ArticleInternational journal of nursing studies2011
Patient demographic characteristics and facial expressions influence nurses' assessment of mood in the context of pain: a virtual human and lens model investigation.
Article in International journal of nursing studies, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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Who cites it
15 citing papers in PubMed, 22 citations in OpenAlex.
- Virtual Human-Delivered Interviews for Patients With Chronic Pain: Feasibility, Acceptability, and a Pilot Randomized Trial of Standard Medical, Psychosocial, and Educational Interviews.Psychosomatic medicine · 2023Trial
- Trial
- Influence of patient immigrant status on physician trainee diabetes treatment decisions: a virtual patient experimental study.Journal of behavioral medicine · 2021Article
- Detecting Welfare in a Non-Verbal Species: Social/Cultural Biases and Difficulties in Horse Welfare Assessment.Animals : an open access journal from MDPI · 2021Review
- Cues used by dentists in the early detection of oral cancer and oral potentially malignant lesions: findings from the National Dental Practice-Based Research Network.Oral surgery, oral medicine, oral pathology and oral radiology · 2020Article
- The influence of patient race, sex, pain-related body postures, and anxiety status on pain management: a virtual human technology investigation.Journal of pain research · 2019Article
- Nurses' Use of Race in Clinical Decision Making.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2016Article
- Assessment of the Influence of Demographic and Professional Characteristics on Health Care Providers' Pain Management Decisions Using Virtual Humans.Journal of dental education · 2016Article
- Effect of pooled comparative information on judgments of quality.IEEE transactions on human-machine systems · 2015Article
- The interaction of patient race, provider bias, and clinical ambiguity on pain management decisions.The journal of pain · 2015Article
- The influence of health care professional characteristics on pain management decisions.Pain medicine (Malden, Mass.) · 2015Article
- Using virtual human technology to provide immediate feedback about participants' use of demographic cues and knowledge of their cue use.The journal of pain · 2014Article
- The impact of patients' gender, race, and age on health care professionals' pain management decisions: an online survey using virtual human technology.International journal of nursing studies · 2014Article
- How accurate are we at assessing others' well-being? The example of welfare assessment in horses.Frontiers in psychology · 2014Article
- The influence of sex, race, and age on pain assessment and treatment decisions using virtual human technology: a cross-national comparison.Journal of pain research · 2013Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
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. SETTINGS: The 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.