首页 | 本学科首页   官方微博 | 高级检索  
检索        


Patient demographic characteristics and facial expressions influence nurses' assessment of mood in the context of pain: a virtual human and lens model investigation
Authors:Hirsh Adam T  Callander Sarah B  Robinson Michael E
Institution:aDepartment of Psychology, Indiana University – Purdue University Indianapolis, 402 N. Blackford St., LD 124, Indianapolis, IN 46202, United States;bIndiana Clinic, Methodist Cardiology Physicians, Indianapolis, IN, United States;cDepartment of Clinical and Health Psychology, University of Florida, Gainesville, FL, United States
Abstract:

Background

Sex, 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.

Objectives

To investigate the influence of patient demographic characteristics and facial expressions on nurses’ assessment of patient mood in the context of pain.

Design

A cross-sectional study employing Virtual Human (VH) technology and lens model methodology.

Settings

The current study was delivered via the internet.

Participants

Participants consisted of 54 registered nurses currently engaged in clinical practice. Nurses were recruited from healthcare settings across the United States.

Methods

Nurses 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.

Results

The 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.

Conclusions

The 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.
Keywords:Decision making  Disparities  Lens model  Mood  Virtual Human technology
本文献已被 ScienceDirect PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号