A comparison of picture and GIF-based preference assessments for social interaction

Researchers have recently begun to evaluate video-based preference assessments; however, only two studies have evaluated the efficacy of this preference assessment modality in assessing preference for social interactions. Four individuals diagnosed with autism spectrum disorder who could not match pictures or graphic-interchange-format images (GIFs) of social interactions to in vivo interaction participated. We compared picture and GIF-based paired-stimulus preference assessments for social interaction and evaluated the preference assessment hierarchies by conducting a concurrent-operant reinforcer assessment including all social interactions. The GIF-based preference assessment produced similar hierarchies to the reinforcer assessment for all participants, whereas the picture-based preference assessments produced similar hierarchies to the reinforcer assessment for 2 of 4 subjects. Additionally, we conducted a modality preference assessment in which we evaluated participants' preference for viewing GIFs or pictures of social interactions, and found that 3 out of 4 subjects displayed a preference for GIFs.     

An analysis of the value of token reinforcement using a multiple-schedule assessment

Token systems are widely used in clinical settings, necessitating the development of methods to evaluate the reinforcing value of these systems. In the current paper, we replicated the use of a multiple-schedule reinforcer assessment (MSA; Smaby, MacDonald, Ahearn, & Dube, 2007) to evaluate the components of a token economy system for 4 learners with autism. Token systems had reinforcing value similar to primary reinforcers for 2 of the 4 learners, but resulted in lower rates of responding than primary reinforcers for the other 2 learners. Differentiated responding across learners may warrant variation in clinical recommendations on the use of tokens. The results of this study support formal assessment of token system effectiveness, and the MSA procedure provides an efficient method by which to conduct such assessments.     

Idiographic network analysis of discrete mood states prior to treatment

Idiographic network models based on time‐series data have received recent attention for their ability to model relationships among symptoms and behaviours as they unfold in time within a single individual (cf. Epskamp, Borsboom, & Fried, 2018; Fisher, Medaglia, & Jeronimus, 2018). Rather than examine the correlational relationships between variables in a sample of individuals, an idiographic network examines correlations within a single person, averaged over many time points. Because the approach averages over time, the data must be stationary (i.e. relatively consistent over time). If individuals experience varying states over time—different mixtures of symptoms and behaviours in one moment or another—then averaging over categorically different moments may undermine model accuracy. Fisher and Bosley (2019) address these concerns via the application of Gaussian finite mixture modelling to identify latent classes of time points in intraindividual time‐series data from a sample of adults with major depressive disorder and/or generalised anxiety disorder (n = 45). The present paper outlines an extension of this work, wherein network analysis is used to model within‐class covariation of symptoms. To illustrate this approach, network models were constructed for each intraindividual class identified by Fisher and Bosley (137 networks across the 45 participants, mean classes/person = ~3, range = 2–4 classes/person). We examine the relative consistency in symptom organisation between each individual's multiple mood state networks and assess emergent group‐level patterns. We highlight opportunities for enhanced treatment personalisation and review nomothetic patterns relevant to transdiagnostic conceptualisations of psychopathology. We address opportunities for integrating this approach into clinical practice and outline potential shortcomings.     

Clinical cut‐off point for the Distrust dimension of the Dimensional Clinical Personality Inventory 2 (IDCP‐2)

The Clinical Dimensional Personality Inventory 2 (IDCP ‐2) is a 206‐item self‐report tool developed for the assessment of 12 dimensions (divided into 47 factors) of personality pathology. One of the scales comprising the instrument, the Distrust scale, is intended to provide psychometric information on traits closely related to the Paranoid Personality Disorder (PPD ). In the present research, we used the Item Response Theory and the Receiver Operating Characteristic curve analysis to establish a clinical meaningful cutoff for the Distrust scale. Participants were 1,679 adults, among outpatients diagnosed with PPD , outpatients diagnosed with other PD s, and adults from the community. The Wright map revealed that outpatients were located at the very high levels on the latent continuum of the Distrust scale, with a very large effect size for the mean difference between patients and non‐patients. The ROC curve supported a cutoff at −1.00 score in theta standardization which yielded 0.87 of sensitivity and 0.54 of specificity. Findings from the present investigation suggest the IDCP ‐2 Distrust scale is useful as a screening tool of the core features of the PPD . We address potential clinical applications for the instrument and discuss limitations from the present study.     

Reflection on metacognition in real life situations: the truth is out there

This article was prepared to extend the traditional view of metacognition to include the orientation of thematic and common features analyses of events in daily-life interactions. A brief historical development of metacognition was presented and discussed to pave the way for this new orientation. This heuristic conceptualization and direction of metacognition was realized and materialized due to research in deaf education. Metacognition, as presented in this article, dispelled misconceptions about the cognitive ability of individuals who live with deafness. It was viewed impetus for continued research.     

驾驶员心理品质检测中的杆型人形图法

在汽车驾驶员心理品质检测研究中,我们根据数学中的多变量图分析方法,并汲取简笔画的优点,用19个人形图变量代表检测所得的17种心理品质数据,来具体、形象地再现每个驾驶员心理品质变量的整体关系。这对于检测结果的分类或进行系统化分析具有重要的实用意义。     

An evaluation of the reliability of probability judgments across response modes and over time

Despite the importance of probability assessment methods in behavioral decision theory and decision analysis, little attention has been directed at evaluating their reliability and validity. In fact, no comprehensive study of reliability has been undertaken. Since reliability is a necessary condition for validity, this oversight is significant. The present study was motivated by that oversight. We investigated the reliability of probability measures derived from three response modes: numerical probabilities, pie diagrams, and odds. Unlike previous studies, the experiment was designed to distinguish systematic deviations in probability judgments, such as those due to experience or practice, from random deviations. It was found that subjects assessed probabilities reliably for all three assessment methods regardless of the reliability measures employed. However, a small but statistically significant decrease over time in the magnitudes of assessed probabilities was observed. This effect was linked to a decrease in subjects overconfidence during the course of the experiment.     

ANALYSIS OF A HIGH-PROBABILITY INSTRUCTIONAL SEQUENCE AND TIME-OUT IN THE TREATMENT OF CHILD NONCOMPLIANCE

This study evaluated the effectiveness of high-probability requests and time-out as treatments for noncompliance that appeared to be maintained by contingent attention in 2 developmental normal children. The introduction of high-probability requests increased compliance for 1 child but not the other. Time-out was effective with both children, and improvements in compliance were maintained at an 8-week follow-up.