Evidence map›Paper›PMID 21987478›Full record

ArticleHealth education research2012

Do smoking cessation websites meet the needs of smokers with severe mental illnesses?

Mary F Brunette, Joelle C Ferron, Timothy Devitt, Pamela Geiger, Wendy M Martin, Sarah Pratt, Meghan Santos, Gregory J McHugo

Abstract read
In one paragraph

Article in Health education research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 3 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

26 citing papers in PubMed, 3 syntheses or guidelines 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

8 authors.

Mary F BrunetteDartmouth Medical School, Psychiatric Research Center, 105 Pleasant St., Concord, NH 03303, USA. mary.f.brunette@dartmouth.edu
Joelle C Ferron
Timothy Devitt
Pamela Geiger
Wendy M Martin
Sarah Pratt
Meghan Santos
Gregory J McHugo

Funding

Treatment Development & Evaluation CoreP30DA029926 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2011 to 2026
$21.5M
NIDA NIH HHS P30 DA029926
6 · The paper itself

Abstract

Many people learn about smoking cessation through information on the Internet. Whether people with severe mental illnesses, who have very high rates of smoking, are able to use currently available websites about smoking cessation is unknown. The study reported here assessed whether four smoking cessation websites met usability guidelines and whether they were usable by smokers with severe mental illnesses. Four websites that appeared first on a Google search and represented an array of sponsors were selected. First, five experts rated the websites on adequacy of content in six areas and usability in 20 areas. Second, 16 smokers with severe mental illnesses performed two search tasks on the websites with researchers observing their searches and interviewing them regarding usability. One of the websites was rated by experts as acceptable for content and usability, but most of the participants were unable to navigate this website. The only website that was navigable received poor content ratings by experts. Four easily accessible websites did not meet the needs of smokers with severe mental illnesses. Although the Internet is a promising strategy to provide education about treatments, website developers must attend to the needs and capacities of multiple user groups.

Indexed as

Health Services Needs and DemandInternetPatient SatisfactionSmoking CessationAdultFemaleHumansInterviews as TopicMaleMental DisordersMiddle AgedSeverity of Illness IndexUnited States

Identifiers

PMID21987478
PMCPMC6281343

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.