Geographic Variation, Economic Activity, and Labor Market Characteristics in Trajectories of Suicide in the United States, 2008-2020.

Suicide rates in the United States have increased over the past 15 years, with substantial geographic variation in these increases; yet there have been few attempts to cluster counties by the magnitude of suicide rate changes according to intercept and slope or to identify the economic precursors of increases. We used vital statistics data and growth mixture models to identify clusters of counties by their magnitude of suicide growth from 2008 to 2020 and examined associations with county economic and labor indices. Our models identified 5 clusters, each differentiated by intercept and slope magnitude, with the highest-rate cluster (4% of counties) being observed mainly in sparsely populated areas in the West and Alaska, starting the time series at 25.4 suicides per 100,000 population, and exhibiting the steepest increase in slope (0.69/100,000/year). There was no cluster for which the suicide rate was stable or declining. Counties in the highest-rate cluster were more likely to have agricultural and service economies and less likely to have urban professional economies. Given the increased burden of suicide, with no clusters of counties improving over time, additional policy and prevention efforts are needed, particularly targeted at rural areas in the West.

Analysis of trajectory changes and predictive factors of sense of coherence in patients after colorectal cancer surgery.

OBJECTIVE: To investigate the trajectories and potential categories of changes in the sense of coherence (SOC) in patients after colorectal cancer surgery and to analyze predictive factors. METHODS: From January to July 2023, 175 patients with colorectal cancer treated at a tertiary Grade A oncology hospital in Jiangsu Province were selected as the study subjects. Prior to surgery, SOC-13 scale, Patient-Generated Subjective Global Assessment (PG-SGA), Brief Illness Perception Questionnaire (BIPQ), and Social Support Rating Scale (SSRS) were used to survey the patients. SOC levels were measured multiple times at 1 week, 1 month, and 3 months post-surgery. Growth Mixture Modeling (GMM) was applied to fit the trajectory changes of SOC in patients after colorectal cancer surgery. Multinomial logistic regression was used to analyze the predictive factors of SOC trajectory changes. RESULTS: The SOC scores of patients at points T1-T4 were (65.27 ± 9.20), (63.65 ± 10.41), (63.85 ± 11.84), and (61.56 ± 12.65), respectively. Multinomial logistic regression results indicated that gender, employment status, disease stage, household monthly income, intestinal stoma, nutritional status, illness perception, and social support were predictors of SOC trajectory changes (P < 0.05). CONCLUSION: There is heterogeneity in the trajectory changes of SOC in patients after colorectal cancer surgery. Healthcare professionals should implement early precision interventions based on the patterns of changes and predictive factors in each trajectory category.

Childhood trauma and outcome trajectories in patients with longstanding eating disorders across 17 years.

BACKGROUND: A large proportion of patients with eating disorders (ED) report experiences of childhood trauma. Latent trajectory analysis in ED samples reveals the complexities in course and outcome and can explore the long-term impact of adverse experiences in childhood. METHOD: A total of 84 patients with longstanding ED were included. ED symptoms were assessed by the Eating Disorder Examination interview at discharge from inpatient treatment, and at 1-, 2-, 5-, and 17-year follow-up, respectively. Change over time was examined using growth mixture modeling, allowing the number of trajectories to emerge through the data. Prevalence of childhood trauma was assessed, and its relation to class membership was tested. RESULTS: We identified four distinct classes: patients with (a) a continuous improvement in the entire follow-up period, and scores within normal range at the end, "continuous improvement" (54.8%); (b) a high symptom level at baseline and moderate decrease over time, "high and declining" (22.6%); (c) initial ED scores below clinical cut-off and stable symptoms throughout the course, "consistently low" (14.3%); and (d) with high scores initially, and a significant increase in symptoms over time, "high and increasing" (8.3%). A history of childhood sexual abuse (CSA) was overrepresented in classes with persistently high symptom levels and poor long-term outcome DISCUSSION: Patients with longstanding ED displayed considerable diversity in trajectories of symptom change across 17 years. To improve long-term outcome, enhanced treatment of sequelae from CSA seems essential. PUBLIC SIGNIFICANCE: Patients with longstanding eating disorders displayed four different trajectories of change in a 17-year follow-up study. Although there were significant changes over time, the majority of patients remained within similar symptom levels as they presented with at discharge from inpatient treatment. Exposure to childhood maltreatment was common within the sample. Childhood sexual abuse predicted poor long-term outcome, which highlights the importance of trauma informed care.

