Tracking Fluctuations in Psychological States Using Social Media Language: A Case Study of Weekly Emotion

Personality psychologists are increasingly documenting dynamic, within-person processes. Big data methodologies can augment this endeavour by allowing for the collection of naturalistic and personality-relevant digital traces from online environments. Whereas big data methods have primarily been used to catalogue static personality dimensions, here we present a case study in how they can be used to track dynamic fluctuations in psychological states. We apply a text-based, machine learning prediction model to Facebook status updates to compute weekly trajectories of emotional valence and arousal. We train this model on 2895 human-annotated Facebook statuses and apply the resulting model to 303 575 Facebook statuses posted by 640 US Facebook users who had previously self-reported their Big Five traits, yielding an average of 28 weekly estimates per user. We examine the correlations between model-predicted emotion and self-reported personality, providing a test of the robustness of these links when using weekly aggregated data, rather than momentary data as in prior work. We further present dynamic visualizations of weekly valence and arousal for every user, while making the final data set of 17 937 weeks openly available. We discuss the strengths and drawbacks of this method in the context of personality psychology's evolution into a dynamic science. © 2020 European Association of Personality Psychology     

Emotional intelligence research in Australia: Past contributions and future directions

Emotional intelligence (EI) is an intriguing and popular area of research, focusing as it does on individual differences in qualities at the intersection of intelligence and emotion. Research to date has focused on three key questions: (a) How to define EI? (b) How to measure EI? and (c) What is EI good for? This review describes the key contributions of Australian researchers to these questions before outlining the current focus and future directions of EI research in Australia. Australian research teams have been instrumental in clarifying the definition of EI, developing innovative measures of EI and examining the life domains EI influences. We suggest that with the contributions of Australian research to the earlier definitional and measurement questions, Australian researchers are now able to address questions about the processes and mechanisms by which EI translates into positive outcomes in diverse life domains.     

Mood and judgments based on sequential sampling

Different adaptive styles characterize cognition and behavior in different affective states. Whereas negative affect supports accommodation (i.e., stimulus‐driven bottom‐up processing), positive affect supports assimilation (i.e., self‐determined top‐down processing). Applying this well‐established rule to binary choices after self‐truncated information sampling, we predicted that positive mood should render choices less dependent on large samples than negative mood. Consequently, the potential primacy advantage underlying Wald's ( 1947 ) sequential testing (i.e., quick and correct decisions from the first few items in a sample) was exploited more efficiently when participants were in positive rather than negative mood. This efficient utilization of small samples in positive mood was obtained under the very conditions derived on a priori ground from a statistical model, namely, when a response criterion or threshold was high and when the true difference between choice options was relatively small. Copyright © 2009 John Wiley & Sons, Ltd.     

Using diffusion models to understand clinical disorders

Sequential sampling models provide an alternative to traditional analyses of reaction times and accuracy in two-choice tasks. These models are reviewed with particular focus on the diffusion model (Ratcliff, 1978) and how its application can aid research on clinical disorders. The advantages of a diffusion model analysis over traditional comparisons are shown through simulations and a simple lexical decision experiment. Application of the diffusion model to a clinically relevant topic is demonstrated through an analysis of data from nonclinical participants with high- and low-trait anxiety in a recognition memory task. The model showed that after committing an error, participants with high-trait anxiety responded more cautiously by increasing their boundary separation, whereas participants with low-trait anxiety did not. The article concludes with suggestions for ways to improve and broaden the application of these models to studies of clinical disorders.     

