Varying Problem Effort and Choice: Using the Interspersal Technique to Influence Choice Towards More Effortful Assignments

College students were exposed to two pairs of mathematics assignments. Assignment Pair A included a high-effort assignment containing 18 long three-digit × two-digit (3×2) multiplication problems with all numerals in each problem being equal to or greater than four and a moderate-effort assignment that contained nine long problems and nine interspersed moderate 3×2 problems with numerals less than four. Assignment Pair B contained similar assignment sheets, the exception being that the high-effort assignment contained six additional one-digit × one-digit (1×1) problems interspersed following every third 3×2 problem. After working on each assignment pair, students ranked assignments and chose a new assignment for homework. Analysis of Assignment Pair A revealed that students overwhelmingly preferred the moderate-effort assignment. Analysis of interaction effects showed that when additional brief problems were added to the high-effort assignments, the proportion of students who chose the high-effort assignment for homework and ranked it as being less difficult, time consuming, and effortful increased significantly. Results support previous research on effort and choice and the hypothesis that a completed discrete problem may serve a reinforcing stimulus.     

Instructive feedback embedded within group instruction for children diagnosed with autism spectrum disorder

The present study evaluated the effects of instructive feedback embedded within a group discrete trial teaching to teach tact relations to nine children diagnosed with autism spectrum disorder using a nonconcurrent multiple‐baseline design. Dependent variables included correct responses for: primary targets (directly taught), secondary targets (taught via instructive feedback), primary observational targets (directly taught to other members of the group), and secondary observational targets (taught via instructive feedback provided to other members of the group). Results showed that all nine participants reached the mastery criterion for the primary targets, as well as acquired the secondary and observational targets without direct teaching. Clinical implications and areas for future research are provided.     

Changes in Multidigit Synergies and Their Feed-Forward Adjustments in Multiple Sclerosis

The authors explored the changes in multidigit synergies in patients with multiple sclerosis (MS) within the framework of the uncontrolled manifold hypothesis. The specific hypotheses were that both synergy indices and anticipatory synergy adjustments prior to the initiation of a self-paced quick action would be diminished in the patients compared to age-matched controls. The MS patients and age-matched controls (n = 13 in both groups) performed one-finger and multifinger force production tasks involving both accurate steady-state force production and quick force pulses. The patients showed significantly lower maximal finger forces and a tendency toward slower force pulses. Enslaving was increased in MS, but only in the lateral fingers (index and little). Indices of multifinger synergies during steady-state force production were lower in MS, mainly due to the lower amount of intertrial variance that did not affect total force. Anticipatory synergy adjustments were significantly delayed in MS. The results show that MS leads to significant changes in multidigit synergies and feed-forward adjustments of the synergies prior to a quick action. The authors discuss possible contributions of subcortical structures to the impaired synergic control.     

Integrating Dimensional and Discrete Theories of Emotions: A New Set of Anger- and Fear-Eliciting Stimuli for Children

The selection of appropriate stimuli for inducing specific emotional states has become one of the most challenging topics in psychological research. In the literature there is a lack of affective picture database specifically suited to investigate emotional response in children. Here the authors present the methodology that led us to create a new database (called Anger- and Fear-Eliciting Stimuli for Children) of affective stimuli inducing experiences of 3 target emotions (neutral, anger, and fear) to use in experimental session involving children. A total of 84 children were asked to (a) indicate the perceived emotion and its intensity and (b) rate the three affective dimensions of the Self-Assessment Manikin (SAM). Based on concordance between labeled and expected target emotion, the authors decided to select 15 stimuli to be included in Multivariate modeling techniques were applied to evaluate the association between expected target emotion and SAM ratings. The authors found that the hit rate for the neutral pictures was good (greater than 81%), for fear-eliciting pictures it was greater than 64%, and for anger-eliciting pictures it was moderate (between 45% and 56%). The study results reveal also an age effect only in the arousal scale. However, the authors did not find significant gender-related differences in SAM ratings.     

A Comparison of Methods for Creating Multiple Imputations of Nominal Variables

Many variables that are analyzed by social scientists are nominal in nature. When missing data occur on these variables, optimal recovery of the analysis model's parameters is a challenging endeavor. One of the most popular methods to deal with missing nominal data is multiple imputation (MI). This study evaluated the capabilities of five MI methods that can be used to treat incomplete nominal variables: multiple imputation with chained equations (MICE) using polytomous regression as the elementary imputation method; MICE based on classification and regression trees (CART); MICE based on nested logistic regressions; the ranking procedure described by Allison (2002 Allison, P. D. (2002). Missing data. Thousand Oaks, CA: Sage Publications. https://doi.org/10.4135/9780857020994.n4[Crossref] , [Google Scholar]); and a joint modeling approach based on the general location model. We first motivate our inquiry with an applied example and then present the results of a Monte Carlo simulation study that compared the performance of the five imputation methods under conditions of varying sample size, percentage of missing data, and number of nominal response categories. We found that MICE with polytomous regression was the strongest performer while the Allison (2002 Allison, P. D. (2002). Missing data. Thousand Oaks, CA: Sage Publications. https://doi.org/10.4135/9780857020994.n4[Crossref] , [Google Scholar]) ranking procedure and MICE with CART performed poorly in most conditions.     

