This article demonstrates the application of residual dynamic structural equation modeling (RDSEM) for analyzing custom contrasts in experimental factorial designs. Previous applications of RDSEM have often focused on ecological momentary assessment and daily diary data. However, RDSEM was explicitly developed for intensive longitudinal data more generally, including settings with very short time intervals between observations. Beyond these types of studies, RDSEM is also well suited for analyzing data from laboratory studies such as eye-tracking or reaction time experiments. We compare three analytic approaches, namely analysis of variance, linear mixed models, and RDSEM, emphasizing the unique advantages of RDSEM. Although often applied to momentary assessment data, RDSEM proves highly effective for experimental analysis, offering the ability to integrate both time-varying and time-invariant covariates, model autoregressive effects, and capture interindividual differences in residual variances / intraindividual variability. These strengths arise from RDSEM's integration of time-series, multilevel, and latent variable modeling, all implemented through Bayesian estimation.

Adolescent tobacco and nicotine use is a major public health concern, with lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority (LGBTQ+) adolescents showing disproportionately high use compared to their heterosexual and cisgender peers. Research suggests factors such as socialization, stress, mood, and craving exacerbate tobacco and nicotine use, however, there is a dearth of knowledge of how these factors influence tobacco, nicotine, and cannabis use among LGBTQ+ adolescents in general, and particularly on a momentary basis. The Puff Break study aimed to utilize ecological momentary assessment (EMA) to assess real-time predictors of tobacco, nicotine, and cannabis product use among LGBTQ+ adolescents. The Puff Break study protocol was adapted from existing EMA protocols, key informant recommendations, LGBTQ+ adolescent perspectives, and insights from community members. Recruitment occurred via multiple channels, with high recruitment results via social media. Eligible participants were ages 14-19, self-identified as LGBTQ+, and used tobacco, nicotine, or cannabis products at least once in the past 30 days. The EMA pilot began with a 1.5 hour-long in-person or virtual meeting where participants completed a timeline-follow-back assessment for tobacco and nicotine use, salivary cotinine assessment, baseline survey, and EMA protocol training. Then, participants completed a 2-week EMA trial where they received 1-2 minute surveys 5 times a day. Within a week of completing the EMA trial, participants concluded with an exit survey and exit interview. Analyses will include overall descriptive statistics on the demographics of our enrolled participants, along with evaluating the feasibility and acceptability of the Puff Break EMA protocol. We will also use multilevel modeling techniques to estimate both contemporaneous and lagged associations between stress, socialization, and craving (exposures) and smoking (outcome: combustible cigarette, smokeless product, e-cigarette, and cannabis use). Lastly, qualitative thematic analysis will be used to identify robust tailoring variables, intervention options, and decision rules to support future Just-in-Time-Adaptive Intervention (JITAI) development. Puff Break is an innovative EMA protocol developed to capture factors influencing tobacco, nicotine, and cannabis use among LGBTQ+ youth. Despite some inherent limitations to the EMA design, the Puff Break protocol has potential to inform the development of a JITAI to reduce tobacco, nicotine, and cannabis use among LGBTQ+ adolescents. Not applicable - This study is not registered as a trial.

