Unconscious bias: Is it impacting your nursing care?
Abstract
FigureHave you ever walked into a patient room with a preconceived picture based on socioeconomic status or ethnicity? Have you feared taking care of someone because he or she is homeless or has opioid use disorder? Although we're caregivers and have devoted our lives to helping people, we sometimes display unintentional biases toward others. Everyone has a cultural lens through which we view the world, which can sometimes create biases. Often, the decisions we make are directly influenced by those biases, even when we espouse other beliefs. The influence occurs without our knowledge because unconscious bias is just that—unconscious—and research has revealed that we all harbor unconscious biases. What's unconscious bias? Unconscious, or implicit, bias is defined as stereotypes or cultural concepts that influence decisions and behaviors. These biases started forming when you were very young and were shaped as you matured into who you are today. Investigations of unconscious bias show that people of all backgrounds, despite claims against partialities, have unconscious preferences based on gender, race, sexual orientation, or other aspects of identity. We also classify people according to educational level, disability, sexuality, accent, social status, and job title, automatically assigning presumed traits to anyone we subconsciously put in those groups. Further research supports that our unconscious biases, and the decisions they cause us to make, may contribute to healthcare…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In these circumstances, stereotyping is used as an energy-saving mechanism that allows for intellectual shortcuts in decision-making that feel comfortable because they fit with what we think we know.
“In these circumstances, stereotyping is used as an energy-saving mechanism that allows for intellectual shortcuts in decision-making that feel comfortable because they fit with what we think we know.11”
From Health professionals implicit bias of patients with low socioeconomic status (SES) and its effects on clinical decision-making: a scoping review (2024) · cites this paper as [11]
Cited by
Sorted by citations
Job, C., Adenipekun, B., Cleves, A., Gill, P., & Samuriwo, R. (2024) · BMJ Open · doi:10.1136/bmjopen-2023-081723 · Cited by 44 · see citing works
- Authors
- Veesart, A., & Barron, A.
- Affiliations
- Texas Tech University (US)
- ORCID
- Veesart, Amanda
- Venue
- Nursing Made Incredibly Easy!
- Published
- 2020-03
- Volume
- 18
- Issue
- 2
- Pages
- 47-49
- ISSN
- 1544-5186 (ISSN-L)
- OpenAlex
- W3005867696
- Cited by
- 2
- References
- 0
- Citations by year
- 2024: 2
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nursing Made Incredibly Easy! (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Cultural Competency in Health Care
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Sociology and Political Science › Racial and Ethnic Identity Research
- Keywords
- implicit bias, nursing practice, health care disparities, stereotyping, bias detection, bias mitigation, patient care, cultural perspective, homeless patients, opioid use disorder, gender bias, racial bias, patient-provider relationship, patient-centered care, cultural competence, patient satisfaction, patient advocacy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review