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Barriers to nutrition as a health promotion practice for women with disabilities

2003· article· en· W1972139462 on OpenAlexaff
Lynda Hall, Angela Colantonio, Karen Yoshida

Bibliographic record

VenueInternational Journal of Rehabilitation Research · 2003
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsPromotion (chess)Government (linguistics)Health promotionEnvironmental healthMedicineGerontologyPsychologyBusinessNursingPublic healthPolitical science

Abstract

fetched live from OpenAlex

The purposes of this study were to examine the barriers to eating well experienced by women with physical disabilities and the services required to improve eating habits. Participants (mean age=48.9, SD=14.4) completed a questionnaire on health promotion behaviours (n=1096), which included a section on nutrition-related behaviours. Of the 31.8% who stated that they experienced barriers to nutrition, 88.9% wished to improve their eating habits. The most common barriers encountered were: too tired to cook (54.6%), organic/health foods too expensive (34.8%), nutritious foods too expensive (34.5%), lack of desire or will power (31.5%), government disability pension does not cover cost of food (30.6%), difficult to shop (25.1%) and not enough time for attendant to shop or prepare food (21.2%). The most common services identified to improve nutrition were: increase in disability pension (45.2%), assistance with shopping (31.3%), programs that deliver food (28.8%), increase attendant time for shopping/cooking (22.0%) and food box programs that provide single servings (20.1%). These results provide a holistic view of health-promoting behaviours in women with physical disabilities and suggest that greater emphasis should be placed on the individual in her social and structural environment when implementing programs for improving nutrition-related behaviours.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.011
metaresearch head score (Gemma)0.047
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.514
Teacher spread0.425 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Observational
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
Published2003
Admission routes1
Has abstractyes

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