In the lab, we generally explore automatic evaluative processing, specifically how the evaluation of threat can be distinguished from other types of negativity, and how such unique processing plays out from a social cognitive perspective. I apply this threat distinction to the study of many phenomena, both basic and more applied. While we pursue more basic work on threat perception, we also see how threat influences social phenomena, specifically prejudice. We also pursue research on attitudes more generally, specifically those that arise from evaluative conditioning. Please see below for brief descriptions of some of these lines of research.
The Dual Implicit Process (DIP) Model
March, D. S., Gaertner, L., & Olson, M. A. (2018). On the prioritized processing of threat in a Dual Implicit Process model of evaluation. Psychological Inquiry, 19, 1-13.
March, D. S., Gaertner, L., & Olson, M. A. (2018). Clarifying the explanatory scope of the Dual Implicit Process model. Psychological Inquiry, 19, 37-43.
I have developed the dual implicit process (DIP) model, which describes two functionally distinct and serially-linked automatic evaluative processes: the first automatic (or implicit) process (i1) is solely oriented toward evolutionarily derived and socially learned threats to bodily harm. This initial process precedes and potentially influences the temporally subsequent automatic (or implicit) process (i2) that encompasses the full evaluative continuum (positive to negative) and includes evaluative information beyond mere threat. These two implicit processes precede and potentially influence explicit and controlled judgments and behaviors. All of these processes feed information forward and back to influence each other. The way that this dual implicit processing occurs is by taking advantage of an evolutionarily adapted dual route for processing information.
In broad terms, humans have a quick and dirty path for rapidly processing and responding to perceived threats, and another more cortical path that provides more nuanced information.By incorporating into dual process models what we argue is a qualitative difference between automatic threat and other automatic evaluative processing, the DIP model advances our understanding of the entire evaluative process. Instead of lumping automatic prejudice, food cravings, phobias, intimate partner violence, and addictions into the same “implicit” box, we propose that some stimuli and events—specifically those indicating an immediate threat of bodily harm—are processed in a unique fashion.
Distinguishing Threat from Negative Valence
March, D. S., Gaertner, L., & Olson, M. A. (2017). In harm’s way: On preferential response to threatening stimuli. Personality and Social Psychology Bulletin, 43, 1519-1529.
Data and materials available on the Open Science Framework website.
Given the evolutionary significance of survival, the mind might be particularly sensitive (in terms of strength and speed of reaction) to stimuli that pose an immediate threat to physical harm. To rectify limitations in past research, I pilot-tested stimuli to obtain images that are threatening, nonthreatening-negative, positive, or neutral. The important thing about these images is that while both the threatening and negative images are indeed negative in valence, only the threatening images contain actual survival threats. That way, any difference in reactions to these two image sets is not due to their valence, since they are both equally negative, but due to their different threat-relevance.These images and valence/arousal ratings can be accessed by downloading this folder.
I used these images in three studies using a visual search task, a facial electromyography paradigm (i.e., the startle-eyeblink paradigm), and eye-tracking. In the figure to the left you can see that participants (a) were faster to detect a threatening than nonthreatening-negative image when each was embedded among positive or neutral images, (b) oriented their initial gaze more frequently toward threatening than nonthreatening-negative, positive, or neutral images, and (c) evidenced larger startle-eyeblinks to threatening than to nonthreatening-negative, positive, or neutral images.
This research indicates that the mind initially responds more strongly and quickly to threatening than nonthreatening-negative stimuli and highlights the nuanced way disparate types of negatively valenced stimuli are evaluated. It also suggests that integrating such sensitivity to threat into social cognitive processes of evaluation in the form of a Dual Implicit Process model could account for a wider array of social functioning.
Distinguishing Threat from Valence as a Source of Bias
March, D., S. & Gaertner, L., & Olson, M. A. (in press). Danger or dislike: Distinguishing threat from valence as sources of automatic anti-Black bias. Journal of Personality and Social Psychology.
Data and materials available on the Open Science Framework website.
