Although racial disparities in pain care are widely reported, much remains to be known about the role of provider and contextual factors. We used computer-simulated patients to examine the influence of patient race, provider racial bias, and clinical ambiguity on pain decisions. One hundred twenty nine medical residents/fellows made assessment (pain intensity) and treatment (opioid and non-opioid analgesics) decisions for 12 virtual patients with acute pain. Race (Black/White) and clinical ambiguity (high/low) were manipulated across vignettes. Participants completed the Implicit Association Test and feeling thermometers, which assess implicit and explicit racial biases, respectively. Individual- and group-level analyses indicated that race and ambiguity had an interactive effect on providers’ decisions, such that decisions varied as a function of ambiguity for White but not Black patients. Individual differences across providers were observed for the effect of race and ambiguity on decisions; however providers’ implicit and explicit biases did not account for this variability. These data highlight the complexity of racial disparities and suggest that differences in care between White and Black patients are, in part, attributable to the nature (i.e., ambiguity) of the clinical scenario. The current study suggests that interventions to reduce disparities should differentially target patient, provider, and contextual factors.
Although Hispanics are a burgeoning ethnic group in the United States, little is known about their pain-related experience. In order to address this gap, we critically reviewed the existing literature on the pain experience and management among Hispanic Americans (HAs). We focused our review to the literature on non-malignant pain, pain behaviors, and pain treatment seeking among HAs. Pain management experiences were examined from HA patients’ and healthcare providers’ perspectives. Our literature search included variations of the term “Hispanic” with “AND pain” in PubMed, Embase, Web of Science, ScienceDirect, and PsycINFO databases. A total of 117 studies met our inclusion criteria. We organized the results into a conceptual model with separate categories for biological/psychological and sociocultural/systems-level influences on HAs’ pain experience, response to pain, and seeking and receiving pain care. We also included information on healthcare providers’ experience of treating HA patients with pain. For each category, we identified future areas of research. We conclude with a discussion of limitations and clinical implications.
Background: Pain treatments often vary across patients' demographic and mental health characteristics. Most research on this topic has been observational, has focused on opioid therapy exclusively and has not examined individual differences in clinician decision making. The current study examined the influence of patient's sex, race and depression on clinicians' chronic pain treatment decisions. Methods: We used virtual human technology and lens model methodology to enhance study realism and facilitate a richer understanding of treatment decisions. Clinicians and trainees (n = 100) made treatment decisions (opioid, antidepressant, pain specialty referral, mental health referral) for 16 computer-simulated patients with chronic low back pain. Patients' sex, race and depression status were manipulated across vignettes (image and text). Results: Individual-and group-level analyses indicated that patient's depression status had the strongest and most consistent influence on treatment decisions. Although less influential overall, patient's sex and race were significantly influential for a subset of participants. Furthermore, the results indicated that participants who were influenced by patient's race had less experience in treating chronic pain than those who were not influenced by patient's race [t(11.59) = 4.75; p = 0.001; d = 1.20]. Conclusions:The results of this study indicated considerable variability in participants' chronic pain treatment decisions. These data suggest that interventions to reduce variability in treatment decision making and improve pain care should be individually tailored according to clinicians' decision profiles.
We conducted a randomized controlled trial of an individually-tailored, virtual perspective-taking intervention to reduce race and socioeconomic (SES) disparities in providers' pain treatment decisions. Physician residents and fellows (n=436) were recruited from across the United States for this two-part online study. Providers first completed a bias assessment task in which they made treatment decisions for virtual patients with chronic pain who varied by race (Black/White) and SES (low/high). Providers who demonstrated a treatment bias were randomized to the intervention or control group. The intervention consisted of personalized feedback about their bias, real-time dynamic interactions with virtual patients, and videos depicting how pain impacts the patients' lives. Treatment bias was re-assessed one week later. Compared to the control group, providers who received the tailored intervention had 85% lower odds of demonstrating a treatment bias against Black patients and 76% lower odds of demonstrating a treatment bias against low SES patients at follow-up. Providers who received the intervention for racial bias also showed increased compassion for patients compared to providers in the control condition. Group differences did not emerge for provider comfort in treating patients. Results suggest an online intervention that is tailored to providers according to their individual treatment biases, delivers feedback about these
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