title: Using virtual human technology to provide immediate feedback about participants' use of demographic cues and knowledge of their cue use.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida.
authors.forename: Laura D
authors.initials: LD
authors.lastname: Wandner
authors.affiliation: Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida.
authors.forename: Janelle E
authors.initials: JE
authors.lastname: Letzen
authors.affiliation: Department of Psychology, The University of Alabama, Tuscaloosa, Alabama.
authors.forename: Calia A
authors.initials: CA
authors.lastname: Torres
authors.affiliation: Department of Computer & Information Science & Engineering, University of Florida, Gainesville, Florida.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Lok
authors.affiliation: Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida. Electronic address: merobin@ufl.edu.
authors.forename: Michael E
authors.initials: ME
authors.lastname: Robinson
mesh_terms: D000328:Adult; D003463:Cues; D003657:Decision Making; D005260:Female; D006801:Humans; D008297:Male; D010146:Pain / Q000175:diagnosis; D059408:Pain Management / Q000523:psychology*; D010147:Pain Measurement / Q000523:psychology*; D013240:Stereotyping; D014584:User-Computer Interface; D055815:Young Adult
keywords: Virtual human technology; age; cues; feedback; race; sex