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Record W4311017326 · doi:10.5964/ejop.5407

Humor styles are related to loneliness across 15 countries

2022· article· en· W4311017326 on OpenAlexaff
Julie Aitken Schermer, Radosław Rogoza, Marija Branković, Óscar Oviedo-Trespalacios, Tatiana Volkodav, Trương Thi Khanh Ha, Maria Magdalena Kwiatkowska, Eva Papazova, Joonha Park, Christopher Marcin Kowalski, Marta Doroszuk, Dzintra Iliško, Sadia Malik, Samuel Lins, Ginés Navarro‐Carrillo, Jorge Torres‐Marín, Anna Włodarczyk, Sibele D. Aquino, Georg Krammer

Bibliographic record

VenueEurope’s Journal of Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsWestern University
FundersUniversitas AirlanggaUniversity of JohannesburgUniversitetet i BergenSakarya ÜniversitesiMagyar Tudományos AkadémiaUniversiteit van AmsterdamUniversität zu KölnUniversiti Tunku Abdul RahmanUniversidad Tecnológica de Bolívar
KeywordsLonelinessPsychologyUCLA Loneliness ScaleStyle (visual arts)Developmental psychologyMental healthClinical psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

The relationships between self-report loneliness and the four humor styles of affiliative, aggressive, self-defeating, and self-enhancing were investigated in 15 countries (N = 4,701). Because loneliness has been suggested to be both commonly experienced and detrimental, we examine if there are similar patterns between humor styles, gender, and age with loneliness in samples of individuals from diverse backgrounds. Across the country samples, affiliative and self-enhancing humor styles negatively correlated with loneliness, self-defeating was positively correlated, and the aggressive humor style was not significantly related. In predicting loneliness, 40.5% of the variance could be accounted. Younger females with lower affiliative, lower self-enhancing, and higher self-defeating humor style scores had higher loneliness scores. The results suggest that although national mean differences may be present, the pattern of relationships between humor styles and loneliness is consistent across these diverse samples, providing some suggestions for mental health promotion among lonely individuals.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.417
Teacher spread0.378 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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