EXPRESS: The More You Ask, the Less You Get: When Additional Questions Hurt External Validity

Researchers and practitioners in marketing, economics, and public policy often use preference elicitation tasks to forecast real-world behaviors. These tasks typically ask a series of similarly-structured questions. The authors posit that every time a respondent answers an additional elicitation question, two things happen: (1) they provide information about some parameter(s) of interest, such as their time preference or the partworth for a product attribute, and (2) the respondent increasingly adapts to the task—i.e., using task-specific decision processes specialized for this task that may or may not apply to other tasks. Importantly, adaptation comes at the cost of potential mismatch between the task-specific decision process and real-world processes that generate the target behaviors, such that asking more questions can reduce external validity. The authors used mouse- and eye-tracking to trace decision processes in time preference measurement and conjoint choice tasks: Respondents increasingly relied on task-specific decision processes as more questions were asked, leading to reduced external validity for both related tasks and real-world behaviors. Importantly, the external validity of measured preferences peaked after as few as seven questions in both types of tasks. When measuring preferences, less can be more.

Persuasive Apps for Sustainable Waste Management: A Comparative Systematic Evaluation of Behavior Change Strategies and State-of-the-Art

With the proliferation of ubiquitous computing and mobile technologies, mobile apps are tailored to support users to perform target behaviors in various domains, including a sustainable future. This article provides a systematic evaluation of mobile apps for sustainable waste management to deconstruct and compare the persuasive strategies employed and their implementations. Specifically, it targeted apps that support various sustainable waste management activities such as personal tracking, recycling, conference management, data collection, food waste management, do-it-yourself (DIY) projects, games, etc. The authors who are persuasive technology researchers retrieved a total of 244 apps from App Store and Google Play, out of which 148 apps were evaluated. Two researchers independently analyzed and coded the apps and a third researcher was involved to resolve any disagreement. They coded the apps based on the persuasive strategies of the persuasive system design framework. Overall, the findings uncover that out of the 148 sustainable waste management apps evaluated, primary task support was the most employed category by 89% (n = 131) apps, followed by system credibility support implemented by 76% (n = 112) apps. The dialogue support was implemented by 71% (n = 105) apps and social support was the least utilized strategy by 34% (n = 51) apps. Specifically, Reduction (n = 97), personalization (n = 90), real-world feel (n = 83), surface credibility (n = 83), reminder (n = 73), and self-monitoring (n = 50) were the most commonly employed persuasive strategies. The findings established that there is a significant association between the number of persuasive strategies employed and the apps’ effectiveness as indicated by user ratings of the apps. How the apps are implemented differs depending on the kind of sustainable waste management activities it was developed for. Based on the findings, this paper offers design implications for personalizing sustainable waste management apps to improve their persuasiveness and effectiveness.

Employability Social Skills Interventions in Transition-Age Youth with Intellectual Disabilities: A Literature Review

Employability skills are necessary for youth with Intellectual Disabilities (IDs) to successfully navigate their transition from educational settings to autonomous adult life. Most importantly, research evidence has shown that individuals with IDs appear to perform adequately on job tasks, yet they frequently face inadequacies in the social aspects of work life. Although much of the existing employability research has focused on social skills training related to employability for individuals with other disabilities, people with IDs are underrepresented in the literature. Thus, this review aimed to provide insight into the existing social skills interventions that promote employability in transition-age youth with IDs. Results indicated that although there is a limited number of studies regarding intervention programs on improving social skills related to employment for individuals with IDs, the majority of them positively impacted target behaviors, thus highlighting the need for further empirical research.

Who accepts nudges? nudge acceptability from a self-regulation perspective

Background Public acceptability of nudging is receiving increasingly more attention, but studies remain limited to evaluations of aspects of the nudge itself or (inferred intentions) of the nudger. Yet, it is important to investigate which individuals are likely to accept nudges, as those who are supposed to benefit from the implementation should not oppose it. The main objective of this study was to integrate research on self-regulation and nudging, and to examine acceptability of nudges as a function of self-regulation capacity and motivation. Method Participants (N = 301) filled in questionnaires about several components of self-regulation capacity (self-control, proactive coping competence, self-efficacy, perceived control and perceived difficulty) and motivation (autonomous motivation and controlled motivation). To evaluate nudge acceptability, we used three vignettes describing three types of nudges (default, portion size, and rearrangement) that stimulated either a pro-self behavior (healthy eating) or pro-social behavior (sustainable eating) and asked participants to rate the nudges on (aspects of) acceptability. Results Results revealed that there were substantial differences in acceptability between the three types of nudges, such that the default nudge was seen as less acceptable and the rearrangement nudge as most acceptable. The behavior that was stimulated did not affect acceptability, even though the nudges that targeted healthy eating were seen as more pro-self than the nudges targeting sustainable eating. From all self-regulation components, autonomous motivation was the only measure that was consistently associated with nudge acceptability across the three nudges. For self-regulatory capacity, only some elements were occasionally related to acceptability for some nudges. Conclusion The current study thus shows that people are more inclined to accept nudges that target behaviors that they are autonomously motivated for, while people do not meaningfully base their judgments of acceptability on self-regulatory capacity.

Getting Your Data Into SSDforR

This chapter covers how to measure target behaviors and use common software to record and edit client data. Readers are then shown how to import data into R and use the SSD for R functions to analyze their data. The first part of this chapter focuses on the type of data that is most appropriate to record and some common issues related to collecting these. Four different types of measurement are covered, each of which has its own strengths and weaknesses. These include direct behavioral observations, standardized scales, individual rating scales, and logs. When selecting one or more methods of measuring a target behavior, readers will want to consider the specific needs of their clients, the identified problem, and the practice or research situation. The second part of this chapter demonstrates how to use Excel or other spreadsheet programs to quickly and effectively record this data.

