Evidence map›Paper›PMID 41593728›Full record

Trial reportSubstance abuse treatment, prevention, and policy2026

Investigating if changing the wording of a study invitation letter increased recruitment in a project promoting tobacco cessation in a town with high smoking rates.

Christina Schell, Alexandra Godinho, John A Cunningham

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Substance abuse treatment, prevention, and policy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04534231 (Offering Nicotine Patches to All Households in a Municipality With High Smoking Rates), which is not on this map. Not yet cited in PubMed.

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

NCT04534231 completednot on this map

Offering Nicotine Patches to All Households in a Municipality With High Smoking Rates: Test of an Idea to Promote Large Increases in Tobacco Cessation

TypeobservationalSponsorCentre for Addiction and Mental HealthRan2020 to 2021Enrolled123ConditionsTobacco Use CessationArmsNicotine patch
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Christina SchellInstitute for Mental Health and Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada.
Alexandra GodinhoHumber River Health Research Institute, Humber River Health, Toronto, ON, Canada.
John A CunninghamInstitute for Mental Health and Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada. john.cunningham@kcl.ac.uk.

Funding

Canadian Cancer Society 706201
6 · The paper itself

Abstract

backgroundInvitation letters can be the first point of contact between research staff and potential participants and a number of modifiable variables have been studied to improve their effectiveness. The aim of this analysis was to determine if lower reading levels and “gain-framed” messages improved recruitment for a RCT that mailed nicotine replacement therapy (NRT) patches for smoking cessation.

methodsInvitation letters were created which varied in a two-by-two design by reading level and message framing. The letters were randomly mailed to all households in a community selected to receive targeted distribution of NRT patches.

resultsThere were no significant differences found in the number of participants enrolled.

conclusionFuture research investigating factors to improve invitation letters is merited despite current project limitations.

trial registrationClinicalTrials.gov NCT04534231.

Indexed as

Correspondence as TopicPatient SelectionSmoking CessationAdultFemaleHumansMaleMiddle AgedNicotine Replacement TherapyTobacco Use Cessation DevicesMessagingNicotine patchesNRTReading levelTobacco cessation

Identifiers

PMID41593728
PMCPMC12918147

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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.