Dan R. Johnson

Emotional Attention Set-Shifting and Its Relationship to Anxiety and Emotion Regulation

Attentional deployment is a primary strategy individuals use to regulate emotion. In 2 experiments, a measure of an individuals ability to deploy attention toward and away from emotional mental representations was developed. This measure of attentional control capacity for emotion adapted an explicit-cuing task switching paradigm in which participants had to shift between emotional and neutral mental sets. Experiment 1 (N = 118) showed that those higher in trait anxiety and worrisome thoughts took longer to switch from a neutral to an emotional mental set. In Experiment 2 (N = 42), participants were given a stressful anagram task, and those who switched more efficiently from a neutral set to an emotional set were more frustrated by the stressful task. In addition, those who switched more efficiently from an emotional set to a neutral set persisted longer on the stressful task. These findings provide an initial step toward identifying possible mechanisms through which individuals apply attentional control to emotional mental representations to regulate emotion.

Participants at your fingertips: Using Amazon’s Mechanical Turk to increase student–faculty collaborative research.

The literature suggests students gain important skills when directly involved with faculty in research. However, students at smaller institutions are often faced with limited research opportunities and faculty members are faced with limited participant-pools, funding, and space to perform research. Amazon’s Mechanical Turk (MTurk) may provide a solution to many of these problems. MTurk provides an online human participant-pool, along with tools to build experiments, and it allows data to be collected quickly and inexpensively. In this study of narrative fiction and empathy, data was collected using the traditional, laboratory-based approach, and on MTurk using identical measures and protocols. Results indicated MTurk data exhibits comparable reliability, gender and ethnicity composition to data collected in the laboratory. Two important differences emerged: MTurk participants were 10 years older, on average, and they demonstrated higher scores on trait measures of empathy and state measures of involvement into the story presented in the study. A brief user’s guide to MTurk is presented that caters to first-time users. Finally, common pitfalls and their solutions are presented with the hope that faculty and students can begin doing research on MTurk immediately.

Changing Race Boundary Perception by Reading Narrative Fiction

Participants read a story about a counterstereotypical Muslim woman and were then asked to determine the race of ambiguous-race Arab-Caucasian faces. Compared to a content-matched control condition, participants who read the narrative exhibited lower categorical race bias by making fewer categorical race judgments and perceiving greater genetic overlap between Arabs and Caucasians (Experiment 1). In Experiment 2, participants determined the race of ambiguous-race Arab-Caucasian faces depicting low and moderate anger. Emotion-related perceptual race bias was observed in the control conditions where higher intensity anger expressions led participants to disproportionately categorize faces as Arab. This bias was eliminated in the narrative condition.

Initial Clinical Validation of an Embedded Performance Validity Measure within the Automated Neuropsychological Metrics (ANAM)

The measurement of effort and performance validity is essential for computerized testing where less direct supervision is needed. The clinical validation of an Automated Neuropsychological Metrics-Performance Validity Index (ANAM-PVI) was examined by converting ANAM test scores into a common metric based on their relative infrequency in an outpatient clinic sample with presumed good effort. Optimal ANAM-PVI cut-points were determined using receiver operator characteristic (ROC) curve analyses and an a priori specificity of 90%. Sensitivity/specificity was examined in available validation samples (controls, simulators, and neurorehabilitation patients). ANAM-PVI scores differed between groups with simulators scoring the highest. ROC curve analysis indicated excellent discriminability of ANAM-PVI scores ≥5 to detect simulators versus controls (area under the curve = 0.858; odds ratio for detecting suboptimal performance = 15.6), but resulted in a 27% false-positive rate in the clinical sample. When specificity in the clinical sample was set at 90%, sensitivity decreased (68%), but was consistent with other embedded effort measures. Results support the ANAM-PVI as an embedded effort measure and demonstrate the value of sample-specific cut-points in groups with cognitive impairment. Examination of different cut-points indicates that clinicians should choose sample-specific cut-points based on sensitivity and specificity rates that are most appropriate for their patient population with higher cut-points for those expected to have severe cognitive impairment (e.g., dementia or severe acquired brain injury).

Threat to the Group’s Image Can Motivate High Identifiers to Take Action Against In-group Transgressions

When transgressions are committed by a group, those highly identified with the group are often least likely to recognize the transgressions, feel collective guilt, and engage in action to address them. We hypothesized that especially among high identifiers, demonstrating that in-group transgressions threaten the group’s image can induce normative conflict and thus collective guilt and action. In the first study, we demonstrate that high (vs. low) image threat increases normative conflict among high identifiers. In Study 2, we show that inducing normative conflict through image threat leads to increased collective guilt and collective action among high identifiers. In Study 3, we replicate this effect with the addition of a control condition to demonstrate increased normative conflict and collective guilt relative to both a low threat and baseline conditions. In Study 4, we again replicate these effects with a modified manipulation that more precisely manipulated image threat. Together, these studies indicate that image threat can be an effective motivator for high identifiers to address in-group transgressions.

Metacognition in argument generation: the misperceived relationship between emotional investment and argument quality

ABSTRACT Overestimation of one’s ability to argue their position on socio-political issues may partially underlie the current climate of political extremism in the U.S. Yet very little is known about what factors influence overestimation in argumentation of socio-political issues. Across three experiments, emotional investment substantially increased participants’ overestimation. Potential confounding factors like topic complexity and familiarity were ruled out as alternative explanations (Experiments 1–3). Belief-based cues were established as a mechanism underlying the relationship between emotional investment and overestimation in a measurement-of-mediation (Experiment 2) and manipulation-of-mediator (Experiment 3) design. Representing a new bias blind spot, participants believed emotional investment helps them argue better than it helps others (Experiments 2 and 3); where in reality emotional investment harmed or had no effect on argument quality. These studies highlight misguided beliefs about emotional investment as a factor underlying metacognitive miscalibration in the context of socio-political issues.