Understanding the Consequences of Collinearity for Multilevel Models: The Importance of Disaggregation Across Levels.

In multilevel models, disaggregating predictors into level-specific parts (typically accomplished via centering) benefits parameter estimates and their interpretations. However, the importance of level-specificity has been sparsely addressed in multilevel literature concerning collinearity. In this study, we develop novel insights into the interactivity of centering and collinearity in multilevel models. After integrating the broad literatures on centering and collinearity, we review level-specific and conflated correlations in multilevel data. Next, by deriving formal relationships between predictor collinearity and multilevel model estimates, we demonstrate how the consequences of collinearity change across different centering specifications and identify data characteristics that may exacerbate or mitigate those consequences. We show that when all or some level-1 predictors are uncentered, slope estimates can be greatly biased by collinearity. Disaggregation of all predictors eliminates the possibility that fixed effect estimates will be biased due to collinearity alone; however, under some data conditions, collinearity is associated with biased standard errors and random effect (co)variance estimates. Finally, we illustrate the importance of disaggregation for diagnosing collinearity in multilevel data and provide recommendations for the use of level-specific collinearity diagnostics. Overall, the necessity of disaggregation for identifying and managing collinearity's consequences in multilevel models is clarified in novel ways.

Modeling variability in treatment effects for cluster randomized controlled trials using by-variable smooth functions in a generalized additive mixed model.

Variability in treatment effects is common in intervention studies using cluster randomized controlled trial (C-RCT) designs. Such variability is often examined in multilevel modeling (MLM) to understand how treatment effects (TRT) differ based on the level of a covariate (COV), called TRT × COV. In detecting TRT × COV effects using MLM, relationships between covariates and outcomes are assumed to vary across clusters linearly. However, this linearity assumption may not hold in all applications and an incorrect assumption may lead to biased statistical inference about TRT × COV effects. In this study, we present generalized additive mixed model (GAMM) specifications in which cluster-specific functional relationships between covariates and outcomes can be modeled using by-variable smooth functions. In addition, the implementation for GAMM specifications is explained using the mgcv R package (Wood, 2021). The usefulness of the GAMM specifications is illustrated using intervention data from a C-RCT. Results of simulation studies showed that parameters and by-variable smooth functions were recovered well in various multilevel designs and the misspecification of the relationship between covariates and outcomes led to biased estimates of TRT × COV effects. Furthermore, this study evaluated the extent to which the GAMM can be treated as an alternative model to MLM in the presence of a linear relationship.

Predictors of engagement in post-discharge quitline counseling among hospitalized smokers.

Quitlines provide evidence-based tobacco treatment and multiple calls yield higher quit rates. This study aimed to identify subgroups of smokers with greater quitline engagement following referral during hospitalization. Data were from a randomized clinical trial assessing the effectiveness of fax referral (referral faxed to proactive quitline) versus warm handoff (patient connected to quitline at bedside) (n = 1054). Classification and regression trees analyses evaluated individual and treatment/health system-related variables and their interactions. Among all participants, warm handoff, higher ratings of the tobacco treatment care transition, and being older predicted completing more quitline calls. Among patients enrolled in the quitline, higher transition of care ratings, being older, and use of cessation medication post-discharge predicted completing more calls. Three of the four factors influencing engagement were characteristics of treatment within the hospital (quality of tobacco treatment care transition and referral method) and therapy (use of cessation medications), suggesting potential targets to increase quitline engagement post-discharge.

Maternal Communication in Childhood Cancer: Factor Analysis and Relation to Maternal Distress.

