Hostile Bias Modification Training Can Ease Social Conflicts

Re-framing perceived provocations as "non-hostile" can mitigate conflict.

Posted Sep 30, 2020

Gerd Altmann/Pixabay
Source: Gerd Altmann/Pixabay

Anger and aggression often stem from mistakenly attributing hostile intentions to harmless and ambiguous actions. Is there a way to nip these misunderstandings in the bud? New research suggests that giving someone the benefit of the doubt before assuming the worst is an easy way to avoid unnecessary social conflicts.

An Army-developed online intervention designed to reduce hostile attribution bias by teaching people not to assume "harmful or adverse intent" in response to a perceived provocation can reduce social conflict and improve anger-related outcomes, according to new research. These findings (Osgood et al., 2020) were published on September 11 in the journal Cognitive Therapy and Research.

This registered clinical trial consisted of two computer-based, double-blind, randomized pilot studies. The research was conducted by scientists at the Walter Reed Army Institute for Research and the Army Research Laboratory led by Jeffrey Osgood, a research psychologist at WRAIR.

This two-part studies' goal was to see if a novel online cognitive intervention called Hostile Bias Modification Training (HBMT) could reduce overall hostile attribution bias as well as perceived hostility, anger, and aggression.

In the first study, volunteers who completed a computer-based HBMT intervention (vs. placebo) subsequently interpreted hypothetical vignettes of "perceived provocation" as significantly less hostile and reported significantly less imagined anger and aggression. In the second study, the computer-based HBMT intervention (vs. placebo) was associated with a reduction of hostile attribution bias. 

Hostile attribution bias was indexed using the "Angry Cognitions Scale" psychometric measure developed by Ryan Martin and Eric Dahlen (Martin & Dahlen, 2007). ACS evaluates adaptive processing, catastrophic evaluating, demandingness, inflammatory labeling, misattributing causation, and overgeneralizing. 

For secondary outcome measures of anger and aggression, the researchers used the Trait Anger Scale (Wilk et al., 2015) and a State Aggression Survey adapted from psychometric measures used to gauge "road rage" based on a Driving Anger Expression Inventory (Deffenbacher et al., 2002) and a Cyber-Aggression Questionnaire (Álvarez-García et al., 2016). 

After following study participants for up to 96 hours after performing HBMT, Osgood et al. found that, in general, this computer-based online intervention reduced hostile attribution bias, aggressive driving, and cyber-aggression. "These results suggest HBMT may be an easily implemented intervention to improve anger-related outcomes," Osgood et al. (2020) concluded.

"Though more research is needed, we believe that HBMT could be effective as both a standalone tool for use at home, in field settings, or in concert with other therapeutic options to help mitigate unwarranted anger and aggression," Osgood stated in a press release. "We are excited about HBMT's potential to both prevent and treat behavioral health concerns."


Jeffrey M. Osgood, Sue E. Kase, Erin G. Zaroukian & Phillip J. Quartana. "Online Intervention Reduces Hostile Attribution Bias, Anger, Aggressive Driving, and Cyber-Aggression, Results of Two Randomized Trials." Cognitive Therapy and Research (First published: September 11, 2020) DOI: 10.1007/s10608-020-10147-8