Impact of yoga-based interventions on cognitive and autonomic functions in major depressive disorder population
Bibliographic record
Abstract
Background: Cognitive and autonomic dysfunction is increasingly being recognized as an important clinical dimension in major depressive disorder. Aim: The aim of this study is to evaluate the effect of a combined approach of yoga and diet intervention on cognitive and autonomic functions in individuals with major depressive disorders. Methods: This experimental observational study was conducted at RUHS College of Medical Sciences and Associated Hospitals, Jaipur, on the major depressive disorder population of either sex cognitive function (mini-mental score, Montreal cognitive protocol A and B, P300 latency and amplitude) and autonomic function parameters (frequency and time domain) were recorded at baseline and after three months of a combined approach of yoga and diet intervention. Results: This study compared cognitive and autonomic function parameters at baseline and after three months of yoga and diet intervention in a major depressive disorder population. Analysis revealed a significant decrease in body mass index (<0.05), systolic blood pressure (<0.001), Hamilton rating scale for depression (<0.001), P300 latency (<0.001), standard deviation of NN interval (SDNN) (<0.001), and mean heart rate (<0.001), whereas there was a significant increase in mini-mental score (<0.001), Montreal cognitive protocol A and B (<0.001), high frequency (HF) (<0.001), root mean square standard deviation (RMSSD) (<0.001), and PNN50 (<0.001) after a combined approach of yoga and diet in the study group as compared to control group participants. Conclusions: Yoga and diet combined may be an effective adjunct therapy for improving brain health and mental performance, lowering the risk of depression by affecting the neurotransmitter system and raising vagal tone which contributes to learning and memory.
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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 | 0.001 | 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) | 0.001 | 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".