Examining the association between psychological wellbeing with daily and intra-individual variation in subjective wellbeing

A number of studies identify distinct dimensions of psychological and subjective wellbeing. However, few investigations have examined how these distinctive wellbeing dimensions may be related over time. The present study aimed to contribute to this growing body of research by adopting a measurement burst design to examine the association between psychological functioning with daily and intra-individual variation in affect over a 14-day period, controlling for personality. Participants (N = 45) comprised a sample of Australian adults from Canberra, Australia who were observed on up to 14 days over a 2-week period (Mobs = 10.9 (SD = 3.1)). Maximum Likelihood (ML) estimates from a multi-level structural equation model identified psychological functioning as only weakly associated with daily positive affect, and unrelated to daily levels of negative affect and intra-individual variation in both affect domains when adjusting for demographic, personality and daily stressors. Positive and negative daily events were most strongly associated with positive and negative feelings, respectively. Post-hoc analysis within a Bayesian context confirmed our ML results whilst a Monte Carlo simulation identified sufficient statistical power of significant parameters. Overall, evidence for an association between psychological functioning and daily affect was not identified.     

Psychometric Evaluation of the Career Decision Scale With Iranian Undergraduate Students

The authors examined the reliability and construct validity of the Career Decision Scale (Osipow, Carney, & Barak, 1976 ) with 1,610 freshman and sophomore students from public universities from a southwestern state in Iran. A Cronbach's alpha of .80 provided strong support for the scale's reliability. Exploratory factor analysis results indicated a 2‐factor model (Diffusion and Internal/External Barriers) of the scale with Iranian students, which was confirmed by confirmatory factor analysis. Implications and recommendations for further research are discussed.     

Identifying expectations about the strength of causal relationships

When we try to identify causal relationships, how strong do we expect that relationship to be? Bayesian models of causal induction rely on assumptions regarding people’s a priori beliefs about causal systems, with recent research focusing on people’s expectations about the strength of causes. These expectations are expressed in terms of prior probability distributions. While proposals about the form of such prior distributions have been made previously, many different distributions are possible, making it difficult to test such proposals exhaustively. In Experiment 1 we used iterated learning—a method in which participants make inferences about data generated based on their own responses in previous trials—to estimate participants’ prior beliefs about the strengths of causes. This method produced estimated prior distributions that were quite different from those previously proposed in the literature. Experiment 2 collected a large set of human judgments on the strength of causal relationships to be used as a benchmark for evaluating different models, using stimuli that cover a wider and more systematic set of contingencies than previous research. Using these judgments, we evaluated the predictions of various Bayesian models. The Bayesian model with priors estimated via iterated learning compared favorably against the others. Experiment 3 estimated participants’ prior beliefs concerning different causal systems, revealing key similarities in their expectations across diverse scenarios.     

Increasing accuracy of rock-climbing techniques in novice athletes using expert modeling and video feedback

Several studies have examined the efficacy of behavior analytic coaching strategies in sports to increase performance fluency. Rock climbing is a multifaceted sport requiring mastery of several complex behavior chains in order to successfully navigate climbing surfaces. To date, most investigations have focused on the physiological aspects of rock climbing, as opposed to training specific rock-climbing movements. In this replication and extension, researchers used a multiple baseline design across skills to examine an expert video modeling plus video and verbal feedback training package on foundational rock-climbing skills of novice adult climbers. Results demonstrated that all participants showed an increase in accurate performance for all three skills that were targeted in the intervention.     

Clustering colors

Regier, Kay, and Khetarpal report the results of computer simulations that cluster color stimuli on the basis of their coordinates in CIELAB space, one of two commonly used perceptual color spaces. Regier and coauthors find partitions of those stimuli that are strikingly similar to the way actual color lexicons partition color space. They do not argue for the custom-made clustering method used in their simulations, nor for the assumption of CIELAB space. The present paper aims to answer the question to what extent their computational results depend on these assumptions. It does this by applying a great variety of known clustering methods to Regier et al.’s stimuli, and by assuming not only CIELAB space but also CIELUV space, the other main color space.     

