 2021]).
Recovery was operationally defined as the number of resolved needs (Total Actionable Items [TAI]; Cordell, 2016). Predictive variables were selected based on previous research and entered directly into a hierarchical linear regression (HLR) in four blocks: 1 (age, gender, people of color, rural, housing stability, transportation, education level), 2 (involvement in recovery, SUD recovery support, optimism, resiliency), 3 (anxiety, depression, eating disorder, interpersonal, SUD), and 4 (duration, cognitive behavioral therapy [CBT; Craske, 2020]).
Findings. All predictors significantly predicted functional recovery (Mean = 3.13 [3.819]). With the addition of each block, the model R2 increased (.041, .106, .143, and .319). Lower levels of recovery were experienced by adults who were younger, female, People of Color, had less than a high school education, lived in rural communities, not actively involved in recovery, and had inadequate SUD support, anxiety, depression, eating disorders, interpersonal difficulties, or SUD. Early identification of housing instability, transportation issues, being optimistic about the future, resiliency, longer duration of services, and CBT predicted better outcomes.
Discussion. Implications for direct practice include identifying and addressing SDOH, (e.g. housing stability, transportation [access] to services, and supporting involvement in recovery, actively planning and managing recovery. Use assessment and outcome information to collaboratively develop and intervention plans, manage programs, and to monitor progress. Adapt services to be culturally responsive, age and gender appropriate. Consider and address developmental tasks of young adults. Identify and utilize or develop strengths to address needs and support well-being. Implications for program evaluation/research include comparing the racial/ethnic profile of program participants with the community/state to identify and address service access issues.
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Walton, B. A., & Holland, S. (2022). Young Adults’ Recovery: Managing Change. Praed Foundation, New Orleans, LA.
Abstract
Informed by relevant literature and combined with demographic, assessment, educational, and service information, program evaluations can identify key factor to manage change. An example follows.
Background. Transition-aged youth (TAY), ages 18 to 26, have higher rates of Substance Use Disorders (SUD) than adolescents or adults over 26 years old. In 2019, 17% experienced a major depressive disorder with 12.1% having severe impairments. Overall, 30.6% experienced mental illness, and 9.7% had serious mental illness. Although TAY reported lower levels of recovery than older adults, predictors of behavioral health recovery for TAY have seldom been explored. Indiana’s Division of Mental Health and Addiction (DMHA) has funded TAY services since 2019 as an effort to positively impact this population.
Methods. Qualitative information from seven currently DMHA funded programs were to support and supplement data analysis. A FFY21 Midwestern sample (n=2575) of treated young adults (ages 18-26) included 688 People of Color (POC; 12% of the sample were Black only, 0.04% Native American only, 0.06% Asian only, 5% other race only, 3% Multiracial, and 6% Hispanic); 0.73% were White only. Half were female. All youth had substance and/or mental health disorders. The Adult Needs and Strengths Assessment (ANSA) identified needs that interfered with functioning and strengths. Transportation, employment, and residential needs were identified early in care. Other need and strength items reflected status when treatment ended.
In a secondary analysis of state-level data, a hierarchical linear regression predicted recovery, the rate of improved Total Actionable Items (Resolved/Ever identified needs). Predictive variables were directly entered into four blocks: 1 (race/ethnicity, gender, employment, transportation, housing stability), 2 (depression, anxiety, substance use [SUD]), 3 (involvement in recovery, SUD recovery support, social functioning, optimism), and 4 (duration of treatment, Motivational Enhancement Therapy [MET). Race was converted to POC and gender to ‘female’.
Results. Each step of the regression model documented significant contributions of added variables (R2s =.013, .239, .319, .350). POC were less likely to improve than white individuals. Women were more likely than men to improve. Individuals with employment, transportation, or housing needs at the beginning of treatment were more likely to improve. Depression, anxiety, and substance use disorders decreased the likelihood of resolved needs. Poor social functioning and inadequate SUD recovery support at the end of treatment were associated with worse outcomes. Having a positive sense of oneself in the future (optimism) predicted recovery. Active involvement in recovery, longer service duration, and Medication Enhancement Therapy were related to higher rates of recovery.
Discussion. In addition to addressing SUD and mental health concerns, young adults’ recovery is related to developmental tasks (employment, recreation, and social relationships), supporting involvement in managing one’s health, and developing resiliency. Attention to social determinants of health, such as transportation, is necessary for access to services and supports. Service adaptations for POC to increase involvement in recovery and equitable outcomes requires consideration and study. Managing change for TAY involves attention to developmental, cultural, behavioral health needs, the concurrent utilization/development of strengths, and monitoring progress.
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Walton, B. A., & Harrold, W. (2022). Collaborate, Review Data and Change; Repeat. Praed Foundation, University of Kentucky, New Orleans, LA.
Conference Proposal
Summary: Behavioral health Recovery and TCOM frameworks were integrated to inform state policy decisions utilizing recovery-related ANSA data. Strategies to manage policy changes (Recovery Support Workgroups, data integration and management, and the implementation process) and findings are discussed.
earning Objectives:
Upon completion of this educational activity, participants will be able to:
describe behavioral health recovery dimensions and principles and compare recovery and TCOM frameworks (ANSA items)
describe the collaborative infrastructure needed to identify, build, and support recovery services and monitor gaps in the system
interpret several ANSA outcomes reportsutilize ANSA recovery-related items to inform policy planning and to manage change
Context. 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?
