It is important to understand racial/ethnic differences in adverse childhood experiences (ACEs), given their relationship to long‐term physical and mental health, and the public health cost of the ...significant disparities that exist. Moreover, in order to inform interventions and promote resilience, it is critical to examine protective factors that mitigate the relationship between adversity and poor health. The current study utilized latent transition analyses (LTA) to examine co‐occurring profiles of ACEs and protective factors (from school, family, and community contexts) and links to health outcomes among 30,668 Black (10.4%), Latinx (12.3%), and White youth (77.3%) ages 12–17 (52.5% male) who participated in the 2011–12 National Survey of Children's Health (NSCH). Results suggested that greater adversity was associated with worse health, while more access to protective factors was associated with better health. White youth had consistently lower endorsement of ACEs, greater access to protective factors, and better health compared to their Black and Latinx counterparts. Efforts to improve child health and racial/ethnic disparities in research and practice must consider adversity, protective factors, and the systemic inequities faced by racial/ethnic minority youth in the United States.
Highlights
Family, school, and community resources can contribute to resilience in the context of ACEs.
Racial/ethnic disparities exist regarding levels of ACEs, protective factors, and health.
Initiatives to improve child health must consider ACEs, protective factors, & systemic inequities.
ACEs intervention must be culturally‐informed and implemented across socioecological levels.
Including auxiliary variables such as antecedent and consequent variables in mixture models provides valuable insight in understanding the population heterogeneity embodied by a latent class ...variable. The model building process regarding how to include predictors/correlates and outcomes of the latent class variables into mixture models is an area of active research. As such, new methods of including these variables continue to emerge and best practices for the application of these methods in real data settings (including simple guidelines for choosing amongst them) are still not well established. This paper focuses on one type of auxiliary variable-distal outcomes-providing an overview of the methods currently available for estimating the effects of latent class membership on subsequent distal outcomes. We illustrate the recommended methods in the software packages Mplus and Latent Gold using a latent class model to capture population heterogeneity in students' mathematics attitudes, linking latent class membership to two distal outcomes.
The 3-step method for estimating the effects of auxiliary variables (i.e., covariates and distal outcome) in mixture modeling provides a useful way to specify complex mixture models. One of the ...benefits of this method is that the measurement parameters of the mixture model are not influenced by the auxiliary variable(s). In addition, it allows for models that involve multiple latent class variables to be specified without each part of the model influencing the others. This article describes a unique latent transition analysis model where the measurement models are a latent class analysis model and a growth mixture model. We highlight the application of this model to study kindergarten readiness profiles and link it to elementary students' reading trajectories. Mplus syntax for the 3-step specification is provided.
Disaster exposure can put survivors at greater risk for subsequent mental health (MH) problems. Within the field of disaster MH research, it is important to understand how the choice of analytic ...approaches and their implicit assumptions may affect results when using a disaster exposure measure. We compared different analytic strategies for quantifying disaster exposure and included a new analytic approach, latent class analysis (LCA), in a sample of parents and youth. Following exposure to multiple floods in Texas, a sample of 555 parents and 486 youth were recruited. Parents were predominantly female (70.9%) and White (60.8%). Parents were asked to have their oldest child between the ages of 10 and 19 years old participate (M = 13.74 years, SD = 2.57; 52.9% male). Participants completed measures on disaster exposure, posttraumatic stress, depression, and anxiety. The LCA revealed four patterns of exposure in both parents and youth: high exposure (15.5% parent, 9.5% child), moderate exposure (19.8% parent, 28.2% child), community exposure (45.9% parent, 34.4% child), and low exposure (18.8% parent, 27.8% child). In terms of MH, there were similarities across analytic approaches, but the LCA highlighted a threshold effect, with the high exposure class doing worse than all others, d = 1.12. These results have important implications in understanding the different exposure experiences of survivors and the linkage to MH outcomes. The findings are also informative in the development and use of screening tools used in postdisaster contexts in determining who may or may not need MH services.
