MétaCan
Menu
Back to cohort
Record W2491724767 · doi:10.3148/cjdpr-2016-009

Dietitians’ Attitudes and Beliefs Regarding Peer Education in Nutrition

2016· article· en· W2491724767 on OpenAlexafffundvenueabout
Paula D.N. Dworatzek, Joanne Stier

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsWestern University
FundersBrescia University College
KeywordsMedicineFamily medicineNutrition EducationHealthy eatingPositive attitudeNursingPhysical activityGerontologyPhysical therapyPsychologySocial psychology

Abstract

fetched live from OpenAlex

PURPOSE: Peer education (PE) has been used effectively in nutrition; however, research examining dietitians' attitudes regarding PE is lacking. METHODS: An online survey was sent to a random sample of 1198 Dietitians of Canada members to assess attitudes regarding PE by practice area. RESULTS: A representative sample of dietitians by practice area and location was obtained (n = 229; 19%). Their total attitude score (TAS) was 226 ± 26 (mean ± SD) out of 295 (maximum). Community/public health dietitians had significantly higher TASs compared with clinical dietitians (234 ± 23 vs. 221 ± 27, respectively; P = 0.03). Dietitians believed PE to be most useful in community settings (P < 0.001), with cultural groups or adolescents (P < 0.001), and for healthy eating program goals (P < 0.001). The barrier most agreed with was limited financial resources, whereas the highest perceived benefits were social support and experience/employment for participants and peer educators, respectively. Overall, 63% agreed PE is an effective model, and 59% agreed that PE should be used more often in nutrition. CONCLUSIONS: Dietitians have a positive attitude towards PE, with community/public health dietitians having the most positive attitudes. Dietitians believe PE is useful with specific target populations and particular program goals/strategies; however, they could be challenged to consider PE in a greater variety of programs.

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)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.122
GPT teacher head0.503
Teacher spread0.381 · 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 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

Citations3
Published2016
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Dietetic Practice and ResearchSame topicDietetics, Nutrition, and EducationFrench-language works237,207