Outline of presentation: (bullet points)
Welcome & introductionsLearning ObjectivesDiscuss recovery and share a crosswalk with TCOM/ANSA (invite input from participants)Explain the state’s recovery strategy and utilization of data to inform recommendations and policy decisionsShare the classification of ANSA items into Recovery Dimensions & other Concern (invite feedback)Discuss recovery data and provide examples of ANSA recovery reportsAddressing Equity. Introduce strategy to address missing recovery component (identifying and addressing disparities): disaggregating the recovery ANSA reports by age, gender, race/ethnicity, geography) Discuss recovery report/information dissemination and use (invite/encourage participants’ suggestions!)With participants identify (discuss) implications (for system level planning, policies, agency/program planning, direct practice, and to research/evaluation.utilize ANSA recovery items to inform policy planning and to manage change.
Target Audience for Presentation: State policy makers, providers who want to look at and develop recovery supports (clinicians, care coordinators, supervisors, program managers, administrators), researchers
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Hong, S., Walton, B. A., & Kim, H.-W. (2021). Examining the intersection of mental illness and suicidal risk in the shadow of a pandemic: A Machine Learning Approach. Praed Foundation, Center for Innovation & Population Health, University of Kentucky, Lexington, KY United States.
TCOM Conference Proposal_2021
To develop the suicidal recovery model for adults with mental illness during the pandemic and better serve them in the mental health system, it is necessary to ensure that we can identify the intersection of mental illness and suicidal risk. In Artificial Intelligence-based psychiatry, the progressive use of machine learning has been utilized to detect and monitor different mental health states and identify between the target response and a set of input features of interest (i.e., Garcia-Ceja et al., 2018; Tate et al., 2020). In this regard, we used machine learning to examine the intersection of mental illness and suicide among adults aged 18 and above who participated in the Midwestern state-funded mental health service (n=135,590) during the calendar years of 2019 and 2020. Classification, regression tree analyses, and chi-square automatic interaction detection (CHAID) were used to identify the intersection of mental illness and suicidal risk and determine their classification accuracy.
Findings included the convergence of several associations among variables of depression, trauma, interpersonal, impulse control, age, substance use, anger control, anxiety, and psychosis. Both depression and trauma emerged as the most important variables intersected with suicidal risk during the COVID-19 pandemic. The machine learning approach provides a better understanding of the associations between mental illness and suicidal risk. It could eventually be a basis for the suicidal recovery model among adults with mental illness.
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Walton, B. A., Kim, H.-W., Hong, S., & Kaboi, M. (2021). Once TCOM is Running, Consider Program Evaluation. Indiana University School of Social Work, Lexington, KY.
Once TCOM implementation is running, ANSA or CANS information can be used for program management and evaluation. This workshop will illustrate different approaches to program evaluation using ANSA and CANS data and related information. Whether in response to system level requests, a call for papers, or a timely issue, program evaluation can demonstrate the usefulness of TCOM tools in managing programs. Building upon existing research, two examples illustrate alternative strategies. For adults with co-occurring mental health and substance use disorders, social determinants of health, recovery, and service factors were examined as potential predictors of functional change (total actionable needs) using hierarchical linear regression. For children and youth with complex needs, the Medicaid wraparound program routinely used patterns of CANS data to predict program eligibility, as compared with program participation. Used to support hiring decisions and manage state programs, the evaluation was enhanced to compare differences between eligible, but not enrolled youth and program participants. Mixed methods included quantitative and qualitative approaches. For enrolled youth, predictors of improvement were informed by demographics, service duration, Medicaid claims, and CANS data.
To engage participants, depending upon group size, brief introductions with questions about program evaluation experience will open the workshop. They will be given a worksheet on which to note program evaluation ideas. Brief group discussion will follow to explore program evaluation opportunities for participants.
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Hong, S., & Walton, B. A. (2021). Predicted Mental Illness of Asian-American amid the COVID-19 Pandemic & Approaches to Treatment. Division of Mental Health & Addiction, Indianapolis, IN.
Given that jointly experiencing such violence and harassment and pandemic-related hardship can worsen the mental health of Asian Americans, this session’s primary purpose highlights patterns and changes in their behavioral health service utilization during the pandemic and to examine race-specific associations among identified behavioral health and functional needs items by using a decision tree algorithm for examining predictors of Asian American’s behavioral health service use, including culturally related stressors.
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Walton, B. A., & Kaboi, M. (2020). Child Mental Health Wraparound (CMHW) Evaluation Overview. Division of Mental Health & Addiction (DMHA), IN Family & Social Services Administration, Indianapolis, IN.
This evaluation utilized administrative data in a series of logistic regressions to examine functional improvement predictors for youth participating in the CMHW program during SFY2019 and SFY2020. Total CMHW Medicaid service cost during their enrollment, initial complexity and severity of youth’s needs, Gender Identity, and Age predicted the likelihood of improved Youth Needs. Higher CMHW program costs, which reflected engagement, intensity, and duration of program services over time, were significantly related to improved needs and strength development. Youth with more complex and dangerous or disabling needs at the beginning of the program were more likely to improve. However, female children and adolescents enrolled in CMHW were less likely to experience functional improvement or to build strengths in the program or in community-based mental health services. Older youth who received Inpatient, Community-based, and CMHW services were more likely than younger youth to benefit (experience improvement in Youth Needs). While reflected as part of significant Total CMHW costs, the impact of specific ancillary program services (Habilitation, Training and Support of Caregivers, and Respite) was indeterminate in this study. Additional research (e.g., analysis of detailed claims data over the course of each youth’s enrollment, adding fidelity information, and examination of factors related to youth who did not improve) is needed.
