ABSTRACT
PURPOSE: Studies in the United States have found that patients' sex, race, and age influence the pain assessment and treatment decisions of laypeople and medical professionals. However, there is limited research as to whether people of other nationalities make pain management decisions differently based on demographic characteristics. Therefore, the purpose of the following study was to compare pain assessment and treatment decisions of undergraduate students in Jordan and the United States as a preliminary examination of nationality as a potential proxy for cultural differences in pain decisions. METHODS: Virtual human (VH) technology was used to examine the influences of patients' sex (male or female), race (light-skinned or dark-skinned), and age (younger or older) on students' pain management decisions. Seventy-five American and 104 Jordanian undergraduate students participated in this web-based study. RESULTS: American and Jordanian students rated pain intensity higher in females and older adults and were more likely to recommend medical help to these groups, relative to males and younger adults. Furthermore, Jordanian participants rated pain intensity higher and were more likely to recommend medical help for all patient demographic groups (ie, sex, race, age) than American participants. CONCLUSION: This is the first cross-national study that compares pain decisions between undergraduate students. The results suggest that sex, race, and age cues are used in pain assessment and treatment by both Americans and Jordanians, with Jordanians more likely to rate pain higher and recommend medical help to patients. Additional research is needed to determine the cultural determinants of these differences.
ABSTRACT
BACKGROUND: Patients' sex, race, and age have been found to affect others' perception of their pain. However, the influence of these characteristics on treatment recommendations from laypersons and healthcare providers is understudied. DESIGN: To address this issue, 75 undergraduates and 107 healthcare trainees (HTs) used a web-based delivery system to view video clips of virtual human (VH) patients presenting with different standardized levels of pain. Subjects then rated the VHs' pain intensity and recommended the amount of medical treatment the VHs should receive. RESULTS: Results indicated that, compared with undergraduates, HTs perceived African Americans and older adults as having less pain but were more willing to recommend medical treatment for these patients than were undergraduate participants. HTs and undergraduates rated female, African American, older, and high-pain-expressing adults as having greater pain intensity than male, Caucasian, younger, and lower-pain-expressing adults. Moreover, they also recommended that female, older, and high-pain-expressing adults receive more medical treatment than male, younger, and lower-pain-expressing adults. CONCLUSIONS: This study found that the characteristics of the VHs and whether the participants were undergraduates or HTs influenced the ratings of pain assessment and treatment recommendations. The findings are consistent with the previous VH literature showing that VH characteristics are important cues in the perception and treatment of pain. However, this is the first study to identify differences in pain-related decisions between individuals who are pursuing healthcare careers and those who are not. Finally, not only does this study serve as further evidence for the validity and potential of VH technology but also it confirms prior research that has shown that biases regarding patient sex, race, and age can affect pain assessment and treatment.
ABSTRACT
This study examined the influence of Virtual Humans' (VH) sex and race on participants' ratings of pain intensity, pain unpleasantness, pain-related negative mood, pain coping, and recommendations for medical help. Seventy-five undergraduates viewed a series of VHs and provided computerized visual analog scale (VAS) ratings for the five domains listed above. Mixed model ANOVA analyses showed that participants of both sexes and races viewed female VHs as experiencing greater pain intensity, greater pain unpleasantness, a greater number of pain-related negative moods, poorer coping skills, and a greater need to seek medical help for their pain. Participants of both races rated Caucasian VHs as experiencing more negative moods and poorer coping skills do deal with their pain. The novel computerized VH technology used herein allowed for the standardization of pain expression across sexes and races of VH stimuli, thus allowing us to remove the influence of biases when creating the study stimuli. This is a notable advantage over other research methodologies in this line of inquiry. Several future research and education applications of this VH technology are discussed.
ABSTRACT
Pain assessment is subject to bias due to characteristics of the individual in pain and of the observing person. Few research studies have examined pain assessment biases in an experimental setting. This study employs innovative virtual human technology to achieve greater experimental control. A lens model design was used to capture decision-making policies at the idiographic and nomothetic level. Seventy-five undergraduates viewed virtual humans (VH) that varied in sex, race, age, and pain expression. Participants provided computerized ratings with Visual Analogue Scales on the VH's pain intensity, pain unpleasantness, negative mood, coping, and need for medical treatment. Idiographic analyses revealed that individuals used pain expression most frequently as a significant cue. Nomothetic analyses showed that higher pain expression VH and female VH were viewed as having higher pain intensity, higher pain unpleasantness, greater negative mood, worse coping, and a greater need to seek medical treatment than lower pain expression VH and male VH, respectively. Older VH were viewed as having worse coping and a greater need to seek medical treatment than younger VH. This innovative paradigm involving VH technology and a lens model design was shown to be highly effective and could serve as a model for future studies investigating pain-related decision making in healthcare providers.
