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Record W34795399 · doi:10.24095/hpcdp.33.1.02

Self-management, health service use and information seeking for diabetes care among recent immigrants in Toronto

2012· article· en· W34795399 on OpenAlexaffvenueabout
Ilene Hyman, Dianne Patychuk, Q. Zaidi, Dragan Kljujic, Yogendra Shakya, JA Rummens, Maria I. Creatore, Bilkis Vissandjée

Bibliographic record

VenueChronic diseases and injuries in Canada · 2012
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsUniversité de MontréalSt. Michael's HospitalInstitute for Clinical Evaluative SciencesAccess Alliance Multicultural Health and Community ServicesHospital for Sick ChildrenYork UniversityPublic Health OntarioSickKids FoundationUniversity of Toronto
Fundersnot available
KeywordsDieticiansImmigrationType 2 diabetesMedicineDiabetes mellitusContext (archaeology)Family medicineGerontologyDiabetes managementHealth careNursingGeographyPolitical scienceEndocrinology

Abstract

fetched live from OpenAlex

INTRODUCTION: Our objective was to explore self-management practices, health services use and information-seeking for type 2 diabetes care among adult men and women from four recent immigrant communities in Toronto. METHODS: A structured questionnaire was adapted for the Canadian context and translated into 4 languages. A total of 184 participants with type 2 diabetes-130 recent immigrants and 54 Canadian-born-were recruited in both community and hospital settings. RESULTS: Recent immigrants were significantly less likely than the Canadian-born group to perform regular blood glucose and foot checks and significantly more likely than the Canadian-born group to be non-smokers, participate in regular physical activity and reduce dietary fat. Recent immigrants were significantly less likely than the Canadian-born group to use a specialist, alternative provider and dietician and less likely to report using dieticians, nurses and diabetes organizations as sources of diabetes-related information. Important differences were observed by sex and country of origin. CONCLUSION: Findings suggest that diabetes prevention and management strategies for recent immigrants must address linguistic, financial, informational and systemic barriers to information and care.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.434
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.247
Teacher spread0.241 · 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

Citations32
Published2012
Admission routes3
Has abstractyes

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