Evidence map›Paper›PMID 33473322›Full record

ArticleDigital health

Smoker profiles and their influence on smokers' intention to use a digital decision aid aimed at the uptake of evidence-based smoking cessation tools: An explorative study.

Thomas Gültzow, Eline Suzanne Smit, Raesita Hudales, Carmen D Dirksen, Ciska Hoving

Registry-linked trialAbstract read
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In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05477420 (A Survey Study and Effect of Web-based Decision Aids on Preferences Shift), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

NCT05477420 nacompletednot on this map

A Survey Study and Effect of Web-based Decision Aids on Preferences Shift

TypeinterventionalSponsorChinese University of Hong KongRan2022 to 2024Enrolled148ConditionsDepression, PsychotherapiesArmsDecision Aid
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Trial
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.

Thomas GültzowDepartment of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands.ORCID https://orcid.org/0000-0002-9268-1880
Eline Suzanne SmitDepartment of Communication Science, Amsterdam School of Communication Research/ASCoR, University of Amsterdam, Amsterdam, the Netherlands.ORCID https://orcid.org/0000-0001-8588-6194
Raesita HudalesDepartment of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands.
Carmen D DirksenDepartment of Clinical Epidemiology and Medical Technology Assessment, CAPHRI Care and Public Health Research Institute, Maastricht University Medical Center, Maastricht, the Netherlands.
Ciska HovingDepartment of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands.ORCID https://orcid.org/0000-0003-1357-863X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesEvidence-based smoking cessation support tools (EBSTs) can double the quitting chances, but uptake among smokers is low. A digital decision aid (DA) could help smokers choose an EBST in concordance with their values and preferences, but it is unclear which type of smokers are interested in a digital DA. We hypothesized that smokers' general decision-making style (GDMS) could be used to identify early adopters. This study therefore aimed to identify smoker profiles based on smokers' GDMS and investigate these profiles' association with intention to use a digital DA.

designA cross-sectional dataset (N = 200 smokers intending to quit) was used to perform a hierarchical cluster analysis based on smokers' GDMS scores.

methodsClusters were compared on demographic and socio-cognitive variables. Mediation analyses were conducted to see if the relationship between cluster membership and intention was mediated through socio-cognitive variables (e.g., attitude).

resultsTwo clusters were identified;

conclusionsThe GDMS can be used to identify smokers who are interested in a digital DA early on. As such, the GDMS can be used to tailor recruitment and DA content.

Indexed as

cluster analysisdecision aiddecision makingdecision-making styledigital healthhealth promotionhealth psychologysmokingSmoking cessation

Identifiers

PMID33473322
PMCPMC7783882

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Registered trials

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.