Effect of Yoga and Naturopathy Treatments on Psychological Burden in Obesity: A Single Case Report
Bibliographic record
Abstract
Obesity is defined as abnormal or excessive fat accumulation in the body and is a major risk factor for various noncommunicable diseases (NCDs), such as diabetes mellitus, cardiovascular diseases, hypertension, and hyperlipidemia. According to the World Health Organization, more than 1 billion people worldwide are obese—650 million adults, 340 million adolescents, and 39 million children. The often ignored component of obesity is the psychological burden associated with the condition impacting multiple aspects such as low self-esteem, depression, and anxiety. This case report shows the effect of an integrated yoga and naturopathy-based lifestyle in a patient with morbid obesity, with special reference to his psychological status. A 19-year-old male college student diagnosed with obesity underwent integrated yoga and naturopathy management for a period of 20 days. Outcome measures such as anthropometric measurements, positive and negative affects scale (PANAS), depression, anxiety, and stress scale (DASS), and day-to-day activity scale were taken before and after the 20-day intervention period. Results showed improvements in negative affect, depression, and anxiety levels, along with a reduction in body weight. Further studies with adequate sample sizes and experimental study designs are required to validate our findings.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".