Association of sex-specific body mass index and waist circumference trajectories with non-alcoholic fatty liver disease incidence based on growth mixture modeling.

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease. The relationship between the trajectories of obesity indicators and incident NAFLD is unknown. Therefore, this study aims to explore the sex-specific association between the trajectories of obesity indicators and the incidence of NAFLD. METHODS AND RESULTS: In total, 9067 participants were recruited for this longitudinal study. Obesity indicators use body mass index (BMI) and waist circumference (WC). The trajectory of obesity indicators was analyzed using the growth mixture modeling. The multivariate logistic regression model was used to analyze the association between obesity indicators' trajectories and incident NAFLD. Over a median follow-up of 1.82 years, 1013 (11.74%) participants developed NAFLD. We identified BMI and WC change trajectories as the stable group, increasing group, and decreasing group. After adjusting for baseline level and other confounders, multivariate logistic regression analysis showed that compared with stable group of BMI, the increasing group, and decreasing group odds ratio and 95% confidence interval of NAFLD were 2.10 (1.06-4.15), and 0.25 (0.09-0.67) in men, and 1.82 (1.08-3.04) and 0.32 (0.16-0.64) in women. Compared with stable group of WC, the increasing group was 2.57 (1.39-4.74) in men, the increasing group, and decreasing group were 2.29 (1.70-3.10) and 0.28 (0.12-0.64) in women. Sensitivity analysis showed that the results were stable. CONCLUSION: The BMI and WC changing trajectories are significantly associated with the incidence of NAFLD in men and women. Populations of real-world health examinations can be categorized based on obesity indicator changes to prevent NAFLD.

Joint developmental trajectories of internalizing and externalizing problems from mid-childhood to late adolescence and childhood risk factors: Findings from a prospective pre-birth cohort.

There is limited evidence on heterogenous co-developmental trajectories of internalizing (INT) and externalizing (EXT) problems from childhood to adolescence and predictors of these joint trajectories. We utilized longitudinal data from Raine Study participants (n = 2393) to identify these joint trajectories from 5 to 17 years using parallel-process latent class growth analysis and analyze childhood individual and family risk factors predicting these joint trajectories using multinomial logistic regression. Five trajectory classes were identified: Low-problems (Low-INT/Low-EXT, 29%), Moderate Externalizing (Moderate-EXT/Low-INT, 26.5%), Primary Internalizing (Moderate High-INT/Low-EXT, 17.5%), Co-occurring (High-INT/High-EXT, 17%), High Co-occurring (Very High-EXT/High-INT, 10%). Children classified in Co-occurring and High Co-occurring trajectories (27% of the sample) exhibited clinically meaningful co-occurring problem behaviors and experienced more adverse childhood risk-factors than other three trajectories. Compared with Low-problems: parental marital problems, low family income, and absent father predicted Co-occurring and High Co-occurring trajectories; maternal mental health problems commonly predicted Primary Internalizing, Co-occurring, and High Co-occurring trajectories; male sex and parental tobacco-smoking uniquely predicted High Co-occurring membership; other substance smoking uniquely predicted Co-occurring membership; speech difficulty uniquely predicted Primary Internalizing membership; child's temper-tantrums predicted all four trajectories, with increased odds ratios for High Co-occurring (OR = 8.95) and Co-occurring (OR = 6.07). Finding two co-occurring trajectories emphasizes the importance of early childhood interventions addressing comorbidity.

Prospective trajectories of depression predict mortality in cancer patients.