Time-Varying Treatments in Observational Studies: Marginal Structural Models of the Effects of Early Grade Retention on Math Achievement

One of the main objectives of many empirical studies in the social and behavioral sciences is to assess the causal effect of a treatment or intervention on the occurrence of a certain event. The randomized controlled trial is generally considered the gold standard to evaluate such causal effects. However, for ethical or practical reasons, social scientists are often bound to the use of nonexperimental, observational designs. When the treatment and control group are different with regard to variables that are related to the outcome, this may induce the problem of confounding. A variety of statistical techniques, such as regression, matching, and subclassification, is now available and routinely used to adjust for confounding due to measured variables. However, these techniques are not appropriate for dealing with time-varying confounding, which arises in situations where the treatment or intervention can be received at multiple timepoints. In this article, we explain the use of marginal structural models and inverse probability weighting to control for time-varying confounding in observational studies. We illustrate the approach with an empirical example of grade retention effects on mathematics development throughout primary school.     

Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task

The purpose of the popular Iowa gambling task is to study decision making deficits in clinical populations by mimicking real-life decision making in an experimental context. Busemeyer and Stout [Busemeyer, J. R., & Stout, J. C. (2002). A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task. Psychological Assessment, 14, 253-262] proposed an “Expectancy Valence” reinforcement learning model that estimates three latent components which are assumed to jointly determine choice behavior in the Iowa gambling task: weighing of wins versus losses, memory for past payoffs, and response consistency. In this article we explore the statistical properties of the Expectancy Valence model. We first demonstrate the difficulty of applying the model on the level of a single participant, we then propose and implement a Bayesian hierarchical estimation procedure to coherently combine information from different participants, and we finally apply the Bayesian estimation procedure to data from an experiment designed to provide a test of specific influence.     

A longitudinal study of student-teacher relationship quality, difficult temperament, and risky behavior from childhood to early adolescence

This study examines the mediating role of student-teacher relationship quality (conflict and closeness) in grades 4, 5, and 6 on the relation between background characteristics, difficult temperament at age 4½ and risky behavior in 6th grade. The longitudinal sample of participants (N = 1156) was from the NICHD Study of Early Child Care and Youth Development. Structural equation modeling was used to estimate paths from (a) background characteristics to student-teacher relationship quality and risky behavior, (b) temperament to student-teacher relationship quality and risky behavior, and (c) student-teacher relationship quality to risky behavior. Findings indicate that students' family income, gender, receipt of special services, and more difficult temperament were associated with risky behavior. In addition, student-teacher conflict was a mediator. Students with more difficult temperaments were more likely to report risky behavior and to have conflict in their relationships with teachers. More conflict predicted more risky behavior. Closer student-teacher relationships were associated with less risky behavior. Results suggest negative relationships, specifically student-teacher relationships, may increase the risk that certain adolescents will engage in risky behavior.     

Learning letter names and sounds: Effects of instruction, letter type, and phonological processing skill

Preschool-age children (N = 58) were randomly assigned to receive instruction in letter names and sounds, letter sounds only, or numbers (control). Multilevel modeling was used to examine letter name and sound learning as a function of instructional condition and characteristics of both letters and children. Specifically, learning was examined in light of letter name structure, whether letter names included cues to their respective sounds, and children’s phonological processing skills. Consistent with past research, children receiving letter name and sound instruction were most likely to learn the sounds of letters whose names included cues to their sounds regardless of phonological processing skills. Only children with higher phonological skills showed a similar effect in the control condition. Practical implications are discussed.     

Structural relaxation and rejuvenation in a metallic glass induced by shot-peening

The metallic glass Pd₄₀Cu₃₀Ni₁₀P₂₀ in as-cast or pre-annealed states was shot-peened successively at room temperature or at 77 K. The structural state of the glass was characterized by the relaxation spectrum measured in a differential scanning calorimeter. Mechanically induced relaxation of the as-cast glass and mechanically induced rejuvenation of pre-annealed samples are both more evident at 77 K than at 298 K, enabling deductions about the underlying mechanisms. The relaxation spectrum of the glass as a function of temperature displays two broad maxima, which occurring at the higher temperature is attributed to the part of the free-volume distribution associated with flow defects. In samples shot-peened at 77 K, the stored energy after deformation can be as high as 20% of the cold work. Shot-peening simultaneously generates flow defects within shear bands and destroys them in the matrix between bands: whose effect dominates is principally dependent on the initial state of relaxation of the glass. Shot-peening of partially crystallized samples appears capable of breaking up and dispersing crystallites without inducing any further significant crystallization.