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Record W1482873473

Current practice in nutrition assessment for the management of Parkinson’s disease in Australia and Canada

2014· article· en· W1482873473 on OpenAlexaboutno aff
Jamie M. Sheard, Susan Ash

Bibliographic record

VenueQUT ePrints (Queensland University of Technology) · 2014
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychological interventionClinical nutritionDiseaseClinical PracticeFamily medicineParkinson's diseaseIdentification (biology)GerontologyNursingPathology
DOInot available

Abstract

fetched live from OpenAlex

AIM: To document and compare current practice in nutrition assessment of Parkinson’s disease by dietitians in Australia and Canada in order to identify priority areas for review and development of practice guidelines and direct future research. METHODS: An online survey was distributed to DAA members and PEN subscribers through their email newsletters. The survey captured current practice in the phases of the Nutrition Care Plan. The results of the assessment phase are presented here. RESULTS: Eighty-four dietitians responded. Differences in practice existed in the choice of nutrition screening and assessment tools, including appropriate BMI ranges. Nutrition impact symptoms were commonly assessed, but information about Parkinson’s disease medication interactions were not consistently assessed. CONCLUSIONS: he variation in practice related to the use of screening and assessment methods may result in the identification of different goals for subsequent interventions. Even more practice variation was evident for those items more specific to Parkinson’s disease and may be due to the lack of evidence to guide practice. Further research is required to support decisions for nutrition assessment of Parkinson’s disease.

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 score0.200
Threshold uncertainty score0.973

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 communication0.0000.000
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 head0.019
GPT teacher head0.311
Teacher spread0.292 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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