An ever-growing body of empirical evidence has demonstrated the relationship between depression and cancer. The objective of this study was to examine whether depression trajectories predict mortality risk above and beyond demographics and other general health-related factors. Participants (n = 2,345) were a part of the Health and Retirement Study. The sample consisted of patients who were assessed once before their cancer diagnosis and thrice after. Depressive symptoms and general health-related factors were based on self-reports. Mortality risk was determined based on whether the patient was alive or not at respective time points. Latent Growth Mixture Modeling was performed to map trajectories of depression, assess differences in trajectories based on demographics and general health-related factors, and predict mortality risk. Four trajectories of depression symptoms emerged: resilient (69.7%), emerging (13.5%), recovery (9.5%), and chronic (7.2%). Overall, females, fewer years of education, higher functional impairment at baseline, and high mortality risk characterized the emerging, recovery, and chronic trajectories. In comparison to the resilient trajectory, mortality risk was highest for the emerging trajectory and accounted for more than half of the deaths recorded for the participants in emerging trajectory. Mortality risk was also significantly elevated, although to a lesser degree, for the recovery and chronic trajectories. The data highlights clinically relevant information about the depression-cancer association that can have useful implications towards cancer treatment, recovery, and public health.

Multiple Trajectories and Predictors of Self-Esteem Change in Later Life: A Latent Growth Mixture Modeling Approach.

Applying latent growth mixture modeling (GMM), this study delves into the examination of self-esteem trajectories in a sample of 5,597 older adults over a nine-year period. Four distinct patterns of self-esteem changes have emerged: low, decreasing, increasing, and high. Additionally, the study explores the relationships between each trajectory and various predictors encompassing demographic factors, socioeconomic status, health, and interpersonal relationships. The findings highlight the significance of these factors in predicting the likelihood of an individual following a specific self-esteem trajectory. Notably, maintaining employment, fostering satisfactory social relationships, and being free of frequent depressive feelings emerged as strong predictors for the stability and increase of high self-esteem. Intriguingly, an average or above-average income was unexpectedly associated with lower levels of self-esteem. The study emphasizes the contribution of GMM to advancing aging research.

Associations of polygenic risk scores with posttraumatic stress symptom trajectories following combat deployment.

BACKGROUND: Identification of genetic risk factors may inform the prevention and treatment of posttraumatic stress disorder (PTSD). This study evaluates the associations of polygenic risk scores (PRS) with patterns of posttraumatic stress symptoms following combat deployment. METHOD: US Army soldiers of European ancestry (n = 4900) provided genomic data and ratings of posttraumatic stress symptoms before and after deployment to Afghanistan in 2012. Latent growth mixture modeling was used to model posttraumatic stress symptom trajectories among participants who provided post-deployment data (n = 4353). Multinomial logistic regression models tested independent associations between trajectory membership and PRS for PTSD, major depressive disorder (MDD), schizophrenia, neuroticism, alcohol use disorder, and suicide attempt, controlling for age, sex, ancestry, and exposure to potentially traumatic events, and weighted to account for uncertainty in trajectory classification and missing data. RESULTS: Participants were classified into low-severity (77.2%), increasing-severity (10.5%), decreasing-severity (8.0%), and high-severity (4.3%) posttraumatic stress symptom trajectories. Standardized PTSD-PRS and MDD-PRS were associated with greater odds of membership in the high-severity v. low-severity trajectory [adjusted odds ratios and 95% confidence intervals, 1.23 (1.06-1.43) and 1.18 (1.02-1.37), respectively] and the increasing-severity v. low-severity trajectory [1.12 (1.01-1.25) and 1.16 (1.04-1.28), respectively]. Additionally, MDD-PRS was associated with greater odds of membership in the decreasing-severity v. low-severity trajectory [1.16 (1.03-1.31)]. No other associations were statistically significant. CONCLUSIONS: Higher polygenic risk for PTSD or MDD is associated with more severe posttraumatic stress symptom trajectories following combat deployment. PRS may help stratify at-risk individuals, enabling more precise targeting of treatment and prevention programs.

Anxiety symptom trajectories from treatment to 5- to 12-year follow-up across childhood and adolescence.

