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Record W4384662856 · doi:10.62547/fsij5401

A Systematic Literature Review of Asian American, Native Hawaiian, and Pacific Islander Youth Electronic Nicotine Delivery Systems (ENDS) Use

2023· review· en· W4384662856 on OpenAlexfundno aff
Kelsey S Manglallan, Dixie L. Johnson, Mistie Hokulani Rosario, Katlyn J. An, Adabelle B. Carson, Kristina T. Phillips, Pallav Pokhrel, Scott K. Okamoto

Bibliographic record

VenueHawai‘i Journal of Health &amp Social Welfare · 2023
Typereview
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchUniversity of Hawai'iNational Cancer InstituteNational Institutes of HealthHawai'i Pacific UniversityKaiser Permanente
KeywordsPsychological interventionPacific islandersIntervention (counseling)Systematic reviewInterpersonal communicationPsychologyGerontologyMedicinePolitical scienceSociologyDemographyMEDLINESocial psychologyPsychiatryLaw

Abstract

fetched live from OpenAlex

Rates of electronic nicotine delivery systems (ENDS) use are exponentially increasing in youth and young adults within the United States, including Asian American, Native Hawaiian, and Pacific Islander (AANHPI) youth in Hawai'i. Disproportionately high ENDS use rates for AANHPI youth point to the need to understand the empirical literature in this area. A systematic literature review is a prerequisite for programs effectively curbing AANHPI youths' elevated use of ENDS. This systematic literature review examines empirical studies published between 2010-2020 on ENDS and their use as it applies to AANHPI youth. A total of 11 articles were identified using specific inclusionary and exclusionary criteria in a literature search. Studies described individual and interpersonal correlates to ENDS use. Notably, there were no published ENDS intervention studies detailed to AANHPI youth. Implications of these studies for prevention and social welfare interventions are discussed.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.074
GPT teacher head0.379
Teacher spread0.305 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHawai‘i Journal of Health &amp Social WelfareSame topicSmoking Behavior and CessationFrench-language works237,207