U.S. Hispanic/Latino households disproportionally experience food insecurity, which may intersect with their food environments and food shopping behaviors to shape diet and health, but more representative findings are needed. We identified latent classes related to household food security (HFS), food environments, and food shopping behaviors among U.S. Hispanic/Latino households, and investigated their relationships with sociodemographic characteristics. We used cross-sectional data from 983 adult caregivers residing with youth (8-16 y) and participating in the multisite Study of Latino Youth. Caregivers completed the USDA HFS Survey Module (high, marginal, low, very low FS), a 5-item perceived neighborhood food environment (healthy food availability, quality, cost) questionnaire, and a 5-item food outlet shopping frequency questionnaire. We identified the best-fitting solution of latent classes by examining standard fit criteria and determined the relationship of latent classes to distal sociodemographic characteristics. We identified a 5-class solution. The “average quality, somewhat costly food environment” class (19.7 %) had low and high HFS and shopped at a variety of food stores; this class had the highest proportion of participants who were foreign-born (96 %) and reporting Spanish as their preferred language (90 %). The “high quality, high-cost food environment, food-insecure household” class (22.6 %) shopped at supermarkets and had the highest proportion of participants with a household income of ≤$20,000 (68 %). The “poor quality, high-cost food environment” class (16.8 %) had low and high HFS and shopped at supermarkets and convenience stores; this class had the highest proportion of participants who were single (33 %), without a vehicle (53 %), and reporting English as their preferred language (39 %). The “high quality, somewhat costly food environment, food-secure household” class (15.0 %) shopped at a variety of food stores and had the highest proportion (65 %) of participants with a household income of >$20,000. The “high quality, affordable food environment, food-secure household” class (25.9 %) shopped at supermarkets and had the highest proportion of participants who were US-born (25 %). U.S. Hispanic/Latino adults living with youth reported distinct combinations of HFS status, perceived neighborhood food environments, and food shopping behaviors, which underscores the complexity of factors defining adequate food access.

Intergenerational risk within families, stemming from familial history of mental health problems and encompassing exposure to childhood adversity, poses challenges to adolescent adjustment. However, it is important to recognize that negative developmental outcomes associated with intergenerational risk are not inevitable. To better understand resilience in this context, there is a need for studies that systematically compare different models of resilience. Further, few studies have estimated what level of adjustment should be expected for youth with high intergenerational risk but also a diverse set of strengths and competencies. Here, an intergenerational risk pathway and compensatory and protective resilience models were evaluated in the Future of Families and Child Wellbeing Study (N = 4,897, 52% female, 49% non-Hispanic Black at the age 15 assessment). The link between history of mental health problems in maternal grandparents and adolescent maladjustment (depressive symptoms, substance use, delinquent behavior, and troubles at school) was serially mediated through maternal mental health problems and its association with children's exposure to adversity. Data-driven trajectory analyses identified participants characterized by increased exposure to multiple types of adversity across childhood. Chronic exposure to multiple adversities, in turn, predicted increased adolescent maladjustment. Yet, resilience factors, including childhood social skills, perseverance, and connectedness at school, effectively offset intergenerational risks. Adolescents with high intergenerational risk who experienced high levels of these childhood assets demonstrated adjustment that was comparable to their average-risk and low-risk peers. These findings advance our understanding of pathways of intergenerational risk and provide new evidence for a compensatory model over a protective model of resilience. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Heterosexist victimization constitutes a severe source of social stress with enduring effects on mental health and the adrenocortical functioning of lesbian, gay, bisexual, transgender, and queer (LGTBQ) emerging adults. However, it is unknown what roles lower or higher diurnal cortisol at waking (cortisol intercepts) and less variable fluctuations ("flatter" slopes) play in the links between heterosexist victimization and depressive symptoms. In accordance with diathesis-stress, allostatic load, and biological embedding perspectives, we examined whether cortisol intercepts and slopes moderated or mediated the predictive associations of heterosexist victimization with depressive symptoms over 24-months. Heterosexist victimization was expected to predict depressive symptoms most strongly for LGBTQ emerging adults with flatter cortisol slopes (i.e., moderation), and cortisol intercepts and slopes were expected to indirectly link heterosexist victimization with depressive symptoms (i.e., mediation). Latinx and White LGBTQ emerging adults (N = 97; ages 18-29, M = 23.91 years, SD = 2.63) provided saliva samples and questionnaire responses during a four-day testing protocol at baseline; two additional assessments of depressive symptoms were completed 9- and 24-months later. Cortisol intercepts and slopes moderated associations of heterosexist victimization with both contemporaneous and prospective depressive symptoms. Heterosexist victimization was positively associated with contemporaneous depressive symptoms and decreases in depressive symptoms over two years when LGBTQ emerging adults also had steeper cortisol slopes. Heterosexist discrimination was associated with increases in depressive symptoms prospectively among participants with lower cortisol intercepts. There was no evidence for mediation. Thus, patterns of diurnal adrenocortical functioning may distinguish between LGBTQ emerging adults who are more prone to acute versus prolonged depressive symptoms when they experience heterosexist victimization.

