Humor Creation Ability and Mental Health: Are Funny People more Psychologically Healthy?
Bibliographic record
Abstract
Sense of humor is a multidimensional personality construct.Some components may be more relevant to psychological health than others.While there has been a considerable amount of research on humor styles, humor creation ability (HCA) has remained relatively understudied in relation to well-being.This study employed two methods of assessing HCA (a cartoon captioning task and a task involving the generation of humorous responses to v ignettes depicting everyday frustrating situations) to study associations with mental health variables.In addition to these humor creation performance tasks, 215 participants completed measures of four humor styles (Humor Styles Questionnaire) and psychological well-being (self-esteem, satisfaction with life, optimism, depression, anxiety, and stress).No significant correlations were found between either of the HCA tasks and any of the well-being measures.I n contrast, humor styles were significantly correlated with well-being variables in ways consistent with previous research.In addition, the frustrating situation humor creation task was positively correlated with all four humor styles.These findings add support to the view that the ability to create humor is less relevant to mental health than are the ways people use humor in their daily lives.I mplications for humor-based interventions are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".