Evidence map›Paper›PMID 29057201›Full record

ArticleCurrent addiction reports2017

"Essentially, All Models are Wrong, but Some Are Useful": A Preliminary Conceptual Model Of Co-Occurring E-Cig and Alcohol Use.

Alexandra Hershberger, Melissa A Cyders

Abstract read
In one paragraph

Article in Current addiction reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

2 authors at 1 institution in 1 country.

Alexandra HershbergerIndiana University Purdue University, Indianapolis.
Melissa A CydersIndiana University Purdue University, Indianapolis.
Indiana University – Purdue University Indianapolis · US

Funding

The Effects of Electronic Cigarette Use on Alcohol Consumption: A Neurocognitive and Behavioral InvestigationF31AA024682 · NIAAA · INDIANA UNIVERSITY INDIANAPOLIS · PI HERSHBERGER, ALEXANDRA · 2016 to 2017
$84k
NIAAA NIH HHS F31 AA024682
6 · The paper itself

Abstract

purpose of reviewAs prevalence rates of electronic cigarette (e-cig) use increase, researchers and clinicians should not only be paying careful attention to the direct health effects of e-cigs, but also the potential impact e-cigs may have on alcohol use behaviors. We review the current state of the literature and propose a conceptual model for the relationship between e-cig and alcohol use, including important consequences, mechanisms, and moderators of this relationship. RECENT

findingsThe model is based in emerging literature examining the direct relationship between e-cig and alcohol use, as well as indirect evidence concerning potential mechanisms from research on cigarette and alcohol use. Overall, research indicates a robust relationship between e-cig and alcohol use. SUMMARY: We suggest that a relationship between e-cig use and alcohol use could be particularly problematic, especially for adolescents and for those with or at risk for alcohol use disorders. We hope the presented conceptual model can stimulate research in this area. We make research recommendations, including the need for more methodological rigor, including improved measurement of e-cig use, and expanding research to longitudinal and experimental designs.

Indexed as

alcoholco-occurringelectronic-cigarettessubstance use

Identifiers

PMID29057201
PMCPMC5647879
OpenAlexW2608910571

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.