Evidence map›Paper›PMID 36189378›Full record

ArticleAddiction research & theory2022

Estimating Usual Grams per Day of Marijuana Use from Purchases.

William C Kerr, Yu Ye

Abstract read
In one paragraph

Article in Addiction research & theory, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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.

William C KerrAlcohol Research Group, Public Health Institute, 6001 Shellmound Ave, Suite 450, Emeryville, CA 94608, USA.
Yu YeAlcohol Research Group, Public Health Institute, 6001 Shellmound Ave, Suite 450, Emeryville, CA 94608, USA.

Funding

Effects of Spirits Privatization on Alcohol Prices and Alcohol-related HarmsR01AA021742 · NIAAA · PUBLIC HEALTH INSTITUTE · PI KERR, WILLIAM C. · 2013 to 2017
$3.0M
Impacts of Recreational Marijuana Legalization and Retail Outlets in Washington: Unique Perspectives from Survey and County Mortality DataR01DA048526 · NIDA · PUBLIC HEALTH INSTITUTE · PI KERR, WILLIAM C. · 2019 to 2022
$2.0M
NIAAA NIH HHS R01 AA021742NIDA NIH HHS R01 DA048526
6 · The paper itself

Abstract

Background: Quantifying average amounts of marijuana used per day or per occasion of use helps inform understanding population-level patterns of use and use-related harm, but better estimates and estimation methods are needed. Users have difficulty in reporting use amounts, but purchase amounts may be more clearly recalled. Methods: Measures of individual's use and purchasing frequency and details of purchases such as the amounts and products bought and the cost of these were collected in six cross-sectional representative surveys of the population 18 and older in the state of Washington from 2014 to 2016. Analyses utilize purchase information on both flower and other marijuana products to estimate mean amounts per use day and predict use amounts for non-purchasers. Results: Mean marijuana use per use day among purchasers was 1.35 grams and non-purchasers estimated mean use amount per day was 0.71 grams. Lower mean use per day was a found for women and the most frequent users. Based on these estimates, total past year marijuana use for purchasers had a mean of 184.8 grams and the mean for non-purchasers was 28 grams. Conclusions: Methods based on purchasing details can be used to estimate individual's marijuana quantity per occasion and total use amount per year, providing additional outcome measures for analyses of predictors of individual marijuana consumption and facilitating more detailed analyses of risks for marijuana harms.

Indexed as

amount per daymarijuanameasurementpurchasingquantity

Identifiers

PMID36189378
PMCPMC9523691

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Registered trials

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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.