Objective: This study aimed to characterize mothers' communication with their children in a sample of families with a new or newly relapsed pediatric cancer diagnosis, first using factor analysis and second using structural equation modeling to examine relations between self-reported maternal distress (anxiety, depression, and posttraumatic stress) and maternal communication in prospective analyses. A hierarchical model of communication was proposed, based on a theoretical framework of warmth and control. Methods: The sample included 115 children (age 5-17 years) with new or newly relapsed cancer (41% leukemia, 18% lymphoma, 6% brain tumor, and 35% other) and their mothers. Mothers reported distress (Beck Anxiety Inventory, Beck Depression Inventory-II, and Impact of Events Scale-Revised) 2 months after diagnosis (Time 1). Three months later (Time 2), mother-child dyads were video-recorded discussing cancer. Maternal communication was coded with the Iowa Family Interaction Ratings Scales. Results: Confirmatory factor analysis demonstrated poor fit. Exploratory factor analysis suggested a six-factor model (root mean square error of approximation = .04) with one factor reflecting Positive Communication, four factors reflecting Negative Communication (Hostile/Intrusive, Lecturing, Withdrawn, and Inconsistent), and one factor reflecting Expression of Negative Affect. Maternal distress symptoms at Time 1 were all significantly, negatively related to Positive Communication and differentially related to Negative Communication factors at Time 2. Maternal posttraumatic stress and depressive symptoms each predicted Expression of Negative Affect. Conclusions: Findings provide a nuanced understanding of maternal communication in pediatric cancer and identify prospective pathways of risk between maternal distress and communication that can be targeted in intervention.

Anxiety and Depression in Children of Depressed Parents: Dynamics of Change in a Preventive Intervention.

The current study examined effects of a preventive intervention on patterns of change in symptoms of anxiety and depression in a sample of children of depressed parents. Parents with a history of depression (N = 180) and their children (N = 242; 50% female; Mage = 11.38; 74% Euro-American) enrolled in an intervention to prevent psychopathology in youth. Families were randomized to a family group cognitive behavioral intervention (FGCB) or a written information (WI) control condition. Parents and youth completed the Child Behavior Checklist and Youth Self Report at baseline, 6-, 12-, 18-, and 24-month follow up. Youth in the FGCB intervention reported significantly greater declines in symptoms of both anxiety and depression at 6, 12, and 18 months compared to youth in the WI condition. Youth with higher baseline levels of each symptom (e.g., anxiety) reported greater declines in the other symptom (e.g., depression) from 0 to 6 months in the FGCB intervention only. Changes in anxiety symptoms from 0 to 6 months predicted different patterns of subsequent changes in depressive symptoms from 6 to 12 months for the two conditions, such that declines in anxiety preceded and predicted greater declines in depression for FGCB youth but lesser increases in depression for WI youth. Findings inform transdiagnostic approaches to preventive interventions for at-risk youth, suggesting that both initial symptom levels and initial magnitude of change in symptoms are important to understand subsequent patterns of change in response to intervention.

Multiple Local Solutions and Geomin Rotation.

In exploratory factor analysis, factor rotation is conducted to improve model interpretability. A promising and increasingly popular factor rotation method is geomin rotation. Geomin rotation, however, frequently encounters multiple local solutions. We report a simulation study that explores the frequency of local solutions in geomin rotation and the implications of such phenomena. The findings include: (1) multiple local solutions exist for geomin rotation in a variety of situations; (2) ϵ = .01 provides satisfactory rotated factor loadings in most situations; (3) 100 random starts appear sufficient to examine the multiple solution phenomenon; and (4) a population global solution may correspond to a sample local solution rather than the sample global solution.

When Emotional Pain Becomes Physical: Adverse Childhood Experiences, Pain, and the Role of Mood and Anxiety Disorders.

