Bulbar deterioration in amyotrophic lateral sclerosis (ALS) is a devastating characteristic that impairs patients’ ability to communicate, and is linked to shorter survival. The existing clinical instruments for assessing bulbar function lack sensitivity to early changes. In this paper, using a cohort of N = 65 ALS patients who provided regular speech samples for 3–9 months, we demonstrated that it is possible to remotely detect early speech changes and track speech progression in ALS via automated algorithmic assessment of speech collected digitally.

Structural equation model trees (SEM Trees) allow for the construction of decision trees with structural equation models fit in each of the nodes (Brandmaier, von Oertzen, McArdle, & Lindenberger, 2013). Based on covariate information, SEM Trees can be used to create distinct subgroups containing individuals with similar parameter estimates. Currently, the structural equation modeling component of SEM Trees is implemented in the R packages OpenMx and lavaan. We extend SEM Trees so that the models can be fit in Mplus, in the hopes that its efficiency and accessibility allow a broader group of researchers to fit a wider range of models.We discuss the Mplus Trees algorithm, its implementation, and its position among the growing number of tree-based methods in psychological research. We also provide several examples using publicly available data to illustrate how Mplus Trees can be implemented in practice with the R package MplusTrees.

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<b><i>Introduction:</i></b> Changes in speech have the potential to provide important information on the diagnosis and progression of various neurological diseases. Many researchers have relied on open-source speech features to develop algorithms for measuring speech changes in clinical populations as they are convenient and easy to use. However, the repeatability of open-source features in the context of neurological diseases has not been studied. <b><i>Methods:</i></b> We used a longitudinal sample of healthy controls, individuals with amyotrophic lateral sclerosis, and individuals with suspected frontotemporal dementia, and we evaluated the repeatability of acoustic and language features separately on these 3 data sets. <b><i>Results:</i></b> Repeatability was evaluated using intraclass correlation (ICC) and the within-subjects coefficient of variation (WSCV). In 3 sets of tasks, the median ICC were between 0.02 and 0.55, and the median WSCV were between 29 and 79%. <b><i>Conclusion:</i></b> Our results demonstrate that the repeatability of speech features extracted using open-source tool kits is low. Researchers should exercise caution when developing digital health models with open-source speech features. We provide a detailed summary of feature-by-feature repeatability results (ICC, WSCV, SE of measurement, limits of agreement for WSCV, and minimal detectable change) in the online supplementary material so that researchers may incorporate repeatability information into the models they develop.

In this article, we introduce nonlinear longitudinal recursive partitioning (nLRP) and the R package longRpart2 to carry out the analysis. This method implements recursive partitioning (also known as decision trees) in order to split data based on individual- (i.e., cluster) level covariates with the goal of predicting differences in nonlinear longitudinal trajectories. At each node, a user-specified linear or nonlinear mixed-effects model is estimated. This method is an extension of Abdolell et al.'s (2002) longitudinal recursive partitioning while permitting a nonlinear mixed-effects model in addition to a linear mixed-effects model in each node. We give an overview of recursive partitioning, nonlinear mixed-effects models for longitudinal data, describe nLRP, and illustrate its use with empirical data from the Early Childhood Longitudinal Study-Kindergarten Cohort.

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Hispanic students are the most likely out of all racial or ethnic groups to be first-generation college students (FGCS). Hispanic FGCS have been shown to be the least likely to persist out of all racial or ethnic backgrounds. However, there is little literature on this population. To address this, the present study investigated the association of accelerated learning in high school (e.g., Advanced Placement courses and dual enrollment) and financial aid on academic outcomes for Hispanic FGCS and Hispanic non-FGCS at a 4-year postsecondary institution ( n = 2,499). Hispanic FGCS fared worse in first-year grade point average (GPA) and first- to second-year retention than Hispanic non-FGCS. After controlling for academic, nonacademic, and demographic variables, results suggested that accelerated learning reduced achievement gaps in first-year GPA and financial aid reduced achievement gaps in retention rates for Hispanic FGCS. These results suggest that environmental supports (i.e., accelerated learning and financial aid) may be able to improve GPA and retention for Hispanic FGCS.

Opioid use disorders are characterized in part by impairments in social functioning. Previous research indicates that laboratory rats, which are frequently used as animal models of addiction-related behaviors, are capable of prosocial behavior. For example, under normal conditions, when a 'free' rat is placed in the vicinity of rat trapped in a plastic restrainer, the rat will release or 'rescue' the other rat from confinement. The present study was conducted to determine the effects of heroin on prosocial behavior in rats. For 2 weeks, rats were given the opportunity to rescue their cagemate from confinement, and the occurrence of and latency to free the confined rat was recorded. After baseline rescuing behavior was established, rats were randomly selected to self-administer heroin (0.06 mg/kg/infusion i.v.) or sucrose pellets (orally) for 14 days. Next, rats were retested for rescuing behavior once daily for 3 days, during which they were provided with a choice between freeing the trapped cagemate and continuing to self-administer their respective reinforcer. Our results indicate that rats self-administering sucrose continued to rescue their cagemate, whereas heroin rats chose to self-administer heroin and not rescue their cagemate. These findings suggest that rats with a history of heroin self-administration show deficits in prosocial behavior, consistent with specific diagnostic criteria for opioid use disorder. Behavioral paradigms providing a choice between engaging in prosocial behavior and continuing drug use may be useful in modeling and investigating the neural basis of social functioning deficits in opioid addiction.