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Walton, B. A., Krompf, A., Howard, J., & Kim, H.-W. (2020). ANSA Roundtable. Praed Foundation, University of Kentucky, Louisville, KY.
This preconference workshop (3 hour) focused on stragies to implement and sustain utilzation of the Adult Needs and Strengths Assessment (ANSA) in a state or agency with examples from three states (Vermont, Illinois, Indiana). Emerging research related to the instruments psychometric priorites with transition age youth was introduced and discussed.
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Hong, S., Kim, H.-W., & Walton, B. A. (2020). Latent Transition Analysis of Strengths’ Pattern among Youth at Risk for Suicide Attempt. Praed Foundation, University of Kentucky, Louisville, KY.
Background: A better understanding variability in strengths of youth with mental health disorders is critical as a strength-based approach leads to mental health recovery. This study aimed to identify subgroups of strengths among youth with serious emotional disturbance and determine whether subgroups were changed during the mental health recovery process. Methods: Youth with serious emotional disturbance (N=2,405) from the statewide databsewere identified as having closed episodes of care in state fiscal year 2019. Latent Profile Analysis (LPA) at the beginning and end of episodes were administered to identify unobserved subgroups, and Latent Transition Analysis (LTA) examined tenability and trajectories of different latent classes at the end of an episode.
Results: These LPA results indicated that three strength profiles emerged for both the beginning of the service and the end of the service. The LTA results also highlighted that most youth, rated as either “Buildable Strengths" or "Useable Strengths," transitioned into a class of youth with useable strengths. However, surprisingly, 83% of youth in the "Centerpiece Strengths" latent class at the beginning of the service moved to "Buildable Strength" at the end of the service.
Conclusions: The majority of youth in either the useable or buildable strengths group at the beginning of the service had developed strengths in the positive direction over time. Thus, the findings suggested that subgroups of strengths may be a promising source to track youth’s progress and guide clinicians to allocate community-based resources more efficiently to improve specific strength areas.
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Walton, B. A. (2020). Identifying & Analyzing DARMHA Disparity Data. Division of Mental Health & Addiction, IN Family & Social Services Administration , Indianapolis, IN.
Administrative data can be used to:
•examine mental health service (MHS) utilization trends
•identify disproportionate MHS access
•monitor functional outcomes for clients and programs
•Identify disparate outcomes
•inform program and policy planning and to monitor progress
•monitor progress
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Walton, B. A., Kim, H.-W., & VanDyke, R. (2020). Mental Health Service Access: Use of Existing Data. Society for Social Work and Research , Washington, DC United States.
Conference Proposal
Mental Health Service Access: Use of Existing Data
Abstract
Background and Purpose. Although about 20% of children (ages 3 to 17) experience mental health disorders, only one in five youth receive specialized treatment. Without intervention, youth experience long lasting adverse effects. Barriers to service access include stigma, poverty, race/ethnicity, gender, and geography. Routine utilization of existing data could inform program and policy planning and monitor progress, but such information is seldom available. This study explored the use of administrative data to examine service utilization and to identify and address disparities in a midwestern state.
Methods. Access to mental health (MH) services was defined as utilizing publically funded mental health. Two types of existing data were evaluated: mental health block grant (MHBG) and Medicaid claims. Uniform Reporting System (URS) Client Level Data for transition age youth (TAY, ages 18-20) 2004-2016 trends were compared by gender and race/ethnicity. Child Medicaid behavioral health service utilization in 2014 was contrasted by age, gender, race/ethnicity, and language. Relationships among language, identification of MH needs, and service utilization were also explored.
Results. According to URS data, TAY youth’s utilization of MHBG funded services doubled then plateaued between 2013 and 2016. A pattern of more young women (55%) receiving services than men remained constant over time, although the 2015 census population estimates were similar. Disportionate access between white and non-white TAY decreased during a home and community based service grant (2008-2012).
Based on SFY14 Medicaid claims, MH needs were most frequently identified for 12-14 year old boys, but service intensity peaked for adolescents between ages 15 and 17. In contrast to MHBG data, more young men, ages 18-25, utilized MH services. After age 25, women more frequently utilized services. However, boys and men consistently received more MH services. MH service utilization by youth of color was lower than by Caucasian youth. A limitation of using administrative date emerged as language was missing for foster youth who had the highest level of Medicaid MH service utilization. Most young Medicaid members (90%) lived in English speaking households; other households primarily spoke Spanish (5%), Burmese, or other languages. Children in English speaking homes received more than twice the amount services compared to children in Spanish speaking homes. MH health needs for children were less often identified in the four largest urban counties than in smaller communities. In contrast to research, the intensity of MH services varied across urban and rural settings.
