Phases of learning: How skill acquisition impacts cognitive processing

This fMRI study examines the changes in participants’ information processing as they repeatedly solve the same mathematical problem. We show that the majority of practice-related speedup is produced by discrete changes in cognitive processing. Because the points at which these changes take place vary from problem to problem, and the underlying information processing steps vary in duration, the existence of such discrete changes can be hard to detect. Using two converging approaches, we establish the existence of three learning phases. When solving a problem in one of these learning phases, participants can go through three cognitive stages: Encoding, Solving, and Responding. Each cognitive stage is associated with a unique brain signature. Using a bottom-up approach combining multi-voxel pattern analysis and hidden semi-Markov modeling, we identify the duration of that stage on any particular trial from participants brain activation patterns. For our top-down approach we developed an ACT-R model of these cognitive stages and simulated how they change over the course of learning. The Solving stage of the first learning phase is long and involves a sequence of arithmetic computations. Participants transition to the second learning phase when they can retrieve the answer, thereby drastically reducing the duration of the Solving stage. With continued practice, participants then transition to the third learning phase when they recognize the problem as a single unit and produce the answer as an automatic response. The duration of this third learning phase is dominated by the Responding stage.     

Resources masquerading as slots: Flexible allocation of visual working memory

Whether the capacity of visual working memory is better characterized by an item-based or a resource-based account continues to be keenly debated. Here, we propose that visual working memory is a flexible resource that is sometimes deployed in a slot-like manner. We develop a computational model that can either encode all items in a memory set, or encode only a subset of those items. A fixed-capacity mnemonic resource is divided among the items in memory. When fewer items are encoded, they are each remembered with higher fidelity, but at the cost of having to rely on an explicit guessing process when probed about an item that is not in memory. We use the new model to test the prediction that participants will more often encode the entire set of items when the demands on memory are predictable.     

Teaching social perception skills to adolescents with autism and intellectual disabilities using video‐based group instruction

Few interventions focus on teaching social skills to adolescents with autism spectrum disorder (ASD) and intellectual disabilities (ID) that are consistently used during interactions with peers ( Carter et al., 2014). The present study evaluated the effects of video‐based group instruction (VGI) on the acquisition of social perception skills of five adolescents with ASD or ID in a public school setting. Social perception involves observing affective behaviors of others, discriminating relevant environmental stimuli, and differentially reinforcing the affective behavior of another person. Typically developing peers supported VGI implementation as social partners for participants. A multiple probe design across behaviors demonstrated the effectiveness of VGI for teaching social perception skills. Four of five participants acquired and maintained the targeted social perception skills, and we observed some transfer to a nontreatment setting. Results of this study suggest VGI may support the acquisition of social perception among adolescents with ASD or ID.     

Teaching help‐seeking when lost to individuals with autism spectrum disorder

Deficits in safety skills and communication deficits place individuals with autism spectrum disorder (ASD) at an increased risk of danger. We used a multiple‐probe across‐participants design to evaluate the effects of video modeling and programming common stimuli to teach low‐ and high‐tech help‐seeking responses to children with ASD when lost. Participants acquired answering or making a FaceTime^® call and exchanging an identification card in contrived and natural settings. Responses generalized to novel community settings and maintained during a one‐ and two‐week follow‐up. Social validity measures showed that the procedures and outcomes of the study were acceptable to indirect and direct consumers, and immediate and extended community members. Implications are that children with ASD can effectively be taught both low‐ and high‐tech help‐seeking responses when lost.     

The Relation of Career Adaptability to Work–Family Experience and Personal Growth Initiative Among Taiwanese Working Parents

This study aimed to explore the effect of career adaptability on 598 working parents in Taiwan. The results showed that career adaptability served an important role in moderating and mediating the effects between work–family conflict, work–family strength, and personal growth initiative.     

On the Computation of the RMSEA and CFI from the Mean-And-Variance Corrected Test Statistic with Nonnormal Data in SEM

A new type of nonnormality correction to the RMSEA has recently been developed, which has several advantages over existing corrections. In particular, the new correction adjusts the sample estimate of the RMSEA for the inflation due to nonnormality, while leaving its population value unchanged, so that established cutoff criteria can still be used to judge the degree of approximate fit. A confidence interval (CI) for the new robust RMSEA based on the mean-corrected (“Satorra-Bentler”) test statistic has also been proposed. Follow up work has provided the same type of nonnormality correction for the CFI (Brosseau-Liard & Savalei, 2014). These developments have recently been implemented in lavaan. This note has three goals: a) to show how to compute the new robust RMSEA and CFI from the mean-and-variance corrected test statistic; b) to offer a new CI for the robust RMSEA based on the mean-and-variance corrected test statistic; and c) to caution that the logic of the new nonnormality corrections to RMSEA and CFI is most appropriate for the maximum likelihood (ML) estimator, and cannot easily be generalized to the most commonly used categorical data estimators.     

