A Latent Variable Framework for Power Estimation Within Intervention Contexts

This paper presents a latent growth SEM approach for the estimation of treatment effects, and power to detect such effects, within a true experimental design setting in which subjects are randomly assigned to treatment and control conditions. Power estimation is a critical component of intervention experiment design and the testing of their results. Although researchers have become increasingly sophisticated in applying tests for statistical significance in intervention contexts, few are aware of the power of these tests. The issues raised in this paper are not new; however, reminding researchers to consider these points is important. Exactly how the researcher handles these issues will depend on the questions asked and the resources available, as well as other considerations. Discussion underscores the relationship between the reliability of a study's measures and concomitant increases in power obtained within the SEM framework.     

Artificial intelligence for the measurement of vocal stereotypy

Both researchers and practitioners often rely on direct observation to measure and monitor behavior. When these behaviors are too complex or numerous to be measured in vivo, relying on direct observation using human observers increases the amount of resources required to conduct research and to monitor the effects of interventions in practice. To address this issue, we conducted a proof of concept examining whether artificial intelligence could measure vocal stereotypy in individuals with autism. More specifically, we used an artificial neural network with over 1,500 minutes of audio data from 8 different individuals to train and test models to measure vocal stereotypy. Our results showed that the artificial neural network performed adequately (i.e., session-by-session correlation near or above .80 with a human observer) in measuring engagement in vocal stereotypy for 6 of 8 participants. Additional research is needed to further improve the generalizability of the approach.     

Self‐Priming in Production: Evidence for a Hybrid Model of Syntactic Priming

Syntactic priming in language production is the increased likelihood of using a recently encountered syntactic structure. In this paper, we examine two theories of why speakers can be primed: error‐driven learning accounts (Bock, Dell, Chang, & Onishi, 2007; Chang, Dell, & Bock, 2006) and activation‐based accounts (Pickering & Branigan, 1999; Reitter, Keller, & Moore, 2011). Both theories predict that speakers should be primed by the syntactic choices of others, but only activation‐based accounts predict that speakers should be able to prime themselves. Here we test whether speakers can be primed by their own productions in three behavioral experiments and find evidence of structural persistence following both comprehension and speakers’ own productions. We also find that comprehension‐based priming effects are larger for rarer syntactic structures than for more common ones, which is most consistent with error‐driven accounts. Because neither error‐driven accounts nor activation‐based accounts fully explain the data, we propose a hybrid model.     

Failures to induce implicit evaluations by means of approach–avoid training

Woud, Becker, and Rinck (2008) asked participants to repeatedly push pictures of certain faces away and to pull pictures of other faces towards them using a joystick. Performance in a subsequent affective priming task showed that previously pulled faces evoked more positive implicit evaluations then previously pushed faces. We report five studies in which we failed to find consistent evidence for the effect of approach–avoid training on implicit evaluations. We also failed to reproduce the effect reported by Woud et al. when reanalysing their data. An overall analysis that included our data, the data of Woud et al. and additional data provided by Woud and colleagues also did not reveal a significant effect of approach–avoid training on implicit evaluations. We conclude that the impact of approach–avoid training on implicit evaluations is subject to subtle boundary conditions.     

Finding Empathy: How Neuroscientific Measures,Evidence and Conceptualizations Interact

ABSTRACT

Questions about how empathy should be conceptualized have long been a preoccupation of the field of empathy research. There are numerous definitions of empathy that have been proposed and that often overlap with other concepts such as sympathy and compassion. This makes communication between research groups or across disciplines difficult. Many researchers seem to see the diversity of definitions as a problem rather than a form of benign pluralism. Within this debate about conceptualization, researchers sometimes suggest that more neuroscientific evidence will make the problem go away – that uncovering the processes underlying empathy will thereby also sort out conceptual difficulties. In this paper, I challenge this assumption by examining how neuroscientists studying empathy use concepts in practice – both in the development of their measures and in the interpretation of their data. I argue that this neuroscientific literature demonstrates that continuity and stability comes from the use of certain established measures, while progress comes from expansion upon those measures and the flexibility of stated concepts. We do not ‘find’ empathy through increased neuroscientific evidence but we do get closer to understanding empathic processes, flexibly understood.     

Reliability and validity of measures of anger/hostility in singapore: Cook & Medley Ho Scale, STAXI and Buss-Durkee hostility inventory

As part of a larger research programme concerned with the role of anger/hostility in heart disease in Singapore, three commonly used measures of anger/hostility (Cook & Medley Ho Scale, STAXI, Buss-Durkee Hostility Inventory) were examined for reliability and validity in an Asian population. A total of 968 Singaporean Chinese, Malay and Indian respondents completed one or more of these measures together with measures of symptom and illness experience. In addition, blood pressure and heart rate measures were taken for 201 respondents. Overall, the Ho and STAXI measures had reasonably high internal consistency and test-retest reliability. Internal consistency and test-retest reliability for the Buss Durkee measure were high for the total score but variable for the component scales. Correlation and regression showed that the Ho and STAXI appeared to be tapping a common core of variance, which can be characterized as trait anger. Correlations of the Ho and STAXI with health measures produced modest but statistically significant correlations for measures of symptom and illness experience and generally low and non-significant correlations for heart rate and blood pressure.     

Examining Individual Differences in Interpersonal Influence: On the Psychometric Properties of the Generalized Opinion Leadership Scale (GOLS)

Opinion leadership describes an individual's tendency to informally influence others’ attitudes and overt behaviors. In contrast to contemporary views of opinion leadership as a highly domain-specific trait, this paper introduces a multi-faceted personality trait, generalized opinion leadership (GOL) that characterizes exceptionally influential individuals independent of a specific subject area. Two studies report on the psychometric properties of a scale to assess GOL. Study 1 is based on three independent samples (N = 1,575, N = 1,275, and N = 231) and demonstrates the factorial structure of the instrument and its measurement invariance across sex, age, and educational levels. Study 2 (N = 310) analyzes multitrait-multiinformant data to highlight the scale's discriminant validity with regard to innovativeness and trendsetting.     

The Implicit Image of God: God as Reality and Psychological Well‐Being

Research has widely demonstrated that religiosity is related to psychological well‐being even in situations of severe illness. To assess religious beliefs, explicit measures have generally been used. In this study, we measured the belief that God is reality as opposed to myth or abstraction by using an implicit technique (the Single Category Implicit Association Test). The study was carried out in Italy, where a large majority of the population is Catholic, and the prevailing image of God is that of a compassionate and supportive father. Participants were cancer patients identifying themselves as believers. As expected, the automatic belief that God is reality (vs. abstraction) was related to beneficial outcomes: lower reported psychophysical anxiety symptoms and a weaker use of avoidance strategies to cope with stress. Thus, also, automatic religious beliefs may affect feelings and behaviors.