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Record W2166318629 · doi:10.3109/09638230903111106

Association between mood and anxiety disorders and self-reported disability: Results from a nationally representative sample of Canadians

2009· article· en· W2166318629 on OpenAlexaffabout
Tahany M. Gadalla

Bibliographic record

VenueJournal of Mental Health · 2009
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAnxietyMood disordersPsychiatryMoodMental healthClinical psychologyPrevalence of mental disordersPsychologyAssociation (psychology)Affect (linguistics)Medicine

Abstract

fetched live from OpenAlex

Background: Mental disorders represent a significant burden to individuals and society. They can lead to occupational impairment, disruption in interpersonal and family relationships, poor health and suicide.Aims: This study aimed to examine socio-economic and demographic factors associated with mood and/or anxiety disorders and to assess the relation of these disorders with short-term disability and work activity.Methods: This study used data collected in the 2005 Canadian Community Health Survey (N = 108,986).Results: Higher rates of mood and/or anxiety disorders were found among women, the 30–69 years old, the single/divorced/widowed, Canadian-born, low-income participants and those with chronic physical illness. The presence of mood and/or anxiety disorders was significantly associated with short-term disability, requiring help with daily activities and reduction/modification of work activity.Conclusions: Our findings underscore the importance of early detection and treatment of mental disorders, especially in those at higher risk of developing them.

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)0.003
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 score0.064
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 integrity0.0000.001
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 head0.021
GPT teacher head0.377
Teacher spread0.357 · 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

Citations10
Published2009
Admission routes2
Has abstractyes

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