Are bilingual language networks flexible enough to dynamically adapt to neurological insult? We examined language lateralization in 24 bilingual and 46 monolingual adults with temporal lobe epilepsy using functional MRI. In a group of primarily early sequential bilingual patients, the first acquired language (L1) showed more bilateral lateralization than in monolingual patients, with no effect of seizure onset laterality. In contrast, the second-acquired language (L2) was more bilateral in the presence of left hemisphere epilepsy and more left-lateralized in right hemisphere epilepsy. Most notably, in left hemisphere epilepsy, seizure onset closer to L2 acquisition was associated with more right-lateralized L2 representation. These findings suggest a compensatory process in which L2 networks strengthen in the hemisphere opposite the seizure focus, potentially reflecting neural adaptation in early bilingualism. Conversely, L1 appears to have less dynamic reorganization in response to neurological insult. Together, these findings highlight the importance of timing in both language experience and neurological stress in shaping language network organization. They support the view that the bilingual brain is not simply the sum of two monolingual systems, but a dynamic and unique system marked by high interindividual variability, in which divergence between languages may emerge under certain experience- and context-dependent conditions.

While racial disparities in HIV antiretroviral treatment (ART) adherence and viral suppression among sexual minority men (SMM) with HIV persist, resilience may serve as an important protective factor. There is, however, a dearth of research exploring the longitudinal associations between resilience and ART adherence among this group. As such, the current study examined prospective associations, including the between- and within-person effects, between resilience and ART adherence among racially diverse SMM with HIV. Data were drawn from Thrive With Me (TWM), a randomized controlled trial of an mHealth intervention targeting ART adherence among SMM. Generalized estimating equations (GEEs) models examined longitudinal associations, including between- and within-person effects, between resilience scores and self-reported 30-day ART adherence, dichotomized as optimal (≥ 90% of doses) versus suboptimal (< 90% of doses) across the 17-month study timeframe, while controlling for covariates. Among 401 SMM with HIV that completed the TWM baseline assessment (M age = 39.1 years, Standard Deviation = 10.8), 59.9% self-identified as Black/African American. In GEE models, resilience scores were prospectively associated with optimal 30-day ART adherence (b = 0.06, β = 0.38, p < 0.001), at the between-person level, above the effects of covariates. In moderation analyses, resilience scores were associated with optimal ART adherence among Black/African American SMM but not among those identifying as White or another race. These results suggest bolstering resilience may be an important strategy for future interventions aiming to improve ART adherence over time for racially and ethnically diverse SMM with HIV.

Objective: An aim of quantitative intersectional research is to model the joint impact of multiple social positions on health risk behaviors. Although moderated multiple regression is frequently used to pursue intersectional research hypotheses, such parametric approaches may produce unreliable effect estimates due to data sparsity and high dimensionality. Machine learning provides viable alternatives, offering greater flexibility in evaluating many candidate interactions amid sparse data conditions, yet remains rarely employed. This study introduces group-lasso interaction network (glinternet), a novel machine learning approach involving hierarchical regularization, to assess intersectional differences in substance use prevalence. Method: Utilizing variable selection and parameter stabilization functionality for main and interaction effects, glinternet was employed to examine two-way interactions between three primary social positions (gender, sexual orientation, and race) predicting heavy episodic drinking, cannabis use, and cigarette use prevalence. Analyses were conducted using the All of Us Research Program (N = 283,403), a national sample with high representation from populations historically underrepresented in biomedical research. Results were replicated using holdout cross-validation and compared against logistic regression estimates. Results: Glinternet prevalence estimates were more stable across discovery and replication samples relative to logistic regression, particularly among sparsely represented groups. Prevalence estimates for cigarette and cannabis use were elevated among sexual minority and White cisgender women compared to heterosexual and non-White women, respectively. Conclusions: Glinternet may improve upon traditional moderated multiple regression methods for pursuing intersectional hypotheses by improving model parsimony and parameter stability, providing novel means for quantifying health disparities among intersectional social positions. Public Health Significance Statement This study demonstrated heterogeneity in substance use prevalence among cisgender women, such that sexual orientation minority and White cisgender women may be at elevated risk for both cigarette and cannabis use. Further, this study showed that group-lasso interaction network, a regularization approach based in machine learning, may improve upon traditional methods of analysis for quantitative intersectional studies by improving stability in prevalence estimates amid small and/or unbalanced sample size conditions.

