ssMousetrack: Analysing computerized tracking data via Bayesian state-space models in {R}

Recent technological advances have provided new settings to enhance individual-based data collection and computerized-tracking data have became common in many behavioral and social research. By adopting instantaneous tracking devices such as computer-mouse, wii, and joysticks, such data provide new insights for analysing the dynamic unfolding of response process. ssMousetrack is a R package for modeling and analysing computerized-tracking data by means of a Bayesian state-space approach. The package provides a set of functions to prepare data, fit the model, and assess results via simple diagnostic checks. This paper describes the package and illustrates how it can be used to model and analyse computerized-tracking data. A case study is also included to show the use of the package in empirical case studies

Entia Non Sunt Multiplicanda … Shall I look for clusters in my cognitive data?

Unsupervised clustering methods are increasingly being applied in psychology. Researchers may use such methods on multivariate data to reveal previously undetected sub-populations of individuals within a larger population. Realistic research scenarios in the cognitive science may not be ideally suited for a successful use of these methods, however, as they are characterized by modest effect sizes, limited sample sizes, and non-orthogonal indicators. This combination of characteristics even presents a high risk of detecting non-existing clusters. A systematic review showed that, among 191 studies published in 2016–2020 that used different clustering methods to classify human participants, the median sample size was only 322, and a median of 3 latent classes/clusters were detected. None of them concluded in favor of a one-cluster solution, potentially giving rise to an extreme publication bias. Dimensionality reduction techniques are almost never used before clustering. In a subsequent simulation study, we examined the performance of popular clustering techniques, including Gaussian mixture model, a partitioning, and a hierarchical agglomerative algorithm. We focused on their ability to detect the correct number of clusters, and on their classification accuracy. Under a reasoned set of scenarios that we considered plausible for the cognitive research, none of the methods adequately discriminates between one vs two true clusters. In addition, non-orthogonal indicators lead to a high risk of incorrectly detecting multiple clusters where none existed, even in the presence of only modest correlation (a frequent case in psychology). In conclusion, it is hard for researchers to be in a condition to achieve a valid unsupervised clustering for inferential purposes with a view to classifying individuals

Mental Health among Former Child Soldiers and Never-Abducted Children in Northern Uganda

The present study aimed to evaluate posttraumatic stress symptoms, psychological distress, and emotional and behavioral problems in former Ugandan child soldiers in comparison with civilian children living in the same conflict setting. Participants included 133 former child soldiers and 101 never-abducted children in northern Uganda, who were interviewed about exposure to traumatic war-related experiences, posttraumatic stress symptoms, psychological distress, and emotional and behavioral problems. Results indicated that former child soldiers had experienced significantly more war-related traumatic events than nonabducted children, with 39.3% of girls having been forced to engage in sexual contact. Total scores on measures of PTSD symptoms, psychological distress, and emotional and behavioral problems were significantly higher among child soldiers compared to their never-abducted peers. Girls reported significantly more emotional and behavioral difficulties than boys. In never-abducted children, more mental health problems were associated with experiencing physical harm, witnessing the killings of other people, and being forced to engage in sexual contact

Factorial validity of the Problematic Facebook Use Scale for adolescents and young adults

Recent research on problematic Facebook use has highlighted the need to develop a specific theory-driven measure to assess this potential behavioral addiction. The aim of the present study was to examine the factorial validity of the Problematic Facebook Use Scale (PFUS) adapted from Caplan’s Generalized Problematic Internet Scale model. Methods A total of 1,460 Italian adolescents and young adults (aged 14–29 years) participated in the study. Confirmatory factor analyses were performed in order to assess the factorial validity of the scale. Results Results revealed that the factor structure of the PFUS provided a good fit to the data. Furthermore, results of the multiple group analyses supported the invariance of the model across age and gender groups. Discussion and conclusions This study provides evidence supporting the factorial validity of the PFUS. This new scale provides a theory-driven tool to assess problematic use of Facebook among male and female adolescents and young adults

