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Record W3098687655 · doi:10.11124/jbies-20-00001

Symptoms, adverse events, and outcomes in the use of medicinal cannabis in children and adolescents with autism spectrum disorder: a scoping review protocol

2020· review· en· W3098687655 on OpenAlexaff
Sarah Fletcher, Colleen Pawliuk, Angie Ip, Tim F. Oberlander, Harold Siden

Bibliographic record

VenueJBI Evidence Synthesis · 2020
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsSunny Hill Health Centre for ChildrenBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsAutism spectrum disorderAutismPsychiatryProtocol (science)MedicineAdverse effectClinical psychologyPsychologyAlternative medicinePharmacology

Abstract

fetched live from OpenAlex

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 INCLUSION CRITERIA: This scoping review will consider all published and unpublished studies that investigate the use of medicinal cannabis in autism spectrum disorder, where at least 50% of the participants have a diagnosis of autism spectrum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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.460
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.360
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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