Abstract Background Pediatric depression is a global concern that has fueled efforts for enhanced detection and treatment engagement. As one example, the US Preventive Services Task Force recommends depression screening for adolescents ages 12–18 years. While many health systems have implemented components of depression screening protocols, there is limited evidence of effective follow-up for pediatric depression. A key barrier is timely team communication and coordination across clinicians and staff within and across service areas for prompt service linkage. However, team effectiveness interventions have been shown to improve team processes and outcomes and can be applied in healthcare settings. Methods This project aims to refine and test a team communication training implementation strategy to improve implementation of an existing pediatric depression screening protocol in a large pediatric healthcare system. The team will be defined as part of the study but is expected to include medical assistants, nurses, physicians, and behavioral health clinicians within and across departments. The implementation strategy will target team mechanisms at the team-level (i.e., intra-organizational alignment and implementation climate) and team member-level (i.e., communication, coordination, psychological safety, and shared cognition). First, the project will use mixed methods to refine the team training strategy to fit the organizational context and workflows. Next, a hybrid type 3 implementation-effectiveness pilot trial will assess the initial effectiveness of the team communication training (implementation strategy) paired with the current universal depression screening protocol (clinical intervention) on implementation outcomes (i.e., feasibility, acceptability, appropriateness, workflow efficiency) and clinical/services outcomes (increased frequency of needed screening and reduced time to service linkage). Finally, the study will assess mechanisms at the team and team member levels that may affect implementation outcomes. Discussion Team communication training is hypothesized to lead to improved, efficient, and effective decision-making to increase the compliance with depression screening and timely service linkage. Findings are expected to yield better understanding and examples of how to optimize team communication to improve efficiency and effectiveness in the pediatric depression screening-to-treatment cascade. This should also culminate in improved implementation outcomes including patient engagement critical to address the youth mental health crisis. Trial registration NCT06527196. Trial Sponsor: University of California San Diego.

Physical exercise is an emerging target for improving cognition in aging and neurological disease. Due to the beneficial impact of exercise on hippocampal health and the vulnerability of the hippocampus in medication- resistant temporal lobe epilepsy (TLE), exercise could present a promising intervention in TLE. We investigated whether exercise engagement is associated with verbal memory function and hippocampal integrity in 29 young to middle-aged adults with refractory TLE and 21 demographically matched controls. Participants completed a self-reported questionnaire of weekly exercise, three tests of verbal memory, and a subset (n = 44) underwent structural MRI. Individuals with TLE self-reported lower exercise scores than controls across all levels of exercise intensity (p < 0.001). In TLE, greater exercise engagement was associated with better verbal memory (word-list recall and associative learning; rho = 0.46-0.47; p s FDR < 0.05), and with larger contralateral hippocampal volumes ( rho = 0.61; p < 0.01). These effects remained significant when controlling for epilepsy- related and demographic factors. Within the limitations of a cross-sectional observational study, these findings suggest that exercise may be a cognitive reserve factor in TLE, potentially mitigating memory decline by enhancing contralateral hippocampal integrity. With future replication and longitudinal studies to clarify the causal pathways of these relationships, exercise holds promise as a low-cost, accessible, and modifiable lifestyle target for improving cognitive health in individuals with refractory TLE.