Resumen
Spanish s by Asociación Chilena de Estrés Traumático (ACET)
Abordando los Problemas de Medición de la Exposición a los Desastres con un Análisis de Clases Latentes
ABORDANDO LA MEDICION DE LA EXPOSICION A DESASTRES
La exposición a los desastres puede poner a los sobrevivientes en un riesgo más alto de posteriores problemas de salud mental (SM). En el campo de investigación de la SM sobre desastres, es importante entender como la elección de perspectivas analíticas y sus supuestos implícitos podrían afectar los resultados cuando se usa una medida de exposición al desastre. Comparamos estrategias analíticas diferentes para cuantificar la exposición al desastre e incluimos una perspectiva analítica nueva, análisis de clase latente (LCA en sus siglas en inglés), en una muestra de padres y jóvenes. Luego de la exposición a numerosas inundaciones en Texas, se reclutó una muestra de 555 padres y 486 jóvenes. Los padres fueron principalmente mujeres (70.9%) y de raza blanca (60.8%). Se les pidió a los padres la participación de su hijo mayor entre las edades de 10 y 19 años (M = 13.74 años, DE = 2.57; 52.9% varones). Los participantes completaron las medidas sobre exposición a desastres, estrés postraumático, depresión, y ansiedad. El LCA reveló cuatro patrones de exposición en ambos padres y jóvenes: alta exposición (15.5% padres, 9.5% niños), exposición moderada (19.8% padres, 28.2% niños), exposición comunitaria (45.9% padres, 34.4% niños), y baja exposición (18.8% padres, 27.8% niños). En términos de la SM, hubo similitudes a lo largo de los enfoques analíticos, pero el LCA destacó un efecto umbral, con la clase de alta exposición presentando características peores que todas las otras, d = 1.12. Estos resultados tienen implicaciones importantes para entender las diferentes experiencias de exposición de los sobrevivientes y su vínculo con resultados de la SM. Los hallazgos son también informativos en el desarrollo y el uso de herramientas de tamizaje usadas en los contextos post‐desastres en determinar quién podría o no necesitar servicios de SM.
抽象
Traditional and Simplified Chinese s by the Asian Society for Traumatic Stress Studies (AsianSTSS)
簡體及繁體中文撮要由亞洲創傷心理研究學會翻譯
Addressing Disaster Exposure Measurement Issues with Latent Class Analysis
Traditional Chinese
標題: 以潛在類別分析處理災難經歷的測量問題
撮要: 災難經歷可致使生還者隨後更大機會患有心理問題(MH)。災難心理問題研究者在測量災難經歷時༌有必要了解其採用的分析方法及內在假設會如何影響所得成果。本研究透過由家長和青少年組成的樣本༌比較用以測量災難經歷的量化分析策略༌當中亦包含新的分析方法:潛在類別分析(LCA)。樣本為於德薩斯州經歷過數次水災的555名家長與486名青年。大多數家長為女性(70.9%)及白人(60.8%);他們最年長而且年齡介乎10‐19歲的孩子亦參與研究(M = 13.74歲, SD = 2.57; 52.9% 男性)。樣本進行以下方面的評估:災難經歷、創傷後壓力、抑鬱症、焦慮症。LCA反映༌家長與青年都有4種經歷模式:高水平經歷(15.5% 家長, 9.5% 孩子)、中水平經歷(19.8% 家長, 28.2% 孩子)、社區經歷(45.9% 家長, 34.4% 孩子)༌以及低水平經歷(18.8% 家長, 27.8% 孩子)。MH方面༌使用不同分析法皆有相似之處༌但LCA則凸顯一種閾限效應༌而且高水平經歷組別有特別差的結果(d = 1.12)。這些重要結果༌有助於了解生還者不同的災難經歷༌及其與MH的關連。結果亦有助我們了解༌用於災後找出個人是否需要心理治療服務的篩查工具其使用和發展。
Simplified Chinese
标题: 以潜在类别分析处理灾难经历的测量问题
撮要: 灾难经历可致使生还者随后更大机会患有心理问题(MH)。灾难心理问题研究者在测量灾难经历时༌有必要了解其采用的分析方法及内在假设会如何影响所得成果。本研究透过由家长和青少年组成的样本༌比较用以测量灾难经历的量化分析策略༌当中亦包含新的分析方法:潜在类别分析(LCA)。样本为于德萨斯州经历过数次水灾的555名家长与486名青年。大多数家长为女性(70.9%)及白人(60.8%);他们最年长而且年龄介乎10‐19岁的孩子亦参与研究(M = 13.74岁, SD = 2.57; 52.9% 男性)。样本进行以下方面的评估:灾难经历、创伤后压力、抑郁症、焦虑症。LCA反映༌家长与青年都有4种经历模式:高水平经历(15.5% 家长, 9.5% 孩子)、中水平经历(19.8% 家长, 28.2% 孩子)、小区经历(45.9% 家长, 34.4% 孩子)༌以及低水平经历(18.8% 家长, 27.8% 孩子)。MH方面༌使用不同分析法皆有相似之处༌但LCA则凸显一种阈限效应༌而且高水平经历组别有特别差的结果(d = 1.12)。这些重要结果༌有助于了解生还者不同的灾难经历༌及其与MH的关连。结果亦有助我们了解༌用于灾后找出个人是否需要心理治疗服务的筛查工具其使用和发展。
