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Record W4318204437 · doi:10.3390/nu15030631

An Examination of the Practice Approaches of Canadian Dietitians Who Counsel Higher-Weight Adults Using a Novel Framework: Emerging Data on Non-Weight-Focused Approaches

2023· article· en· W4318204437 on OpenAlexafffundabout
Kori Lichtfuss, Beatriz Franco‐Arellano, Jennifer Brady, JoAnne Arcand

Bibliographic record

VenueNutrients · 2023
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsAcadia UniversityOntario Tech University
FundersUniversity of Ontario Institute of Technology
KeywordsMedicineMEDLINEMedical educationFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Non-weight-focused approaches (NWFAs) may be used by some clinicians when working with higher-weight clients. In contrast to weight-focused approaches (WFAs), NWFAs de-emphasize or negate weight loss and emphasize overall diet quality and physical activity. The extent to which WFAs, NWFAs, or a combination of both WFAs and NWFAs are used by dietitians is unknown in Canada and globally. This study surveyed Canadian Registered Dietitians (RDs) who counsel higher-weight clients to assess which practice approaches are most commonly used, how they view the importance of weight, and how they define "obesity" for the study population. Five practice approaches were initially defined and used to inform the survey: solely weight-focused; moderately weight-focused; those who fluctuate between weight-focused/weight-inclusive approaches (e.g., used both approaches); weight inclusive and; weight liberated. Participants (n = 383; 94.8% women; 82.2% white) were recruited using social media and professional listservs. Overall, 45.4% of participants used NWFAs, 40.5% fluctuated between weight-focused/moderately weight-focused, and 14.1% used weight-focused approaches (solely weight focused and moderately weight focused). Many participants (63%) agreed that weight loss was not important for higher-weight clients. However, 81% of participants received no formal preparation in NWFAs during their education or training. More research is needed to understand NWFAs and to inform dietetic education in support of efforts to eliminate weight stigma and provide inclusive access to care.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.265
GPT teacher head0.417
Teacher spread0.152 · 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.

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

Citations11
Published2023
Admission routes3
Has abstractyes

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