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Finally, self-report pain scales of clinical pain have been shown to be both


reliable and repeatable (Coghill et al. 2003 ; Robinson et al. 2013 ; Rosier et al.


2002 ). Further, greater than 50% of the variability in clinical pain reports is pre-


dictable (Staud 2005 ; Staud et al.2003b), i.e., related to the variability in pain


experience. The validity of pain self-reports is supported by the sensitivity of these


measures to pain treatments for a variety of clinical pain conditions (Flor et al.


1992 ; Hoffman et al. 2007 ; Price et al. 2002 ; Staud et al. 2005 ).


Do Clinicians’Assessments of Patients’Pain Levels


Communicated by Verbal and Nonverbal Interaction


Impact Treatment Decisions?


Sex, gender, ethnic, and racial group differences have been reported in not only pain


reports and behaviors, but also clinicians’assessments and management of clinical


pain. However, there have been limited opportunities for studies to systematically


assess how differences in the demographic characteristics of patients as well as


healthcare providers might influence treatment decisions for clinical pain


management.


Robinson and colleagues have developed virtual human simulations that stan-
dardize patient facial expressiveness (for low and high pain expression) within


patient simulations that vary by sex, race (European versus African American), and


age (old versus young) (Hirsh et al. 2008 ; Wandner et al. 2013 , 2014 ). Physicians,


nurses, and dentists were provided with a clinical vignette that described the cir-


cumstances related to a patient presentation for pain treatment, and then viewed a


series of virtual human simulations of patients presenting with the related history.


Patient simulations varied by high versus low pain expression, sex, race, and age.


Healthcare provider demographic information was collected.


In a study with a dental pain vignette (Fig.6.5), 67 dentists rated patient and


treatment factors using separate visual analog scales. After viewing each simula-


tion, dentists rated the patient’s level of pain intensity, pain unpleasantness, their


willingness to recommend non-opiate analgesics, their willingness to prescribe


non-opiate analgesics, their willingness to recommend opiate analgesics, their


willingness to prescribe opiate analgesics, and ratings of patient’s positive and


negative mood.


As expected, patient demographic and nonverbal emotive factors influenced


dentists’assessments of patients’pain and the dentists’treatment decisions. Older,


high expressing females were rated by dentists as having higher levels of pain


intensity and unpleasantness. High expressing females were rated as having a more


negative mood and were more likely to be prescribed non-opiate analgesics by the


dentists. Finally, female patients were more likely to be prescribed both opiate and


non-opiate analgesics than males (Wandner et al. 2013 ). The results of this study as
well as those with physicians and nurses assessing other relevant pain vignettes


112 M.W. Heft and M.E. Robinson

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