For some time, there have been differing recommendations about how and when to include covariates in the mixture model building process. Some have advocated the inclusion of covariates after ...enumeration, whereas others recommend including them early on in the modeling process. These conflicting recommendations have led to inconsistent practices and unease in trusting modeling results. In an attempt to resolve this discord, we conducted a Monte Carlo simulation to examine the impact of covariate exclusion and misspecification of covariate effects on the enumeration process. We considered population and analysis models with both direct and indirect paths from the covariates to the latent class indicators. As expected, misspecified covariate effects most commonly led to the overextraction of classes. Findings suggest that the number of classes could be reliably determined using the unconditional latent class model, thus our recommendation is that class enumeration be done prior to the inclusion of covariates.
Increasing knowledge of factors that promote health among youth from diverse backgrounds is an important step towards addressing health disparities. Although many promotive factors have been ...identified individually, there is an overabundance of research on risk factors, and a comparable dearth of knowledge regarding the influence of combinations of promotive factors. The current study examined how promotive factors across family, school, and community contexts co-occur to promote health among youth of different race/ethnicity. Utilizing a nationally representative sample of Black (10%), Latinx (12%), and White (77%) youth ages 12–17 (
N
= 30,668), latent class analysis was employed to identify classes of youth who endorsed homogenous patterns of promotive factors. Associations between class membership and health were explored. Each subsample was best characterized by its own 4-class model, with significant differences in patterns of promotive factors experienced by Black, Latinx, and White youth. Youth health outcomes also varied significantly by class membership (
p
< .05). Greater access to more promotive factors was associated with better health, and low access to community and school promotive factors was associated with worse health. Results suggest that increasing promotive factors in school, family, and community settings may help to prevent poor health outcomes; however, jointly addressing discrimination against racial/ethnic minority youth through education, policy, and practice is also needed to address health disparities.
Abstract Differences in trauma symptoms among men and women in two court-involved substance abuse treatment programs were examined using latent transition analysis (LTA). It was hypothesized that ...women would be more likely to report clinical-level trauma symptoms than would men, but that both groups would show reductions in symptoms over time. Symptom classifications were determined by the LTA. Scores on the Trauma Symptom Inventory (TSI) were obtained on 381 program participants, 112 men and 269 women, at intake and after 6 months in treatment. Three ordered classes were obtained for men and women at each time point: non-clinical (no TSI scales elevated), moderate symptoms (1 or 2 scales elevated) and severe symptoms (all scales elevated). Men were more likely to be represented in the non-clinical class at intake, while women had higher representation in the severe symptom s classification. There was a reduction of trauma symptoms for most men and women, but some groupings had symptoms that remained the same or became worse over time. Using gender and trauma-symptoms to help determine interventions is discussed.