OBJECTIVE: The current study examined trajectories of anxiety during (a) acute treatment and (b) extended follow-up to better characterize the long-term symptom trajectories of youth who received evidence-based intervention for anxiety disorders using a person-centered approach. METHOD: Participants were 319 youth (age 7-17 years at enrollment), who participated in a multicenter randomized controlled trial for the treatment of pediatric anxiety disorders, Child/Adolescent Anxiety Multimodal Study, and a 4-year naturalistic follow-up, Child/Adolescent Anxiety Multimodal Extended Long-term Study, an average of 6.5 years later. Using growth mixture modeling, the study identified distinct trajectories of anxiety across acute treatment (Weeks 0-12), posttreatment (Weeks 12-36), and the 4-year-long follow-up, and identified baseline predictors of these trajectories. RESULTS: Three nonlinear anxiety trajectories emerged: "short-term responders" who showed rapid treatment response but had higher levels of anxiety during the extended follow-up; "durable responders" who sustained treatment gains; and "delayed remitters" who did not show an initial response to treatment, but showed low levels of anxiety during the maintenance and extended follow-up periods. Worse anxiety severity and better family functioning at baseline predicted membership in the delayed remitters group. Caregiver strain differentiated short-term responders from durable responders. CONCLUSIONS: Findings suggest that initial response to treatment does not guarantee sustained treatment gains over time for some youth. Future follow-up studies that track treated youth across key developmental transitions and in the context of changing social environments are needed to inform best practices for the long-term management of anxiety.

Exploration of model misspecification in latent class methods for longitudinal data: Correlation structure matters.

Modeling longitudinal trajectories and identifying latent classes of trajectories is of great interest in biomedical research, and software to identify latent classes of such is readily available for latent class trajectory analysis (LCTA), growth mixture modeling (GMM) and covariance pattern mixture models (CPMM). In biomedical applications, the level of within-person correlation is often non-negligible, which can impact the model choice and interpretation. LCTA does not incorporate this correlation. GMM does so through random effects, while CPMM specifies a model for within-class marginal covariance matrix. Previous work has investigated the impact of constraining covariance structures, both within and across classes, in GMMs-an approach often used to solve convergence problems. Using simulation, we focused specifically on how misspecification of the temporal correlation structure and strength, but correct variances, impacts class enumeration and parameter estimation under LCTA and CPMM. We found (1) even in the presence of weak correlation, LCTA often does not reproduce original classes, (2) CPMM performs well in class enumeration when the correct correlation structure is selected, and (3) regardless of misspecification of the correlation structure, both LCTA and CPMM give unbiased estimates of the class trajectory parameters when the within-individual correlation is weak and the number of classes is correctly specified. However, the bias increases markedly when the correlation is moderate for LCTA and when the incorrect correlation structure is used for CPMM. This work highlights the importance of correlation alone in obtaining appropriate model interpretations and provides insight into model choice.

Influence of systolic blood pressure trajectory on in-hospital mortality in patients with sepsis.

BACKGROUND: Numerous studies have investigated the mean arterial pressure in patients with sepsis, and many meaningful results have been obtained. However, few studies have measured the systolic blood pressure (SBP) multiple times and established trajectory models for patients with sepsis with different SBP trajectories. METHODS: Data from patients with sepsis were extracted from the Medical Information Mart for Intensive Care-III database for inclusion in a retrospective cohort study. Ten SBP values within 10 h after hospitalization were extracted, and the interval between each SBP value was 1 h. The SBP measured ten times after admission was analyzed using latent growth mixture modeling to construct a trajectory model. The outcome was in-hospital mortality. The survival probability of different trajectory groups was investigated using Kaplan-Meier (K-M) analysis, and the relationship between different SBP trajectories and in-hospital mortality risk was investigated using Cox proportional-hazards regression model. RESULTS: This study included 3034 patients with sepsis. The median survival time was 67 years (interquartile range: 56-77 years). Seven different SBP trajectories were identified based on model-fit criteria. The in-hospital mortality rates of the patients in trajectory classes 1-7 were 25.5%, 40.5%, 11.8%, 18.3%, 23.5%, 13.8%, and 10.5%, respectively. The K-M analysis indicated that patients in class 2 had the lowest probability of survival. Univariate and multivariate Cox regression analysis indicated that, with class 1 as a reference, patients in class 2 had the highest in-hospital mortality risk (P < 0.001). Subgroup analysis indicated that a nominal interaction occurred between age group and blood pressure trajectory in the in-hospital mortality (P < 0.05). CONCLUSION: Maintaining a systolic blood pressure of approximately 140 mmHg in patients with sepsis within 10 h of admission was associated with a lower risk of in-hospital mortality. Analyzing data from multiple measurements and identifying different categories of patient populations with sepsis will help identify the risks among these categories.

