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Record W2592502584 · doi:10.1016/j.ijnss.2017.03.003

Healthcare needs and access in a sample of Chinese young adults in Vancouver, British Columbia: A qualitative analysis

2017· article· en· W2592502584 on OpenAlexaffabout
Christine Ou, Sabrina T. Wong, Jean‐Frédéric Lévesque, Elizabeth Saewyc

Bibliographic record

VenueInternational Journal of Nursing Sciences · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHealth careEthnic groupYoung adultImmigrationQualitative researchFilial pietyMedicineGerontologyFamily medicineChinese americansPsychologyNursingSociologyGender studiesPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: Immigrants of Chinese ethnicity and young people (between 18 and 30 years of age) are known to access health services less frequently and may be at greater risk for experiencing unmet health needs. The purpose of this study was to examine the health beliefs, health behaviors, primary care access, and perceived unmet healthcare needs of Chinese young adults. METHODS: Semi-structured in-depth interviews were carried out with eight Chinese young adults in Vancouver, Canada. RESULTS: A content analysis revealed that these Chinese young adults experienced unmet healthcare needs, did not have a primary care provider, and did not access preventive services. Cultural factors such as strong family ties, filial piety, and the practice of Traditional Chinese Medicine influenced their health behaviors and healthcare access patterns. CONCLUSION: Chinese young adults share similar issues with other young adults in relation to not having a primary care provider and accessing preventive care but their health beliefs and practices make their needs for care unique from other young adults.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.095
GPT teacher head0.553
Teacher spread0.458 · 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 designObservational
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".

Quick stats

Citations6
Published2017
Admission routes2
Has abstractyes

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