Cannabidiol in Treatment of Autism Spectrum Disorder: A Case Study
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.
Bibliographic record
Abstract
This case study aims to demonstrate the use of cannabidiol (CBD) with low-dose tetrahydrocannabinol (THC) in managing symptoms associated with autism spectrum disorder (ASD) to increase the overall quality of life for these individuals and their families. ASD is a neurodevelopmental disorder affecting cognitive development, behavior, social communication, and motor skills. Despite the increasing awareness of ASD, there is still a lack of safe and effective treatment options. The study includes a nine-year-old male patient who was diagnosed with nonverbal ASD. He exhibited emotional outbursts, inappropriate behaviors, and social deficits including challenges in communicating his needs with others. Since the patient was unable to attain independence at school and at home, his condition was a significant burden to his caregivers. The patient was treated with full-spectrum high CBD and low THC oil formulation, with each milliliter containing 20 mg of CBD and <1 mg of THC. CBD oil starting dose was 0.1ml twice daily, increased every three to four days to 0.5ml twice daily. Overall, the patient experienced a reduction in negative behaviors, including violent outbursts, self-injurious behaviors, and sleep disruptions. There was an improvement in social interactions, concentration, and emotional stability. A combination of high CBD and low-dose THC oil was demonstrated to be an effective treatment option for managing symptoms associated with autism, leading to a better quality of life for both the patient and the caregivers.
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 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 | 0.000 | 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) | 0.001 | 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 it