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Record W3000540642 · doi:10.1016/j.ssmph.2020.100542

Asian American mental health: Longitudinal trend and explanatory factors among young Filipino- and Korean Americans

2020· article· en· W3000540642 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSSM - Population Health · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsAsian americansMental healthPsychologyLongitudinal studyDemographyGerontologyMedicineEthnic groupPsychiatrySociologyAnthropology

Abstract

fetched live from OpenAlex

OBJECTIVES: This study examined a longitudinal trend of mental health among young Asian Americans during the transition from adolescence to emerging adulthood and investigated explanatory factors of the trend. METHOD: = 15 in W1). RESULTS: Depressive symptoms and suicidal ideation significantly increased among the samples between 2014 and 2018, which also became more serious in severity. Intergenerational cultural conflict in the family and the experience of racial discrimination significantly contributed to the upsurge of mental health distress. Conversely, a strong peer relationship and ethnic identity were critical resources suppressing both depressive symptoms and suicidal ideation. CONCLUSIONS: This study substantiated a troubling upward trend in mental health struggles among young Asian Americans and demonstrated a significant additive influence of culture and race/ethnicity on mental health beyond the normative influences of family process and peers. These key factors should be targeted in intervention to better serve Asian American young people who may mask their internal struggles.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.087
GPT teacher head0.403
Teacher spread0.316 · 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