Conclusions and Implications. Consistent with research, this examination of administrative data found disproportionate identification of behavioral health needs and utilization of services by age, gender, race and ethnicity. Routine monitoring of existing data could help monitor MH service utilization and the impact of policy or programs on access to care. Gender differences between MHBG and Medicaid MH service utilization require further exploration. Additional research is needed regarding factors affecting geographic differences and the effectiveness of routinely using existing data to manage programs and inform policy.
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Karikari, I., Walton, B. A., & Bishop, C. (2019). Divergent Caregiver and Youth Perspectives Regarding Behavioral Health Needs and Psychosocial Functioning: An Exploratory Study. American Public Health Association, Philadelphia , PA United States.
To promote effectiveness in behavioral health treatment, the system of care framework and wraparound model accentuate the inclusion of families and children/youth as important stakeholders, not just as consumers. This has changed conventional practices; and youth and caregivers’ perspectives have become integral to treatment planning and delivery. This study explored caregivers and youth’s perspectives of behavioral health needs and psychosocial functioning. This exploratory study utilized data collected in a Midwestern, Suburban County as part of the national Child and Family Study of children/youth with complex behavioral health needs enrolled in the Child Mental Health Wraparound Initiative (CMHW). The sample consisted of 25 caregiver-youth pairs. Measures of assessment included the Pediatric Symptom Checklist (PSC) and the Columbia Impairment Scale (CIS). Independent t-tests were used to examine differences in caregiver and youth perspectives. Significant differences were identified in caregivers and youth’s perspectives of youth’s behavioral health based on the PSC measure, but no significant differences between caregivers and youth on the CIS measure. Responses showed that compared to youth, caregivers perceived a higher level of functional impairment in interpersonal relationships, academic, and community functioning. Further, caregivers’ views of the severity of functional impairment varied based on the type of biological relationship with the youth. Divergent perspectives of youth and their caregivers of youth’s behavioral health needs and psychosocial function have implications for behavioral health treatment planning and service delivery. Additional research is needed on collaborative assessments. The need to strengthen the evidence base for treatment models remains paramount.
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Walton, B. A., & Kim, H.-W. (2019). Co-occurring Substance Use and Mental Health Needs: Enhancing the ANSA to Manage Services. Praed Foundation, University of Kentucky, Palm Springs, CA United States.
Co-occurring Substance Use and Mental Health Needs: Enhancing the Adult Needs Strength Assessment (ANSA) to Manage Services
Abstract
Background. Substance use disorders (SUD) are common, affecting one in 25 adolescents (ages 12 -17), one in seven young adults (ages 18 to 25), and one in 16 adults (ages 26 and older) during 2017. 1 While 16.7% of adults without SUD experienced mental health (MH) disorders, 45.6% of adults with SUD experienced co-occurring MH disorders.1 Related research found much higher rates of adults with MH or SUD disorders (50-75%) have co-occurring disorders. 2, 3, 4, 5 Co-occurring MH and SUD make treatment more difficult, increase use of health resources, and interfere with individuals’ life functioning.2, 3, 4 In response to the opioid crisis, SUD treatment funding and services are expanding. Effective treatment requires identification of co-occurring disorders (COD). The goal of this study was to examine how well practitioners assess and identify COD in practice.
Emerging questions. 1. Using the Adult Needs and Strengths Assessment (ANSA, Lyons, 2009), what is the rate of identified actionable co-occurring disorders (COD) - SUD and mental health disorders – for young adults in substance use and in mental health treatment? 2. How much did young adults with COD improve over time?
Evaluation Methods. We analyzed existing state ANSA data and outcome reports to compare rates of identified COD for young adults. Through the lens of young adults participating in SUD or MH treatment, we also explored different approaches to measuring change over time with the ANSA: resolved needs, building strengths, clinical progress (getting better), and reliable change in one domain.
Results. Consistent with the literature, for young adults participating in SUD treatment, 55.4% had COD. In contrast, only 16.9% of young adults involved in mental health specialty treatment had identified COD. Yet, consistent with research, about 50% of young adults with psychosis had co-occurring SUD.5 Outcome reports were disaggregated to identify outcome disparities by gender. Across commonly identified needs, men experienced more improvement than women in the areas of resolved substance use (22.7% versus 17.69%), legal involvement (7.19 % versus 4.62%), and recent criminal behavior (7.88% versus 6.86%). Men also improved anger control (2.84%), social functioning (7.19%), and involvement in recovery (4.11%). Women were more likely than men to improve decision making (11.66% versus 9.88%) and experienced improved family functioning (5.74%) and recreational activities (9.29%). Implications. Statewide, COD was identified through the ANSA at expected rates in most SUD treatment settings.1, 4 Significantly lower rates of identified COD in MH treatment settings documented the need for better substance use screening, assessment, and focused quality improvement initiatives. Disaggregating outcome reports identified different need profiles and disparate outcomes by gender. Developmentally-appropriate, individualized behavioral health services for young adults will improve engagement, assessment and outcomes. 6, 7
References
1Substance Abuse and Mental Health Services Administration. (2018). Key substance use and mental health indicators in the United States: Results from the 2017 National Survey on Drug Use and Health (HHS Publication No. SMA 18-5068, NSDUH Series H-53). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Retrieved from https://www.samhsa.gov/data/
2Mee-Lee, D., Shulman, G.D., Fishman, M.J., Gastfried, D.R., Miller, M.M., & Provence, S.M. (Eds.) (2013). The ASAM criteria: Treatment criteria for addictive, substance-related, and co-occurring conditions, 3rd Edition. Carson City, NV: The Change Companies.
