Comparing computer‐based training and lecture formats to teach visual analysis of baseline‐treatment graphs

Accurate analysis of data is vital to the validation of interventions. As such, there has been a recent increase in studies evaluating visual analysis training procedures. However, past investigations have not evaluated direct and indirect visual analysis training methods with matched instructional content that was systematically designed. Furthermore, training has rarely included assessment of generalization and maintenance of visual analysis skills. The purpose of the current dissertation study was to compare the effectiveness and efficiency of (a) computer‐based training, (b) lecture formats with and (c) without the opportunity to pause, and (d) a no‐training group to teach visual analysis of AB graphs to university students. To make these formats directly comparable, the instructional content was equated by ensuring information and examples were identical across the three training procedures. Eighty‐three students were randomly assigned to one of the four groups. Results showed that all three training formats produced increases in accurate responding compared to the no‐training group. Visual analysis skills generalized to novel graphs and maintained approximately 2 weeks following all trainings. These results suggest that structured approaches that are carefully designed to train visual analysis are effective and lead to gains that generalize and maintain in the absence of training.     

Risk and Resilience Factors for Mental Health among Transgender and Gender Nonconforming (TGNC) Youth: A Systematic Review

Clinical Child and Family Psychology Review - In recent years, there has been a proliferation of research regarding transgender and gender nonconforming (TGNC) people. The stigma and legal...     

Correction to: The development of dynamic perceptual simulations during sentence comprehension

Cognitive Processing - A correction to this paper has been published: https://doi.org/10.1007/s10339-021-01027-4     

Predictors to Happiness in Primary Students: Positive Relationships or Academic Achievement

This study aimed to examine the role of positive relationships and academic achievement in predicting student well-being, i.e. subjective happiness. This study employed a longitudinal design with two waves of data collection on a sample of 786 primary school students in Hong Kong. Students completed questionnaires on parent-child relationship, teacher-student relationship, peer relationship, academic achievement, and happiness at the beginning and end of the school year. Path analysis was used for data analysis. The results indicated that Time 1 parent-child relationship and peer relationship were associated with Time 2 academic achievement, after controlling for Time 1 academic achievement. However, only Time 1 parent-child relationship was predictive of Time 2 happiness. Time 2 academic achievement was a mediator between Time 1 parent-child relationship and peer relationship and Time 2 happiness. Furthermore, girls reported higher levels of academic achievement when they perceived better peer relationship than did boys, and girls were happier when they had higher levels of academic achievement than were boys. The results suggested the need to put in place strategies to enhance parent-child relationship, peer relationship, and a harmonious classroom.

     

Family interaction: A process model of deviancy training

A model was presented describing the reciprocal influence of disruptions in parent discipline practices on irritable exchanges between the target child and other family members. Disrupted parent discipline and irritable microsocial exchanges within the family were hypothesized to provide a basic training for aggression that generalizes to other settings such that the child is identified by peers, teachers, and parents as physically aggressive. Physical fighting was thought to lead to rejection by the normal peer group, which was hypothesized to feed back to further exacerbate fighting. Multilevel assessment including interview, questionnaires, laboratory studies, and home observations were carried out with the families of 91 preadolescent and adolescent boys. Nine indicators from the assessment battery were used to define the constructs Inept Parental Discipline, Negative Microsocial Exchanges, Physical Fighting, and Poor Peer Relations. Structural equations (LISREL VI) were used to describe the relations among the constructs. The t values for the path coefficients were significant. A chi-square analysis showed an acceptable fit between the model and the empirical findings. The findings were interpreted as being consistent with the hypothesis that under certain circumstances, family interaction may serve as basic training for aggression. In the present study, interactions with siblings in the home seemed to serve a pivotal role.     

Effects of naturally-occuring nontraumatic separations from mother

Thirty-three twelve-month-old infants were divided into three groups based on the frequency and length of naturally-occurring nontraumatic separations from mother during the first year. One group had experienced only brief separations when left with a babysitter for an evening. A second group had been left once or twice for an average of five days while parents vacationed. A third group had been left regularly and frequently during the daytime, usually because mother was working. These groups were compared on measures of reaction to separation and reunion, in the home and in the laboratory, at one year of age. No group differences were found on any of the dependent variables. It is suggested that the quality of substitute care is probably more important than separation per se in mediating the impact of employment or daycare on infant development.     

Temperamental Factors in the Execution of Interrupted Editing Tasks

The question investigated in this study is how the temperament traits of strength of excitation (SE), strength of inhibition (SI), and mobility (MO) affect behaviour during the execution of computer tasks and tasks interrupting them. Several hypotheses, partly derived from the regulative theory of temperament, were tested in an experiment in which the natural environment and the types of task commonly performed by secretaries were simulated. The sample consisted of 39 female secretaries (21–64 years old). It was found that individuals high on SE and MO needed less time to resume tasks after an interruption than individuals low on these temperament traits. Interruptions similar to the main task resulted in longer resumption times for low-SE individuals. MO was negatively related to the time needed to perform the main task. A model describing the relationship between the frequency of switches between tasks and the speed of task performance in low-MO and high-MO individuals is presented.     

The danger of conflating level-specific effects of control variables when primary interest lies in level-2 effects

In the multilevel modelling literature, methodologists widely acknowledge that a level-1 variable can have distinct within-cluster and between-cluster effects, and that failing to disaggregate these can yield a slope estimate that is an uninterpretable, conflated blend of the two. Methodologists have stated, however, that including conflated slopes of level-1 variables in a model is not problematic if substantive interest lies only in effects of level-2 predictors. Researchers commonly follow this advice and use methods that do not disaggregate effects of level-1 control variables (e.g., grand mean centering) when examining effects of level-2 predictors. The primary purpose of this paper is to show that this is a dangerous practice. When level-specific effects of level-1 variables differ, failing to disaggregate them can severely bias estimation of level-2 predictor slopes. We show mathematically why this is the case and highlight factors that can exacerbate such bias. We corroborate these findings with simulations and present an empirical example, showing how such distortions can severely alter substantive conclusions. We ultimately recommend that simply including the cluster mean of the level-1 variable as a control will alleviate the problem.