-
- Adam T Hirsh, Sarah B Callander, and Michael E Robinson.
- Department of Psychology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA. athirsh@iupui.edu
- Int J Nurs Stud. 2011 Nov 1;48(11):1330-8.
BackgroundSex, race, and age disparities in pain assessment and treatment have been reported in the literature. However, less is known about how these demographic characteristics influence nurses' assessment of the emotional experiences of patients who are in pain.ObjectivesTo investigate the influence of patient demographic characteristics and facial expressions on nurses' assessment of patient mood in the context of pain.DesignA cross-sectional study employing Virtual Human (VH) technology and lens model methodology.SettingsThe current study was delivered via the internet.ParticipantsParticipants consisted of 54 registered nurses currently engaged in clinical practice. Nurses were recruited from healthcare settings across the United States.MethodsNurses viewed 32 patient vignettes consisting of a video clip of the VH patient and text-based clinical summary information describing a post-surgical context. Patient sex, race, age, and facial expression of pain were systematically manipulated across vignettes. Participants made positive and negative mood assessment ratings on computerized visual analogue scales. Idiographic multiple regression analyses were used to examine the patient characteristics that were significant predictors of nurses' assessment ratings. Nomothetic paired samples t-tests were used to compare ratings within cue for the entire sample.ResultsThe results of idiographic and nomothetic analyses indicated that VH sex, race, age, and facial expression cues were significant predictors of the mood assessment ratings of many nurses. The age cue had the largest impact among the demographic variables.ConclusionsThe results of the current study suggest that patient demographic characteristics and facial expressions may influence how nurses assess patient emotional status in the clinical pain context. These findings may lead to greater awareness by individual nurses and nursing administrators about the influence of patient demographic characteristics on clinical decision-making. Future research is needed to better understand these relationships, with the ultimate goal of improving patient care.Copyright © 2011 Elsevier Ltd. All rights reserved.
Notes
Knowledge, pearl, summary or comment to share?You can also include formatting, links, images and footnotes in your notes
- Simple formatting can be added to notes, such as
*italics*
,_underline_
or**bold**
. - Superscript can be denoted by
<sup>text</sup>
and subscript<sub>text</sub>
. - Numbered or bulleted lists can be created using either numbered lines
1. 2. 3.
, hyphens-
or asterisks*
. - Links can be included with:
[my link to pubmed](http://pubmed.com)
- Images can be included with:
![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
- For footnotes use
[^1](This is a footnote.)
inline. - Or use an inline reference
[^1]
to refer to a longer footnote elseweher in the document[^1]: This is a long footnote.
.