Studying appraisal-driven emotion processes: taking stock and moving to the future

ABSTRACT

Appraisal theories of emotion, and particularly the Component Process Model, have claimed over the past three decades that the different components of the emotion process (action tendencies, physiological reactions, expressions, and feeling experiences) are essentially driven by the results of multi-level cognitive appraisals and that the feeling component constitutes a central integration and representation of these processes. Given the complexity of the proposed architecture of emotion generation, comprehensive experimental tests of these predictions are difficult to perform and thus evidence has been slow to appear. Complementing earlier work on self-reported appraisal, a massive amount of empirical results from studies with experimental designs based on appraisal manipulation, using electroencephalographic and electromyographic measures, now confirms many of the theoretical predictions with respect to the effect of different appraisal checks, their interactions, and their exact timing. A major issue for future research is the nature of the coherence or synchronisation of the appraisal-driven components in the unfolding emotion process. It is suggested that interdisciplinary multi-team research will be needed to face the theoretical and methodological challenges of experimentally investigating the dynamics of the emotion process.     

A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial

Death by suicide demonstrates profound personal suffering and societal failure. While basic sciences provide the opportunity to understand biological markers related to suicide, computer science provides opportunities to understand suicide thought markers. In this novel prospective, multimodal, multicenter, mixed demographic study, we used machine learning to measure and fuse two classes of suicidal thought markers: verbal and nonverbal. Machine learning algorithms were used with the subjects’ words and vocal characteristics to classify 379 subjects recruited from two academic medical centers and a rural community hospital into one of three groups: suicidal, mentally ill but not suicidal, or controls. By combining linguistic and acoustic characteristics, subjects could be classified into one of the three groups with up to 85% accuracy. The results provide insight into how advanced technology can be used for suicide assessment and prevention.     

The Relation of Cognitive Reappraisal and Expressive Suppression to Suicidal Ideation and Suicidal Desire

The differential relations between the emotion regulation strategies “cognitive reappraisal” and “expressive suppression” and suicidality in a mixed inpatient sample (N = 232, 69.4% female) of a German psychotherapeutic hospital were examined. Patients filled in the Emotion Regulation Questionnaire and items on suicidal ideation and desire. A structural equation model fitted the data (RMSEA = .044; CFI = .96) and revealed that “expressive suppression” significantly predicted increased suicidal ideation. Moderation analysis showed that results were independent from a current depressive episode. Potential implications for psychotherapeutic treatment of suicidality are discussed.     

BIOLOGY: WHAT ONE NEEDS TO KNOW

Abstract. Biology on this planet represents an astonishing experiment in carbon-based chemistry which, over billions of years, has generated billions of species adapted to countless major and minor fluctuations in ecological circumstances. In one sense there is no way to generalize about biology. While biological activities can all be ultimately explained by physical laws (like everything else in the universe), it is the emergent intensely particular properties of organisms that most interest us. This essay represents an attempt to describe some of the more prominent patterns that emerge from the sea of biological particularities, patterns that present many opportunities for religous reflection.