The measurement of left—right asymmetries in the Simon effect: A fine-grained analysis

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PRDA: An R package for Prospective and Retrospective Design Analysis

The paper describes the PRDA package available at https://cran.r-project.org/web/packages/PRDA/ . PRDA is an R package performing prospective or retrospective design analysis (see Gelman & Carlin, 2014 and Altoè et al., 2020) to evaluate inferential risks (i.e., power, Type M error, and Type S error) in a study considering Pearson’s correlation between two variables or mean comparisons (one-sample, paired, two-sample, andWelch’st-test). Prospective Design Analysis is performed in the planning stage of a study to define the required sample size to obtain a given level of power. Retrospective Design Analysis, instead, is performed when the data have already been collected to evaluate the inferential risks associated with the study. PRDA, additionally, offers the possibility to conduct a prospective/retroprospective design analysis taking into account for the uncertainty about the hypothetical value of effect size. In fact, hypothetical effect size can be defined as a single value according to previous results in the literature or experts indications, or by specifying a distribution of plausible values

Effectiveness of digital-based interventions for children with mathematical learning difficulties : A meta-analysis

Abstract The purpose of this work was to meta-analyze empirical evidence about the effectiveness of digital-based interventions for students with mathematical learning difficulties. Furthermore, we investigated whether the school level of the participants and the software instructional approach were decisive modulated factors. A systematic search of randomized controlled studies published between 2003 and 2019 was conducted. A total of 15 studies with 1073 participants met the study selection criterion. A random effects meta-analysis indicated that digital-based interventions generally improved mathematical performance (mean ES = 0.55), though there was a significant heterogeneity across studies. There was no evidence that videogames offer additional advantages with respect to digital-based drilling and tutoring approaches. Moreover, effect size was not moderated when interventions were delivered in primary school or in preschool

developing a simulated environment to study naturalistic decision making processes

Motivation - Combination of qualitative and quantitative methodologies to develop a simulated environment to study decision-making processes from a NDM perspective. Research approach - Discourse analysis to find interpretative repertoires, use of Visual Analog Scales and ANOVA to validate the repertoires. Findings/Design - Usefulness of qualitative and quantitative methodologies to develop the simulation, importance of a rigorous validation. Research limitations/Implications - Need for comparison with a real website in further studies. Originality/Value - Use of NDM perspective to investigate processes that were studied just from a DM perspective. Take away message - It is possible to study decision-making by naturally simulating them with computer technology in a laboratory

Interpersonal motor synchrony in autism: a systematic review and meta-analysis

IntroductionInterpersonal motor synchrony (IMS) is the spontaneous, voluntary, or instructed coordination of movements between interacting partners. Throughout the life cycle, it shapes social exchanges and interplays with intra- and inter-individual characteristics that may diverge in Autism Spectrum Disorder (ASD). Here we perform a systematic review and meta-analysis to summarize the extant literature and quantify the evidence about reduced IMS in dyads including at least one participant with a diagnosis of ASD. MethodsEmpirical evidence from sixteen experimental studies was systematically reviewed, encompassing spontaneous and instructed paradigms as well as a paucity of measures used to assess IMS. Of these, thirteen studies (n = 512 dyads) contributed measures of IMS with an in situ neurotypical partner (TD) for ASD and control groups, which could be used for meta-analyses. ResultsReduced synchronization in ASD-TD dyads emerged from both the systematic review and meta-analyses, although both small and large effect sizes (i.e., Hedge’s g) in favor of the control group are consistent with the data (Hedge’s g = .85, p < 0.001, 95% CI[.35, 1.35], 95% PI[-.89, 2.60]). DiscussionUncertainty is discussed relative to the type of task, measures, and age range considered in each study. We further discuss that sharing similar experiences of the world might help to synchronize with one another. Future studies should not only assess whether reduced IMS is consistently observed in ASD-TD dyads and how this shapes social exchanges, but also explore whether and how ASD-ASD dyads synchronize during interpersonal exchanges