Relationship between Types of Forced Laughter and Mental Health: Mediating Effects of Social Support and Self-Concept Clarity
Bibliographic record
Abstract
We explored the relationship between four types of forced laughter (expression control, intimacy maintenance, action control, and affect manipulation) and mental health as well as the mediating effects of social support and self-concept clarity. The Forced Laughter Scale (FLS), General Health Questionnaire-12 (GHQ-12), Multidimensional Scale of Perceived Social Support (MPSS), and Self-Concept Clarity Scale (SCC) were completed by 184 (63 male, 119 female) Japanese university students. The results of investigating the relationships between the four types of forced laughter and mental health demonstrated that expression control had a negative correlation with mental health, while intimacy maintenance had a positive correlation. Affect manipulation and action control did not demonstrate significant correlations. Mediation analysis revealed that the negative correlation between expression control and mental health can be explained by a low level of perceived social support and self-concept clarity. Conversely, it was revealed that the positive correlation between intimacy maintenance and mental health can be explained by a high level of perceived social support. This study found that forced laughter in daily life can have both positive and negative correlations with mental health depending on the situation in which one forces a laugh and their intention for doing so.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".