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Record W2045348916 · doi:10.1080/13548506.2011.608808

The association between depression and thyroid disorders in a regionally representative Canadian sample

2011· article· en· W2045348916 on OpenAlexaffabout
Esme Fuller–Thomson, Jasmik Saini, Sarah Brennenstuhl

Bibliographic record

VenuePsychology Health & Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsDepression (economics)MedicineOdds ratioLogistic regressionOddsThyroidDemographyPsychiatryInternal medicineGerontology

Abstract

fetched live from OpenAlex

A subsample of six provinces (n = 67,621) from the 2005 Canadian Community Health Survey was used to determine the gender-specific prevalence of depression among those with and without thyroid disorders. Information was not available on the type of thyroid disorder. Logistic regression analyses were conducted to determine the odds and socio-demographic correlates of depression among those with and without thyroid disorders. Women had a significantly higher prevalence of thyroid disorders (9.3%) and depression (6.6%) than men (2.4% and 3.7%, respectively). Thyroid disorders were associated with 22% higher odds of depression in women after adjusting for socio-demographic factors, but no association was found in men. Among women with and without thyroid disorders, younger age, lower income, and limitations in Activities in Daily Living (ADL) were associated with higher odds of depression. Results suggest that women with thyroid disorders are more vulnerable to depression, and socio-demographic correlates of depression are similar among women with and without thyroid disorders.

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)0.001
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 score0.297
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.043
GPT teacher head0.379
Teacher spread0.336 · 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

Citations7
Published2011
Admission routes2
Has abstractyes

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