Mental health symptoms,well-being and experiences of the COVID-19 pandemic: A mixed-methods practice-based study

The COVID-19 pandemic necessitated abrupt and substantial changes in daily life, and public health strategies intended to protect physical health can negatively affect mental health and well-being, especially for individuals with pre-existing mental health challenges. For this study, we surveyed a sample of clients (N = 94) in the summer of 2020 from a community mental health clinic in the northeast United States. A mixed-methods, concurrent triangulation design was used to (a) identify client subgroups on indicators of mental health (i.e. anxious and depressive symptoms) and emotional, psychological, and social well-being using latent profile analysis (LPA), and (b) within these subgroups, examine qualitative, thematic patterns in self-described challenges, benefits and learning related to the pandemic. The LPA revealed five distinct subgroups with various levels of symptoms and well-being, including Stagnant (moderate symptoms/moderate well-being), Languishing (high symptoms/low well-being), Flourishing (low symptoms, high well-being), Fortitudinous (high symptoms, moderate well-being) and Mobilized (moderate symptoms, high well-being). These divergent subgroups support the need to conceptualise mental health symptoms apart from well-being and assess for heterogeneous constellations of such constructs among psychotherapy clients. Thematic analysis offered additional insight into pandemic experiences within each subgroup, including attention to psychological, emotional, behavioural/lifestyle, relational, physical and ecological/contextual dimensions of self-experience, as well as the ways clients had adjusted to the pandemic's circumstances. Findings support nuanced conceptualisations of positive mental health and offer insight into coping and adaptation during this public health crisis.     

Extending exploratory diagnostic classification models: Inferring the effect of covariates

Diagnostic models provide a statistical framework for designing formative assessments by classifying student knowledge profiles according to a collection of fine-grained attributes. The context and ecosystem in which students learn may play an important role in skill mastery, and it is therefore important to develop methods for incorporating student covariates into diagnostic models. Including covariates may provide researchers and practitioners with the ability to evaluate novel interventions or understand the role of background knowledge in attribute mastery. Existing research is designed to include covariates in confirmatory diagnostic models, which are also known as restricted latent class models. We propose new methods for including covariates in exploratory RLCMs that jointly infer the latent structure and evaluate the role of covariates on performance and skill mastery. We present a novel Bayesian formulation and report a Markov chain Monte Carlo algorithm using a Metropolis-within-Gibbs algorithm for approximating the model parameter posterior distribution. We report Monte Carlo simulation evidence regarding the accuracy of our new methods and present results from an application that examines the role of student background knowledge on the mastery of a probability data set.     

Status faking on the SVIB-M

A study and replication of students faking interest in high status occupations on the Strong Vocational Interest Blank for Men. In general, the faking was successful in shifting the specific target occupational scales and especially the occupational level scale. Other scales are affected, many with decisive upward or downward shifts. Demonstration is made of the extent to which the faking condition led to differences in the overall test results. Various aspects of the general problem of test faking are reviewed.     

The effect of memory load on reaction time in character classification

In order to investigate the effect of memory load on reaction time (RT), choice RT trials were embedded in a binary character classification task using the varied set procedure. Twelve Ss performed in experimental blocks, as well as in control blocks consisting of character classification trials only. In experimental blocks, every trial began as a classification trial with the presentation of a new positive set. On a random half of these trials, however, a choice RT stimulus was presented instead of a probe letter and S simply made the indicated response. Results indicated that memory load had no effect on the choice RT trials. Embedding choice RT trials in the classification task affected the intercept (but not the slope) of the function relating classification RT to memory load. This result implies that the increase in latency usually obtained in classification experiments is entirely due to an increase in the duration of the memory searching stage of processing.     

Social validation of an objective measure of dominance in captive monkeys

The validity of a primate dominance hierarchy was examined in terms of its relationship to social interactions. Twelve social behaviors associated with dominance and aggression were recorded during 61 h of observation of six pigtail macaques (Macaca nemestrina). Of the 1,462 interactions recorded, 94.7% were oriented in the water dominance hierarchy in the direction that would be predicted on the basis of their ascribed functions.     

Mediating interpersonal expectancies via vocal cues: Differential speech intensity as a means of social influence

Differential vocal emphasis in the tape-recorded instruction reading for a standard person perception task was manipulated by mechanically raising or lowering the volume of the key words describing the success or failure response alternatives on the rating scale. In a series of three experiments, Ss exposed to success emphasis in the instructions rated the stimulus persons as more successful than did Ss exposed to failure emphasis. This trend was reversed for Ss who listened twice to the instructions. None of the Ss reported awareness of the influence attempt.     

The asymptotic distribution of response probabilities in the Audley-Jonckheere learning model

The asymptotic distributions of response probabilities in the Audley-Jonckheere learning model, as applied to the two-choice learning situation, are described for (1) the experimenter-controlled events model, (2) the subject-controlled events model, and (3) the experimenter-subject-controlled events model.