Evidence map›Paper›PMID 30849943›Full record

ArticleBMC public health2019

Mass media promotion of a smartphone smoking cessation app: modelled health and cost-saving impacts.

Nhung Nghiem, William Leung, Christine Cleghorn, Tony Blakely, Nick Wilson

Abstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 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, 1 synthesis or guideline pooled it.

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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

5 authors.

Nhung NghiemDepartment of Public Health, University of Otago, Wellington, New Zealand.
William LeungDunedin School of Medicine, University of Otago, Dunedin, New Zealand.
Christine CleghornDepartment of Public Health, University of Otago, Wellington, New Zealand.
Tony BlakelyDepartment of Public Health, University of Otago, Wellington, New Zealand.
Nick WilsonDepartment of Public Health, University of Otago, Wellington, New Zealand. nick.wilson@otago.ac.nz.ORCID http://orcid.org/0000-0002-5118-0676

Funding

Health Research Council of New Zealand 10/248Ministry of Business, Innovation and Employment UOOX1406
6 · The paper itself

Abstract

backgroundSmartphones are increasingly available and some high quality apps are available for smoking cessation. However, the cost-effectiveness of promoting such apps has never been studied. We therefore aimed to estimate the health gain, inequality impacts and cost-utility from a five-year promotion campaign of a smoking cessation smartphone app compared to business-as-usual (no app use for quitting).

methodsA well-established Markov macro-simulation model utilising a multi-state life-table was adapted to the intervention (lifetime horizon, 3% discount rate). The setting was the New Zealand (NZ) population (N = 4.4 million). The intervention effect size was from a multi-country randomised trial: relative risk for quitting at 6 months = 2.23 (95%CI: 1.08 to 4.77), albeit subsequently adjusted to consider long-term relapse. Intervention costs were based on NZ mass media promotion data and the NZ cost of attracting a smoker to smoking cessation services (NZ$64 per person).

resultsThe five-year intervention was estimated to generate 6760 QALYs (95%UI: 5420 to 8420) over the remaining lifetime of the population. For Māori (Indigenous population) there was 2.8 times the per capita age-standardised QALY gain relative to non-Māori. The intervention was also estimated to be cost-saving to the health system (saving NZ$115 million [m], 95%UI: 72.5m to 171m; US$81.8m). The cost-saving aspect of the intervention was maintained in scenario and sensitivity analyses where the discount rate was doubled to 6%, the effect size halved, and the intervention run for just 1 year.

conclusionsThis study provides modelling-level evidence that mass-media promotion of a smartphone app for smoking cessation could generate health gain, reduce ethnic inequalities in health and save health system costs. Nevertheless, there are other tobacco control measures which generate considerably larger health gains and cost-savings such as raising tobacco taxes.

Indexed as

Cost-Benefit AnalysisMass MediaMobile ApplicationsSmartphoneSmoking CessationAdolescentAdultAdvertisingAgedCost SavingsFemaleHealth PromotionHumansLife TablesMaleMiddle AgedCost-utility analysisMass mediamHealthSmartphone appsSmoking cessationTobacco control

Identifiers

PMID30849943
PMCPMC6408783

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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.