Abstract: Latent Transition Analysis to Determine Change in Health Services Use (Society for Social Work and Research 26th Annual Conference - Social Work Science for Racial, Social, and Political Justice)

636P Latent Transition Analysis to Determine Change in Health Services Use

Sunday, January 16, 2022
Marquis BR Salon 6, ML 2 (Marriott Marquis Washington, DC)
* noted as presenting author
Jeremiah Jaggers, PhD, Assistant Professor, University of Utah, Salt Lake City, UT
Kyle Rehn, Doctoral Student, University of Utah, Salt Lake City, UT
Jorge Arciniegas, Research Analyst, University of Utah, Salt Lake City, UT
Background: In the United States, approximately 2.1 million youth under the age of 18 are arrested in a given year. Research identifies health seeking behavior as a significant predictor for violent behavior. It is therefore imperative to identify the combination of health care services that impact violence related arrests among youth. Multiple health-related factors increase risk for violent behavior among adolescents including a diagnosable mental health disorder, sexually transmitted diseases, and substance misuse. Despite a strong need for treatment services for current and formerly incarcerated youth, there is limited effort to increase the availability of services. The current study examines patterns of health services need and how those patterns change over time.

Methods: This study used Latent Transition Analysis (LTA) to analyze longitudinal data, using three longitudinal time periods, from the National Longitudinal Study of Adolescent to Adult Health. LTA models analyze and identify changes between latent classes over time, how classes are characterized at each point in time, and the probability of changing classes over time. The final longitudinal analysis used n = 5,059 participants in wave 1, n = 3,885 in wave 2, and n = 4,163 in wave 3. Yes/No frequencies from four health service questions were used at each time period: counseling services, STD treatment, substance abuse treatment, and needing care but not receiving care. The outcome of interest was whether participants had shot or stabbed someone by that specific longitudinal time period. The primary objectives of this study were to 1) identify groups of individuals based upon health service utilization and violent behavior and 2) ascertain the longitudinal change in group membership occurring between predominantly adolescent youth into early adulthood.

Results: The LTA model identified three latent classes based on violent behavior patterns and were characterized as Low Lifetime Probability (LP), Low Youth Probability (YP), and Low Adult Probability (AP). The LP group had consistently low probabilities of health service usage and engaging in violent behavior across all 3 points in time. The YP group had a lower probability of engaging in violent behavior during the first two waves but a higher probability of violent behavior in adulthood during the third time wave. The YP group in wave 3 was also more likely to receive health-related services for STDs and needing care but not receiving care. The AP group had a higher likelihood of violent behavior during adolescence but had a lower probability of violent conduct during adulthood in wave three. The AP group also had consistently high health service rates for counseling, substance abuse treatment, STD treatment and needing care but not receiving care over all three longitudinal periods.

Implications: Early identification of individuals who may not use health and mental health services could provide valuable information for predicting future violent behaviors. Providing easy, safe access to treatment for those at the greatest risk can both improve health and mitigate violent behavior.