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Record W3197471031 · doi:10.2196/31281

Pharmacokinetics and Perceptions of Children and Young Adults Using Cannabis for Attention-Deficit/Hyperactivity Disorder and Oppositional Defiant Disorder: Protocol for a Mixed Methods Proof-of-Concept Study

2021· article· en· W3197471031 on OpenAlexafffundvenueabout
Holly Mansell, Declan Quinn, Lauren E. Kelly, Michael Szafron, Jane Alcorn

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of ManitobaUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsCannabisPsychiatryAnxietyAttention deficit hyperactivity disorderCannabis DependenceClinical psychologyPsychologyStimulantMedicineCannabidiol

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the lack of evidence on the use of cannabis for the treatment of attention-deficit/hyperactivity disorder (ADHD), the growing perception that cannabis is safe has led more patients and caregivers to self-medicate. Some psychiatrists now authorize medicinal cannabis for patients with ADHD with features of oppositional defiant disorder (ODD) to curtail the unregulated (ie, self-medicated) use of recreational cannabis or to offer a therapeutic option to those who continue to experience symptoms after exhausting all other treatment options. OBJECTIVE: This protocol aims to explore the perceived effectiveness and pharmacokinetics of cannabis in youth and young adults, who are currently taking it as part of their treatment plan for ADHD with features of ODD, under the supervision of a psychiatrist. METHODS: -tetrahydrocannabinol [THC]:cannabidiol [CBD] ratio of 1:20) as a treatment adjunct to stimulant pharmacotherapy will be recruited. A sample size of 10-20 individuals is estimated. The study interview will consist of (1) validated symptom rating scales (Swanson, Nolan, and Pelham-IV Questionnaire [SNAP-IV], 90-item; Patient Health Questionnaire, 9-item [PHQ-9]; and Screen for Child Anxiety Related Emotional Disorders [SCARED] tool to measure symptoms of ADHD and ODD, depression, and anxiety, respectively); (2) a semistructured interview to probe the experiences of using cannabis; and (3) a cannabis side effects survey. A cannabis product sample as well as 2 blood samples (a trough level and 2-hour postdose level) will be collected to measure plasma concentrations of cannabinoids and relevant metabolites (THC, CBD, 11-hydroxy-THC, 7-hydroxy-CBD, cannabichromene, and 11-nor-9-carboxy-THB) using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Self-report rating scales (SNAP-IV, SCARED, and PHQ-9) will be scored in accordance with standard protocols and compared to retrospective scores obtained from the participant's chart. Demographic variables (age, weight, and race), symptom scores, and blood levels (peaks and troughs) of THC, CBD, cannabichromene (CBC), and metabolites will be summarized using descriptive statistics. Relationships between plasma concentrations and symptom scores will be determined using analysis of variance, and multiple regression analysis will be performed to determine associations between plasma concentrations and demographic variables (age, weight, and ethnicity). The qualitative data will be audio-recorded and transcribed and organized into themes. RESULTS: The protocol was approved by the Biomedical Research Ethics Board at the University of Saskatchewan (protocol #1726), and recruitment began in May 2021. CONCLUSIONS: This proof-of-concept study will explore the potential treatment effectiveness of medical cannabis in participants with ADHD and ODD through a mixed methods approach to inform future research in this area. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/31281.

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 imitation

Not 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.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.048
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.020
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0480.007

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 head0.095
GPT teacher head0.533
Teacher spread0.438 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations12
Published2021
Admission routes4
Has abstractyes

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