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Record W4389889073 · doi:10.1371/journal.pone.0295995

Do humour styles moderate the association between hopelessness and suicide ideation? A comparison of student and community samples

2023· article· en· W4389889073 on OpenAlexafffundabout
Aaron Drake, Christopher R. Sears

Bibliographic record

VenuePLoS ONE · 2023
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsUniversity of Calgary
FundersFaculty of Arts, University of Calgary
KeywordsGeneralizability theoryPsychologySuicidal ideationClinical psychologyMental healthAssociation (psychology)Intervention (counseling)Suicide preventionPoison controlDevelopmental psychologyPsychiatryMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Research has found that humour styles can moderate the relationship between various facets of mental health and well-being. Most of these studies have used college student samples, however, and the generalizability of these findings has not been firmly established. This study examined how humour styles moderate the relationship between hopelessness and suicide ideation in both student and community samples. Community participants from the U.S. and Canada (n = 554) and student participants from a Canadian university (n = 208) completed several self-report measures including the Humor Styles Questionnaire. Analyses revealed differences in humour styles between the samples, as well as differences in humour styles between men and women. Regression analyses showed that self-defeating humour moderated the relationship between hopelessness and suicide ideation for student participants but not for community participants. Conversely, self-enhancing humour moderated the relationship between hopelessness and suicide ideation for community participants but not for student participants. These results suggest that high levels of self-defeating humour and self-enhancing humour may be uniquely maladaptive for these respective samples. These and other findings point to the necessity of recruiting diverse samples to better understand the beneficial and detrimental associations between humour styles and mental health. The potential to use measures of humour style as a tool to help identify at-risk individuals and to inform the development of intervention programs is 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 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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.235
GPT teacher head0.408
Teacher spread0.173 · 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

Citations2
Published2023
Admission routes3
Has abstractyes

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