Discouraging unethicality versus encouraging ethicality: Unraveling the differential effects of prevention‐ and promotion‐focused ethical leadership

Theory on the impact of ethical leadership has traditionally been based on a deontological approach to morality. Underlying this perspective is the assumption that all leader behaviors that encourage “normatively appropriate conduct” will influence followers in a similar fashion. Put differently, the current consensus seems to suggest that actions that focus on preventing unethical behavior—attending to “the wrong”—will have the same impact as actions that focus on promoting ethical behavior—attending to “the right.” Taking a within‐person approach, we draw upon social exchange theory to challenge this consensus and build theory that suggests a follower's felt trust from their leader will be differentially impacted by prevention‐ versus promotion‐focused ethical leadership. We also explore how these different types of ethical leadership may indirectly, through felt trust, impact citizenship behavior and counterproductive work behavior. Finally, we consider how the role of the “moral manager” may interact with the “moral person” by identifying leader moral hypocrisy as an important between‐person moderator of these effects. Given the importance of ethical decision‐making in organizations and the calls for increased ethical leadership, our findings have important implications for both theory and practice.     

Posttraumatic stress and depression: potential pathways to disease burden among heart failure patients

Background and Objectives: Posttraumatic stress disorder (PTSD) and Major Depressive Disorder (MDD) are associated with high disease burden. Pathways by which PTSD and MDD contribute to disease burden are not understood. Design: Path analysis was used to examine pathways between PTSD symptoms, MDD symptoms, and disease burden among 251 low-income heart failure patients. Methods: In Model 1, we explored the independent relationship between PTSD and MDD symptoms on disease burden. In Model 2, we examined the association of PTSD symptoms and disease burden on MDD symptoms. We also examined indirect associations of PTSD symptoms on MDD symptoms, mediated by disease burden, and of PTSD symptoms on disease burden mediated by MDD symptoms. Results: Disease burden correlated with PTSD symptoms (r = .41; p < .001) and MDD symptoms (r = .43; p < .001) symptoms. Both models fit the data well and displayed comparable fit. MDD symptoms did not mediate the association of PTSD symptoms with disease burden. Disease burden did mediate the relationship between PTSD symptoms and MDD symptoms. Conclusions: Results support the importance of detection of PTSD in individuals with disease. Results also provide preliminary models for testing longitudinal data in future studies.     

Experiences of father carers of children with Autism Spectrum Disorder: An exploratory study

This study aimed to explore the carer experiences of fathers of children with Autism Spectrum Disorder (ASD). A total of eight South African fathers between the ages of 38 and 45 years were the interview informants. They cared for at least one child with ASD each and their children with ASD were within the age range of five to nine years (n=9, males=7, females=2, Low functioning=4, Moderately functioning=4, High functioning=1).The father carers completed a semi-structured interview. The data were analysed thematically. Four primary themes emerged from the analysis pertaining to aspects of rescoping their futures to include the care of a child with ASD, relationship issues, access to and management of resources, information and support, and carer compassion and satisfaction. The fathers shared a view that caring for their children with ASD was both stimulating and enriching, and that with time, they were able to adapt, and better respond, to the specific needs of their child.     

The distribution matters: two types of sample-size tasks

Different studies on how well people take sample size into account have found a wide range of solution rates. In a recent review, Sedlmeier and Gigerenzer (1997) suggested that a substantial part of the variation in results can be explained by the fact that experimenters have used two different types of sample-size tasks, one involving frequency distributions and the other sampling distributions. This suggestion rested on an analysis of studies that, with one exception, did not systematically manipulate type of distribution. In the research reported in this paper, well-known sample-size tasks were used to examine the hypothesis that frequency distribution versions of sample-size tasks yield higher solution rates than corresponding sampling distribution versions. In Study 1, a substantial difference between solution rates for the two types of task was found. Study 2 replicated this finding and ruled out an alternative explanation for it, namely, that the solution rate for sampling distribution tasks was lower because the information they contained was harder to extract than that in frequency distribution tasks. Finally, in Study 3 an attempt was made to reduce the gap between the solution rates for the two types of tasks by giving participants as many hints as possible for solving a sampling distribution task. Even with hints, the gap in performance remained. A new computational model of statistical reasoning specifies cognitive processes that might explain why people are better at solving frequency than sampling distribution tasks. Copyright© 1998 John Wiley & Sons, Ltd.