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Record W3142624297 · doi:10.31372/20200504.1109

Deconstructing Racialized Experiences in Healthcare: What a Missed Opportunityfor Healing Looks Like and Healthcare Resources for Children and Their Families

2021· article· en· W3142624297 on OpenAlexvenueno aff
Connie Kim Yen Nguyen-Truong, Shameem Rakha, Deborah U. Eti, Lisa Angelesco

Bibliographic record

VenueAsian/Pacific Island Nursing Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsnot available
Fundersnot available
KeywordsXenophobiaRacismVietnameseHealth careInstitutional racismContext (archaeology)PsychologyCriminologySociologyGender studiesPolitical scienceHistory

Abstract

fetched live from OpenAlex

Some patients and families of color, including Asian Americans, face significant adverse stressors due to living within a White-dominant society. Xenophobia and racism can impact health. Research evidence points to early exposure to adverse childhood experiences such as racial discrimination as being detrimental and having significant short-term and long-term impact on physical and mental health. The purpose of this commentary article is to illuminate the need of patients and their families who may seek health care providers (HCPs) to express their concerns and fears when issues of xenophobia and racism arise. Patients and families need space in a healthcare setting to feel heard and understood. Anti-Asian xenophobia and racism among medically underserved Asian Americans persists and has been heightened during the COVID-19 pandemic. We describe tenets of Critical Race Theory and AsianCrit, and use this lens to understand an example actual scenario, a counter-story, of a Vietnamese mother, and her Vietnamese-Chinese American family's experience with xenophobia and racism at a community recreation center and the subsequent communication of this experience with a HCP. We describe the impacts of these experiences of seeking healing including discontinuity of a HCP-patient-family relationship. It takes bravery for patients and families to tell their story of xenophobia and racism to a HCP. There are Asian Americans who are afraid to seek healthcare because of anti-Asian xenophobia and concerns about White fragility. Following, we highlight research evidence on implicit bias, also known as unconscious bias, as context about its persistent and widespread existence among healthcare professionals in general and the need to address this in healthcare. Implicit bias can influence care provided to a patient-family and the interactions between a HCP-patient-family. We include additional resources such as those from the National Association of Pediatric Nurse Practitioners, American Psychological Association Office on Children Youth and Families, the Office of Ethnic Minority Affairs, the Office on Socioeconomic Status, and American Academy of Pediatrics to consider in support of equity in healthcare practice of children and their families.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.354
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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