This randomized controlled study assessed the feasibility, acceptability, and preliminary impact of the PrEP iT! mHealth intervention designed to improve PrEP adherence among young men who have sex with men (YMSM). A national sample of 80 YMSM in the U.S. (Mage = 25 years; 54

Latent repeated measures ANOVA (L-RM-ANOVA) has recently been proposed as an alternative to traditional repeated measures ANOVA. L-RM-ANOVA builds upon structural equation modeling and enables researchers to investigate interindividual differences in main/interaction effects, examine custom contrasts, incorporate a measurement model, and account for missing data. However, L-RM-ANOVA uses maximum likelihood and thus cannot incorporate prior information and can have poor statistical properties in small samples. We show how L-RM-ANOVA can be used with Bayesian estimation to resolve the aforementioned issues. We demonstrate how to place informative priors on model parameters that constitute main and interaction effects. We further show how to place weakly informative priors on standardized parameters which can be used when no prior information is available. We conclude that Bayesian estimation can lower Type 1 error and bias, and increase power and efficiency when priors are chosen adequately. We demonstrate the approach using a real empirical example and guide the readers through specification of the model. We argue that ANOVA tables and incomplete descriptive statistics are not sufficient information to specify informative priors, and we identify which parameter estimates should be reported in future research; thereby promoting cumulative research.

Background. Patients with primary brain tumors demonstrate heterogeneous patterns of cognitive dysfunction, which we explore using latent profile analysis to identify cognitive phenotypes and their trajectories in patients receiving radiotherapy (RT). Methods. Ninety-six patients completed neuropsychological testing before and post-RT (3, 6, and 12 months) on a prospective longitudinal trial, including measures of processing speed, executive function, language, and verbal and visual memory. Models with 2-4 classes were examined. Demographic and clinical data were examined across phenotypes and post-RT cognitive change was evaluated. Results. The optimal model identified 3 unique cognitive phenotypes including a group of patients with generalized impairments (11.5%), a group with isolated verbal memory impairments (21.9%), and a group with minimal impairments (66.7%). The Verbal Memory phenotype had fewer years of education (P = .007) and a greater proportion of males (P < .001); the Generalized group had a greater proportion of patients with IDH-wild type gliomas and showed greater symptoms of anxiety and poorer quality of life (P-values < .05); and the Minimal Impairment phenotype had higher rates of IDH-Mutant gliomas. Approximately 50% of patients declined on at least one cognitive domain with memory being the most vulnerable. Patients who declined reported greater symptoms of depression (P = .007) and poorer quality of life (P = .025). Conclusions. We identified 3 distinct cognitive phenotypes in patients with primary brain tumors receiving RT, each associated with unique demographic and clinical (eg, IDH mutational status) profiles, with mood symptoms associated with late cognitive decline. This patient-centered approach enhances our understanding of clinical profiles associated with cognitive dysfunction and treatment-related neurotoxicity.

OBJECTIVE Posttraumatic cognitions are a mechanism of posttraumatic stress disorder (PTSD) symptom reduction in trauma-focused interventions for PTSD. It is unclear how changes in posttraumatic cognitions are associated with important clinical correlates of PTSD, including drinking and psychosocial functioning. This study examined if changes in posttraumatic cognitions during integrated treatment for co-occurring PTSD/alcohol use disorder (AUD) were associated with concurrent improvements in PTSD severity, heavy drinking, and psychosocial functioning. METHOD One hundred nineteen veterans (65.5% white and 89.9% men) with PTSD/AUD randomized to receive Concurrent Treatment of PTSD and Substance Use Disorders using Prolonged Exposure or Seeking Safety completed assessments of posttraumatic cognitions (Posttraumatic Cognitions Inventory), PTSD severity (Clinician-Administered PTSD Scale for DSM-5), drinking (Timeline Followback), and psychosocial functioning (Medical Outcomes Survey SF-36) at baseline, posttreatment, 3- and 6-month follow-up. RESULTS Structural equation models indicated that posttraumatic cognitions improved significantly during treatments for PTSD/AUD with no significant treatment differences. Reductions in posttraumatic cognitions during treatment were associated with concurrent improvements in PTSD severity and functioning, and differentially associated with drinking. CONCLUSIONS Findings suggest that changes in posttraumatic cognitions in integrated treatments for PTSD/AUD are not solely important for symptom change but are implicated in improvements in functioning. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

