Evidence map›Paper›PMID 33930639›Full record

ArticleDrug and alcohol dependence2021

A mixed-methods study to inform the clarity and accuracy of cannabis-use and cannabis-tobacco co-use survey measures.

Shannon Lea Watkins, Pearl Karliner-Li, Youn Ok Lee, Kimberly A Koester, Pamela M Ling

Open access · greenAbstract read
In one paragraph

Article in Drug and alcohol dependence, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Cannabis Use and Subsequent Cigarette Discontinuation Among U.S. Adults in the Population Assessment of Tobacco and Health Study, Waves 1-5.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
    Article
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. 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 at 2 institutions in 1 country.

Shannon Lea WatkinsCenter for Tobacco Control Research and Education and Division of General Internal Medicine, Department of Medicine, University of California San Francisco, 530 Parnassus Ave. Ste 366, San Francisco, CA, 94143, United States. Electronic address: shannon-watkins@uiowa.edu.
Pearl Karliner-LiUniversity of California, San Francisco, United States. Electronic address: pearl.karliner-li@ucsf.edu.
Youn Ok LeeCenter for Health Policy Science and Tobacco Research, RTI International, United States. Electronic address: younlee@rti.org.
Kimberly A KoesterUniversity of California, Department of Medicine, San Francisco, United States. Electronic address: Kimberly.Koester@ucsf.edu.
Pamela M LingCenter for Tobacco Control Research and Education and Division of General Internal Medicine, Department of Medicine, University of California San Francisco, 530 Parnassus Ave. Ste 366, San Francisco, CA, 94143, United States. Electronic address: pamela.ling@ucsf.edu.
University of California, San Francisco · USRTI International · US

Funding

Understanding Smokeless Tobacco MarketingR01CA141661 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LING, PAMELA MAY · 2009 to 2019
$5.4M
Co-Abuse Cannabis and TobaccoR33DA044377 · NIDA · RESEARCH TRIANGLE INSTITUTE · PI MARUSICH, JULIE A · 2019 to 2021
$2.7M
Postdoctoral training in tobacco controlT32CA113710 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LING, PAMELA MAY · 2016 to 2020
$2.6M
Co-Abuse Cannabis and TobaccoR21DA044377 · NIDA · RESEARCH TRIANGLE INSTITUTE · PI WILEY, JENNY L. · 2017 to 2018
$412k
NCI NIH HHS R01 CA141661NCI NIH HHS T32 CA113710NIDA NIH HHS R21 DA044377NIDA NIH HHS R33 DA044377
6 · The paper itself

Abstract

backgroundLegalization of medical and recreational cannabis in US states has been accompanied by increases in availability, acceptability, and diversity in methods of cannabis use, as well as an increase in devices and methods for cannabis-tobacco co-use. Updated and specific survey measures of cannabis and cannabis-tobacco co-use are needed.

methodsWe employed a mixed-methods approach to identify sources of specification and measurement error in cannabis and cannabis-tobacco co-use measures. We surveyed and interviewed 36 young adult (age 18-29) cannabis and tobacco co-users in California (2017-2018), triangulated with document analysis of online cannabis websites and forums. We investigated how survey reports of cannabis use and cannabis-tobacco co-use compared to narrative descriptions provided during in-depth interviews. We identify key strategies for researchers collecting self-reported survey data to enhance accuracy and comprehensiveness of measures.

findingsPotential sources of survey error included: broad variation in cannabinoid content and concentration, inconsistent interpretation of questions between participants and researchers (e.g. blunts were not considered co-use), and substantial variation in dosage within and between products. No evidence of survey recall bias or response editing was detected.

conclusionTo enhance survey accuracy, we recommend surveys specify which cannabis delivery methods and forms are included and excluded in each measure, differentiate between cannabis products, and explicitly include or exclude CBD product use.

Indexed as

CannabisAdolescentAdultAnalgesicsHumansSurveys and QuestionnairesTobacco ProductsTobacco UseYoung AdultAnalgesicsCannabisHashishMarijuanaMixed methodsQuestionnaire designSubstance useSurvey measurement

Identifiers

PMID33930639
PMCPMC8180503
OpenAlexW3153371017

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.