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Record W2145788538 · doi:10.1016/j.rmta.2015.05.001

Disordered eating behaviors in Mexican patients with and without type 2 diabetes mellitus

2015· article· en· W2145788538 on OpenAlexafffund
Teresita de Jesús Saucedo-Molina, Lita Villalón, Jessica Zaragoza-Cortes, Rodrigo León Hernández, Zuli Calderón Ramos

Bibliographic record

VenueRevista Mexicana de Trastornos Alimentarios/Mexican Journal of Eating Disorders · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Lifestyle Studies
Canadian institutionsUniversité de Moncton
FundersUniversité de Moncton
KeywordsMedicineDiabetes mellitusBinge eatingEating disordersInternal medicineNormal weightGastroenterologyBody mass indexObesityEndocrinologyClinical psychologyOverweight

Abstract

fetched live from OpenAlex

The aim of this work was to compare the distribution of disordered eating behaviors (DEB) in Mexican adult patients, with and without type 2 diabetes. A cross-sectional descriptive and comparative field research was carried out in a sample of 169 subjects (54% females; 46% males) with a mean age of 47.9 years. The sample was matched in two groups: patients with type 2 diabetes and patients without diabetes. DEB were assessed with a valid Mexican scale named EFRATA (Escala de Factores de Riesgo Asociados a Trastornos Alimentarios). Results confirmed significant differences in food and weight concern (t = 4.15, df 152.09, p = 0.000), normal eating behavior (t = 4.03, df 151.45, p = 0.000) and emotional eating (t = 1.93, df 160.76, p < 0.05), EFRATA's factors in which diabetic subjects obtained higher values in comparison with no diabetic patients. Subjects without diabetes achieved higher value only in binge eating behavior with statistically significant difference (t = 2.11, df 128.8, p < 0.05) in contrast with diabetic patients. Since these findings have been open the possibility to propose specific strategies that encourage healthy eating behaviors, both in adult patients with and without diabetes.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.342
Teacher spread0.315 · 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

Citations3
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueRevista Mexicana de Trastornos Alimentarios/Mexican Journal of Eating DisordersSame topicHealth and Lifestyle StudiesFrench-language works237,207