Evidence map›Paper›PMID 27260952›Full record

ArticleJournal of medical Internet research2016

Health Information Brokers in the General Population: An Analysis of the Health Information National Trends Survey 2013-2014.

Sarah L Cutrona, Kathleen M Mazor, Amenah A Agunwamba, Sruthi Valluri, Patrick M Wilson, Rajani S Sadasivam, Lila J Finney Rutten

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
9.0field-weighted citation impact, top 2% of its field
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

13 citing papers in PubMed, 38 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Sarah L CutronaUniversity of Massachusetts Medical School, Department of Medicine, Worcester, MA, United States. Sarah.Cutrona@umassmemorial.org.ORCID 0000-0002-4795-8377
Amenah A AgunwambaORCID 0000-0002-5445-5065
Rajani S SadasivamORCID 0000-0001-8406-6207
Lila J Finney RuttenORCID 0000-0001-7487-9407
Mayo Clinic in Arizona · USUniversity of Massachusetts Chan Medical School · USUniversity of Minnesota · US

Funding

University of Massachusetts Center for Clinical Science and Translational SupplementUL1TR001453 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LUZURIAGA, KATHERINE F · 2015 to 2024
$39.0M
University of Massachusetts Center for Clinical and Translational ScienceKL2TR000160 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LUZURIAGA, KATHERINE F · 2012 to 2014
$1.7M
Developing Smokers for Smoker (S4S): A Collective Intelligence tailoring systemK07CA172677 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI SADASIVAM, RAJANI · 2013 to 2017
$702k
NCATS NIH HHS KL2 TR000160NCATS NIH HHS UL1 TR001453NCI NIH HHS K07 CA172677
6 · The paper itself

Abstract

backgroundHealth information exchanged between friends or family members can influence decision making, both for routine health questions and for serious health issues. A health information broker is a person to whom friends and family turn for advice or information on health-related topics. Characteristics and online behaviors of health information brokers have not previously been studied in a national population.

objectiveThe objective of this study was to examine sociodemographic characteristics, health information seeking behaviors, and other online behaviors among health information brokers.

methodsData from the Health Information National Trends Survey (2013-2014; n=3142) were used to compare brokers with nonbrokers. Modified Poisson regression was used to examine the relationship between broker status and sociodemographics and online information seeking.

resultsOver half (54.8%) of the respondents were consulted by family or friends for advice or information on health topics (ie, they acted as health information brokers). Brokers represented 54.1% of respondents earning <$20,000 yearly and 56.5% of respondents born outside the United States. Women were more likely to be brokers (PR 1.34, 95% CI 1.23-1.47) as were those with education past high school (PR 1.42, CI 1.22-1.65). People aged ≥75 were less likely to be brokers as compared to respondents aged 35-49 (PR 0.81, CI 0.67-0.99). Brokers used the Internet more frequently for a variety of online behaviors such as seeking health information, creating and sharing online content, and downloading health information onto a mobile device; and also reported greater confidence in obtaining health information online.

conclusionsMore than 50% of adults who responded to this national survey, including those with low income and those born abroad, were providing health information or advice to friends and family. These individuals may prove to be effective targets for initiatives supporting patient engagement and disease management, and may also be well-positioned within their respective social networks to propagate health messages.

Indexed as

Consumer Health InformationFamilyFriendsInformation Seeking BehaviorInternetAdolescentAdultAgedAge FactorsDecision MakingFemaleHumansIncomeMaleMiddle AgedPeer Grouphealth care decision-makinghealth information seekingpatient self-managementpeer communicationsocial network

Identifiers

PMID27260952
PMCPMC4912679
OpenAlexW2418955315

What OpenQuestion holds

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LicenceCC BY
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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.