OBJECTIVE: We examined the association between retrospective reports of adverse childhood experiences (ACEs) and painful medical conditions. We also examined the mediating and moderating roles of mood and anxiety disorders in the ACEs-painful medical conditions relationship. METHOD: Ten-year longitudinal data were obtained from the National Comorbidity Surveys (NCS-1, NCS-2; N = 5001). The NCS-1 obtained reports of ACEs, current health conditions, current pain severity, and mood and anxiety disorders. The NCS-2 assessed for painful medical conditions (e.g., arthritis/rheumatism, chronic back/neck problems, severe headaches, other chronic pain). RESULTS: Specific ACEs (e.g., verbal and sexual abuse, parental psychopathology, and early parental loss) were associated with the painful medical conditions. Baseline measures of depression, bipolar disorder, and posttraumatic stress disorder were also associated with the number of painful medical conditions. Anxiety and mood disorders were found to partially mediate the ACEs-painful medical conditions relationship. We determined through mediation analyses that ACEs were linked to an increase in anxiety and mood disorders, which, in turn, were associated with an increase in the number of painful medical conditions. We determined through moderation analyses that ACEs had an effect on increasing the painful medical conditions at both high and low levels of anxiety and mood disorders; though, surprisingly, the effect was greater among participants at lower levels of mood and anxiety disorders. CONCLUSION: There are pernicious effects of ACEs across mental and physical domains. Dysregulation of the hypothalamic-pituitary-adrenal stress response and the theory of reserve capacity are reviewed to integrate our findings of the complex relationships.

Advances in mediation analysis: a survey and synthesis of new developments.

Mediation processes are fundamental to many classic and emerging theoretical paradigms within psychology. Innovative methods continue to be developed to address the diverse needs of researchers studying such indirect effects. This review provides a survey and synthesis of four areas of active methodological research: (a) mediation analysis for longitudinal data, (b) causal inference for indirect effects, (c) mediation analysis for discrete and nonnormal variables, and (d) mediation assessment in multilevel designs. The aim of this review is to aid in the dissemination of developments in these four areas and suggest directions for future research.

Comparative and cost effectiveness of telemedicine versus telephone counseling for smoking cessation.

BACKGROUND: In rural America, cigarette smoking is prevalent and health care providers lack the time and resources to help smokers quit. Telephone quitlines are important avenues for cessation services in rural areas, but they are poorly integrated with local health care resources. OBJECTIVE: The intent of the study was to assess the comparative effectiveness and cost effectiveness of two models for delivering expert tobacco treatment at a distance: telemedicine counseling that was integrated into smokers' primary care clinics (Integrated Telemedicine-ITM) versus telephone counseling, similar to telephone quitline counseling, delivered to smokers in their homes (Phone). METHODS: Smokers (n=566) were recruited offline from 20 primary care and safety net clinics across Kansas. They were randomly assigned to receive 4 sessions of ITM or 4 sessions of Phone counseling. Patients in ITM received real-time video counseling, similar to Skype, delivered by computer/webcams in clinic exam rooms. Three full-time equivalent trained counselors delivered the counseling. The counseling duration and content was the same in both groups and was available in Spanish or English. Both groups also received identical materials and assistance in selecting and obtaining cessation medications. The primary outcome was verified 7-day point prevalence smoking abstinence at month 12, using an intent-to-treat analysis. RESULTS: There were no significant baseline differences between groups, and the trial achieved 88% follow-up at 12 months. Verified abstinence at 12 months did not significantly differ between ITM or Phone (9.8%, 27/280 vs 12%, 34/286; P=.406). Phone participants completed somewhat more counseling sessions than ITM (mean 2.6, SD 1.5 vs mean 2.4, SD 1.5; P=.0837); however, participants in ITM were significantly more likely to use cessation medications than participants in Phone (55.9%, 128/280 vs 46.1%, 107/286; P=.03). Compared to Phone participants, ITM participants were significantly more likely to recommend the program to a family member or friend (P=.0075). From the combined provider plus participant (societal) perspective, Phone was significantly less costly than ITM. Participants in ITM had to incur time and mileage costs to travel to clinics for ITM sessions. From the provider perspective, counseling costs were similar between ITM (US $45.46, SD 31.50) and Phone (US $49.58, SD 33.35); however, total provider costs varied widely depending on how the clinic space for delivering ITM was valued. CONCLUSIONS: Findings did not support the superiority of ITM over telephone counseling for helping rural patients quit smoking. ITM increased utilization of cessation pharmacotherapy and produced higher participant satisfaction, but Phone counseling was significantly less expensive. Future interventions could combine elements of both approaches to optimize pharmacotherapy utilization, counseling adherence, and satisfaction. Such an approach could commence with a telemedicine-delivered clinic office visit for pharmacotherapy guidance, and continue with telephone or real-time video counseling delivered via mobile phones to flexibly deliver behavioral support to patients where they most need it-in their homes and communities. TRIAL REGISTRATION: Clinicaltrials.gov NCT00843505; http://clinicaltrials.gov/ct2/show/NCT00843505 (Archived by WebCite at http://www.webcitation.org/6YKSinVZ9).

