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Mediated and moderated associations between cumulative lifetime stressor exposure, emotional dysregulation, impulsivity, and lifetime alcohol use: A cross-sectional scoping study of UK drinkers

2023· article· en· W4380991706 on OpenAlexaff
James M. Clay, Kiera A. Baker, Roxana Mezabrovschi, G Berti, Grant S. Shields, George M. Slavich, Lorenzo D. Stafford, Matthew O. Parker

Bibliographic record

VenueJournal of Psychiatric Research · 2023
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsUniversity of Victoria
FundersNational Institute of Mental HealthEconomic and Social Research CouncilUniversity of Portsmouth
KeywordsImpulsivityStressorPsychologyEmotional dysregulationClinical psychologyYoung adultPsychological interventionAssociation (psychology)Developmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Stress, trait impulsivity, and emotional dysregulation are independent predictors of alcohol use and misuse, but little is known about the potential mechanisms that link these risk factors together. To address this issue, we carried out an exploratory cross-sectional study, on UK-based participants. Our preregistered, hypothesised theoretical framework was that emotional dysregulation mediates the association between cumulative lifetime stressor exposure and lifetime alcohol use. We also hypothesised that heightened impulsivity would strengthen these relations. As hypothesised, emotional dysregulation fully mediated the relation between cumulative lifetime stressor exposure and lifetime alcohol use. Several facets of impulsivity moderated these associations. For example, as levels of negative urgency increased, the associations between cumulative lifetime stressor exposure and emotional dysregulation, emotional dysregulation and lifetime alcohol use, and lifetime stress exposure and lifetime alcohol use, via emotional dysregulation, strengthened. These preliminary findings propose a theoretically framed model which integrates several prominent risk-factors for alcohol misuse, extending prior research and generating interesting and novel lines of enquiry for longitudinal and cross-cultural analyses. The findings also highlight the potential clinical utility of screening for lifetime stress exposure while tailoring personalised treatment interventions.

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)0.007
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.241
GPT teacher head0.527
Teacher spread0.285 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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