Interactive effects of social network centrality and social identification on stress

The present study aimed to integrate the social identity approach to health and well-being with social network analysis. Previous research on the effects of social network centrality on stress has yielded mixed results. Building on the social identity approach, we argued that these mixed results can be explained, in part, by taking into account the degree to which individuals identify with the social network. We hence hypothesized that the effects of social network centrality on stress are moderated by social identification. Using a full roster method, we assessed the social network of first-year psychology students right after the start of their study programme and three months later. The effects of network centrality (betweenness, closeness, eigenvector centrality) and social identification on stress were examined using structural equation models. As predicted, our results revealed a significant interaction between network centrality and social identification on stress: For weakly or moderately identified students, network centrality was positively related to stress. By contrast, for strongly identified students, network centrality was unrelated to stress. In conclusion, our results point to the perils of being well-connected yet not feeling like one belongs to a group.     

A note on computing Louis’ observed information matrix identity for IRT and cognitive diagnostic models

Using Louis’ formula, it is possible to obtain the observed information matrix and the corresponding large-sample standard error estimates after the expectation–maximization (EM) algorithm has converged. However, Louis’ formula is commonly de-emphasized due to its relatively complex integration representation, particularly when studying latent variable models. This paper provides a holistic overview that demonstrates how Louis’ formula can be applied efficiently to item response theory (IRT) models and other popular latent variable models, such as cognitive diagnostic models (CDMs). After presenting the algebraic components required for Louis’ formula, two real data analyses, with accompanying numerical illustrations, are presented. Next, a Monte Carlo simulation is presented to compare the computational efficiency of Louis’ formula with previously existing methods. Results from these presentations suggest that Louis’ formula should be adopted as a standard method when computing the observed information matrix for IRT models and CDMs fitted with the EM algorithm due to its computational efficiency and flexibility.     

Murray Sidman: fostering progress through foundational choices

The contributions of Murray Sidman to the field of behavior analysis have helped to put the field on a progressive path. In this paper we describe three areas as examples, drawn from the larger set of his notable contributions: the analysis of stimulus equivalence in a way that has fostered a behavior-analytic approach to derived stimulus relations and symbolic meaning; the observation and measurement of individual behavior through time; and his stance against punitive applied methods. In each of these areas Sidman was a dedicated behaviorist, avoiding appeals to mentalistic or transcendental forces, opposing hypothetical mediational accounts, and taking a functional and contextual approach. Clarity of assumptions was at the heart of Sidman's effective scientific practices and there is no reason to think that those same assumptions will not carry us further, as evidence mounts in support of these views on psychological research and practice.     

Caveats of non-ipsatization of basic values: A review of issues and a simulation study

Ipsatization, or a correction of variables by their common component, is routinely applied to measures of basic values. Although ipsatization has been criticized, the consequences of non-ipsatization are rarely discussed. We show that the ipsatization of values is intertwined with their definition. A common factor involved in ipsatization was suggested to represent a nuisance variable, a response style, social desirability, or other constructs. A simulation study illustrated that within-individual centering revealed more accurate value scores when the common factor was in the data, with exception of the situation when values were consistently and positively correlated with each other. We conclude that in different conditions both applying and failing to apply ipsatization can cause bias. Therefore, no general advice in regard to ipsatization can be provided.     

A coordinated analysis of the associations among personality traits,cognitive decline,and dementia in older adulthood

There are individual differences in the rates of cognitive decline across later adulthood. Personality traits are among the factors that may account for these differences. The current project investigated whether personality traits were associated with trajectories of cognitive decline, and whether the associations were different before and after dementia diagnosis. The data was analyzed using linear mixed effects regression. Across study aims is a focus on replicability and generalizability. Each question was addressed in four independent longitudinal studies (EAS, MAP, ROS, SATSA), then meta-analyzed, providing estimates of replicability. Results indicated that low neuroticism and high openness were associated with total cognitive function. We detected evidence for cognitive decline in all four samples, and openness was associated with decline post dementia diagnosis.     

A time series analysis of the relation between motor skill acquisition and sleep in infancy

To systematically examine the relation between motor milestone onset and disruption of night sleep in infancy, three families kept microgenetic, prospective, daily checklist diaries of their infants’ motor behavior and sleep (197-313 observation days; 19,000 diary entries). Process control and interrupted time series analyses examined whether deviations from the moving average for night wakings and evening sleep duration were temporally linked to motor skill onset and tested for meaningful differences in individual sleep patterns before and after skill onset. Model assumptions defined skill onset as first day of occurrence or as mastery and moving average windows as 3, 7, or 14 days. Changes in infants’ sleep patterns were associated with changing expertise for motor milestones. The temporal relation varied depending on infant and sleep parameter. Intensive longitudinal data collection may increase our understanding of micro-events in infant development.     

Female Offenders Under Community Supervision: A Phenomenological Analysis

In this phenomenological study, we examined the lived experiences of 10 female offenders under community supervision. Findings include five essential themes. We propose clinical implications and actionable service recommendations for clinical mental health counselors working with this population.     

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.     

The motivations for using bike sharing during the COVID-19 pandemic: Insights from Lisbon

Urban mobility has been severely impacted by the coronavirus pandemic, with public transport (PT) particularly affected due to infection risks and fears. The promotion of alternative modes of transport such as bike sharing systems (BSS) has gained a new drive as a possible way of providing an alternative to PT and limit a potential surge in private car use.In this study, we provide insights on the motivations for using bike sharing during the COVID-19 pandemic through a survey to the BSS users of Lisbon (entitled GIRA). Before the coronavirus pandemic, the most influential motivations were those connected to the BSS’ Service Coverage & Quality (such as the convenient location of BSS stations near the users’ destinations or the availability of shared e-bikes) as well as to the Personal Interests & Well-being of BSS users (namely the pleasure of cycling as well as the perceived environmental and health benefits). With the emergence of the COVID-19 pandemic, although the motivations of Service Coverage & Quality continue to be the most valued by respondents, the motivations associated with using BSS to avoid PT and to maintain a social distance during the trip are now as important as the motivations linked to Personal Interests & Well-being. Furthermore, new users who have joined bike sharing during COVID-19 give more importance to the Social Influence (such as seeing other people using the system or the influence of their social circle) comparatively to those who were already users before the pandemic and continue to use BSS.This research provides evidence on the importance of bike sharing to the resilience of urban transport systems, particularly during disruptive public health crises. It supports that BSS should continue to operate during the coronavirus pandemic as such systems offer a transport alternative to PT that is perceived to be capable of preserving a physical distance.