The Importance of Temporal Design: How Do Measurement Intervals Affect the Accuracy and Efficiency of Parameter Estimates in Longitudinal Research?

The timing (spacing) of assessments is an important component of longitudinal research. The purpose of the present study is to determine methods of timing the collection of longitudinal data that provide better parameter recovery in mixed effects nonlinear growth modeling. A simulation study was conducted, varying function type, as well as the number of measurement occasions, in order to examine the effect of timing on the accuracy and efficiency of parameter estimates. The number of measurement occasions was associated with greater efficiency for all functional forms and was associated with greater accuracy for the intrinsically nonlinear functions. In general, concentrating measurement occasions toward the left or at the extremes was associated with increased efficiency when estimating the intercepts of intrinsically linear functions, and concentrating values where the curvature of the function was greatest generally resulted in the best recovery for intrinsically nonlinear functions. Results from this study can be used in conjunction with theory to improve the design of longitudinal research studies. In addition, an R program is provided for researchers to run customized simulations to identify optimal sampling schedules for their own research.

Sensitive periods for the effect of peer victimization on self-cognition: moderation by age and gender.

The link between the experience of peer victimization (PV) and future psychological maladjustment has been consistently documented; however, little is known about intermediary cognitive processes that underlie this relation or how these processes vary across childhood. The present study examined the prospective relations between physical and relational PV and the development of negative and positive automatic thoughts and self-cognitions. Self-reports of cognitions and peer nomination measures of victimization were obtained from 1,242 children and young adolescents (Grades 3 through 6) in a two-wave longitudinal study. The results revealed that PV predicted significant increases in negative views of the self, world, and future and decreases in self-perceived competence for girls under 11 years of age, with the effect being stronger for younger girls. PV was not significantly associated with changes in positive or negative self-cognitions for older girls or for boys of any age. These findings support the hypothesis that PV may be linked to future psychopathology through its influence on self-cognitions, but only for girls.

Advancing complex explanatory conceptualizations of daily negative and positive affect: trigger and maintenance coping action patterns.

The present study addressed a fundamental gap between research and clinical work by advancing complex explanatory conceptualizations of coping action patterns that trigger and maintain daily negative affect and (low) positive affect. One hundred ninety-six community adults completed measures of perfectionism, and then 6 months later completed questionnaires at the end of the day for 14 consecutive days to provide simultaneous assessments of appraisals, coping, and affect across different stressful situations in everyday life. Multilevel structural equation modeling (MSEM) supported complex explanatory conceptualizations that demonstrated (a) disengagement trigger patterns consisting of several distinct appraisals (e.g., event stress) and coping strategies (e.g., avoidant coping) that commonly operate together across many different stressors when the typical individual experiences daily increases in negative affect and drops in positive affect; and (b) disengagement maintenance patterns composed of different appraisal and coping maintenance factors that, in combination, can explain why individuals with higher levels of self-critical perfectionism have persistent daily negative affect and low positive mood 6 months later. In parallel, engagement patterns (triggers and maintenance) composed of distinct appraisals (e.g., perceived social support) and coping strategies (e.g., problem-focused coping) were linked to compensatory experiences of daily positive affect. These findings demonstrate the promise of using daily diary methodologies and MSEM to promote a shared understanding between therapists and clients of trigger and maintenance coping action patterns that explain what precipitates and perpetuates clients' difficulties, which, in turn, can help achieve the 2 overarching therapy goals of reducing clients' distress and bolstering resilience.

