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Record W1611773767 · doi:10.1300/j052v23n01_02

Dietary and Activity Profiles of Selected Immigrant Older Adults in Canada

2003· article· en· W1611773767 on OpenAlexaffabout
Shanthi Johnson, Alicia C. Garcia

Bibliographic record

VenueJournal of Nutrition for the Elderly · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsAcadia University
Fundersnot available
KeywordsMedicineVietnameseGerontologyImmigrationPhysical activityEthnically diverseHealth promotionEthnic groupPromotion (chess)PopulationEnvironmental healthPublic healthPhysical therapyNursing

Abstract

fetched live from OpenAlex

In Canada, the population of older adults is becoming ethnically diverse. However, our understanding of the health behaviors including diet and physical activity among this group is limited. The purpose of this study is to examine the dietary and physical activity profiles, and the factors that influence these behaviors, among older immigrants. The sample included 54 participants (mean age = 68 +/- 6 years) from Cambodian, Latin-American, Vietnamese and Polish groups. Measures included background questionnaire, nutrition screening tool, 24-hour dietary recall, and physical activity assessment. Results showed that 72.5% were at moderate to high risk for poor nutrition. Identified dietary issues were related to food preparation, nutrition management for diseases, and nutritional needs of the elderly. Although 83.3% reported to be physically active, the level was less than optimal, and barriers to physical activity were identified. The results are further discussed in light of health promotion and nutrition education among immigrant older 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 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)0.000
metaresearch head score (Gemma)0.001
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 score0.075
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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

Citations29
Published2003
Admission routes2
Has abstractyes

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