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Record W3158715832 · doi:10.2196/28997

Influence of Stress, Gender, and Minority Status on Cardiovascular Disease Risk in the Hispanic/Latino Community: Protocol for a Longitudinal Observational Cohort Study

2021· article· en· W3158715832 on OpenAlexvenueno aff
Tonia Poteat, Linda C. Gallo, Audrey Harkness, Carmen R. Isasi, Alicia K. Matthews, Neil Schneiderman, Bharat Thyagarajan, Martha L. Daviglus, Daniela Sotres‐Alvarez, Krista M. Perreira

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
FundersNational Institute of Mental HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood Institute
KeywordsSexual minoritySexual orientationEthnic groupMinority stressMedicineHealth equityStressorDemographyGerontologyClinical psychologyCohortPsychologyPublic healthSocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Hispanic/Latino sexual and gender minorities (SGM) are the fastest growing ethnic group of SGM in the United States. Cardiovascular disease (CVD) is a leading cause of morbidity and mortality among Hispanics/Latinos. SGM inequities in CVD risk have been identified as early as young adulthood, and minority stress has been identified as a potential mediator. Yet, the small number of ethnic or racial minority participants in SGM studies have precluded the examination of the intersections of sexual orientation, gender identity, and race and ethnicity. OBJECTIVE: Minority stress models conceptualize relationships between stressors in minority groups and health outcomes. In this study, we will (1) examine the influence of sexual orientation and gender identity on CVD risk among all Hispanic Community Health Study/Study of Latinos (HCHS/SOL) participants at visit 3 (2021-2024; N~9300); (2) model pathways from sexual orientation and gender identity to CVD risk through stigma, discrimination, and stress in a 1:2 matched subcohort of SGM and non-SGM participants at visit 3 (n~1680); and (3) examine the influence of resilience factors on sexual orientation or gender identity and CVD risk relationships among subcohort participants at visit 3 (n~1680). METHODS: This study will leverage existing data from the parent HCHS/SOL study (collected since 2008) while collecting new data on sexual orientation, gender identity, stigma, discrimination, stress, coping, social support, and CVD risk. Data analysis will follow the SGM minority stress model, which states that excess stigma against SGM populations leads to minority stress that increases CVD risk. In this model, coping and social support serve as resilience factors that can mitigate the impact of minority stress on CVD risk. Cross-sectional and longitudinal regression models as well as structural equation models will be used to test these relationships. RESULTS: This study was funded by the National Heart, Lung, and Blood Institute in March 2020. Recruitment is scheduled to begin in the first quarter of 2021 and continue through 2024. CONCLUSIONS: Understanding the influence of stigma-induced stress on CVD risk among Hispanic/Latino SGM has significant implications for the development of culturally specific CVD risk reduction strategies. Study findings will be used to build on identified Hispanic/Latino cultural strengths to inform adaptation and testing of family and community acceptance interventions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/28997.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.017
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.003
Science and technology studies0.0060.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0230.006

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 head0.501
GPT teacher head0.592
Teacher spread0.091 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations13
Published2021
Admission routes1
Has abstractyes

Explore more

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