Ignoring Clustering in Confirmatory Factor Analysis: Some Consequences for Model Fit and Standardized Parameter Estimates.

In many situations, researchers collect multilevel (clustered or nested) data yet analyze the data either ignoring the clustering (disaggregation) or averaging the micro-level units within each cluster and analyzing the aggregated data at the macro level (aggregation). In this study we investigate the effects of ignoring the nested nature of data in confirmatory factor analysis (CFA). The bias incurred by ignoring clustering is examined in terms of model fit and standardized parameter estimates, which are usually of interest to researchers who use CFA. We find that the disaggregation approach increases model misfit, especially when the intraclass correlation (ICC) is high, whereas the aggregation approach results in accurate detection of model misfit in the macro level. Standardized parameter estimates from the disaggregation and aggregation approaches are deviated toward the values of the macro- and micro-level standardized parameter estimates, respectively. The degree of deviation depends on ICC and cluster size, particularly for the aggregation method. The standard errors of standardized parameter estimates from the disaggregation approach depend on the macro-level item communalities. Those from the aggregation approach underestimate the standard errors in multilevel CFA (MCFA), especially when ICC is low. Thus, we conclude that MCFA or an alternative approach should be used if possible.

A Computationally Efficient State Space Approach to Estimating Multilevel Regression Models and Multilevel Confirmatory Factor Models.

Although the state space approach for estimating multilevel regression models has been well established for decades in the time series literature, it does not receive much attention from educational and psychological researchers. In this article, we (a) introduce the state space approach for estimating multilevel regression models and (b) extend the state space approach for estimating multilevel factor models. A brief outline of the state space formulation is provided and then state space forms for univariate and multivariate multilevel regression models, and a multilevel confirmatory factor model, are illustrated. The utility of the state space approach is demonstrated with either a simulated or real example for each multilevel model. It is concluded that the results from the state space approach are essentially identical to those from specialized multilevel regression modeling and structural equation modeling software. More importantly, the state space approach offers researchers a computationally more efficient alternative to fit multilevel regression models with a large number of Level 1 units within each Level 2 unit or a large number of observations on each subject in a longitudinal study.

Structural Equation Modeling Approaches for Analyzing Partially Nested Data.

Study designs involving clustering in some study arms, but not all study arms, are common in clinical treatment-outcome and educational settings. For instance, in a treatment arm, persons may be nested in therapy groups, whereas in a control arm there are no groups. Methodological approaches for handling such partially nested designs have recently been developed in a multilevel modeling framework (MLM-PN) and have proved very useful. We introduce two alternative structural equation modeling (SEM) approaches for analyzing partially nested data: a multivariate single-level SEM (SSEM-PN) and a multiple-arm multilevel SEM (MSEM-PN). We show how SSEM-PN and MSEM-PN can produce results equivalent to existing MLM-PNs and can be extended to flexibly accommodate several modeling features that are difficult or impossible to handle in MLM-PNs. For instance, using an SSEM-PN or MSEM-PN, it is possible to specify complex structural models involving cluster-level outcomes, obtain absolute model fit, decompose person-level predictor effects in the treatment arm using latent cluster means, and include traditional factors as predictors/outcomes. Importantly, implementation of such features for partially nested designs differs from that for fully nested designs. An empirical example involving a partially nested depression intervention combines several of these features in an analysis of interest for treatment-outcome studies.

Centering categorical predictors in multilevel models: Best practices and interpretation.

