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Record W2196361058 · doi:10.3148/cjdpr-2014-023

Pilot Evaluation of an In-Store Nutrition Label Education Program

2014· article· en· W2196361058 on OpenAlexafffundvenue
Steven Dukeshire, Emily Nicks, Jennifer Ferguson

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2014
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health Research
KeywordsLimitingNutrition EducationMedical educationProgram evaluationMedicinePatient satisfactionApplied psychologyPsychologyNursingGerontologyEngineering

Abstract

fetched live from OpenAlex

PURPOSE: To describe and provide recommendations for the implementation of an evaluation for an already existing, in-store Nutrition Label Education Program (NLEP). METHODS: We describe the development and implementation of an evaluation consisting of a pre- and postsurvey and one month follow-up. The evaluation was designed to assess satisfaction with the NLEP as well as changes in participant nutrition label knowledge, confidence in using nutrition labels, and actual changes in nutrition label use. RESULTS: Nineteen participants took part in the pilot evaluation. The evaluation was successful in demonstrating high levels of satisfaction with the NLEP as well as positive changes in participant confidence and some increased knowledge in using nutrition labels. However, only 3 people participated in the follow-up, limiting the ability to assess behaviour change. CONCLUSIONS: Ideally, NLEPs should include ongoing evaluation that extends beyond just assessing participant satisfaction. Recommendations are provided for conducting such evaluations, including the importance of incorporating the evaluation into the program itself, using existing questionnaires when possible, and employing pre- and postsurveys as well as follow-up interviews to assess change.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.167
GPT teacher head0.478
Teacher spread0.311 · 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 designOther design
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

Citations7
Published2014
Admission routes3
Has abstractyes

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