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Record W2912455468 · doi:10.1037/adb0000578

Relationships on the rocks: A meta-analysis of romantic partner effects on alcohol use.

2020· review· en· W2912455468 on OpenAlexfundno aff
Lydia Muyingo, Martin M. Smith, Simon Sherry, Eleri L.F. McEachern, Kenneth E. Leonard, Sherry H. Stewart

Bibliographic record

VenuePsychology of Addictive Behaviors · 2020
Typereview
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchNova Scotia Health Research Foundation
KeywordsPsycINFOPsychologyMeta-analysisContext (archaeology)AlcoholSocial psychologyStructural equation modelingBivariate analysisSocial environmentDevelopmental psychologyClinical psychologyMEDLINEMedicine

Abstract

fetched live from OpenAlex

< .05) influence than men (β = .12). Results also suggest time lag between assessment, alcohol indicator, married, and year of publication may moderate partner influence. Thus, social influences on individual alcohol use include important partner influences. These influences can serve either risk or protective functions. Given the economic, social, and health consequences associated with alcohol misuse, advancing knowledge of social risk factors for alcohol misuse is essential. Therefore, assessment and treatment of alcohol misuse should extend beyond the person to the social context. We encourage clinicians to consider involving romantic partners when assessing and treating alcohol misuse. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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)0.008
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.017
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.474
GPT teacher head0.517
Teacher spread0.042 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations26
Published2020
Admission routes1
Has abstractyes

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