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Record W2271288773 · doi:10.1176/appi.pn.2014.11a4

Lack of Culturally Competent Care Keeps Hispanics From Seeking Help

2014· article· en· W2271288773 on OpenAlexaboutno aff
Vabren Watts

Bibliographic record

VenuePsychiatric News · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Back to table of contents Previous article Next article Professional NewsFull AccessLack of Culturally Competent Care Keeps Hispanics From Seeking HelpVabren WattsVabren WattsPublished Online:3 Nov 2014https://doi.org/10.1176/appi.pn.2014.11a4AbstractWith Hispanic Americans likely to make up more than one-fourth of the U.S. population by 2050, advocates are asking for more cultural competence from mental health clinicians, as well as more efforts to diversify clinical trials.As the United States becomes more ethnically diverse, there is a call for physicians and health care professionals to develop greater cultural competency so they can provide more effective care to patients of different ethnic backgrounds. Prominent among these are people of Hispanic descent, the fastest growing minority population in the country. Jane Delgado, Ph.D., M.S., says that there should be increased efforts to include subjects of diverse races, ethnicities, and genders in clinical trials involving potential psychiatric medicines.Raymond Riley"Currently, 1 in 6 [56 million] people in the U.S. is Hispanic," said President and CEO of the National Alliance for Hispanic Health (NAHH) Jane Delgado, Ph.D., M.S., who was the guest speaker at a program in September sponsored by APA's Diversity at Work project. "This number is just 2 million people less than the population of both Australia and Canada combined." Her presentation was held in observance of National Hispanic Heritage Month, which falls from September 15 to October 15. Delgado, a Cuban-born American, immigrated to the United States at age 2 with her parents and sister. She overcame difficulties with English in her youth to become one of the most respected figures in clinical psychology and health policy—serving as senior policy advisor in the Immediate Office of the Secretary of Health and Human Services, which coordinates the secretary's policies and includes health care reform initiatives, and a member of the National Advisory Council for the Carter Center Mental Health Task Force founded by Former First Lady Rosalynn Carter. Delgado, the first woman to serve as president and CEO of NAHH, has dedicated her career to improving the health of Hispanic and Latino Americans. Words That Hispanic Patients May Use To Describe Psychiatric SymptomsPeople in some Latino cultures describe mental illnesses in ways that are different from other ethnic groups in the United States. Below is a list of terms of which clinicians should be aware when asking patients of Hispanic descent to describe their symptoms.Ataque: A feeling of being out of control, anxious, and deeply distressed. Common symptoms include shouting, crying, trembling, heat in the chest rising into the head, and aggressive behaviors.Nervios: A general sense of vulnerability and stress brought on by difficult events. Symptoms include headaches and "brain aches," irritability, stomach pains, sleep problems, nervousness, easy tearfulness, and mareos (dizziness or spells of lightheadedness).Susto: An illness due to a frightening event resulting in unhappiness and sickness. Typical symptoms include changes in appetite, troubled sleep and dreams, headaches and stomach aches, sadness, and lack of motivation.Mal de ojo: The concept of being the target of an "evil eye." Children are believed to be especially at risk. Symptoms include fitful sleep, crying without apparent cause, diarrhea, vomiting, and fever.For other common terms that may be used to describe illness symptoms by patients of Hispanic descent, see Mental Health: A Guide for Latinos and Their Families."Mental health involves more than the brain," Delgado noted. "We really need to understand the people who we serve … and listen to them." During an interview with Psychiatric News, she said a crucial factor that keeps Hispanic Americans from accessing mental health care, as well as other health care, is the fear of not being understood due to language barriers and the lack of cultural competence by clinicians who may not fully understand the symptoms that these patients are describing.Delgado described one situation in which a person of Hispanic descent visited the emergency department and repeatedly said "dȳbil" when asked to describe his symptoms. Under the assumption that the patient was trying to convey that he was seeing the devil, the medical staff concluded that the patient's illness was related to mental illness. "'Dȳbil' means 'weak' in Spanish," Delgado explained. "This is but one of many examples of how misunderstandings" of patients' ethnic background and language can affect the health care they receive.Other obstacles that keep Hispanic Americans from accessing mental health services include lack of insurance and stigma. "We, as a country, are still working on decreasing stigma," said Delgado. "People still think that the issue of mental health is something that you should get over and is a sign of weakness. We have to recast this way of thinking, not just for Hispanics but for everyone."Delgado, who advocates for minority health issues on Capitol Hill, also stressed the importance of increasing the diversity of subjects participating in clinical trials, particularly involving psychiatric drugs. "Hispanics metabolize fat differently from the general population, making certain medications intended for diabetes more effective in this population, for example. Certain heart medications are more effective in African Americans," she said. "Does this [concept] hold true for psychiatric medication that we give patients? We need to know." She added that "mental health professionals must push for better and more diverse data to make the best decisions for our patients." ■ ISSUES NewArchived

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.042
GPT teacher head0.338
Teacher spread0.296 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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