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Record W2769095286 · doi:10.1080/13548506.2017.1384552

Do mental disorders moderate the association between diabetes status and alcohol consumption?

2017· article· en· W2769095286 on OpenAlexaffabout
Randa Elgendy, Sonya S. Deschênes, Rachel J. Burns, Norbert Schmitz

Bibliographic record

VenuePsychology Health & Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsDiabetes mellitusMajor depressive disorderMedicinePsychiatryAlcohol use disorderMental healthPsychological interventionAnxietyPopulationBipolar disorderPrevalence of mental disordersClinical psychologyAlcoholEnvironmental healthEndocrinologyMood

Abstract

fetched live from OpenAlex

Although heavy alcohol consumption is associated with diabetes-related complications, little is known about patterns of alcohol use among people with diabetes. Moreover, heavy drinking is more common among individuals with major depressive disorder (MDD), bipolar disorder (BD), and generalized anxiety disorder (GAD) than in the general population, and these disorders are often comorbid with diabetes. The present study tested the hypothesis that mental disorders moderate the association between diabetes status and alcohol consumption. A total of 14,302 adult participants aged 40-79 were included from the cross-sectional 2012 Canadian Community Health Survey-Mental Health (1,698 with diabetes). Data were analyzed using hierarchical linear regression models. MDD and BD, but not GAD, significantly moderated the association between diabetes status and alcohol quantity, such that the presence of diabetes was strongly and negatively associated with alcohol quantity if individuals had MDD or BD. There was no interaction between diabetes status and any of the mental disorders and alcohol frequency. This study suggests that among individuals with diabetes, those with comorbid MDD or BD drink less than those without MDD or BD. Further investigation of this association is needed and could help inform future alcohol-related interventions among individuals with 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)0.001
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 score0.238
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.062
GPT teacher head0.433
Teacher spread0.371 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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