Evidence map›Paper›PMID 29065390›Full record

Trial reportDrug and alcohol dependence2017

Improving tobacco dependence treatment outcomes for smokers of lower socioeconomic status: A randomized clinical trial.

Christine E Sheffer, Warren K Bickel, Christopher T Franck, Luana Panissidi, Jami C Pittman, Helen Stayna, Shenell Evans

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Drug and alcohol dependence, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 3 pooled it
–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

12 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Article
  9. Article
  10. A Machine-Learning Approach to Predicting Smoking Cessation Treatment Outcomes.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2020
    Article
  11. Article
  12. 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

7 authors.

Christine E ShefferCity University of New York School of Medicine, City College of New York, 160 Convent Ave, New York, NY 10031, United States. Electronic address: Christine.sheffer@roswellpark.org.
Warren K BickelAdvanced Recovery Research Center, Virginia Tech Carilion Research Institute, 2 Riverside Circle, Roanoke, VA 24016, United States.
Christopher T FranckDepartment of Statistics, Virginia Tech, Blacksburg, VA 24061, United States.
Luana PanissidiCity University of New York School of Medicine, City College of New York, 160 Convent Ave, New York, NY 10031, United States.
Jami C PittmanCity University of New York School of Medicine, City College of New York, 160 Convent Ave, New York, NY 10031, United States.
Helen StaynaCity University of New York School of Medicine, City College of New York, 160 Convent Ave, New York, NY 10031, United States.
Shenell EvansCity University of New York School of Medicine, City College of New York, 160 Convent Ave, New York, NY 10031, United States.

Funding

Reducing socioeconomic disparities in tobacco dependence treatment outcomesR01MD007054 · NIMHD · CITY COLLEGE OF NEW YORK · PI SHEFFER, CHRISTINE ELIZABETH · 2012 to 2016
$1.4M
The TREND Partnership: Translational Research Education and Training to Eliminate Tobacco Disparities (1/2)P20CA192993 · NCI · CITY COLLEGE OF NEW YORK · PI SHEFFER, CHRISTINE ELIZABETH · 2014 to 2017
$766k
NCI NIH HHS P20 CA192993NIMHD NIH HHS R01 MD007054
6 · The paper itself

Abstract

introductionEvidence-based treatments for tobacco dependence are significantly less effective for smokers of lower socioeconomic status which contributes to socioeconomic disparities in smoking prevalence rates and health. We aimed to reduce the socioeconomic gradient in treatment outcomes by systematically adapting evidence-based, cognitive-behavioral treatment for tobacco dependence for diverse lower socioeconomic smokers.

methodsParticipants were randomized to adapted or standard treatment, received six 1-h group treatment sessions, and were followed for six months. We examined the effectiveness of the adapted treatment to improve treatment outcomes for lower socioeconomic groups.

resultsParticipants (n=227) were ethnically, racially, and socioeconomically diverse. The adapted treatment significantly reduced the days to relapse for the two lowest socioeconomic groups: SES1: M=76.6 (SD 72.9) vs. 38.3 (SD 60.1) days to relapse (RR=0.63 95% CI, 0.45, 0.88, p=0.0013); SES2: M=88.2 (SD 67.3) vs. 40.1 (SD 62.6 days to relapse (RR=0.57 95% CI, 0.18, 0.70, p=0.0024). Interactions between socioeconomic status and condition were significant for initial abstinence (OR=1.26, 95% CI 1.09, 1.46, p=0.002), approached significance for 3-month abstinence (OR=0.90, 95% CI 0.80, 1.01, p<0.071), and were not significant for 6-month abstinence (OR=0.99 95% CI 0.88, 1.10, p=0.795). No significant differences in long-term abstinence were observed.

conclusionSystematic adaption of evidence-based treatment for tobacco dependence can significantly improve initial and short-term treatment outcomes for diverse lower socioeconomic smokers and reduce inequities in days to relapse. Novel methods of providing targeted extended support are needed to improve long-term outcomes.

Indexed as

Social ClassAdultAgedCognitive Behavioral TherapyFemaleHumansMaleMiddle AgedPovertyRecurrenceSmoking CessationTobacco Use DisorderTreatment OutcomeYoung AdultBlack or african americanDisparitiesLower socioeconomic statusRelapseSmoking cessationTreatment for tobacco dependence

Identifiers

PMID29065390
PMCPMC7780926

What OpenQuestion holds

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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.