The threat-valence distinction may be particularly relevant for understanding specific group-based prejudices. For example, Black individuals are disproportionate victims of police violence. This could merely be due to a stronger dislike of Black individuals relative to members of other racial backgrounds (police are 4, 18, and 3 times more likely to use force on Blacks than Hispanics, Asians, and Whites, respectively). Alternatively, despite a range of negative stereotypes with which Blacks are associated, this pattern might be primarily due to associations of Black men with physical threat. To test this, we methodologically differentiated threat and negativity in examining anti-black bias among White Americans.In Studies 1 and 2, positive, negative, and threatening targets (from the above-described image set) were evaluated following Black or White face primes in evaluative priming tasks. In both studies, participants were faster to evaluate threat but not negative targets following Black vs. White primes. This implies that threat, but not general negative valence, is a primary source of automatic anti-Black bias.
Using mouse-tracking, Studies 3 and 4 assessed the relative strength of Black-threat vs. Black-negative associations by pitting threat and non-threat negative response labels within singular trials (see “TICC” under current research for a full explanation of the mouse-tracking analyses). In study 3, participants tended to categorize angry Black (vs. White or Asian) faces as threatening (“Dangerous” response label), and this was no more affected by negative distractor labels (“Depressed”) than positive (“Happy”) or neutral (“Calm”) distractors. Study 4 replicated these findings using alternative response labels (positive, dangerous, and negative vs. not-positive, not-dangerous, and not-negative). By simultaneously pitting threat against negativity within single trials, these findings demonstrate that Black-threat associations are stronger than Black-negative associations.Last, Study 5 combined the evaluative priming task of Studies 1 and 2 with the simultaneous pairings of threat and negativity of Studies 3 and 4. Participants categorized non-threatening negative (e.g., awful, disliked, inferior) or threatening word targets (e.g., aggressive, harmful, murderous) following typical Black (e.g., Darnell, DeAndre, DeShawn) or White (e.g. Brad, Connor, Ethan) name primes. Here, participants were faster to categorize threatening words following Black vs. White primes yet demonstrated a non-significantly slower response to negative words after Black vs. White primes. These results conceptually replicate the findings of Studies 3 and 4, demonstrating that White Americans more strongly associate Black men with threat than negativity.
Methodologically differentiating threat from valence showed that that White Americans automatically evaluate Black men as survival threats. Critically, this work does not suggest that White Americans lack negative (or positive) stereotypes of Black men but rather that White Americans’ initial (or early automatic) evaluation of Black men is that they pose a survival threat. This distinction holds several implications for anti-Black prejudice. Indeed, certain instances of anti-Black bias may specifically result from automatic threat evaluations. The racial disparity in police violence, for instance, may specifically reflect threat responses due to implicit threat evaluations rather than merely reflecting disdain or dislike. If so, interventions aimed at reducing such bias would benefit from particularly addressing threat response or danger associations.
In-group and Out-group Bias Toward Hispanics
March, D. S.& Graham, R. (2015). Exploring implicit ingroup and outgroup bias toward Hispanics. Group Processes and Intergroup Relations, 18, 89-103.
For an overview, see: March, D. S., Olson, M. A. & Fazio, R. H. (2018). The Implicit Misattribution Model of Evaluative Conditioning. Social Psychological Bulletin, 13, e27574.
News Media Depictions of Obama Influence Automatic Attitudes – Implications for the Obama Effect
March, D. S., Kendrick, R., Fritzlen, K., & Olson, M. A. (2016). News media depictions of Obama influence automatic evaluative associations: Implications for the Obama Effect. Social Cognition, 34, 504-522.
In Study 1, images of Obama from FoxNews.com were rated more negatively than images of him from CNN.com. In Study 2 (n=215), participants with weaker attitudes exposed to FoxNews.com images (versus all other images) evinced the most negative SC-IAT bias toward Obama. Thus, incidental exposure to valenced media portrayals can impact attitudes toward public figures.