Patient-reported mental health and well-being trajectories in oncology patients during radiation therapy: an exploratory retrospective cohort analysis using the Ontario Cancer Registry.

PURPOSE: Mental health and well-being trajectories are not expected to be homogeneous in diverse clinical populations. This exploratory study aims to identify subgroups of patients with cancer receiving radiation therapy who have different mental health and well-being trajectories, and examine which socio-demographic, physical symptoms, and clinical variables are associated with such trajectories. METHODS: Retrospective analysis of radiation therapy patients diagnosed with cancer in 2017 was conducted using data from the Ontario Cancer Registry (Canada) and linked with administrative health data. Mental health and well-being were measured using items from the Edmonton Symptom Assessment System-revised questionnaire. Patients completed up to 6 repeated measurements. We used latent class growth mixture models to identify heterogeneous mental health trajectories of anxiety, depression, and well-being. Bivariate multinomial logistic regressions were conducted to explore variables associated with the latent classes (subgroups). RESULTS: The cohort (N = 3416) with a mean age of 64.5 years consisted of 51.7% females. Respiratory cancer was the most common diagnosis (30.4%) with moderate to severe comorbidity burden. Four latent classes with distinct anxiety, depression, and well-being trajectories were identified. Decreasing mental health and well-being trajectories are associated with being female; living in neighborhoods with lower income, greater population density, and higher proportion of foreign-born individuals; and having higher comorbidity burden. CONCLUSIONS: The findings highlight the importance of considering social determinants of mental health and well-being, in addition to symptoms and clinical variables, when providing care for patients undergoing radiation therapy.

A prospective longitudinal study of multidomain resilience among youths with and without maltreatment histories.

The majority of children with maltreatment histories do not go on to develop depression in their adolescent and adult years. These individuals are often identified as being "resilient", but this characterization may conceal difficulties that individuals with maltreatment histories might face in their interpersonal relationships, substance use, physical health, and/or socioeconomic outcomes in their later lives. This study examined how adolescents with maltreatment histories who exhibit low levels of depression function in other domains during their adult years. Longitudinal trajectories of depression (across ages 13-32) in individuals with (n = 3,809) and without (n = 8,249) maltreatment histories were modeled in the National Longitudinal Study of Adolescent to Adult Health. The same "Low," "increasing," and "declining" depression trajectories in both individuals with and without maltreatment histories were identified. Youths with maltreatment histories in the "low" depression trajectory reported lower romantic relationship satisfaction, more exposure to intimate partner and sexual violence, more alcohol abuse/dependency, and poorer general physical health compared to individuals without maltreatment histories in the same "low" depression trajectory in adulthood. Findings add further caution against labeling individuals as "resilient" based on a just single domain of functioning (low depression), as childhood maltreatment has harmful effects on a broad spectrum of functional domains.

Pubertal progression and its relationship to psychological and behavioral outcomes among adolescent boys.

