Evidence map›Paper›PMID 37296470›Full record

ArticleJournal of cannabis research2023

Naturalistic examination of the anxiolytic effects of medical cannabis and associated gender and age differences in a Canadian cohort.

Meenu Minhas, Stephanie E Lunn

Open access · goldAbstract read
In one paragraph

Article in Journal of cannabis research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 2 countries.

Meenu MinhasAurora Cannabis Inc, Edmonton, AB, Canada.
Stephanie E LunnAurora Cannabis Inc, Edmonton, AB, Canada. stephanie.lunn@auroramj.com.ORCID http://orcid.org/0000-0001-9521-9256
Aurora University · USBC Hydro (Canada) · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of the current study was to examine patterns of medical cannabis use in those using it to treat anxiety and to investigate if the anxiolytic effects of cannabis were impacted by gender and/or age.

methodsPatient-reported data (n = 184 participants, 61% female, 34.7 ± 8.0 years) was collected through the Strainprint

resultsCannabis consumption resulted in a significant decrease in anxiety scores among both males and females (average efficacy of 50%) and efficacy was similar across the three cultivars. However, gender differences in efficacy were identified in two of the cultivars. All age groups experienced significant reductions in their anxiety post cannabis consumption; however, the 40 + year old group had significantly less efficacy than the other groups. The overall optimal dosing for the entire cohort was 9-11 inhalations for males and 5-7 inhalations for females, with some variation in dosing across the different cultivars, genders and age groups.

conclusionsWe found all three cultivars had significant anxiolytic effects and were well-tolerated. Some limitations of the study are the moderate sample size, self-reported diagnosis of anxiety, unknown comorbidities and experience with cannabis, whether other drugs or cannabis products were used, and restriction to solely inhaled administration. We suggest that the gender and age differences in optimal dosing could support both healthcare practitioners and patients initiate medical cannabis treatment for anxiety.

Indexed as

AnxietyCannabisCBDReal-world dataSex differencesTHC

Identifiers

PMID37296470
PMCPMC10251626
OpenAlexW4380089524

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.