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Record W4405989020 · doi:10.3148/cjdpr-2024-023

Investigating Dietitians’ Knowledge and Comfort in Supporting Muslim Clients and Communities Who Fast During Ramadan

2025· article· en· W4405989020 on OpenAlexaffvenueabout
Katherine Hillier, Sharon E. Walker, Ajmal Anjum, Keara Lubchenko, Jayden Souchotte

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2025
Typearticle
Languageen
FieldMedicine
TopicDietary Effects on Health
Canadian institutionsUniversity of SaskatchewanSaskatchewan HealthSaskatchewan Health Authority
Fundersnot available
KeywordsMedicineMicrosoft excelFamily medicineNursing

Abstract

fetched live from OpenAlex

Purpose: The purpose of this preliminary study was to explore Saskatchewan Registered Dietitians’ perceived knowledge, comfort, and access to resources in supporting Muslims who choose to fast during Ramadan. Methods: An online anonymous survey was distributed to Saskatchewan dietitians from January 31 to February 22, 2022. Quantitative data analysis was employed using Microsoft Excel. Results: A total of 93 dietitians completed the survey. Most participants understood that fasting involved abstaining from food and drink (90%, 80/90). Further, participants (71%, 65/92) reported they had never provided care during Ramadan to fasting Muslims, and some (55%, 48/88) felt they did not have access to nutrition guidelines to help Muslims choosing to fast during Ramadan. Yet, 97% (85/88) of participants believe understanding Ramadan is important to providing culturally safe care. Conclusion: Few registered dietitians in Saskatchewan had knowledge regarding Ramadan fasting practices. Some Saskatchewan dietitians may feel uncomfortable due to the limited experience reported providing care to Muslims during Ramadan. Future research should further investigate Canadian dietitians’ knowledge, attitude, and practices providing culturally safe care to Muslims during Ramadan.

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)0.004
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 score0.100
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.068
GPT teacher head0.429
Teacher spread0.361 · 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
Published2025
Admission routes3
Has abstractyes

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