Bayesian PTSD-Trajectory Analysis with Informed Priors Based on a Systematic Literature Search and Expert Elicitation

There is a recent increase in interest of Bayesian analysis. However, little effort has been made thus far to directly incorporate background knowledge via the prior distribution into the analyses. This process might be especially useful in the context of latent growth mixture modeling when one or more of the latent groups are expected to be relatively small due to what we refer to as limited data. We argue that the use of Bayesian statistics has great advantages in limited data situations, but only if background knowledge can be incorporated into the analysis via prior distributions. We highlight these advantages through a data set including patients with burn injuries and analyze trajectories of posttraumatic stress symptoms using the Bayesian framework following the steps of the WAMBS-checklist. In the included example, we illustrate how to obtain background information using previous literature based on a systematic literature search and by using expert knowledge. Finally, we show how to translate this knowledge into prior distributions and we illustrate the importance of conducting a prior sensitivity analysis. Although our example is from the trauma field, the techniques we illustrate can be applied to any field.     

Estimation of a Latent Variable Regression Growth Curve Model for Individuals Cross-Classified by Clusters

The cross-classified multiple membership latent variable regression (CCMM-LVR) model is a recent extension to the three-level latent variable regression (HM3-LVR) model which can be utilized for longitudinal data that contains individuals who changed clusters over time (for instance, student mobility across schools). The HM3-LVR model can include the initial status on growth effect as varying across those clusters and allows testing of more flexible hypotheses about the influence of initial status on growth and of factors that might impact that relationship, but only in the presence of pure clustering of participants within higher-level units. This Monte Carlo study was conducted to evaluate model estimation under a variety of conditions and to measure the impact of ignoring cross-classified data when estimating the incorrectly specified HM3-LVR model in a scenario in which true values for parameters are known. Furthermore, results from a real-data analysis were used to inform the design of the simulation. Overall, it would be recommended for researchers to utilize the CCMM-LVR model over the HM3-LVR model when individuals are cross-classified, and to use a bare minimum of more than 100 clustering units in order to avoid overestimation of the level-3 variance component estimates.     

Communal coping and rumination in the aftermath of Chile earthquake: Multiple mediation analysis of the relationship between subjective severity and posttraumatic growth

Communal coping and collective participation were recently proposed as a potential mechanism that may favour not only individual's capacity to bounce back but also community cohesion and social well‐being and posttraumatic growth in the aftermath of natural disasters. To date, there is a lack of studies simultaneously assessing the effect of communal coping strategies and cognitive strategies on the development of posttraumatic growth. Therefore, the aim of this study was to examine the role of communal coping strategies and cognitive strategies such as intrusive and deliberated rumination as potential mediators between subjective severity of the event and posttraumatic growth and positive adjustment in the context of natural disaster. The questionnaire was administrated to 225 people affected by the most intense earthquake recorded in Chile in this century. The results of multiple mediation analysis showed that both cognitive strategies, such as deliberative rumination, and communal coping strategies, such as communal positive reappraisal and participation in spiritual rituals, are potential mediators between subjective severity and posttraumatic growth. Overall, the present work offers researchers and professionals interested in this area of study an interesting approach to analyse individual and collective coping strategies and its interrelation.     

Post-combat adaptation: improving social support and reaching constructive growth

Background and Objectives: Posttraumatic stress disorder, a commonly researched mental health outcome associated with trauma, does not develop in the majority of survivors. More common trajectories of adaptation include resilience, and posttraumatic growth (PTG). The objectives of the current study were to: (1) describe posttrauma adaptation profiles in a sample of Israeli male military veterans (N?=?448); and (2) to explore the protective factors that promote constructive PTG within two profiles of posttrauma adaptation.

Methods: The study used secondary data to estimate latent profile mixture models and a series of logistic regression analyses.

Results: Demographic controls, combat related variables, endorsement of coping strategies, and reports of improvement in social support were not significant predictors of constructive growth in the resilient class. However, those in the struggling growth subset of the sample who reported improvement in perceived social support increased the odds of reaching constructive growth.

Conclusion: These findings highlight the importance of tailored clinical interventions that account for more complex profiles of posttrauma adaptation; and further, provide evidence that adaptation takes place over time. Finally, these findings call for future research to continue to explore the quality of PTG and the contexts in which protective factors promote positive adaptation.