OBJECTIVE: To test the hypothesis that racial biases in opioid prescribing would be more likely under high levels of cognitive load, defined as the amount of mental activity imposed on working memory, which may come from environmental factors such as stressful conditions, chaotic workplace, staffing insufficiency, and competing demands, one's own psychological or physiological state, as well as from demands inherent in the task at hand. DESIGN:Two (patient race: White vs Black) by two (cognitive load: low vs high) between-subjects factorial design. SETTING AND PARTICIPANTS: Ninety-eight primary care physicians from the Veterans Affairs Healthcare System. METHODS: Web-based experimental study. Physicians were randomly assigned to read vignettes about either a Black or White patient, under low vs high cognitive load, and to indicate their likelihood of prescribing opioids. High cognitive load was induced by having physicians perform a concurrent task under time pressure. RESULTS: There was a three-way interaction between patient race, cognitive load, and physician gender on prescribing decisions (P = 0.034). Hypotheses were partially confirmed. Male physicians were less likely to prescribe opioids for Black than White patients under high cognitive load (12.5% vs 30.0%) and were more likely to prescribe opioids for Black than White patients under low cognitive load (30.8% vs 10.5%). By contrast, female physicians were more likely to prescribe opioids for Black than White patients in both conditions, with greater racial differences under high (39.1% vs 15.8%) vs low cognitive load (28.6% vs 21.7%). CONCLUSIONS: Physician gender affected the way in which patient race and cognitive load influenced decisions to prescribe opioids for chronic pain. Future research is needed to further explore the potential effects of physician gender on racial biases in pain treatment, and the effects of physician cognitive load on pain treatment. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.
RCT Entities:
OBJECTIVE: To test the hypothesis that racial biases in opioid prescribing would be more likely under high levels of cognitive load, defined as the amount of mental activity imposed on working memory, which may come from environmental factors such as stressful conditions, chaotic workplace, staffing insufficiency, and competing demands, one's own psychological or physiological state, as well as from demands inherent in the task at hand. DESIGN: Two (patient race: White vs Black) by two (cognitive load: low vs high) between-subjects factorial design. SETTING AND PARTICIPANTS: Ninety-eight primary care physicians from the Veterans Affairs Healthcare System. METHODS: Web-based experimental study. Physicians were randomly assigned to read vignettes about either a Black or White patient, under low vs high cognitive load, and to indicate their likelihood of prescribing opioids. High cognitive load was induced by having physicians perform a concurrent task under time pressure. RESULTS: There was a three-way interaction between patient race, cognitive load, and physician gender on prescribing decisions (P = 0.034). Hypotheses were partially confirmed. Male physicians were less likely to prescribe opioids for Black than White patients under high cognitive load (12.5% vs 30.0%) and were more likely to prescribe opioids for Black than White patients under low cognitive load (30.8% vs 10.5%). By contrast, female physicians were more likely to prescribe opioids for Black than White patients in both conditions, with greater racial differences under high (39.1% vs 15.8%) vs low cognitive load (28.6% vs 21.7%). CONCLUSIONS: Physician gender affected the way in which patient race and cognitive load influenced decisions to prescribe opioids for chronic pain. Future research is needed to further explore the potential effects of physician gender on racial biases in pain treatment, and the effects of physician cognitive load on pain treatment. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.
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