3Bergman, B. G., Greene, C., Slaymaker, V., Hoeppner, B. B., & Kelly, J. F. (2014). Young adults with co-occurring disorders: Substance use disorder treatment response and outcomes. Journal of Substance Abuse Treatment, 46(4), 420-428.
4Wustfhoff, L. E., Waal, J., Ruud, T., Roislien, J., & Grawe, R. W. (2011). Identifying co-occurring substance use disorders in community mental health centres. Nordic Journal of Psychiatry, 65(1), 58-64.
5Hawke L.D., Koyama, E., & Henderson, J. (2018). Cannabis, other substance use, and co-occurring concerns among youth presenting for substance use treatment services: Sex and age differences. Journal of Substance Abuse Treatment, 91, 12-19.
6Priester, M.A., Browne, T., Lachini A., Clone, S., DeHart, D., & Seay, K.D. (2016). Treatment access barriers and disparities among individuals with co-occurring mental
7Logan, D. & Mullen, M. (2018). Strategies for engaging young adults. Strewsbury, MA: University of Massachusetts, Systems and Psychological Advances Research Center (SPARC).
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Walton, B. A. (2019). Monitoring Outcome Disparities. Indiana Division of Mental Health & Addiction, Noblesville, IN United States.
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Walton, B. A. (2019). Young adults with co-occurring disorders: Identification and outcomes. Indiana University School of Social Work, Indianapolis, United States.
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Karikari, I., Walton, B. A., & Christine, B. (2019). Future direction for child mental health: Developing a blueprint using the system of care framework. University of South Florida, Tampa, FL United States.
Behavioral health problems can be tied to impacts on life functioning and difficulty with regard to receiving effective treatment. In order to help clients effectively when it comes to evaluation and quality improvement, a joint effort is needed at system, program, and direct levels. In Indiana, a Wraparound program and System of Care are utilized to support children and families struggling with the aforementioned issues. The development of the state’s System of Care and its residents’ behavioral health outcomes have proven to have made great strides, due to routine evaluation and making necessary adjustments when deemed appropriate. This presentation includes multiple charts/graphics (via descriptive statistical analysis and independent sample t-tests) that demonstrate the strides that have been made in multiple behavioral health domains throughout the state within the past several years.
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Walton, B. A., & Moynihan, S. (2018). Developing Effective Cross-System Training. University of Maryland School of Social Work, Washington , DC United States.
Cross-system training is often suggested as a strategy to increase knowledge and skills across systems and agencies that provide services to children, youth, and families. This poster describes strategies to develop and improve training and to support the effective implementation of assessment and outcome management tools in behavioral health and behavioral health systems. Analyses of cross-system workshop evaluation ratings and comments identified challenges and later documented improvement in workshops’ perceived impact on behavioral health and social service practice.
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Walton, B., Kivisto, K. L., Wall, J., Maureen, M., & Beryl, C. (2018). Academics Panel/Questions. Indiana Association of Resources and Child Advocacy (IARCA), Indianapolis.
Invited panelists were asked to respond to a series of questions regarding role of research in shaping outcome measures design and implementation, impact of the Family First Act, ethical challenges, and suggestions about overcoming resistance or ambivalence to outcome programs. Panelists presented information and engaged in discussion with conference participants. There was no slide presentation.
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Walton, B. A., & Harrold, W. (2018). Use of person-centered information for planning, monitoring progress, and for evaluation/research,. Chapin Hall, University of Chicago, Chicago, IL United States.
Converting practice-based data into information that informs person-centered care, programs, organizations, and system level management is a core TCOM concept. Infrastructure is necessary (training, certification, technical assistance, local coaches, outcome reports, and quality improvement initiatives). Resulting data, viewed in the context of identified issues, becomes useful information. Real world examples from a multi-system, statewide implementation illustrate the potential use of CANS and ANSA information to address direct service and management challenges. Administrative data (demographic information, NOMS, living environment, assessment ratings, diagnoses, and service data) can provide a platform to identify specific service needs, monitor availability, and inform policy. Examples include combining data to estimate the need for a specific service, availability, utilization, and outcomes. Increasing funding for substance use services required a specific SUD decision model to support service planning. Interim initiatives help develop a culture of using person-centered information to help manage services and to develop policies.
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Karikari, I., Walton, B. A., & Garry, C. (2018). A longitudinal review of systems of care (SOC) development: A case study from the mid-west. University of Maryland School of Social Work, Washington , DC United States.
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Walton, B. A., Karikari, I., Tock, E., & Gerry, C. (2018). Knowledge Diffusion and Utilization within a System of Care Model: Successes and Challenges. University of Maryland School of Social Work, Washington , DC United States.
The workshop focuses on how to transition from collecting required grant data to supporting a culture of using information for planning and quality improvement processes at direct service, program, and system levels. The strategies to be highlighted are measuring, assessing, and communicating information about needs, resources, service gaps, progress, and outcomes. Successful use of information depends upon building a common vision, consensus, and trust among state system teams, service providers, youth and families, advocates, and other stakeholders. The highlighted workshop is based on the work and experience of the Indiana state system of care implementation and evaluation teams.
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Walton, B. (2018). Benefits of family and youth involvement in systems of care. Division of Mental Health & Addiction, Indiana Family & Social Services Administration, Indianapolis, IN.
