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Record W2175635490 · doi:10.3148/64.4.2003.195

<i>Nutritional Risk</i>in Vulnerable Community-Living Seniors

2003· article· en· W2175635490 on OpenAlexafffundvenueabout
Heather Keller, Jacquelyn D. McKenzie

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2003
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Guelph
FundersMcMaster University
KeywordsEnvironmental healthMedicineGerontologyRisk assessmentPopulationSample (material)

Abstract

fetched live from OpenAlex

The purpose of this study was to quantify nutritional risk in a convenience sample of vulnerable, community-living seniors, and to determine patterns of nutritional risk in these seniors. The sample consisted of 367 seniors who provided health, functional, and nutritional risk information during an interview in which the Seniors in the Community: Risk Evaluation for Eating and Nutrition questionnaire was used. The majority (73.6%) of the sample was female, and the mean age was 79 years. Nutritional risk was identified in 68.7% of the sample, with 44.4% being at high nutritional risk. Common nutritional risk factors were weight change, restricting food, low fruit and vegetable intake, difficulty with chewing, cooking, or shopping, and poor appetite. Principal components analysis identified four independent components within the Seniors in the Community: Risk Evaluation for Eating and Nutrition questionnaire; these components can be described as low food intake, poor appetite, physical and external challenges, and instrumental activity challenges. Data are sparse on nutritional risk in community-living Canadian seniors; despite methodologic limitations in the recruitment process, this study provides some indication of the level of nutrition problems. The patterns of nutritional risk identified in this vulnerable population may help providers identify useful strategies for ameliorating risk. The Seniors in the Community: Risk Evaluation for Eating and Nutrition questionnaire could be used to identify risk and patterns of risk in Canadian seniors, so that treatment could be individualized.

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)0.013
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.115
GPT teacher head0.431
Teacher spread0.315 · 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 designNot applicable
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

Citations57
Published2003
Admission routes4
Has abstractyes

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