MétaCan
Menu
Back to cohort
Record W2052455699 · doi:10.1111/sdi.12194

Laughter and Humor Therapy in Dialysis

2014· review· en· W2052455699 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSeminars in Dialysis · 2014
Typereview
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsLaughterMedicineContext (archaeology)PopulationAnxietyPsychological interventionPsychotherapistQuality of life (healthcare)DialysisPhysical therapyPsychiatryPsychologyNursing

Abstract

fetched live from OpenAlex

Laughter and humor therapy have been used in health care to achieve physiological and psychological health-related benefits. The application of these therapies to the dialysis context remains unclear. This paper reviews the evidence related to laughter and humor therapy as a medical therapy relevant to the dialysis patient population. Studies from other groups such as children, the elderly, and persons with mental health, cancer, and other chronic conditions are included to inform potential applications of laughter therapy to the dialysis population. Therapeutic interventions could range from humorous videos, stories, laughter clowns through to raucous simulated laughter and Laughter Yoga. The effect of laughter and humor on depression, anxiety, pain, immunity, fatigue, sleep quality, respiratory function and blood glucose may have applications to the dialysis context and require further research.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.043
GPT teacher head0.392
Teacher spread0.349 · 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