At the request of the Family and Youth Subcommittee of the Indiana state SOC, a study examined evidence of the benefit of family and youth involvement in systems of care. In addition to a literature search, an analysis of data from the IN SOC evaluation identified factors predicting local access to home and community services coordinated through a wraparound process. The Family Committee utilized the study to support their technical assistance to local SOCs.
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Walton, B. A., & Isaac, K. (2018). Telling Your Story. Indiana Division of Mental Health & Addiction, Noblesville, IN United States.
Discussion engaged system of care (SOC) coordinators and state SOC implementation partners in using information to plan activities, to monitor progress, and to modify plans. Relationship of access to effective behavioral health services for children, youth, and their families to level of SOC development was highlighted. While experienced SOC partners were aware of the significance, the was a new concept for some newer coordinators.
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Dunn, B., Walton, B. A., Bowlin, W., Accomazzo, S., Short, R., & Israel, N. (2018). National CANS Analysis of Wraparound: Site Level Discussion into Compelling Questions. University of South Florida, Tampa, FL United States.
Child mental health problems are common, affecting about 20% of children and youth, but only about one-third receive treatment (Institute of Medicine & National Research Council, 2009; SAMHSA, 2017). In addition to systems of care philosophy (Stroul & Freidman, 1986, 1994), two practice frameworks emerged: Wraparound Care Coordination (Schurer Coldiron, Bruns, & Quick, 2017) and Transformational Collaborative Outcome Management (TCOM, Lyons, 2017; Lyons & Weiner, 2009; McGill, 2015). Within each practice model, tools support implementation (e.g., training and certification, fidelity measures, and instruments). Both wraparound (Schurer Coldiron et al.) and TCOM’s Child and Adolescent Needs and Strengths (CANS, Lyons, 2009; Lyons & Walton, 2008) assessment are widely used, often within the same programs (Bruns, Schurer Coldiron, & Hensley, 2017). In 2014, SAMHSA funded a wraparound-CANS benchmarking study. In response to an invitation from the Praed Foundation and the Wraparound Evaluation and Research Team (WERT), 12 states or jurisdictions shared CANS and related data with WERT. WERT shared interim findings at annual conferences (Bruns, Schurer Coldiron, & Hensley, 2016; Schurer Coldiron et al.; Schurer Coldiron, Hensley, Bruns & Parigoris, 2016). As a continuation of that study, this symposium responds to emerging questions:
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Karikari, I., Walton, B. A., Garry, C., Stephanie, M., & , . (2018). Participatory and Collaborative Evaluation Strategies to Support Data-Informed Decisions and Management. University of South Florida, Tampa, FL United States.
Building effective behavioral health service systems requires diverse stakeholders. Understanding stakeholders’ perceptions are critical for system development and assessing the provision of services. Moving from collecting required data for a grant to using information to support data-informed management is possible. This presentation illustrates evaluation strategies to create meaningful participation and collaboration in collecting, analyzing, and using data to support decisions and to monitor progress. Further, this study examined the perceptions of stakeholders on the development of systems of care (SOC) at state and local levels. Views of stakeholders, including youth, families, and advocates, contrasted with service providers on SOC development. Instead of reporting mean ratings, parametric statistics revealed meaningful differences in perspectives.
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Walto, B. A. (2018). Parents with Mental Health and Addiction. Indiana Public Defender Council (IPDC), Indianapolis, IN United States.
To help prepare public defenders for parents with child welfare involvement, a public health overview reframed mental health and addition into health conditions and provided a framework for treatment and support. Tips on supporting recovery followed the introduction of functional and personal recovery concepts. We discussed challenges, including access to services and ongoing stigma, a barrier to treatment and recovery. Examples of recovery focused person-first language helped shift from a moral to disease-recovery perspective. Treatment frameworks for mental health and substance use disorders supported individualized services in a continuum of care based on severity of symptoms, functioning, risks, resources, readiness for change, and environment. Research supported a discussion of relationship of parental behavioral health needs on parenting and of effective interventions by child welfare, clinicians, and public defenders to support reunification of families and avoid re-entry into the child welfare system.
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Walton, B. A. (2018). Systems of Care. Indiana University School of Social Work, Indianapolis, IN United States.
Based on System of Care (SOC) theory (values and philosophy) and infrastructure since the mid-1980s, national child mental health policy, implementation evolved, and funding continued based on research and evaluation. SOC development in one Midwestern state illustrates incremental development of value-based systematic cross-system collaboration at state and levels. Families, youth, professionals, and community partners are encouraged to get involved in supporting effective behavioral health services children and youth through local and/or state identifying resources/needs, planning, and monitoring progress.
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Sarah, M. A., Walton, B. A., & Stephanie, M. (2017). Specialization and time: Two core principles for adult learning. The Council for Adult & Experimental Learning(CAEL), San Diego, CA United States.
