Evidence map›Paper›PMID 41270716›Full record

ArticleDrug and alcohol dependence2025

Development and evaluation of a method to compile a national list of cannabis dispensaries.

Jennifer L Pearson, Luciana Borges, Lyndsey A Darrow, Grant Nippler, Abigail S Friedman

Abstract readEvaluation Study
In one paragraph

Article in Drug and alcohol dependence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Jennifer L PearsonDepartment of Health, Policy, and Administration Sciences, School of Public Health, University of Nevada, Reno, NV, USA. Electronic address: jennipearson@unr.edu.
Luciana BorgesDepartment of Health, Policy, and Administration Sciences, School of Public Health, University of Nevada, Reno, NV, USA.
Lyndsey A DarrowDepartment of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Nevada, Reno, NV, USA.
Grant NipplerDepartment of Health Policy and Management, Yale School of Public Health, Yale University, New Haven, CT, USA.
Abigail S FriedmanDepartment of Health Policy and Management, Yale School of Public Health, Yale University, New Haven, CT, USA.

Funding

Cannabis Legalization's Effects on Youth and Adult Nicotine and Tobacco UseR37DA058005 · NIDA · YALE UNIVERSITY · PI Abigail S. Friedman · 2024 to 2026
$1.6M
NIDA NIH HHS R37 DA058005
6 · The paper itself

Abstract

introductionUnderstanding how retail availability impacts cannabis attitudes and use requires data on the geographic distribution of cannabis dispensaries. However, with no single comprehensive source for dispensary locations, accurately mapping dispensaries presents unique challenges. This study's purpose was to: 1) describe a systematic process for identifying dispensaries that can be applied nationwide using two unexplored resources-RefUSA and Google Maps; 2) compare the accuracy of these resources with three commonly used sources of location data - state regulatory lists, Weedmaps, and Potguide; and 3) examine whether accuracy varies by urbanicity.

methodsWe obtained dispensary lists from Google Maps, Weedmaps, Potguide, RefUSA, and state regulatory data in three zip codes in every state that had legal recreational cannabis marketplaces, calling the dispensaries to confirm that they were operational. We present sensitivity and positive predictive value (PPV) by list and by Rural-Urban Commuting Area Codes (RUCAs), using the call-verified dispensary list as the gold standard.

resultsGoogle Maps identified the greatest number of dispensaries (n = 264), had the best sensitivity of all lists (96.0 %; 95 % CI: 92.6, 99.2), and yielded the highest proportion of potentially unlicensed dispensaries (29 %). There were no clear trends in sensitivity or PPV by RUCA. Removing listings that Google Maps marked as closed or that lacked phone numbers increased PPV from 82.2 % (95 % CI: 77.0, 86.6) to 96.4 % (95 % CI: 93.1, 98.5) without decreasing sensitivity.

conclusionsGoogle Maps currently offers the most accurate source of dispensary data for cross sectional analyses and performs equally well in urban and rural areas.

Indexed as

CannabisCommerceMarijuana UseHumansRural PopulationUnited StatesCannabisDispensariesGeospatial

Identifiers

PMID41270716
PMCPMC12767619

What OpenQuestion holds

Textmetadata
LicenceTDM
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.