OBJECTIVE:Risk for memory decline is a common concern for individuals with temporal lobe epilepsy (TLE) undergoing surgery. Global and local network abnormalities are well documented in TLE. However, it is less known whether network abnormalities predict postsurgical memory decline. The authors examined the role of preoperative global and local white matter network organization and risk of postoperative memory decline in TLE. METHODS:One hundred one individuals with TLE (n = 51 with left TLE and 50 with right TLE) underwent preoperative T1-weighted MRI, diffusion MRI, and neuropsychological memory testing in a prospective longitudinal study. Fifty-six age- and sex-matched controls completed the same protocol. Forty-four patients (22 with left TLE and 22 with right TLE) subsequently underwent temporal lobe surgery and postoperative memory testing. Preoperative structural connectomes were generated via diffusion tractography and analyzed using measures of global and local (i.e., medial temporal lobe [MTL]) network organization. Global metrics measured network integration and specialization. The local metric was calculated as an asymmetry of the mean local efficiency between the ipsilateral and contralateral MTLs (i.e., MTL network asymmetry). RESULTS:Higher preoperative global network integration and specialization were associated with higher preoperative verbal memory function in patients with left TLE. Higher preoperative global network integration and specialization, as well as greater leftward MTL network asymmetry, predicted greater postoperative verbal memory decline for patients with left TLE. No significant effects were observed in right TLE. Accounting for preoperative memory score and hippocampal volume asymmetry, MTL network asymmetry uniquely explained 25%-33% of the variance in verbal memory decline for left TLE and outperformed hippocampal volume asymmetry and global network metrics. MTL network asymmetry alone produced good diagnostic classification of memory decline in left TLE (i.e., an area under the receiver operating characteristic curve of 0.80-0.84 and correct classification of 65%-76% of cases with cross-validation). CONCLUSIONS:These preliminary data suggest that global white matter network disruption contributes to verbal memory impairment preoperatively and predicts postsurgical verbal memory outcomes in left TLE. However, a leftward asymmetry of MTL white matter network organization may confer the highest risk for verbal memory decline. Although this requires replication in a larger sample, the authors demonstrate the importance of characterizing preoperative local white matter network properties within the to-be-operated hemisphere and the reserve capacity of the contralateral MTL network, which may eventually be useful in presurgical planning.

Consuming too few fruits and vegetables and excess fat can increase the risk of childhood obesity. Interventions which target mediators such as caregivers’ dietary intake, parenting strategies, and the family meal context can improve children’s diets. A quasi-experimental, pre–post intervention with four conditions (healthcare (HC-only), public health (PH-only), HC + PH, and control) was implemented to assess the effects of the interventions and the effects of the mediators. HC (implemented with the Obesity Care Model) and PH interventions entailed capacity building; policy, system, and environment changes; and a small-scale media campaign to promote healthy eating. Linear mixed models were used to assess intervention effects and the mediation analysis was performed. Predominantly Hispanic/Latino children and caregivers from rural communities in Imperial County, California, were measured at baseline (N = 1186 children/848 caregivers) and 12 months post-baseline (N = 985/706, respectively). Children who were overweight/obese in the HC-only condition (M = 1.32) consumed more cups of fruits at the 12-month follow-up than those in the control condition (M = 1.09; p = 0.04). No significant mediation was observed. Children in the PH-only condition consumed a significantly higher percentage of energy from fat (M = 36.01) at the follow-up than those in the control condition (M = 34.94, p < 0.01). An obesity intervention delivered through healthcare settings slightly improved fruit intake among at-risk children, but the mechanisms of effect remain unclear.

