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Record W2103876377 · doi:10.1037/0893-164x.18.3.231

Mood-Induced Increases in Alcohol Expectancy Strength in Internally Motivated Drinkers.

2004· article· en· W2103876377 on OpenAlexaff
Cheryl D. Birch, Sherry H. Stewart, Anne-Marie Wall, Sherry A. McKee, Shondalee J. Eisnor, Jennifer Theakston

Bibliographic record

VenuePsychology of Addictive Behaviors · 2004
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsYork UniversityDalhousie University
Fundersnot available
KeywordsExpectancy theoryPsychologyMoodCravingClinical psychologyAlcoholCoping (psychology)Negative moodPsychiatryAddictionSocial psychology

Abstract

fetched live from OpenAlex

This study investigated whether exposure to musical mood induction procedures (MMIP) differentially increases the strength of specific alcohol expectancies for coping motivated (CM) versus enhancement motivated (EM) drinkers. Participants were 86 undergraduates who had elevated scores on either the CM or EM subscale of the Drinking Motives Questionnaire (M. L. Cooper, 1994). Participants were randomly assigned to either a positive or negative mood condition. The Alcohol Craving Questionnaire (E. G. Singleton, S. T. Tiffany, & J. E. Henningfield, 1994) was administered at baseline and after MMIP to assess phasic changes in alcohol expectancy strength. Consistent with hypotheses, only CM drinkers in the negative mood condition reported increased relief expectancies, and only EM drinkers in the positive mood condition reported increased reward expectancies. Theoretical and clinical implications are discussed.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.033
GPT teacher head0.352
Teacher spread0.319 · 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 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

Citations97
Published2004
Admission routes1
Has abstractyes

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