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Record W2142775415 · doi:10.1093/ntr/ntr165

Depression, Anxiety, and COPD: The Unexamined Role of Nicotine Dependence

2011· article· en· W2142775415 on OpenAlexaff
R. D. Goodwin, Kim Lavoie, Adina R. Lemeshow, Emily Jenkins, E. Sherwood Brown, David A. Fedoronko

Bibliographic record

VenueNicotine & Tobacco Research · 2011
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsHôpital du Sacré-Cœur de MontréalMontreal Heart InstituteUniversité du Québec à Montréal
FundersNational Institute on Drug AbuseNational Institutes of Health
KeywordsCOPDConfoundingAnxietyNicotineDepression (economics)ComorbidityMedicinePsychiatrySmoking cessationMoodNicotine dependenceNational Comorbidity SurveyClinical psychologyInternal medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Previous studies have shown links between anxiety and depression and chronic obstructive pulmonary disease (COPD), but little is known about possible mechanisms of this association. The current study examined whether the observed relationship between anxiety and depression and COPD is explained by confounding due to cigarette smoking and lifetime nicotine dependence. METHODS: Data were drawn from the National Comorbidity Survey Replication, a community-based representative sample of adults in the United States. RESULTS: Analyses suggest that the association between anxiety disorders and COPD appears to be largely explained by confounding by former cigarette smoking and lifetime nicotine dependence. The association between mood disorders and COPD appears to be largely explained by confounding by lifetime nicotine dependence. CONCLUSIONS: These findings provide initial evidence suggesting that the association between anxiety, depression, and COPD may be at least partly attributable to confounding by cigarette smoking and nicotine dependence. Efforts toward prevention of chronic lung disease may be more effective if treatment and prevention efforts aimed at smoking cessation address mental health problems.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.333
Teacher spread0.283 · 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.

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

Citations76
Published2011
Admission routes1
Has abstractyes

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