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The purpose of the study was to investigate the influence of weight bias and demographic characteristics on the assessment of pediatric chronic pain. Weight status, race, and sex were manipulated in a series of virtual human (VH) digital images of children. Using a web-based platform, 96 undergraduate students with health care-related majors (e.g., Health Science, Nursing, Biology, and Pre-Medicine) read a clinical vignette and provided five ratings targeting the assessment of each VH child's pain. Students also answered a weight bias questionnaire. Group-based analyses were conducted to determine the influence of the VH child's weight and demographic cues, as well as greater weight bias on assessment ratings. Male and VH children with obesity were rated as more likely to avoid non-preferred activities due to pain compared to female and healthy weight children, respectively (both p < .001). The pain of VH children with obesity was rated as more likely to be influenced by psychological/behavioral issues compared to the pain of healthy weight VH children (p = .022). African American VH children were rated as experiencing significantly greater pain than Caucasian VH children (p = .037). As child weight increased, low weight bias participants felt more sympathy, while high weight bias participants felt less sympathy (p = .002). Also, low weight bias participants showed increased motivation to help, while high weight bias participants showed less motivation to help, as VH patient weight increased (p = .008). Child weight and evaluator weight bias may be influential in the assessment of pediatric pain. If supported by future research, results highlight the importance of training in evidence-based practice and education on weight bias for students majoring in health-care fields.

Disparities in health care associated with patients' gender, race, and age are well documented. Previous studies using virtual human (VH) technology have demonstrated that provider characteristics may play an important role in pain management decisions. However, these studies have largely emphasized group differences. The aims of this study were to examine dentists' and physicians' use of VH characteristics when making clinical judgments (i.e., cue use) and to identify provider characteristics associated with the magnitude of the impact of these cues (β-weights). Providers (N=152; 76 physicians, 76 dentists) viewed video vignettes of VH patients varying in gender (male/female), race (white/black), and age (younger/older). Participants rated VH patients' pain intensity and unpleasantness and then rated their own likelihood of administering non-opioid and opioid analgesics. Compared to physicians, dentists had significantly lower β-weights associated with VH age cues for all ratings (p<0.001; d>0.69). These effects varied by provider race and gender. For pain intensity, professional differences were present only among non-white providers. White providers had greater β-weights than non-white providers for pain unpleasantness but only among men. Provider differences regarding the use of VH age cues in non-opioid analgesic administration were present among all providers except non-white males. These findings highlight the interaction of patient and provider factors in driving clinical decision making. Although profession was related to use of VH age cues in pain-related clinical judgments, this relationship was modified by providers' personal characteristics. Additional research is needed to understand what aspects of professional training or practice may account for differences between physicians and dentists and what forms of continuing education may help to mitigate the disparities.

Unlabelled: Demographic characteristics have been found to influence pain management decisions, but limited focus has been placed on participants' reactions to feedback about their use of sex, race, or age to make these decisions. The present study aimed to examine the effects of providing feedback about the use of demographic cues to participants making pain management decisions. Participants (N = 107) viewed 32 virtual human patients with standardized levels of pain and provided ratings for virtual humans' pain intensity and their treatment decisions. Real-time lens model idiographic analyses determined participants' decision policies based on cues used. Participants were subsequently informed about cue use and completed feedback questions. Frequency analyses were conducted on responses to these questions. Between 7.4 and 89.4% of participants indicated awareness of their use of demographic or pain expression cues. Of those individuals, 26.9 to 55.5% believed this awareness would change their future clinical decisions, and 66.6 to 75.9% endorsed that their attitudes affect their imagined clinical practice. Between 66.6 and 79.1% of participants who used cues reported willingness to complete an online tutorial about pain across demographic groups. This study was novel because it provided participants feedback about their cue use. Most participants who used cues indicated willingness to participate in an online intervention, suggesting this technology's utility for modifying biases., Perspective: This is the first study to make individuals aware of whether a virtual human's sex, race, or age influences their decision making. Findings suggest that a majority of the individuals who were made aware of their use of demographic cues would be willing to participate in an online intervention., (Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.)