Analyzing Baseline Phase Data

This chapter discusses the analysis of the baseline phase. The baseline serves as the comparison for information collected during subsequent phases. It allows the researcher or practitioner to determine if the target behaviors are changing in a desirable or undesirable direction. Two different types of baselines are presented, concurrent and reconstructed. In a concurrent baseline, data are collected simultaneously, while other assessment activities are being conducted. A reconstructed baseline is an attempt to approximate naturally occurring behavior based on memories or case records. Issues related to comparing phases are discussed and illustrated, including stability of the baseline, trending data, and autocorrelation (or serial dependency). Guidance is provided on how each of these can be assessed and addressed, including the transformation of highly autocorrelated data. Examples are provided throughout to illustrate each concept.

Resonant Learning in Scale-free Networks

Over the last decades, analyses of the connectivity of large biological and artificial networks have identified a common scale-free topology, where few of the network elements, called hubs, control many other network elements. In monitoring the dynamics of networks hubs, recent experiments have revealed that they can show behaviors oscillating between ON and OFF states of activation. Prompted by these observations, we ask whether the existence of oscillatory hubs states could contribute to the emergence of specific network dynamical behaviors. Here, we use Boolean threshold networks with scale-free architecture as representative models to demonstrate how periodic activation of the network hub can provide a network-level advantage in learning specific new dynamical behaviors. First, we find that hub oscillations with distinct periods can induce robust and distinct attractors whose lengths depend upon the hub oscillation period. Second, we determine that a given network can exhibit series of different attractors when we sequentially change the period of hub pulses. Using rounds of evolution and selection, these different attractors could independently learn distinct target functions. We term this network-based learning strategy resonant learning, as the emergence of new learned dynamical behaviors depends on the choice of the period of the hub oscillations. Finally, we find that resonant learning leads to convergence towards target behaviors over an order of magnitude faster than standard learning procedures. While it is already known that modular network architecture contributes to learning separate tasks, our results reveal an alternative design principle based on forced oscillations of the network hub.

Examining Benchmarks for the Daily Report Card Intervention in a Therapeutic Recreational Setting

Objective: This study aimed to (1) examine benchmarks for the benefits of the Daily Report Card (DRC) within a therapeutic recreation setting, that is, the Summer Treatment Program (STP) and (2) explore differences in baseline characteristics and treatment outcomes among optimal and suboptimal responders. Benchmarks were examined for children’s DRC target behaviors using standardized mean difference (SMD) effect sizes (ES) across 2-week periods of the STP. Method: Participants were 38 children attending an STP. Results: Aside from teasing, all DRC targets showed improvement by the second 2-week period that was sustained through the third 2-week period. Optimal responders demonstrated greater improvement in parent-rated impairment and camp behaviors than suboptimal responders. Some baseline differences between responder groups were found. Conclusion: This study provides the first benchmarks for change in DRC targets within a therapeutic recreational setting, offering guidelines for treatment expectations. Implications for clinical decision-making, treatment planning, and future research are discussed.

The Implementation of Application Software to Improve Verbal Communication in Children with Autism Spectrum Disorder: A Review

Autism-assistive apps offer therapists and caregivers new approaches for educating and assisting individuals with autism spectrum disorder (ASD), mainly in social interaction. Even though these apps are deemed effective, they are not. These autism-assistive apps are not highly customizable, which limits their usefulness. This article examined the application software that was applied to encourage verbal communication in the intervention for children with ASD. The aim was to determine the minimum requirements for a verbal communication intervention app that adequately satisfies children with ASD, caregivers, and therapists. Databases were searched, including Scopus, Springer, PubMed, Education Resources Information Centre, and Google Scholar, with the following free-text terms combining Boolean operators: autism, children, intervention, verbal communication, software, app, and technology. A total of fifteen studies were found relevant, and the following information was collected: participant characteristics, information on the devices and apps, target behaviors, intervention procedures, and intervention outcomes. The findings suggest that the autism-assistive apps effectively improve verbal communication of children with ASD. For that, the apps should be attractive and engaging to the children with ASD, able to identify the child’s capability and suggest appropriate lesson activities, as well as encompass specific learning outcomes with multilevel lesson strategy. The apps should also use systematic evidence-based intervention procedures in the activities, be able to evaluate the child’s learning progress, and allow caregivers or therapists to keep track of application usage and performance. The use of apps in intervention does provide many benefits. However, they should never replace qualified therapists. App-based interventions make home-based treatment more focused, systematic, and economical.

A Primer on Harnessing Non-enzymatic Posttranslational Modifications for Drug Design

Of the manifold concepts in drug discovery and design, covalent drugs have re-emerged as one of the most promising over the past 20-or so years. All such drugs harness the ability of a covalent bond to drive an interaction between a target biomolecule, typically a protein, and a small molecule. Formation of a covalent bond necessarily prolongs target engagement, opening avenues to targeting shallower binding sites, protein complexes, and other difficult to drug manifolds, amongst other virtues. This opinion piece discusses frameworks around which to develop covalent drugs. Our argument, based on results from our research program on natural electrophile signaling, is that targeting specific residues innately involved in native signaling programs are ideally poised to be targeted by covalent drugs. We outline ways to identify electrophile-sensing residues, and discuss how studying ramifications of innate signaling by endogenous molecules can provide a means to predict drug mechanism and function and assess on- versus off-target behaviors.