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The nutrition knowledge of older adults living in sheltered housing accommodation

2007· article· en· W1977147838 on OpenAlexaff
Paula Moynihan, Charlotte E. Mulvaney, Ashley Adamson, C. J. Seal, N. Steen, John C. Mathers, F. V. Zohouri

Bibliographic record

VenueJournal of Human Nutrition and Dietetics · 2007
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsAgriculture Food and Rural Development
Fundersnot available
KeywordsMedicineUnderweightOverweightGerontologyAccommodationIntervention (counseling)MealEnvironmental healthObesityNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Nutrition knowledge enables informed dietary choices. This paper reports on the nutrition knowledge of older adults residing in sheltered housing accommodation in socially deprived areas of north-east England. METHOD: As part of a cluster randomized dietary intervention trial, a validated questionnaire measured the knowledge of current dietary recommendations, nutrient sources, ability to select healthy meal options and knowledge of associations between diet and diseases of older adults aged 60 years and over residing in sheltered accommodation. RESULTS: Completed questionnaires were obtained from 177 (59%) subjects (147 female, 30 male), of whom 76% were overweight/obese and 2% underweight. The mean (SD) age was 76.4 (8.0) years. Of a possible score of 47, the mean score was 23.2, indicating that approximately 50% of questions were answered incorrectly. Knowledge of associations between diet and diseases was particularly poor; 90% of subjects being unaware of the benefits of high fruit and vegetable consumption. Respondents in the highest 10% of the nutrition knowledge score had a significantly higher intake of fruit and vegetables compared with those in the lowest 10%. CONCLUSION: A high proportion of older adults had little basic nutrition knowledge; this presents a barrier to healthier eating that should be addressed.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.036
GPT teacher head0.365
Teacher spread0.329 · 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

Citations49
Published2007
Admission routes1
Has abstractyes

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