The effects of laughter therapy on depression symptoms in patients undergoing center hemodialysis: A pragmatic randomized controlled trial
Bibliographic record
Abstract
INTRODUCTION: People with end-stage renal disease undergoing hemodialysis are at increased risk for stress, anxiety, and depression. The study objective was to measure the effect of intradialytic group laughter therapy on depressive symptoms in people on hemodialysis (HD). METHODS: Pragmatic randomized controlled trial conducted with prevalent HD patients in 10 centers in Northern California. The intervention group received a once weekly, 30-minute group laughter therapy session for 8 weeks. Primary outcome was the number of people with depressive symptoms as measured using the four Item Patient Health Questionnaire. Secondary outcomes were anxiety, subjective well-being, and patient-reported outcome measures. FINDINGS: In all, 151 participants completed both predepression and postdepression symptom measures (72 intervention and 79 control). The proportion of patients with self-reported depressive symptoms changed from 17 (22%) to 16 (20%), in the control and from 11 (17%) to 5 (8%) in the intervention arms, respectively (P = 0.04). In the control arm, 7 out of the 17 patients with self-reported depressive symptoms at baseline continued to report depressive symptoms at follow up compared to the intervention arm where only 1 of 12 patients continued to report depressive symptoms. No differences were noted between the groups for reported anxiety, patient-reported dialysis symptoms, and subjective well-being. DISCUSSION: This study found intradialytic group laughter can decrease the number of people with depressive symptoms receiving hemodialysis. Larger and long-term studies are required to evaluate the effect of intradialytic laughter on patient related outcomes and quality of life.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".