Laura D Wandner1, Marc W Heft2, Benjamin C Lok3, Adam T Hirsh4, Steven Z George5, Anne L Horgas6, James W Atchison7, Calia A Torres1, Michael E Robinson8. 1. Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, United States. 2. College of Dentistry, University of Florida, Gainesville, FL, United States. 3. Computer and Information Science and Engineering Department, University of Florida, FL, United States. 4. Department of Psychology, Indiana University - Purdue University Indianapolis, Indianapolis, IN, United States. 5. Department of Physical Therapy, University of Florida, Gainesville, FL, United States. 6. College of Nursing, University of Florida, Gainesville, FL, United States. 7. Rehabilitation Institute of Chicago, Chicago, IL, United States. 8. Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, United States. Electronic address: merobin@ufl.edu.
Abstract
BACKGROUND: Previous literature indicates that biases exist in pain ratings. Healthcare professionals have been found to use patient demographic cues such as sex, race, and age when making decisions about pain treatment. However, there has been little research comparing healthcare professionals' (i.e., physicians and nurses) pain decision policies based on patient demographic cues. METHODS: The current study used virtual human technology to examine the impact of patients' sex, race, and age on healthcare professionals' pain ratings. One hundred and ninety-three healthcare professionals (nurses and physicians) participated in this online study. RESULTS: Healthcare professionals assessed virtual human patients who were male and African American to be experiencing greater pain intensity and were more willing to administer opioid analgesics to them than to their demographic counterparts. Similarly, nurses were more willing to administer opioids make treatment decisions than physicians. There was also a significant virtual human-sex by healthcare professional interaction for pain assessment and treatment decisions. The sex difference (male>female) was greater for nurses than physicians. CONCLUSIONS: Results replicated findings of previous studies using virtual human patients to assess the effect of sex, race, and age in pain decision-making. In addition, healthcare professionals' pain ratings differed depending on healthcare profession. Nurses were more likely to rate pain higher and be more willing to administer opioid analgesics than were physicians. Healthcare professionals rated male and African American virtual human patients as having higher pain in most pain assessment and treatment domains compared to their demographic counterparts. Similarly the virtual human-sex difference ratings were more pronounced for nurses than physicians. Given the large number of patients seen throughout the healthcare professionals' careers, these pain practice biases have important public health implications. This study suggests attention to the influence of patient demographic cues in pain management education is needed.
BACKGROUND: Previous literature indicates that biases exist in pain ratings. Healthcare professionals have been found to use patient demographic cues such as sex, race, and age when making decisions about pain treatment. However, there has been little research comparing healthcare professionals' (i.e., physicians and nurses) pain decision policies based on patient demographic cues. METHODS: The current study used virtual human technology to examine the impact of patients' sex, race, and age on healthcare professionals' pain ratings. One hundred and ninety-three healthcare professionals (nurses and physicians) participated in this online study. RESULTS: Healthcare professionals assessed virtual humanpatients who were male and African American to be experiencing greater pain intensity and were more willing to administer opioid analgesics to them than to their demographic counterparts. Similarly, nurses were more willing to administer opioids make treatment decisions than physicians. There was also a significant virtual human-sex by healthcare professional interaction for pain assessment and treatment decisions. The sex difference (male>female) was greater for nurses than physicians. CONCLUSIONS: Results replicated findings of previous studies using virtual humanpatients to assess the effect of sex, race, and age in pain decision-making. In addition, healthcare professionals' pain ratings differed depending on healthcare profession. Nurses were more likely to rate pain higher and be more willing to administer opioid analgesics than were physicians. Healthcare professionals rated male and African American virtual humanpatients as having higher pain in most pain assessment and treatment domains compared to their demographic counterparts. Similarly the virtual human-sex difference ratings were more pronounced for nurses than physicians. Given the large number of patients seen throughout the healthcare professionals' careers, these pain practice biases have important public health implications. This study suggests attention to the influence of patient demographic cues in pain management education is needed.
Authors: C S Cleeland; R Gonin; A K Hatfield; J H Edmonson; R H Blum; J A Stewart; K J Pandya Journal: N Engl J Med Date: 1994-03-03 Impact factor: 91.245
Authors: Laura D Wandner; Lauren A Stutts; Ashraf F Alqudah; Jason G Craggs; Cindy D Scipio; Adam T Hirsh; Michael E Robinson Journal: J Pain Res Date: 2010-12-07 Impact factor: 3.133
Authors: Emily J Bartley; Jeff Boissoneault; Alison M Vargovich; Laura D Wandner; Adam T Hirsh; Benjamin C Lok; Marc W Heft; Michael E Robinson Journal: Pain Med Date: 2014-10-23 Impact factor: 3.750
Authors: William E Rosa; Barbara Riegel; Connie M Ulrich; Jesse Chittams; Ryan Quinn; Salimah H Meghani Journal: Oncol Nurs Forum Date: 2021-01-04 Impact factor: 2.172
Authors: Paul I Musey; Sarah D Linnstaedt; Timothy F Platts-Mills; James R Miner; Andrey V Bortsov; Basmah Safdar; Polly Bijur; Alex Rosenau; Daniel S Tsze; Andrew K Chang; Suprina Dorai; Kirsten G Engel; James A Feldman; Angela M Fusaro; David C Lee; Mark Rosenberg; Francis J Keefe; David A Peak; Catherine S Nam; Roma G Patel; Roger B Fillingim; Samuel A McLean Journal: Acad Emerg Med Date: 2014-11-24 Impact factor: 3.451
Authors: Jeff Boissoneault; Jennifer M Mundt; Emily J Bartley; Laura D Wandner; Adam T Hirsh; Michael E Robinson Journal: J Dent Educ Date: 2016-05 Impact factor: 2.264
Authors: Sherrill L Sellers; Melissa E Moss; Kathleen Calzone; Khadijah E Abdallah; Jean F Jenkins; Vence L Bonham Journal: J Nurs Scholarsh Date: 2016-09-27 Impact factor: 3.176
Authors: Adam T Hirsh; Megan M Miller; Nicole A Hollingshead; Tracy Anastas; Stephanie T Carnell; Benjamin C Lok; Chenghao Chu; Ying Zhang; Michael E Robinson; Kurt Kroenke; Leslie Ashburn-Nardo Journal: Pain Date: 2019-10 Impact factor: 7.926
Authors: David C Cron; Jay S Lee; James M Dupree; John D Syrjamaki; Hsou Mei Hu; William C Palazzolo; Michael J Englesbe; Chad M Brummett; Jennifer F Waljee Journal: Ann Surg Date: 2020-04 Impact factor: 13.787