Evaluation of Multi-parameter Test Statistics for Multiple Imputation

In Ordinary Least Square regression, researchers often are interested in knowing whether a set of parameters is different from zero. With complete data, this could be achieved using the gain in prediction test, hierarchical multiple regression, or an omnibus F test. However, in substantive research scenarios, missing data often exist. In the context of multiple imputation, one of the current state-of-art missing data strategies, there are several different analogous multi-parameter tests of the joint significance of a set of parameters, and these multi-parameter test statistics can be referenced to various distributions to make statistical inferences. However, little is known about the performance of these tests, and virtually no research study has compared the Type 1 error rates and statistical power of these tests in scenarios that are typical of behavioral science data (e.g., small to moderate samples, etc.). This paper uses Monte Carlo simulation techniques to examine the performance of these multi-parameter test statistics for multiple imputation under a variety of realistic conditions. We provide a number of practical recommendations for substantive researchers based on the simulation results, and illustrate the calculation of these test statistics with an empirical example.     

Introductory remarks by the issue editors: The multiple dimensions of the parent–baby story

Abstract

In their introductory remarks, the guest editors, themselves presenters at the conference “Parent–Infant Disturbance: Theory and Therapy,” introduce the philosophy and methodology underlying this interdisciplinary psychoanalytic conference and outline the multiple dimensions of the issue at hand, as they are addressed by the individual contributions to this volume. The paper concludes with a remembrance of and dedication to the victims of the Paris terrorist attack of November 13, 2015.     

Navigation in multiobjective optimization methods

Building on previous work of the authors, this paper formally defines and reviews the first approach, referred to as navigation , towards a common understanding of search and decision‐making strategies to identify the most preferred solution among the Pareto set for a multiobjective optimization problem. In navigation methods, the decision maker interactively learns about the problem, whereas the decision support system learns about the preferences of the decision maker. This work introduces a detailed view on navigation leading to the identification of integral components and features. A number of different existing navigation methods are reviewed and characterized. Finally, an overview of applications involving navigation is given, and promising future research direction are discussed.     

Design and analysis of semi-controlled studies

Semi-controlled studies provide a hybrid approach in between controlled experiments and naturalistic driving studies. As in controlled experiments, the researcher can assign participants to groups, select the route and define the tasks, but the participants are given more freedom when it comes to if, when, where and how to perform the tasks. Increased flexibility makes it possible to investigate how drivers use tactical behaviour to accommodate task execution. The disadvantage is decreased control and more complicated analyses. The main objective of this paper is to discuss how to analyse data obtained in semi-controlled studies.The analysis of data from a semi-controlled study include three types of variables: (i) variables that describe the experimental design, (ii) variables that describe the tactical choices of the participants and (iii), operational variables such as speed, lateral position or glance behaviour. To analyse the three types of variables a two-step procedure is suggested. First, the tactical indicators are analysed with regard to the experimental design. Second, the operational indicators are analysed and the tactical indicators are used to divide participants into sub-populations. The semi-controlled design does not need any new statistical procedures to be developed. It is more important that the analysis conditions on the initial properties and not on structures that happen to occur during the experiment, like where the participant chose to do a certain task.We recommend to use the semi-controlled study method when investigating questions involving adaptive and compensatory behaviour on the tactical level. It is especially useful if causal relationships are of interest, if the data collection should be accelerated in comparison to naturalistic studies, and if certain geographical locations definitely should be included.     

心理理论的ERP研究:基于多重成分框架的视角

心理理论是社会认知的核心能力之一。现有的心理理论ERP研究以心理理论较为公认的4个成分信念、愿望、意图和情绪为框架,表现出了一些一致性的规律:心理理论相关的脑电成分根据不同的心理理论成分而有所区分;不同心理理论成分诱发的相关脑电出现的位置表现出跨任务的一致性;心理理论的ERP发展研究在儿童身上表现出与成人类似的结果,但也具有时间窗口更长,位置分布更宽广的特性。未来的研究需要设计出更符合ERP研究技术要求的任务范式,并注意心理理论概念结构的完整性,还应探寻心理理论各成分加工的共同电生理基础。