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Record W4391818803 · doi:10.3389/fnut.2024.1332953

Nutritional considerations for gender-diverse people: a qualitative mini review

2024· article· en· W4391818803 on OpenAlexafffund
Em Jun Eng Mittertreiner, Abbey Hunter, Emilie Lacroix

Bibliographic record

VenueFrontiers in Nutrition · 2024
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsSt. Thomas UniversityUniversity of New Brunswick
FundersSocial Sciences and Humanities Research Council of CanadaHarrison McCain Foundation
KeywordsEating disordersDisordered eatingQualitative researchPsychologyPopulationMedicineHealth careGerontologyClinical psychologyEnvironmental health

Abstract

fetched live from OpenAlex

Dietitians working with gender-diverse people may require different skills and knowledge than those caring for cisgender men and women, as indicated by a growing body of literature that highlights gender-diverse people's unique experiences with and relationships to nutrition and eating behaviors. To provide insight into how dietitians can best serve this population, this mini review identifies and summarizes qualitative studies that investigate gender-diverse people's lived experiences and perspectives regarding nutrition, eating disorders, and access to eating-related healthcare services. Fourteen studies examining nutrition or eating behaviors among gender-diverse samples were selected through a systematic search and screening process: 11 focused on disordered eating or eating disorders and the remaining three focused on nutritional needs, nutritional knowledge, and food insecurity. Extracted themes included: using dietary restriction to suppress secondary sex characteristics or conform to societal norms; the impact of gender-affirming care on disordered eating; negative experiences with, and beliefs about, nutrition and eating disorders healthcare services; and suggestions for clinicians. Recommendations discuss the need for increased trans literacy among clinicians, the creation of safe spaces for gender-diverse people with eating disorders, and the importance of dual competencies in eating disorders treatment and gender-affirming 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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.944

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)0.0010.000

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 head0.087
GPT teacher head0.406
Teacher spread0.319 · 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
GenreReview

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
Published2024
Admission routes2
Has abstractyes

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