MétaCan
Menu
Back to cohort
Record W3086721864 · doi:10.1080/07448481.2020.1818758

Mindfulness facets, self-compassion, and drinking to cope: How do associations differ by gender in undergraduates with harmful alcohol consumption?

2020· article· en· W3086721864 on OpenAlexaff
Melanie Wisener, Bassam Khoury

Bibliographic record

VenueJournal of American College Health · 2020
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsMcGill University
Fundersnot available
KeywordsMindfulnessSelf-compassionPsychologyCoping (psychology)Clinical psychologyAnxietyAlcohol consumptionCompassionMultilevel modelAssociation (psychology)AlcoholPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Objective: Undergraduate students show high rates of harmful alcohol consumption, and coping-motivated use has been consistently shown to be the most problematic. The present study examines associations between mindfulness facets, self-compassion, and coping-motivated use, and how these associations differ by gender. Participants and Methods: Undergraduate students reporting harmful alcohol consumption (N = 146; 55.5% women) completed self-report measures assessing their dispositional mindfulness facets, self-compassion, and drinking motives. Results: Regression analyses revealed that for both genders, mindfulness facets and self-compassion were negatively associated with drinking to cope with depression, but not anxiety. Non-judging was uniquely negatively associated with drinking to cope with depression in women, but in men, non-reactivity was the sole unique association. Conclusions: Future research should investigate whether mindfulness and self-compassion training for undergraduates with harmful alcohol consumption is more effective if they target students who drink to cope with depression and emphasize different skills depending on the student’s gender.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.342
Teacher spread0.297 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of American College HealthSame topicMindfulness and Compassion InterventionsFrench-language works237,207