Humor styles and negative affect as predictors of different components of physical health
Bibliographic record
Abstract
The extent to which humor and negative affect each predict different components of physical health was examined by having 105 participants complete measures of four distinct humor styles, negative affect, and three indices of physical health.An increased number of physical symptoms and more negative attitudes about illness were associated with higher levels of negative affect, but were unrelated to the humor styles.Conversely, three of the humor styles significantly predicted coping strategies for physical ailments and complaints, whereas negative affect did not.Adaptive selfenhancing humor was associated with facilitative coping strategies such as changing perspective, planning, and the effective use of humor.Maladaptive aggressive humor was linked to a more dysfunctional coping pattern that included greater denial and a reduction in the ability to change perspective.These findings reinforce the need to consider more complex models of humor that explicitly address the effects of both adaptive and maladaptive humor styles across a broad range of physical health measures while also considering effects that may be attributable to other highly-relevant attributes, such as negative affect.Key Words: humor, negative
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".