Variations in pubertal timing and tempo have relevance to psychosocial development. Accounting for pubertal timing, tempo, and psychosocial development simultaneously in a model remains challenging. This study aimed to document the typology of pubertal development in a cohort of Taiwanese adolescent boys and then to examine how the associations between psychosocial variables across time vary by the patterns of pubertal development. A group of adolescent boys (n = 1,368) reported pubertal signs and psychosocial variables for 3 years since seventh grade. The growth mixture model revealed three major classes of pubertal transition: average pubertal growth, late-onset with rapid catch-up, and late-onset with slow catch-up. In a cross-lagged panel model, the multigroup analysis found the regression coefficients mostly invariant across all three classes, except those between deviant behavior and subsequent changes in depressive symptoms that were significantly positive only in the late-onset with slow catch-up group. Adolescent boys in this group were estimated to have the highest marginal level of depressive symptoms and deviant behavior in ninth grade among the three classes. Our study highlights the heterogeneity in boys' pubertal development and the role of the pubertal development pattern in their psychosocial development.

Heterogeneous trajectories of suicidal ideation among homeless youth: predictors and suicide-related outcomes.

The current study examined heterogeneous trajectories of suicidal ideation among homeless youth experiencing suicidal ideation over 9 months in a randomized controlled intervention study. Suicidal homeless youth (N = 150) were randomly assigned to Cognitive Therapy for Suicide Prevention (CTSP) + Treatment as Usual (TAU) or TAU alone. Youth reported their suicidal ideation four times during a 9-month period. We also assessed pretreatment mental health, demographic information and session attendance as predictors of the subgroups, as well as suicide-related factors as outcomes at the 9-month follow-up. Growth mixture models suggested three distinct trajectory groups among youth: Fast Declining (74.7%), Chronic (19.3%), and Steadily Declining (6.0%). Youth in the Chronic group used more substances at baseline than the Steadily Declining group, were more likely to be White, non-Hispanic than the Fast Declining group, and attended more CTSP sessions than other groups. Contrastingly, youth in the Steadily Declining group all experienced childhood abuse. Finally, youth in the Chronic group showed significant higher risk for future suicide compared to those in the Fast Declining group at 9 months. Findings support the heterogeneity of treatment responses in suicide intervention among homeless youth, with implications to improve treatment efforts in this very high-risk population.

The working life expectancy of American adults experiencing depression.

OBJECTIVES: To estimate the working life expectancies (WLE) of men and women with depression, examining depression by symptom trajectories from the late 20s to early 50s, and to estimate WLE by race/ethnicity and educational attainment. METHODS: Data from 9206 participants collected from 1979 to 2018 in the US National Longitudinal Survey of Youth 1979 cohort were used. Depression was measured using the Center for Epidemiologic Studies Depression Scale Short Form at four time points (age 28-35, age 30-37, age 40, and age 50). Labor force status was measured monthly starting at age 30 until age 58-62. Depressive symptom trajectories were estimated using growth mixture modeling and multistate modeling estimated WLE from age 30-60 for each gender and depressive symptom trajectory. RESULTS: Five latent symptom trajectories were established: a persistent low symptom trajectory (n = 6838), an episodic trajectory with high symptoms occurring before age 40 (n = 995), an episodic trajectory with high symptoms occurring around age 40 (n = 526), a trajectory with high symptoms occurring around age 50 (n = 570), and a persistent high symptom trajectory (n = 277). The WLE for men at age 30 was 30.3 years for the persistent low symptom trajectory, 22.8 years for the episodic before 40 trajectory, 19.6 years for the episodic around age 40 trajectory, 18.6 years for the episodic around age 50 trajectory, and 13.2 years for the persistent high symptom trajectory. Results were similar for women. WLE disparities between depression trajectories grew when stratified by race/ethnicity and education level. CONCLUSIONS: Roughly a quarter of individuals experienced episodic depressive symptoms. However, despite periods of low depressive symptoms, individuals were expected to be employed ~5-17 years less at age 30 compared to those with low symptoms. Accessible employment and mental health disability support policies and programs across the working life course may be effective in maintaining work attachment and improving WLE among those who experience depression.

Associations between hope and trajectories of critical consciousness among U.S. youth of color.

