Humor and Quality of Life in Adults With Chronic Diseases: A Systematic Review
Bibliographic record
Abstract
Individuals grappling with chronic ailments often undergo a deterioration in their overall quality of life (QoL), encompassing psychological, social, and physical dimensions of well-being. Acknowledging that humor has demonstrated the potential to engender favorable effects on QoL, this systematic review endeavors to investigate the correlation between humor and QoL among adults contending with chronic health conditions. A comprehensive review of quantitative data was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. PubMed/MEDLINE, PsycINFO, and Cumulative Index to Nursing & Allied Health (CINAHL) were comprehensively searched from the establishment of each database up to June 22, 2023. Furthermore, reference lists of the included datasets and pertinent review articles were scrutinized exhaustively. The Newcastle-Ottawa Scale (NOS) was employed to assess the quality of eligible studies. A total of 18 studies satisfied the inclusion criteria. These studies encompassed a diverse spectrum of chronic disease categories (including cardiovascular diseases, various types of cancer, etc.) and collectively involved a participant cohort comprising 4,325 individuals. Remarkable findings surfaced, indicating a noteworthy association between distinct facets of humor-such as one's sense of humor, coping humor, humor styles, and laughter-and psychological QoL. Nonetheless, the relationship between humor and physical QoL exhibited a more intricate pattern, characterized by mixed outcomes. Despite the limited and inconsistent evidence across studies, humor appears to exhibit a positive association with QoL.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".