Evidence map›Paper›PMID 23748381›Full record

ArticlePsychopharmacology2013

Compensation predicts smoking cessation failure.

Raymond S Niaura, Jennifer L Pearson, David B Abrams

Open access · greenAbstract read
In one paragraph

Article in Psychopharmacology, 2013. 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
0.4field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

3 authors at 2 institutions in 1 country.

Raymond S NiauraThe Schroeder Institute for Tobacco Research and Policy Studies at Legacy, 1724 Massachusetts Ave. NW, Washington, DC, 20036, USA, rniaura@legacyforhealth.org.
Jennifer L Pearson
David B Abrams
American Legacy Foundation · USGeorgetown University Medical Center · US

Funding

Statistical Sciences CoreP50CA084719 · NCI · MIRIAM HOSPITAL · PI CLARK, MELISSA A · 1999 to 2008
$17.8M
PSYCHOSOCIAL STRESSORS, SMOKING CESSATION AND C V RISKR01HL032318 · NHLBI · MIRIAM HOSPITAL · PI NIAURA, RAYMOND S. · 1986 to 2000
$251k
NCI NIH HHS P50 CA084719NHLBI NIH HHS HL32318
6 · The paper itself

Abstract

rationaleCompensation is a potential result of decreasing the available nicotine and tar dose in cigarettes. There is little published data linking compensation with cessation.

objectivesWe sought to examine whether compensation in response to restricted cigarette yield is associated with difficulty quitting smoking.

methodsQuestionnaires and blood samples were collected from 174 smokers interested in quitting smoking as part of a larger smoking cessation study. Participants were instructed to use a filter designed to remove 50 % of tar and nicotine from the cigarette but otherwise smoke normally. Participants returned after 3 days of using the filter for follow-up data collection.

resultsNicotine levels and cigarettes per day decreased after use of the filter. Baseline nicotine and change in nicotine pre/post filter use, but not cigarettes per day or change in cigarettes per day were associated with smoking abstinence at 30 days.

conclusionsSmokers who demonstrate sensitivity to the biological or behavioral consequences of decreased nicotine content in tobacco smoke have greater difficulty quitting. These findings suggest the need for personalized cessation treatment linked to behavioral compensation.

Indexed as

SmokingAdultFemaleFollow-Up StudiesHumansMaleMiddle AgedNicotineSmoking CessationSurveys and QuestionnairesTarsTobacco ProductsNicotineTarstobacco tar

Identifiers

PMID23748381
PMCPMC3809341
OpenAlexW2029297967

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.