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Record W2197264603 · doi:10.1177/1054773815587486

Health Beliefs and Practices of African Immigrants in Canada

2015· article· en· W2197264603 on OpenAlexaffabout
Angela Cooper Brathwaite, Manon Lemonde

Bibliographic record

VenueClinical Nursing Research · 2015
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsImmigrationFocus groupPsychological interventionCulturally appropriateLatin AmericansCulturally sensitivePsychologyCultural diversityGerontologyMedicineNursingSocial psychologySociologyPolitical science

Abstract

fetched live from OpenAlex

A purposive sample of 14 immigrants living in Ontario, Canada, participated in two focus groups. The researchers used semi-structured interviews to collect data and five themes emerged from the data: beliefs about diabetes were centered on diverse factors, preserving culture through food preferences and preparation, cultural practices to stay healthy, cultural practices determined number of servings of fruit and vegetables per day, and engaging in physical activity to stay healthy. Findings indicated how health beliefs and cultural practices influenced behavior in preventing type 2 diabetes (T2D). Future research should focus on other high-risk minority groups (South Asian, Caribbean, and Latin American) to examine their health beliefs and cultural practices and use these finding to develop best practice guidelines, which should be incorporated into culturally tailored interventions.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.002
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.322
GPT teacher head0.579
Teacher spread0.257 · 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
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

Citations17
Published2015
Admission routes2
Has abstractyes

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