The topic of centering in multilevel modeling (MLM) has received substantial attention from methodologists, as different centering choices for lower-level predictors present important ramifications for the estimation and interpretation of model parameters. However, the centering literature has focused almost exclusively on continuous predictors, with little attention paid to whether and how categorical predictors should be centered, despite their ubiquity across applied fields. Alongside this gap in the methodological literature, a review of applied articles showed that researchers center categorical predictors infrequently and inconsistently. Algebraically and statistically, continuous and categorical predictors behave the same, but researchers using them do not, and for many, interpreting the effects of categorical predictors is not intuitive. Thus, the goals of this tutorial article are twofold: to clarify why and how categorical predictors should be centered in MLM, and to explain how multilevel regression coefficients resulting from centered categorical predictors should be interpreted. We first provide algebraic support showing that uncentered coding variables result in a conflated blend of the within- and between-cluster effects of a multicategorical predictor, whereas appropriate centering techniques yield level-specific effects. Next, we provide algebraic derivations to illuminate precisely how the within- and between-cluster effects of a multicategorical predictor should be interpreted under dummy, contrast, and effect coding schemes. Finally, we provide a detailed demonstration of our conclusions with an empirical example. Implications for practice, including relevance of our findings to categorical control variables (i.e., covariates), interaction terms with categorical focal predictors, and multilevel latent variable models, are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Testing the nightmare cognitive arousal processing model.

OBJECTIVE: Posttrauma nightmares are recurring nightmares that begin after a traumatic experience. Research has only recently begun to identify variables that predict posttrauma nightmare occurrences. Research has identified presleep arousal-cognitive (PSA-C) and presleep arousal physiological (PSA-PHYS), sleep onset latency (SOL), and sleep-disordered breathing (SDB) as potential predictors of posttrauma nightmares. However, previous research includes methodological limitations, such as a lack of physiological measures and a homogeneous sample. To replicate previous findings and increase generalizability, the current study investigated predictors of nightmare occurrences in a sample of male inpatient veterans with mixed-trauma history. METHOD: Participants (n = 15) completed an initial assessment battery and seven consecutive days of pre and postsleep diaries, including measures of posttrauma nightmare triggers and posttrauma nightmare occurrences. Portable objective measurements of sleep and presleep states were used to examine sleep quality and physical arousal. RESULTS: Analyses revealed that PSA-C and SOL both predicted posttrauma nightmare occurrences and that PSA-PHYS was significantly higher on nights when nightmares occurred. CONCLUSION: Results replicate earlier research which posits that PSA and SOL play a role in triggering the occurrence of posttrauma nightmares. It should be noted that the sample was relatively small, warranting cautious interpretation of results. However, when taken together with the findings of the replicated study, results could suggest the plausibility of therapies targeting presleep cognitions, SOL, and presleep arousal in the treatment of posttrauma nightmares. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Prevalence and correlates of fear of recurrence among oral and oropharyngeal cancer survivors.

PURPOSE: Fear of recurrence (FoR) is a prevalent and difficult experience among cancer patients. Most research has focused on FoR among breast cancer patients, with less attention paid to characterizing levels and correlates of FoR among oral and oropharyngeal cancer survivors. The purpose was to characterize FoR with a measure assessing both global fears and the nature of specific worries as well as evaluate the role of sociodemographic and clinical factors, survivorship care transition practices, lifestyle factors, and depressive symptoms in FoR. METHODS: Three hundred eighty-nine oral and oropharyngeal survivors recruited from two cancer registries completed a survey assessing demographics, cancer treatment, symptoms, alcohol and tobacco use, survivorship care practices, depression, and FoR. RESULTS: Forty percent reported elevated global FoR, with similar percentages for death (46%) and health worries (40.3%). Younger, female survivors and survivors experiencing more physical and depressive symptoms reported more global fears and specific fears about the impact of recurrence on roles, health, and identity, and fears about death. Depression accounted for a large percent of the variance. Lower income was associated with more role and identity/sexuality worries, and financial hardship was associated with more role worries. CONCLUSIONS: FoR is a relatively common experience for oral and oropharyngeal cancer survivors. Many of its correlates are modifiable factors that could be addressed with multifocal, tailored survivorship care interventions. IMPLICATIONS FOR CANCER SURVIVORS: Assessing and addressing depressive symptoms, financial concerns, expected physical symptoms in the first several years of survivorship may impact FoR among oral and oropharyngeal cancer survivors.