Training plays an important role in the profession of social services to improve the quality of services. Interviewing ten social service providers, data analysis demonstrated that the most important principles pursued by participants are specialization and time. Consistent with adult learning theory, if training is designed to meet these principles, participants will become actively involved in training, and their perceived relevancy and in-depth learning will be improved. Abstract: Training plays an important role in the profession of social services to improve the quality of services through workforce development. Since 2006, the Indiana Family and Social Services Administration, Division of Mental Health and Addiction in collaboration with Indiana University has sponsored training for the staff. Annually, more than 500 trainees attend these in-person statewide workshops. In this study, ten social service providers who attended these trainings were interviewed in order to understand strategies to improve effectiveness of workshops. Grounded theory approach was applied to analyze data. Data analysis demonstrated that the most important principles and values pursued by participants are specialization and time. Participants frequently emphasized the importance of specialized learning tailored toward their needs. Time is also crucial. Adult learners would rather shorter trainings for several reasons. For example, participants leave their workplace for training purposes, when they come back; they face many in-complete tasks, which is overwhelming for them. If trainings are designed to meet these principles, participants will become actively involved in training, and their perceived relevancy and in-depth learning will be improved. These two core principles are consistent with adult learning theory mentioned by Knowles (1980, 1990). According to this theory, understanding of intrinsic value, autonomy, direct impact on the work and meaningful engagement are important components for adult learning. Adherence to these two principles, in designing training for adult, helps meet fundamental components of adult learning theory and attract adult learners. In this case, technology, organizational supportive environment and activities beside and out of workshops can be employed to serve these two principles. It is also helpful to consider dynamics of any specific group of participants to tailor the training toward their needs. In this case, having need assessment a few days before training is recommended to discover expectations.
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Isaac, K., & Walton, B. A. (2017). Giving a comprehensive understanding of service utilization through data integration. Praed Foundation, San Antonio, TX United States.
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Dunn, B., Walton, B. A., Wendy, B., Rachel, S., & Letecia, G. (2017). National CANS analysis: Site level discussion to compelling questions. Praed Foundation, San Antonio, TX United States.
The Wraparound Evaluation and Research Team created cross-site CANS profiles in ten large multi-site samples of wraparound enrolled youth. The variation in CANS use, the impact in youth- and family-level ratings and trajectories of change, and other factors associated with differences in profiles lead to weighty questions in considering the implications of CANS local practices. A panel from several sites will dive into local answers to the University of Washington findings to further the national analysis discussion. Eligibility: Does using CANS information for eligibility influence the data? Change Measurement in Wraparound: What is meaningful change? Other site level differences affect CANS variability: Programs, policies, strategies, and fidelity.
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Walton, B. A., & Stephanie, M. (2017). Training to support implementation: Applying intervention-planning strategies. Praed Foundation, San Antonio, TX United States.
This two-part workshop become part of the required curriculum for individuals seeking train-the-trainer certification a the national Total Clinical Outcomes Management conference in 2017. Implementation strategies (training, technical assistance, and person-centered-planning [PCP]) were discussed. Participants practiced using the PCP model with a vignette and identified strategies that might be useful local jurisdictions.
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Walton, B. A. (2017). Wraparound Implementation. National Wraparound Implementation Network, Baltimore, MD United States.
As part of a panel of three states implementation wraparound care coordination mode, this presentation shared lessons learned and provided examples of using information to support manage wraparound implementation and related policy. Panel presenters were recognized a part of the National Wraparound Academy’s faculty.
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Walton, B. A., & Moynihan, S. (2017). Predicting Impact of Cross-Sector Training to Support Access to Behavioral Health Services. Society for Social Work and Research, New Orleans, LA United States.
Abstract
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Walton, B. A., & Harrold, W. (2016). Addressing Disparities through TCOM Strategies. Praed Foundation, Princeton, NJ United States.
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Walton, B. A. (2016). Integrating Technology into Effective Social Work Practice. Indiana University School of Social Work, Indianapolis, IN United States.
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Walton, B. A. (2016). Using the Early Childhood CANS to Guide Practice. Foster Family-Based Treatment Assocciation, New Orleans, LA United States.
As one part of conference symposium focused on the use of the CANS tool in foster family treatment or with other families, I introduced the use of the Early Childhood CANS tool. In addition to engaging families and identifying social/emotional or other early childhood problems, patterns of CANS ratings were used to create a screening tool for referral to an evidence based treatments. Specifically, the Incredible Years, a series of parenting programs, was mapped to the CANS tool. We discussed implications for practice and the potential impact on outcomes.
