Evidence map›Paper›PMID 30256305›Full record

ArticleJournal of occupational and environmental medicine2019

Associations Between Marijuana Use and Involuntary Job Loss in the United States: Representative Longitudinal and Cross-Sectional Samples.

Cassandra A Okechukwu, Janine Molino, Yenee Soh

Abstract read
In one paragraph

Article in Journal of occupational and environmental medicine, 2019. 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
1.3field-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

9 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Association Between Unemployment and Mental Disorders: A Narrative Update of the Literature.International journal of environmental research and public health · 2024
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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

3 authors at 1 institution in 1 country.

Cassandra A OkechukwuHarvard T.H. Chan School of Public Health, Boston, Massachusetts (Dr Okechukwu, Ms Soh); Brown University School of Public Health, Providence, Rhode Island (Dr Molino).
Janine Molino
Yenee Soh
Rhode Island Department of Health · US

Funding

Drug abuse and jobs: racial disparities in labor force participation and outcomesR03DA038697 · NIDA · HARVARD SCHOOL OF PUBLIC HEALTH · PI OKECHUKWU, CASSANDRA A. · 2015 to 2016
$161k
NIDA NIH HHS R03 DA038697
6 · The paper itself

Abstract

objectiveTo investigate whether marijuana use is associated with involuntary job loss.

methodsMultivariable survey logistic analysis of longitudinal (2001 to 2002/2003 to 2004) and cross-sectional data (2012 to 2013) from National Epidemiologic Survey on Alcohol and Related Conditions (NESARC).

resultsMarijuana use increased for all user groups with most workers who use marijuana using marijuana monthly (2.7% in 2001 to 2002 and 10.8% in 2012 to 2013). Past year marijuana users in 2001 to 2002 had higher odds of involuntary job loss in 2003 to 2004 (odds ratio [OR] 1.27; 95% confidence interval [CI] 1.13 to 1.41). Daily marijuana use is associated with higher odds of job loss in adjusted analyses using longitudinal (OR 2.18; 95%CI 1.71 to 2.77) and cross-sectional data (OR 1.40; 95%CI 1.06 to 1.86). Income significantly modifies these effects.

conclusionsFindings indicate that job loss may be an overlooked social cost of marijuana use for US workers. Future studies using an occupational health perspective are needed.

Indexed as

AdolescentAdultAgedCross-Sectional StudiesFemaleHumansLogistic ModelsLongitudinal StudiesMaleMarijuana UseMiddle AgedRisk FactorsUnemploymentUnited StatesYoung Adult

Identifiers

PMID30256305
PMCPMC6314892
OpenAlexW2894028402

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.