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Record W3096668031 · doi:10.1177/1099800420968889

A Systematic Review of Physical Health Consequences and Acculturation Stress Among Latinx Individuals in the United States

2020· review· en· W3096668031 on OpenAlexaff
Rosa M. González‐Guarda, Allison McCord Stafford, Gabriela A. Nagy, Deanna Befus, Jamie Conklin

Bibliographic record

VenueBiological Research For Nursing · 2020
Typereview
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsWestern University
FundersNational Institute on Minority Health and Health Disparities
KeywordsAcculturationPsychological resiliencePsychological interventionGerontologyMental healthImmigrationPsychologyPopulationPhysical healthSocial supportClinical psychologyMedicineEnvironmental healthSocial psychologyPsychiatryGeography

Abstract

fetched live from OpenAlex

The health of Latinx immigrants decays over time and across generations. Acculturation stress influences decays in behavioral and mental health in this population, but the effect on physical health outcomes is less understood. This systematic review synthesizes findings from 22 studies that examined the influence of acculturation stress on physical health outcomes among Latinx populations in the United States. The Society-to-Cell Resilience Framework was used to synthesize findings according to individual, physiological, and cellular levels. There is mounting evidence identifying acculturation stress as an important social contributor to negative physical health outcomes, especially at the individual level. More research is needed to identify the physiological and cellular mechanisms involved. Interventions are also needed to address the damaging effects of acculturation stress on a variety of physical health conditions in this population.

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)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0100.011
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.431
GPT teacher head0.581
Teacher spread0.149 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations71
Published2020
Admission routes1
Has abstractyes

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