Objective: We explored the internal structure of within-group variation in the syndemic construct among bisexual adolescents, an understudied and highly vulnerable population known to experience ...health disparities compared with monosexuals (those attracted to a single gender). We sought to identify patterns of co-occurrence among three domains of high priority behavioral risks-sexual risk factors, substance use, and victimization-and their implications for suicidality. Method: We used a national sample of 1,053 ethnically/racially diverse, high school age bisexual adolescents drawn from the 2015 Youth Risk Behavior Surveillance System (YRBSS). We applied latent class analysis (LCA) to 15 indicators measuring the three aforementioned domains and modeled predictors and an outcome of class membership. Results: Within-group variation in the syndemic construct appears categorical, systematic, and comprised of Low Risk (38%), Alcohol Use (20%), Peer-victimization (14%), Sexually Active (11%), Syndemic (11%), and Risk-taking (7%) classes. Classes were well-separated per classification statistics. The proportions of bisexual identification, sex, and race varied significantly across classes. Syndemic and Peer-victimization classes were equivalent and elevated in their suicidality risk, out of all classes. Conclusions: Results revealed multiple and diverging forms of conjoint behavioral risk that conferred differential health implications; illuminated the shape and functional form of the syndemic construct among bisexual adolescents; and illustrated the utility of LCA for classifying typologies of risky and normative health behavior patterns. Psychologists are recommended to carefully consider the comorbidly operant nature of behavioral risks in this population. Future directions include addressing replication, multiple-group invariance, additional auxiliary variables, and alternative mixture techniques.
What is the public health significance of this article?
This study suggests that patterns of conjoint behavioral risk among bisexual adolescents can be classified into six subtypes: Low Risk (38%), Alcohol Use (20%), Peer-victimization (14%), Sexually Active (11%), Syndemic (11%), and Risk-taking (7%). The Syndemic and Peer-victimization classes were most at risk for suicidality, and girls and behaviorally bisexual adolescents were overrepresented in the riskier classes. Findings highlight the need for refined assessment and targeted intervention for hidden subgroups of bisexual adolescents that are most vulnerable to compounded behavioral risks and associated mortality.
Research has demonstrated the negative impact of Adverse Childhood Experiences (ACEs) on long-term trajectories of mental and physical health. Yet existing literature on this topic is limited in its ...understanding of outcomes among youth samples, optimal measurement items and methods, and differences in adverse experiences across race/ethnicity. The current study used a person-centered approach to measure ACEs and their impact on youth health outcomes across three different racial/ethnic groups from a large national database. Patterns of exposure to adverse experiences among Black, Latinx, and White youth (N = 30,668, ages 12–17) were determined empirically using latent class analysis (LCA). Significant differences in class membership by demographic indicators (age, household income, sex) and concurrent health outcomes were identified. Different models emerged for Black (2 classes), Latinx (3 classes), and White youth (3 classes). Older and lower-income youth were more likely to have experienced adversities, but there were no differences in adversity likelihood by sex. Additionally, racial/ethnic minority youth were at greater risk of experiencing higher levels of adversity, poverty, and poor health when compared to their White counterparts. Rather than occuring in meaningful clusters, adverse experiences among youth reflected a cumulative risk model such that classes were defined by the overall intensity of adverse experiences (i.e., low, moderate, high). Findings provide greater knowledge regarding the relationship between ACEs and health and future research directions to inform more targeted and culturally-appropriate screening, prevention, and intervention programs.
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