Evidence map›Paper›PMID 29020085›Full record

ArticlePloS one2017

Success rates in smoking cessation: Psychological preparation plays a critical role and interacts with other factors such as psychoactive substances.

Bertrand Joly, Jean Perriot, Philippe d'Athis, Emmanuel Chazard, Georges Brousse, Catherine Quantin

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

  1. Identifying Key Predictors of Smoking Cessation Success: Text-Based Feature Selection Using a Large Language Model.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026
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  10. Personalized medicine for patients with COPD: where are we?International journal of chronic obstructive pulmonary disease · 2019
    Review
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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

6 authors.

Bertrand JolyBiostatistics and Bioinformatics (DIM), University Hospital, Dijon, France; Bourgogne Franche-Comté University, Dijon, France.
Jean PerriotDispensaire Emile Roux, Centre d'Aide à I'Arrêt du Tabagisme (IRAAT), Centre de Lutte Anti-Tuberculeuse (CLAT), Clermont-Ferrand, France.
Philippe d'AthisBiostatistics and Bioinformatics (DIM), University Hospital, Dijon, France; Bourgogne Franche-Comté University, Dijon, France.
Emmanuel ChazardUniv. Lille, CHU Lille, Department of Public Health, Lille, France.
Georges BroussePsychiatry B-Department of Addictology, Université Clermont 1, UFR Médecine, Clermont-Ferrand, and CHU Clermont-Ferrand, Clermont-Ferrand, France.
Catherine QuantinBiostatistics and Bioinformatics (DIM), University Hospital, Dijon, France; Bourgogne Franche-Comté University, Dijon, France.ORCID http://orcid.org/0000-0001-5134-9411

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe aim of this study was to identify factors associated with the results of smoking cessation attempts.

methodsData were collected in Clermont-Ferrand from a smoking cessation clinic between 1999 and 2009 (1,361 patients). Smoking cessation was considered a success when patients were abstinent 6 months after the beginning of cessation. Multivariate logistic regression was used to investigate the association between abstinence and different factors.

resultsThe significant factors were a history of depression (ORadjusted = 0.57, p = 0.003), state of depression at the initial consultation (ORa = 0.64, p = 0.005), other psychoactive substances (ORa = 0.52, p<0.0001), heart, lung and Ear-Nose-Throat diseases (ORa = 0.65, p = 0.005), age (ORa = 1.04, p<0.0001), the Richmond test (p<0.0001; when the patient's motivation went from insufficient to moderate, the frequency of abstinence was twice as high) and the Prochaska algorithm (p<0.0001; when the patient went from the 'pre-contemplation' to the 'contemplation' level, the frequency of success was four times higher). A high score in the Richmond test had a greater impact on success with increasing age (significant interaction: p = 0.01). In exclusive smokers, the contemplation level in the Prochaska algorithm was enough to obtain a satisfactory abstinence rate (65.5%) whereas among consumers of other psychoactive substances, it was necessary to reach the preparation level in the Prochaska algorithm to achieve a success rate greater than 50% (significant interaction: p = 0.02).

conclusionThe psychological preparation of the smoker plays a critical role. The management of smoking cessation must be personalized, especially for consumers of other psychoactive substances and/or smokers with a history of depression.

Indexed as

AlgorithmsFemaleHumansMaleMultivariate AnalysisPsychotropic DrugsSmoking CessationPsychotropic Drugs

Identifiers

PMID29020085
PMCPMC5636087

What OpenQuestion holds

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Registered trials

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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.