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.

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.

Recruiting Fathers for Parenting Research: An Evaluation of Eight Recruitment Methods and an Exploration of Fathers' Motivations for Participation.

Objective: We evaluated eight recruitment methods (Craigslist, Facebook ads, Google AdWords, in-person, newspaper, parenting magazines, ResearchMatch, and direct mailing) in terms of their ability to accrue fathers of 3- to 7-year-old children into a laboratory-based behavioral trial for parents. The trial was related to child obesity risk and parental health behaviors.

Design: Each recruitment method was implemented such that half its occurrences advertised for fathers only, and half advertised for mothers and fathers.

Modelling multilevel nonlinear treatment-by-covariate interactions in cluster randomized controlled trials using a generalized additive mixed model.

A cluster randomized controlled trial (C-RCT) is common in educational intervention studies. Multilevel modelling (MLM) is a dominant analytic method to evaluate treatment effects in a C-RCT. In most MLM applications intended to detect an interaction effect, a single interaction effect (called a conflated effect) is considered instead of level-specific interaction effects in a multilevel design (called unconflated multilevel interaction effects), and the linear interaction effect is modelled.

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.

Decision-making about genetic health information among family dyads: a systematic literature review.

Decisions involving two individuals (i.e., dyadic decision-making) have been increasingly studied in healthcare research.

Zoom or In-Person: An Ecological Momentary Assessment Study of Time with Friends and Depressive Symptoms on Affect in Emerging Adults.

Introduction: Depression is associated with increased negative affect (NA) and low positive affect (PA), as well as interpersonal difficulties. Although most studies examine symptoms and affect at only one time point, ecological momentary assessment (EMA) captures data on affect and activity in real time and across contexts. The present study used EMA to explore the links between in-person and virtual social interactions, depressive symptoms, and momentary affect.

Mothers' and fathers' cognitive and affective responses to epigenetics concepts.

Advances in our understanding of epigenetics present new opportunities to improve children's health through the counseling of parents about epigenetics concepts. However, it is important to first evaluate how parents respond to this type of information and determine the consequences of educating parents about epigenetics. We have taken an initial step toward this goal by assessing parental responses to an epigenetics learning module.

Investigating the Efficacy of Genetic, Environmental, and Multifactorial Risk Information When Communicating Obesity Risk to Parents of Young Children.

Background: Effectively communicating with parents about children's obesity risk is of critical importance for preventive medicine and public health.

Purpose: The current study investigates the efficacy of communications focused on two primary causes of obesity: genes and environment.

Methods: We compared parental feeding responses to messages focused on (i) genetics alone, (ii) family environment alone, (iii) genetics-family environment interaction (G × FE), and (iv) no causal message.

Tracing Physical Behavior in Virtual Reality: A Narrative Review of Applications to Social Psychology.

Virtual reality (VR) offers unique benefits to social psychological research, including a high degree of experimental control alongside strong ecological validity, a capacity to manipulate any variable of interest, and an ability to trace the physical, nonverbal behavior of the user in a very fine-grained and automated manner. VR improves upon traditional behavioral measurement techniques (e.g.

Parents' genetic attributions for children's eating behaviors: Relationships with beliefs, emotions, and food choice behavior.

Considering genetic influences on children's eating behavior could result in reduced self-efficacy for healthy child feeding and less healthy feeding behavior among parents. Indeed, one's eating behaviors are typically thought of as the volitional aspects of weight management that one can directly control. The current study assessed parental genetic attributions for their child's eating behavior, and relationships between these attributions and self-efficacy, guilt, and feeding behaviors.

Path Tortuosity in Virtual Reality: A Novel Approach for Quantifying Behavioral Process in a Food Choice Context.

There is a pressing need to better understand how parents make feeding decisions for their children, but extant measures focus primarily on outcomes rather than examining the process of food choice as it unfolds. This exploratory study examined parents' translational movement as they moved throughout a virtual reality-based buffet restaurant to select a lunch for their child. Our aim was to explore whether translational movement would be related to cognitive and affective variables that underlie motivation, effort, and ultimate choices within food decision-making contexts (e.

Effects of Fruit and Vegetable Feeding Messages on Mothers and Fathers: Interactions Between Emotional State and Health Message Framing.

Background: There is a pressing need to craft optimal public health messages promoting healthy feeding behaviors among parents. How these messages influence such feeding decisions are affected by multiple interactive factors including emotional states, message framing, and gender, but these factors have not been studied in the domain of parents' feeding of their children.

Purpose: To evaluate the role of message framing, emotional state, and parent gender on feeding choices that parents make for their children.