Neural Mechanisms of Cannabinoid-impaired Decision-Making in Emerging Adults

Study at a glance

From the registry record, last updated by the sponsor on 5 Apr 2024. Recruitment status is as the sponsor reported it: confirm with the study team.

Official title

Neural Mechanisms of Cannabinoid-impaired Decision-Making in Emerging Adults

ClinicalTrials.gov ID

NCT03944954

Acronym / sponsor ID

K01DA043652

Conditions

Neurosciences, Substance-Related Disorders, Behavior Problem

Phase

Early Phase 1

Study type

Interventional

Recruitment status

Completed

Enrolment

66 participants (actual)

Lead sponsor

Michael J. Wesley, PhDUniversity, hospital or other

Collaborators

National Institute on Drug Abuse (NIDA)

Study start

15 Jul 2017 (actual)

Primary completion

13 Dec 2023 (actual)

Study completion

13 Dec 2023 (actual)

First posted

10 May 2019 (actual)

Results

Posted 5 Apr 2024

Clinical summary

The research question as the sponsor registered it. This describes what the study plans to test, not what it found.

Study design

Primary purpose

Basic science

Allocation

Randomised

Intervention model

Parallel groups

Masking

Single blind (investigator)

Number of arms

2

Model description

Participants will be assigned to either excitatory or inhibitory TMS treatment arms. All individuals will receive multiple doses of oral THC (0, 10 and 30mg) and TMS (real or sham).

Who may qualify

Ages

18 to 34 years

Sex

All

Healthy volunteers

Not accepted

Age groups

Adult

Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.

Interventions

Primary outcome

1. Alpha Learning Rate

   Time frame: Measure collected at 2 time points: Baseline (0HR) and Post TMS Administration (3HR)

   In a Probabilistic Reinforcement Learning Choice (PRLC) task, two stimuli are presented and choosing either could result in a monetary reinforcer, but the reinforcement probabilities of the stimuli differ, and change throughout the task. Individuals attempt to optimize choices according to learned probabilities and track changing probabilities over time. PRLC performance allows mathematical modeling of trial-by-trial data under "real-world" uncertainty and yields computational parameters, such as the learning rate. Choice data were analyzed using a Rescorla-Wanger learning model with an alpha learning rate, beta inverse temperature, and perseveration global parameters. Model-derived learning rates are indicative of an individual's ability to learn from previous choice outcomes to update future decision-making. For this task, learning rates range from 0-1 with lower values indicative of more optimal learning.

2. Self-Report Subjective "High"

   Time frame: Measured 2 times: Baseline (0HR) and 3 hours (3HR) after capsule administration on each drug condition (0mg, 10mg, 30mg)

   A Visual Analogue Scale (VAS) was used to measure the acute subjective effects of THC at varying doses (0mg, 10mg, 30mg). Responses are made for VAS items along a 100-unit scale anchored on the extremes by "Not At All" (0) and "Extremely" (100) with a higher score meaning more of the effect. Participants were instructed to select "Not At All" (0) for all baseline (0HR) measures. Post-TMS administration (real or sham), participant self-reported their subjective "high" on the VAS with higher values indicating a more intense sensation of "high".

3. Elasticity of Demand

   Time frame: Measured 2 times: Baseline (0HR) and Post-TMS (3HR) after THC administration on each drug condition (0mg, 10mg, 30mg).

   Elasticity of Demand was measured by the Cannabis Purchase Task (CPT) where participants are asked how many "hits" of cannabis they would consume at 16 different price points in ascending order ($0-$140). Higher elasticity values indicate a greater sensitivity to changing price points resulting in a reduced demand for "hits" of THC at increasing price points.

4. Working Memory Performance

   Time frame: Measured 2 times: Baseline (0HR) and Post-TMS (3HR) after THC administration on each drug condition (0mg, 10mg, 30mg).

   Working memory (WM), the ability to hold a finite amount of information for a set amount of time, is measured by the N-Back task. Here, participants were presented with a sequence of letters and must indicate when the letter currently being viewed matches the one from N steps earlier in the sequence. The load factor "N" is adjusted between 0, 1, and 2 to adjust the difficulty of the task (0-Back = no WM load, 1-Back = minimal WM load, 2-Back = greater WM load) where a higher score means better memory performance. Outcomes are reported as the Total Accuracy Percentage (Correct Choices/Total Choices) x 100%

Results and safety

Loading the posted results from ClinicalTrials.gov…

Research links

• Official record on ClinicalTrials.govLast updated by the sponsor 5 Apr 2024.
• Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
• Individual participant dataSharing planned: No

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Referral and contact

AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.

1 site in 1 country: see every site and its status.