Evidence map›Paper›PMID 30952692›Full record

ArticleTobacco control2020

Impact of the NHS Stop Smoking Services on smoking prevalence in England: a simulation modelling evaluation.

Fujian Song, Tim Elwell-Sutton, Felix Naughton

Abstract read
In one paragraph

Article in Tobacco control, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Fujian SongNorwich Medical School, University of East Anglia, Norwich, UK fujian.song@uea.ac.uk.ORCID 0000-0002-4039-1531
Tim Elwell-SuttonPublic Health, Thurrock Council, Civic Offices, Essex, UK.
Felix NaughtonSchool of Health Sciences, University of East Anglia, Norwich, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe English National Health Service NHS Stop Smoking Services (SSS), established in 2001, were the first such services in the world. An appropriate evaluation of the SSS has national and international significance. This modelling study sought to evaluate the impact of the SSS on changes in smoking prevalence in England.

methodsA discrete time state-transition model was developed to simulate changes in smoking status among the adult population in England during 2001-2016. Input parameters were based on data from national statistics, population representative surveys and published literature. The main outcome was the percentage point reduction in smoking prevalence attributable to the SSS.

resultsSmoking prevalence was reduced by 10.8 % in absolute terms during 2001-2016 in England, and 15.3 % of the reduction could be attributable to the SSS. The percentage point reduction in smoking prevalence each year was on average 0.72%, and 0.11 % could be attributable to the SSS. The proportion of SSS supported quit attempts increased from 5.5 % in 2001, to as high as 18.9 % in 2011, and then reduced to 8.2 % in 2016. Quit attempts with SSS support had a higher success rate than those without SSS support (15.1% vs 11.3%). Smoking prevalence in England continued to decline after the SSS was much reduced from 2013 onwards.

conclusionsApproximately 15% of the percentage point reduction in smoking prevalence during 2001-2016 in England may be attributable to the NHS SSS, although uncertainty remains regarding the actual impact of the formal smoking cessation services.

Indexed as

AdolescentAdultComputer SimulationEnglandFemaleHumansMaleMiddle AgedPrevalenceSmoking CessationSmoking PreventionState MedicineTobacco SmokingYoung Adultaddictioncessationhealth services

Identifiers

PMID30952692
PMCPMC7042976

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.