BACKGROUND AND OBJECTIVES:There is growing evidence that bilingualism can induce neuroplasticity and modulate neural efficiency, resulting in greater resistance to neurologic disease. However, whether bilingualism is beneficial to neural health in the presence of epilepsy is unknown. We tested whether bilingual individuals with temporal lobe epilepsy (TLE) have improved whole-brain structural white matter network organization.METHODS:Healthy controls and individuals with TLE recruited from 2 specialized epilepsy centers completed diffusion-weighted MRI and neuropsychological testing as part of an observational cohort study. Whole-brain connectomes were generated via diffusion tractography and analyzed using graph theory. Global analyses compared network integration (path length) and specialization (transitivity) in TLE vs controls and in a 2 (left vs right TLE) × 2 (bilingual vs monolingual) model. Local analyses compared mean local efficiency of predefined frontal-executive and language (i.e., perisylvian) subnetworks. Exploratory correlations examined associations between network organization and neuropsychological performance.RESULTS:A total of 29 bilingual and 88 monolingual individuals with TLE matched on several demographic and clinical variables and 81 age-matched healthy controls were included. Globally, a significant interaction between language status and side of seizure onset revealed higher network organization in bilinguals compared with monolinguals but only in left TLE (LTLE). Locally, bilinguals with LTLE showed higher efficiency in frontal-executive but not in perisylvian networks compared with LTLE monolinguals. Improved whole-brain network organization was associated with better executive function performance in bilingual but not monolingual LTLE.DISCUSSION:Higher white matter network organization in bilingual individuals with LTLE suggests a neuromodulatory effect of bilingualism on whole-brain connectivity in epilepsy, providing evidence for neural reserve. This may reflect attenuation of or compensation for epilepsy-related dysfunction of the left hemisphere, potentially driven by increased efficiency of frontal-executive networks that mediate dual-language control. This highlights a potential role of bilingualism as a protective factor in epilepsy, motivating further research across neurologic disorders to define mechanisms and develop interventions.

Cannabis use is rapidly increasing among older adults in the United States, in part to treat symptoms of common health conditions (e.g., chronic pain, sleep problems). Longitudinal studies of cannabis use and cognitive decline in aging populations living with chronic disease are lacking. We examined different levels of cannabis use and cognitive and everyday function over time among 297 older adults with HIV (ages 50–84 at baseline). Participants were classified based on average cannabis use: frequent (> weekly) ( n = 23), occasional (≤ weekly) ( n = 83), and non-cannabis users ( n =191) and were followed longitudinally for up to 10 years (average years of follow-up = 3.9). Multi-level models examined the effects of average and recent cannabis use on global cognition, global cognitive decline, and functional independence. Occasional cannabis users showed better global cognitive performance overall compared to non-cannabis users. Rates of cognitive decline and functional problems did not vary by average cannabis use. Recent cannabis use was linked to worse cognition at study visits when participants had THC+ urine toxicology—this short-term decrement in cognition was driven by worse memory and did not extend to reports of functional declines. Occasional (≤ weekly) cannabis use was associated with better global cognition over time in older adults with HIV, a group vulnerable to chronic inflammation and cognitive impairment. Recent THC exposure may have a temporary adverse impact on memory. To inform safe and efficacious medical cannabis use, the effects of specific cannabinoid doses on cognition and biological mechanisms must be investigated in older adults.

This article demonstrates how to perform univariate repeated measures ANOVA (U-RM-ANOVA) as a special case of structural equation models (SEMs). In the literature, sphericity is usually defined in terms of variances of pairwise differences of within-subject conditions. This article illustrates the original definition by Huynh and Feldt (1970) in terms of (co)variances of contrasts using SEM and demonstrates how to impose, test, and relax sphericity, and how to test main/interaction effects with and without the assumption of sphericity in SEM. We perform two simulation studies. The first study compares Mauchly’s sphericity test with an SEM based test and shows that the two approaches have a very similar Type 1 error and power. The second study compares U-RM-ANOVA with SEM for different degrees of departure from sphericity and shows that U-RM-ANOVA and SEM have similar statistical properties in terms of Type 1 error, power, as well as similar bias and efficiency of effect size estimates of main and interaction effects. We furthermore show how to implement sphericity in latent variable models and provide software to perform the proposed tests and analyses.

This article demonstrates how to use structural equation modeling (SEMing) in place of between-subjects analysis of variance (BS-ANOVA). More specifically, this article demonstrates how to closely reproduce the F-values and p-values from ANOVA (for all main and interactions effects) using an SEM model comparison approach (i.e., chi(2) difference tests between two SEMs that conform to the main and interaction effects of the null and alternative hypotheses of an ANOVA main or interaction effect). Therefore, researchers less familiar with SEM can use this article to test hypotheses common to BS-ANOVA, and potentially use this article as a steppingstone for implementing more complex SEMs (including modern methods for missing data, estimation of latent variables, and relaxation of homogeneity of variance assumptions).