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.     

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.     

Exceptionalism or Chinamerica: Measuring Religious Change in the Globalizing World Today

Religion is changing fast in this era of globalization. Major global trends include the growth of Muslims, the shrinking percentage of unaffiliated, and the rapid rise of Christianity in global China. By 2030, China is likely to become the largest Christian country in the world while retaining large numbers of Buddhists, Muslims, and folk religious believers. To capture religious changes more accurately, social scientists of religion must sharpen their measurement tools regarding religiosity; pay more attention to the reality of nonalignment among religious identity, belief, and practice; and acknowledge the reality of nonexclusive/multiple religious beliefs, practices, and identities. Scholars must also take responsibility for developing a clear and nuanced definition of religion, abandon exceptionalist thinking, and seek to discover common patterns of religious change across societies. Conceptual and measurement tools at the disposal of social scientists of religion should enable us to perceive and understand the converging changes of religion in China, the United States, and other societies, without ignoring their historical differences and contemporary particularities.     

Nesselroade and Molenaar's Measurement Concerns and Proposals: An Introduction

In this special section Nesselroade and Molenaar (N & M) propose a provocative new approach to measurement invariance. When measures are collected repeatedly over time (e.g., daily diary studies), a potentially unique measurement model relating the items to the underlying construct can be created for each individual. If hypothesized causal paths specified between constructs (e.g., frustration → aggression) can be constrained to be equal across the individuals, a model with idiographic measurement of the constructs, but with nomothetic structural relationships can be specified. Three commentaries react to N & M's proposal. Revelle and Wilt challenge the priority given by N & M to unique individual measurement structures, arguing that between subjects differences in structural relationships are empirically important and meaningful. Markus's uses David Hume's framework to raise philosophy of science challenges for N & M's approach. Maydeu-Olivares challenges the incremental validity of N & M's approach, arguing that N & M's approach is unlikely to improve the prediction of between subjects criteria. Finally, N & M present a rejoinder to the three commentaries.     

Quantification of human confidence in functional relations

What makes people infer that two continuous-valued entities are functionally related? Involving factors influencing human confidence in the existence of a functional link between two supposed variables has not so far been discussed in function learning literature. By examining this problem and based on relevant results from cognitive psychology, I propose a hypothesis according to which human confidence in a link between cue and criterion is affected by three factors: The difficulty of functions, the level of noise in observed data, and the sample size. Here, the formalization of this hypothesis forms a novel mathematical model of function learning which can also be used for predictions; so the resulting model receives cue-criterion pairs of a supposed relation and produces two outputs: Confidence and predicting function. In an experiment, the performance of a computational implementation of the model is compared with human data. The results show that the model is successful in tracking changes in human confidence. A close correspondence between the predictions of the model and humans was also achieved.     

Cross‐cultural Generalizability of the Alternative Five‐factor Model Using the Zuckerman–Kuhlman–Aluja Personality Questionnaire

Several personality models are known for being replicable across cultures, such as the Five‐Factor Model (FFM) or Eysenck's Psychoticism–Extraversion–Neuroticism (PEN) model, and are for this reason considered universal. The aim of the current study was to evaluate the cross‐cultural replicability of the recently revised Alternative FFM (AFFM). A total of 15 048 participants from 23 cultures completed the Zuckerman–Kuhlman–Aluja Personality Questionnaire (ZKA‐PQ) aimed at assessing personality according to this revised AFFM. Internal consistencies, gender differences and correlations with age were similar across cultures for all five factors and facet scales. The AFFM structure was very similar across samples and can be considered as highly replicable with total congruence coefficients ranging from .94 to .99. Measurement invariance across cultures was assessed using multi‐group confirmatory factor analyses, and each higher‐order personality factor did reach configural and metric invariance. Scalar invariance was never reached, which implies that culture‐specific norms should be considered. The underlying structure of the ZKA‐PQ replicates well across cultures, suggesting that this questionnaire can be used in a large diversity of cultures and that the AFFM might be as universal as the FFM or the PEN model. This suggests that more research is needed to identify and define an integrative framework underlying these personality models. Copyright © 2016 European Association of Personality Psychology