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Record W4402196059 · doi:10.3390/bs14090766

Association of Dietary Habits with Eating Disorders among Latvian Youth Aged 18–24

2024· article· en· W4402196059 on OpenAlexaboutno aff
Inna Gellere, Ilze Beitāne

Bibliographic record

VenueBehavioral Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsLatvianEating disordersAssociation (psychology)PsychologyEnvironmental healthMedicineClinical psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Eating disorders are serious health issues among young people that contribute to increased morbidity rates. The prevalence and severity of eating disorders among Latvian youth aged 18-24 and their relationship with the Healthy Eating Index, dietary habits, and BMI were analyzed in the present study. At the beginning of the study, 190 respondents participated by completing the SCOFF questionnaire, from which the sample group was selected based on the criterion of SCOFF ≥ 2. For the next stage of the study, the responses of 74 participants who completed the EDE-Q-6 questionnaire and the Canadian Food Intake Screener were analyzed. The symptoms of eating disorders were identified in 38.9% of the respondents (SCOFF ≥ 2). The global score of the EDE-Q-6 was 2.00 ± 1.81 where subscales such as body shape concerns (2.93 ± 1.44) and weight concerns (2.68 ± 1.36) were the most important factors that young people paid attention to. The severity of eating disorders was 3.20 for males and 2.62 for females, where a score of 4 and above is classified as an eating disorder. Participants with eating disorder symptoms had a higher BMI, with females having a BMI of 22.5 (normal weight) and 25.5 for males (overweight). The study sample had a poor diet, as the Healthy Eating Index was 8.7 with a maximum score of 24. Weak negative correlations were found between eating disorder severity and eating habits. The issue of eating disorders is topical among young people in Latvia, which requires solutions such as the inclusion of educational programs on healthy nutrition and eating disorders, and psychological support for young people.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.713

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 communication0.0000.000
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 head0.056
GPT teacher head0.345
Teacher spread0.289 · 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
Published2024
Admission routes1
Has abstractyes

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