Contract Fellowship Grants
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TCOM Training, Technical Assistance, and Research
Program Director (PD)/Principal Investigator (PI): Betty Walton -
Racial and Ethnic Disparities in Prevalence, Severity, and Comorbidity of Mental Illnesses during the COVID-19 pandemic
Program Director (PD)/Principal Investigator (PI): Saahoon Hong
Co-PD/PI: Betty Walton
Co-PD/PI: Hea-Won Kim
Co-PD/PI: Stephanie Moynihan -
CANS & ANSA (TCOM) Training, Coaching, Evaluation, & Research
Program Director (PD)/Principal Investigator (PI): Betty Walton -
CANS and ANSA Training and Consultative Services
Program Director (PD)/Principal Investigator (PI): Betty Walton -
System of Care Implementation Grant Amendment SFY 2018 & 2019
Program Director (PD)/Principal Investigator (PI): Betty Walton -
Outcome Mangement Report Development (CSpring Amendment)
Program Director (PD)/Principal Investigator (PI): Betty Walton -
System of Care Implementation Grant
Program Director (PD)/Principal Investigator (PI): Betty Walton -
CANS and ANSA Training and Consultative Services
Program Director (PD)/Principal Investigator (PI): Betty Walton
Institutional Services
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Committee Member
2021 - IU School of Social Work Research Advisory CommitteIn November 2021, I volunteered to service as member of the new Research Advisory Committee. In January 2022, we reviewed and commented on plan to developed research within IUSSW and met to provide feedback on Funding Application Guidelines for new Research Seed Grants. Members were asked to help review resulting grant applications. -
Other
2021 - Indiana University School of Social Work (IUSSW)I collaborated with IUSSW faculty, including Jessica Lee, grant lead, to develop a Health Resources and Services Administration (HRSA) proposal to educate and certify paraprofessionals, including non-IU students. I helped advocate/collaborate with the state behavioral health authority (including peer support advocates) and workforce devleopment. IUSSW was awarded the multi-grant in August 2021. Officially, I'mdesignated as an 'investigator'. -
Other
College of Public Health, University of KentuckyI was asked to serve on a promotion committee for an assistant professor, a pysychologist, who was seeking promotion to the level of associate professor. -
Other
2020 - Search Committee - Associate Research DirectorAs a member of the second and third search committees for a new position, Associate Director of Research, I helped review applications, select applicants for interviews, frame interveiw questions, interview, and review applicants. -
Other
2019 - Indiana University School of Social WorkFacilitator for a IUSSW Strategic Planning Workgroup (Showing Evidence of Community Impact) within the objective Increase Community and Global Engagement. In 2020, I also helped revise/draft final the recommendations related to this component of the school's strategic plan. -
Committee Member
2017 - Indiana University Purdue Universuty Indianapolis & IUSSWAs a member of the Search Committee for IUSSW Dean, we completed orientation, helped draft the announcement, job description and develop video interview questions. Applicants were screened, and candidates selected for video interviews. Final candidates were then selected for campus visits and interviews. We also helped contact and summarize comments of references. Lastly, strengths and challenges/concerns regarding each candidate were identified. Representing non-tenure research faculty during this well planned process helped further develop working relationships with colleagues and better appreciate challenges in moving into academic leadership positions.
Licensure
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Licensed Clinical Social Worker (LCSW)
Indiana Professional Licensing AgencyThe LCSW license credentials social workers as clinical practitioners in behavioral health, social services settings, or private practice.
Memberships
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TCOM University Partners
2020 to 2022 -
Indiana System of Care Advisory Committee
2020 to 2020 -
American Public Health Association
2019 to 2021 -
Council for Adult and Experiential Learners
2017 to 2018 -
Society for Social Work and Research
2016 to 2023 -
Early Learning Advisory Committee- Indiana
2016 to 2017 -
Family Focused Treatment Association
2015 to 2021 -
Indiana Association for Infant and Toddler Mental Health
2004 to 2007 -
Academy of Certified Social Workers
1975 to Present -
National Association of Social Workers
1973 to Present -
Phi Beta Kappa
1971 to Present
Professional Services
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Reviewer, Journal Article
2024 to 2024 - Child Psychiatry & Human DevelopmentAsked to review a manuscript for publication.
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Member
2020 to 2021 - Praed Foundation Annual Conference Planning & Review CommitteeI was invited to be a member of the planning and review committee for the 2020 TCOM conference committee. Responsibilities included participating in a series of planning meetings, reviewing workshop proposals, corresponding and coaching a group of presenters. In 2021, I participated in six conference planning meetings, reviewed and provided feedback/coaching for six proposals and two posters.
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Reviewer, Ad Hoc Reviewer
2020 to 2021 - PublonsReviewer (three times) for article recently published (September 3, 2021) article in Social Work in Mental Health, Mental Health Care Services in Rural South Africa: A Human Capabilities Approach.
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Reviewer, Journal Article
2020 to 2022 - Elsevier ReviewerI reviewed the initial and resubmitted draft of a manuscript regarding access to mental health services in a developing country.
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Reviewer, Journal Article
2019 to Present - Advances in Social WorkBetween 2020-2022, I reviewed two trauma-informed manuscripts that proposed improved trauma screening (1- three times; 2- two times).
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Committee Member
2016 to 2017 - Early Learning Advisory CommitteeMember of the Data Coordination and System Integration work group for the Indiana Early Learning Advisory Committee (ELAC) to the Governor. This workshop supported the integration of existing data related to early learning into a new data base.
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Committee Member
2006 to 2021 - Marion County Juvenile CourtSince 2006, I have been meeting of the Marion County Juvenile Detention Alternative Initiative (JDAI) Admission Subcommittee and Resources Committee. With a goal of only detaining youth who are not likely to appear in court or who may be a danger, we meet quarterly to monitor admission trends, disparities, alternatives, and discuss challenges.
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Reviewer, Book
to 2021 - Palgrave Macmillan (publisher)At the request of the business editor, I review the proposal and three book chapters for an interim review of a new book related to managing human services.
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Reviewer, Ad Hoc Reviewer
to 2021 - College of Public Health, University of KentuckyI served as an external evaluation for an assistant professor who was seeking promotion to associate professor in the College of Public Health, University of Kentucky.
Public Services
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Board Member
2020 to 2021 - Indiana Family & Social Service Administration, Division of Mental Health & Addiction (DMHA)Invited member of reconstituted Indiana Child Mental Health Advisory Board
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