We examined associations between hope as an internal asset that supports positive youth development, and growth trajectories of three critical consciousness components. Using five waves of data collected over the course of high school (N = 618), we modeled growth trajectories of awareness of inequity (critical reflection), a sense of agency about taking sociopolitical action (critical agency), and behaviors targeting systems of oppression (critical action). Hope was highest among those with high trajectories of critical agency and critical action. Clear associations with hope emerged at the last time point for critical reflection, suggesting that sustained growth in critical reflection is associated with hope. When supporting the critical consciousness development of youth of color, concurrent support for hope may be instrumental.

Facilitating Growth Mixture Model Convergence in Preventive Interventions.

Growth mixture models (GMMs) are applied to intervention studies with repeated measures to explore heterogeneity in the intervention effect. However, traditional GMMs are known to be difficult to estimate, especially at sample sizes common in single-center interventions. Common strategies to coerce GMMs to converge involve post hoc adjustments to the model, particularly constraining covariance parameters to equality across classes. Methodological studies have shown that although convergence is improved with post hoc adjustments, they embed additional tenuous assumptions into the model that can adversely impact key aspects of the model such as number of classes extracted and the estimated growth trajectories in each class. To facilitate convergence without post hoc adjustments, this paper reviews the recent literature on covariance pattern mixture models, which approach GMMs from a marginal modeling tradition rather than the random effect modeling tradition used by traditional GMMs. We discuss how the marginal modeling tradition can avoid complexities in estimation encountered by GMMs that feature random effects, and we use data from a lifestyle intervention for increasing insulin sensitivity (a risk factor for type 2 diabetes) among 90 Latino adolescents with obesity to demonstrate our point. Specifically, GMMs featuring random effects-even with post hoc adjustments-fail to converge due to estimation errors, whereas covariance pattern mixture models following the marginal model tradition encounter no issues with estimation while maintaining the ability to answer all the research questions.

Reorienting Latent Variable Modeling for Supervised Learning.

Despite its potentials benefits, using prediction targets generated based on latent variable (LV) modeling is not a common practice in supervised learning, a dominating framework for developing prediction models. In supervised learning, it is typically assumed that the outcome to be predicted is clear and readily available, and therefore validating outcomes before predicting them is a foreign concept and an unnecessary step. The usual goal of LV modeling is inference, and therefore using it in supervised learning and in the prediction context requires a major conceptual shift. This study lays out methodological adjustments and conceptual shifts necessary for integrating LV modeling into supervised learning. It is shown that such integration is possible by combining the traditions of LV modeling, psychometrics, and supervised learning. In this interdisciplinary learning framework, generating practical outcomes using LV modeling and systematically validating them based on clinical validators are the two main strategies. In the example using the data from the Longitudinal Assessment of Manic Symptoms (LAMS) Study, a large pool of candidate outcomes is generated by flexible LV modeling. It is demonstrated that this exploratory situation can be used as an opportunity to tailor desirable prediction targets taking advantage of contemporary science and clinical insights.

Parent and child adjustment dual trajectories at the beginning of the COVID-19 syndemic.

Children and their families have been significantly impacted by the unfolding of the COVID-19 syndemic. We sought to identify (1) groups of families with distinct profiles of joint trajectories of parental anxiety and child emotional distress and (2) protective and risk factors associated with these dual-trajectory profiles. A sample of 488 parents (65% White; 77% mothers) with 3- to 8-year-old children (MAge  = 5.04, SDAge  = 1.59) was followed from late March to early July in 2020. Survey data on parent (i.e., anxiety symptoms) and child (i.e., emotional distress) adjustment were collected at three time points. Using multivariate growth mixture modeling, we identified one group with low parental anxiety and child emotional distress (42.7%) and three other distinct groups with varying risk levels among parents and/or children. We also identified protective (e.g., positive parenting) and risk (e.g., child negative affect, negative parenting, perceived stress with racism) factors in predicting parent and child adjustment. It can be concluded that, overall, our sample (mostly middle- and high-socioeconomic status families) demonstrated family resilience amid COVID-19, consistent with prior disaster coping literature. At the same time, our findings also indicated the need to identify at-risk families and modifiable factors for post-disaster public health interventions.