Symptoms, adverse events, and outcomes in the use of medicinal cannabis in children and adolescents with autism spectrum disorder: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this scoping review is to map and identify the symptoms, adverse events, and outcomes in the use of medicinal cannabis in children and adolescents with autism spectrum disorder. INTRODUCTION: Autism spectrum disorder is a neurodevelopmental disorder that impacts social communication and social interaction, and is associated with restrictive and repetitive behaviors and interests. Medicinal cannabis has become a potential area of interest for parents for the treatment of autism spectrum disorder symptoms in their children. There is some evidence that cannabinoids may be involved in autism spectrum disorder, laying a potential foundation for medicinal cannabis utility; however, previous reviews did not identify any clinical research on this topic. INCLUSION CRITERIA: This scoping review will consider all published and unpublished studies that investigate the use of medicinal cannabis in autism spectrum disorder, where at least 50% of the participants have a diagnosis of autism spectrum disorder and at least 50% of the study population is 0 to 18 years of age, or where pediatric data are reported separately. Studies undertaken in any context (hospital or community) and in any geographic location will be included. METHODS: We will search MEDLINE, Embase, CINAHL, PsycINFO, Web of Science, and Google Scholar, and the gray literature sources for studies. Two independent team members will screen titles and abstracts, review full texts for potential inclusion, and extract data for all studies. The results will be presented as a narrative synthesis and in tabular form.
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.
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 | 0.093 | 0.083 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.015 |
| Bibliometrics | 0.025 | 0.016 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.055 | 0.010 |
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".