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Record W2138205817 · doi:10.1080/19390210802519622

Factors Associated with the Use of St. John's Wort among Adults with Depressive Symptoms

2008· article· en· W2138205817 on OpenAlexaboutno aff
Chung‐Hsuen Wu, David A. Sclar

Bibliographic record

VenueJournal of Dietary Supplements · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsnot available
FundersNational Institute of Mental Health
KeywordsNational Health Interview SurveyMedicineDepression (economics)Socioeconomic statusDepressive symptomsHealth careAlternative medicineHealth insuranceMedical carePopulationLogistic regressionPsychiatryGerontologyFamily medicineEnvironmental healthDemographyAnxietyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the association between access to conventional health care and the use of St. John's wort among adults who report depressive symptoms. STUDY DESIGN: Logistic secondary analysis of the Complementary and Alternative Medicine Supplement to the 2002 National Health Interview Survey (NHIS). STUDY POPULATION: Adults who report depressive symptoms and used St. John's wort (n = 246) were compared to nonusers with depressive symptoms (n = 5,111). RESULTS: After controlling for various sociodemographic and socioeconomic factors, depressed adults who could not afford needed medical care due to cost were nearly two times (AOR 1.92, 95% CI 1.38-2.67) more likely to use St. John's wort than those who could afford conventional medical care. Higher income, education, and health status were also positively associated with the use of St. John's wort. CONCLUSION: The growing use of complementary and alternative therapies in the US is widely interpreted as evidence of changing consumer tastes and dissatisfaction with conventional medical treatment for chronic conditions like depression. However, the rising costs of conventional therapies and diminishing access to health insurance may also play a role.

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 score0.009
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.067
GPT teacher head0.249
Teacher spread0.182 · 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
Published2008
Admission routes1
Has abstractyes

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