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Record W7035747625

Acculturation and Emotional Eating Among Arabic Middle Eastern Women in the United States

2022· article· en· W7035747625 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks (Walden University) · 2022
Typearticle
Languageen
FieldComputer Science
TopicEducational Robotics and Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationTubulopathyMicrostomiaDiafiltration
DOInot available

Abstract

fetched live from OpenAlex

Obesity is a substantial problem that occurs worldwide and is highly associated with increased risks of chronic diseases such as Type II diabetes mellitus, cardiac-related diseases, hypertension, and some cancers. Middle Eastern cultures have one of the highest rates of overweight and obesity, estimated to be the second highest worldwide. The purpose of this study was to examine the relationship among stress, depression, emotional eating, and weight gain in Middle Eastern women, specifically Arabs, who have moved to the United States, using a quantitative approach. The theoretical foundation was psychosomatic theory, which explains the connection between psychological problems and emotional eating. This theory suggests that mental conditions increase the chances of overeating among people who find food rewarding. An online survey was used to collect data from a convenience sample of approximately 150 participants using demographics, Cohen’s Perceived Stress questionnaire, the Hamilton Depression Rating Scale, the Vancouver Index of Acculturation questionnaire, and the 25-item Emotional Eating Scale. Arabic Middle Eastern women were focused on in this study to understand whether mental changes such as stress, depression, and acculturation may increase overeating because of moving to the United States. The findings, although they did not reach significance, may promote positive social change by showing the need for more medical practitioners who understand how better to treat Arabic Middle Eastern women who suffer from obesity as well as help these women to identify factors that may contribute to their overeating and subsequent weight gain.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.190
Teacher spread0.172 · 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 designSimulation or modeling
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

Citations0
Published2022
Admission routes1
Has abstractyes

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