The Effects of GABA, L-Theanine, Passiflora Incarnata and Prunus Cerasus in Reducing the Symptoms of Nervousness in Individuals with Anxiety and/or Depression
Bibliographic record
Abstract
Introduction: Affecting more than 21 million American children and adults, anxiety with or without depression is the leading cause of disability in the USA for individuals ages 15 – 44. Treatment, traditionally has been with prescription medication that is addictive, prone to pharmaceutical abuse and if prescribed appropriately, requires intensive physician involvement and monitoring. The utilization of herbal supplementation has been successfully utilized for many years to treat mood disorders, however scientific analysis of benefits has been lacking. The objective of this study is to scientifically analyze the effectiveness of the combination of GABA, L-theanine, passiflora incarnata and prunus cerasus in the treatment of the symptoms associated with Anxiety. Methods: Two cohorts of volunteers received study compound (n=30) or placebo (n=30). Subjects were instructed to take 4 capsules daily for 7 consecutive days. Every participant completed both the HAM-A (Hamilton anxiety scale) and the SAS (Zung Self Rating Anxiety Scale). Both scales were completed pre & post study. The Student – T test was performed on all data. Results: HAM-A: Subjects receiving active study compound showed marked improvements in the HAM-A global score. SAS: The Zung SAS symptom scores of all subjects receiving active study compound were markedly improved. There were no side effects reported by any of the study participants. Conclusions: Subjects receiving this unique study compound (GABA, L-theanine, passiflora incarnata and prunus cerasus) received marked improvement in their symptoms of anxiety as demonstrated via two separate and clinically significant assessment tools (HAM-A & Zung SAS) when compared to placebo group. This combination of supplements represents a viable and safe adjunct to the short term treatment of mild to moderate anxiety without the use of prescription medication.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".