| Title |
Why Do Providers Contribute to Disparities and What Can Be Done About It?
|
|---|---|
| Published in |
Journal of General Internal Medicine, November 2004
|
| DOI | 10.1111/j.1525-1497.2004.30227.x |
| Pubmed ID | |
| Authors |
Diana J Burgess, Steven S Fu, Michelle van Ryn |
| Abstract |
This paper applies social cognition research to understanding and ameliorating the provider contribution to racial/ethnic disparities in health care. We discuss how fundamental cognitive mechanisms such as automatic, unconscious processes (e.g., stereotyping) can help explain provider bias. Even well-intentioned providers who are motivated to be nonprejudiced may stereotype racial/ethnic minority members, particularly under conditions of that diminish cognitive capacity. These conditions-time pressure, fatigue, and information overload-are frequently found in health care settings. We conclude with implications of the social-cognitive perspective for developing interventions to reduce provider bias. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| United States | 1 | <1% |
| Canada | 1 | <1% |
| Switzerland | 1 | <1% |
| Unknown | 170 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 15% |
| Researcher | 20 | 11% |
| Student > Doctoral Student | 17 | 10% |
| Student > Master | 16 | 9% |
| Student > Bachelor | 16 | 9% |
| Other | 43 | 25% |
| Unknown | 36 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 42 | 24% |
| Social Sciences | 28 | 16% |
| Psychology | 22 | 13% |
| Nursing and Health Professions | 15 | 9% |
| Agricultural and Biological Sciences | 4 | 2% |
| Other | 14 | 8% |
| Unknown | 49 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 November 2020.
All research outputs
#6,930,204
of 25,374,917 outputs
Outputs from Journal of General Internal Medicine
#3,736
of 8,175 outputs
Outputs of similar age
#21,548
of 70,440 outputs
Outputs of similar age from Journal of General Internal Medicine
#11
of 19 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 8,175 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.1. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 70,440 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.