Addressing health disparities by addressing structural racism and implicit bias in nursing education

Ochs, Jessica H.

doi:10.1016/j.nedt.2022.105670

Cited by 3 publications

(1 citation statement)

References 31 publications

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“…One indication of their impact is the growing number of minority nurse scientists actively involved in health disparities research, fueled partly by significant grant opportunities provided by institutions such as the National Institute of Nursing Research (NINR) (Cary Jr et al, 2020). With a longstanding commitment to advancing health equity and eliminating disparities, NINR is pivotal in supporting research funding and career development to achieve these goals (Ochs, 2023). The recruitment and retention strategy also influences partnerships with high schools, colleges, and professional organizations with diverse representation to attract and retain minority students (Brewer et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Increasing Diversity in Nursing to Reduce Health Disparities and Achieve Health Equity

SAFDAR,

QADIR

2024

Biol Clin Sci Res J

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In modern healthcare systems, achieving health equity remains paramount, yet persistent health disparities among diverse populations present significant challenges. The study's main objective is to find the increasing diversity in nursing to reduce health disparities and achieve health equity. This mixed-methods study was conducted in Bahawal Victoria Hospital Bahawalpur from January 2023 till December 2023. The study enrolled a diverse cohort of 550 participants, including registered nurses (RNs), nursing students, nurse educators, and healthcare administrators. Participants were recruited from various healthcare settings, including hospitals, community health centers, and academic institutions. The study included 300 registered nurses (RNs) aged 22 to 65, comprising 75% females and 25% males, demonstrating diverse ethnic representation. Additionally, 150 nursing students aged between 20 and 30 years participated, with 85% females and 15% males, reflecting a diverse demographic composition. Furthermore, 50 nurse educators aged 30 to 55 years were involved, with 60% females and 40% males showcasing diversity. Most participants, comprising 70%, acknowledged that nursing diversity positively impacts patient care and outcomes. However, only 45% felt that their workplace adequately supports diversity initiatives. Regarding healthcare disparities, 60% identified access to care, 50% recognized quality of care, and 45% acknowledged health outcomes disparities as prevalent issues. It is concluded that diversity in nursing holds significant promise for reducing health disparities and advancing health equity. The study's findings underscore the importance of organizational support for diversity initiatives to address systemic barriers in healthcare delivery.

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Section: Discussionmentioning

confidence: 99%

Increasing Diversity in Nursing to Reduce Health Disparities and Achieve Health Equity

SAFDAR,

QADIR

2024

Biol Clin Sci Res J

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Representation of dark skin tones in foundational nursing textbooks: An image analysis

Pusey-Reid,

Quinn,

Wong

et al. 2023

Nurse Education Today

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The use of artificial neural networks and decision trees: Implications for health-care research

Smith,

McConnell

2024

Open Computer Science

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The use of decision trees and artificial neural networks (ANNs) in health-care research is widespread, as they enable health-care providers with the tools they need to make better medical decisions with their patients. ANNs specifically are extremely helpful in predictive research as they can provide investigators with knowledge about future trends and patterns. However, a major downside to ANNs is their lack of interpretability. Understandability of the model is important as it ensures the outcomes are true to the dataset’s original labels and are not impacted by algorithmic bias. In comparison, decision trees map out their entire process before providing the results, which leads to a higher level of trust in the model and the conclusions it supplies the investigators with. This is essential as many historical datasets lack equal and fair representation of all races and sexes, which might directly correlate to a lesser treatment given to females and individuals in minority groups. Here, we review existing work around the differences and connections between ANNs and decision trees with implications for research in health care.

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Addressing health disparities by addressing structural racism and implicit bias in nursing education

Cited by 3 publications

References 31 publications

Increasing Diversity in Nursing to Reduce Health Disparities and Achieve Health Equity

Increasing Diversity in Nursing to Reduce Health Disparities and Achieve Health Equity

Representation of dark skin tones in foundational nursing textbooks: An image analysis

The use of artificial neural networks and decision trees: Implications for health-care research

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