Discretizing continuous variables in nutrition and obesity research: a practice that needs to be cut short.

BACKGROUND/OBJECTIVES: Nutrition and obesity researchers often dichotomize or discretize continuous independent variables to conduct an analysis of variance to examine group differences. We describe consequences associated with dichotomizing and discretizing continuous variables using two cross-sectional studies related to nutrition. SUBJECTS/METHODS: Study 1 investigated the effects of health literacy and nutrition knowledge on nutrition label accuracy (n = 612). Study 2 investigated the effects of cognitive restraint and BMI on fruit and vegetable (F/V) intake (n = 586). We compare analytic approaches where continuous independent variables were either discretized/dichotomized or analyzed as continuous variables. RESULTS: In Study 1, dichotomization of health literacy and nutrition knowledge for 2 × 2 ANOVA revealed health literacy had an effect on nutrition label accuracy. Nutrition knowledge has an effect on nutrition label accuracy, but the health literacy by nutrition knowledge interaction was not significant. When analyzed using regression, the nutrition knowledge effect was significant. The simple effect of health literacy was also significant when health literacy equals zero. Finally, the quadratic effect of health literacy was negative and significant. In Study 2, dichotomization and discretization of cognitive restraint and BMI were used for three ANOVAs, which discretized BMI in three ways. For all ANOVAs, the BMI main effect for predicting fruit and vegetable intake was significant, the interaction between BMI and cognitive restraint was non-significant, and cognitive restraint was only significant when both variables were dichotomized. When analyzed using regression, the continuous mean-centered variables, and their interaction each significantly predicted F/V intake. CONCLUSIONS: Dichotomizing continuous independent variables resulted in distortions of effect sizes across studies, an inability to assess the quadratic effect of health literacy, and an inability to detect the moderating effect of BMI. We discourage researchers from dichotomizing and discretizing continuous independent variables and instead use multiple regression to examine relationships between continuous independent and dependent variables.

Peers, play, and performance to build social salience in autistic youth: A multisite randomized clinical trial.

OBJECTIVE: Individuals with autism spectrum disorder (ASD) have significant impairment in social competence and reduced social salience. SENSE Theatre, a peer-mediated, theater-based intervention has demonstrated posttreatment gains in face memory and social communication. The multisite randomized clinical trial compared the Experimental (EXP; SENSE Theatre) to an Active Control Condition (ACC; Tackling Teenage Training, TTT) at pretest, posttest, and follow-up. It was hypothesized that the EXP group would demonstrate greater incidental face memory (IFM) and better social behavior (interaction with novel peers) and social functioning (social engagement in daily life) than the ACC group, and posttest IFM would mediate the treatment effect on follow-up social behavior and functioning. METHOD: Two hundred ninety participants were randomized to EXP (N = 144) or ACC (N = 146). Per protocol sample (≥ 7/10 sessions) resulted in 207 autistic children 10-16 years. Event-related potentials measured IFM. Naive examiners measured social behavior (Vocal Expressiveness, Quality of Rapport, Social Anxiety) and functioning (Social Communication). Structural equation modeling was used to assess treatment effects. RESULTS: SENSE Theatre participants showed significantly better IFM (b = .874, p = .039) at posttest, and significant indirect effects on follow-up Vocal Expressiveness a × b = .064, with 90% CI [.014, .118] and Quality of Rapport a × b = .032, with 90% CI [.002, .087] through posttest IFM. CONCLUSIONS: SENSE Theatre increases social salience as reflected by IFM, which in turn affected Vocal Expressiveness and Quality of Rapport. Results indicate that a neural mechanism supporting social cognition and driven by social salience is engaged by the treatment and has a generalized, indirect effect on clinically meaningful functional outcomes related to core symptoms of autism. (PsycInfo Database Record (c) 2023 APA, all rights reserved).