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Does the Association Between Alcohol Consumption and Depression Depend on How They Are Measured?

2006· article· en· W2004853469 on OpenAlexafffund
Kathryn Graham, Agnes Massak, Andrée Demers, Jürgen Rehm

Bibliographic record

VenueAlcoholism Clinical and Experimental Research · 2006
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of TorontoUniversité de MontréalCentre de Santé et de Services Sociaux de la Vieille-CapitaleCentre for Addiction and Mental HealthWestern University
FundersCanadian Institutes of Health ResearchYork University
KeywordsDepression (economics)Random digit dialingDemographyPsychologyAlcohol consumptionPopulationPsychiatryMedicineAlcoholEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Inconsistent findings regarding the relationship between alcohol consumption and depression, including whether the relationship is J-shaped or U-shaped, may be at least partly due to the types of measures used for both alcohol consumption and depression. METHODS: We conducted a general population survey using random digit dialing (RDD) and computer-assisted telephone interviewing (CATI) with 6,009 males and 8,054 females aged 18 to 76 years. The survey included 4 types of alcohol measures (frequency, usual and maximum quantity per occasion, volume, and heavy episodic drinking) covering both the past week and the past year, and 2 types of depression measures (meeting DSM criteria for a clinical diagnosis of major depression, recent depressed affect). RESULTS: The overall relationship between depression and alcohol consumption did not vary by gender or type of depression measure but did vary significantly by type of alcohol measure, with the strongest relationship found for heavy episodic drinking and high quantity per occasion. There were also significant gender interactions with both depression and alcohol measures, with females showing a stronger relationship than males when depression was measured as meeting the criteria for major depression and when alcohol consumption was measured as quantity per occasion or heavy episodic drinking. There was some evidence of a J-shaped relationship, that is, greater depression among abstainers compared with those who usually drank 1 drink and never drank as much as 5 drinks for both former drinkers and lifetime abstainers when depression was measured as recent symptoms of depression but the J shape was found only for former drinkers when depression was measured as meeting the criteria for major depression and did not reach statistical significance in some analyses. CONCLUSIONS: The results of the present study suggest that measurement and gender are key issues in interpreting findings on the relationship between alcohol and depression. First, depression is primarily related to drinking larger quantities per occasion, less related to volume, and unrelated to drinking frequency, and this effect is stronger for women than for men. Second, the overall relationship between depression and alcohol consumption is stronger for women than for men only when depression is measured as meeting a clinical diagnosis of major depression and not when measured as recent depressed affect. Finally, while there was some evidence that former drinkers had slightly higher rates of major depression and higher scores on recent depressed affect compared with light drinkers, there was no evidence that light drinking was protective for major depression when compared with lifetime abstainers, although light drinkers did report fewer recent symptoms of depressed affect.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.990
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.057
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.204
GPT teacher head0.459
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
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

Citations203
Published2006
Admission routes2
Has abstractyes

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