Evidence map›Paper›PMID 26940637›Full record

ArticleJournal of medical Internet research2016

Entertainment or Health? Exploring the Internet Usage Patterns of the Urban Poor: A Secondary Analysis of a Randomized Controlled Trial.

Rachel F McCloud, Cassandra A Okechukwu, Glorian Sorensen, Kasisomayajula Viswanath

Abstract 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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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.

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

11 citing papers in PubMed.

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  8. How COVID-19 Changed the Information Needs of Italian Citizens.International journal of environmental research and public health · 2020
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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

4 authors.

Rachel F McCloudDana-Farber Cancer Institute, Center for Community-Based Research, Boston, MA, United States. rachel_faulkenberry@dfci.harvard.edu.ORCID http://orcid.org/0000-0003-0174-2260

Funding

Harvard Education Program in Cancer Prevention Control (R25T)R25CA057711 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI DAVISON, KIRSTEN · 1992 to 2018
$8.5M
The Harvard Chan Education Program in Cancer Prevention and ControlT32CA057711 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Karen M. Emmons, ANNE LINDSAY FRAZIER · 2019 to 2026
$3.3M
Click to Connect: Improving Health Literacy through Internet LiteracyR01CA122894 · NCI · DANA-FARBER CANCER INST · PI VISWANATH, KASISOMAYAJULA · 2006 to 2010
$2.6M
NCI NIH HHS R01 CA122894NCI NIH HHS R25 CA057711NCI NIH HHS T32 CA057711
6 · The paper itself

Abstract

backgroundImportant gaps remain in our knowledge of how individuals from low socioeconomic position (SEP) use the Internet for resources and in understanding the full range of activities they perform online. Although self-report data indicate that low SEP individuals use the Internet less than high SEP people for health information and for other beneficial capital-enhancing activities, these results may not provide an accurate overall view of online use.

objectiveThe aim of this study was to determine the ways in which low SEP individuals use the Internet, including for entertainment, social networking, and capital-enhancing functions, and how they are associated with health information seeking.

methodsDetailed Web tracking data were collected from 118 low SEP individuals who participated in the intervention group of a randomized controlled trial that provided Internet access. Websites were grouped by topic, including categories of capital-enhancing websites that provided access to resources and information. Different types of online activities were summed into an Internet use index. Single and multiple negative binomial regression models were fitted with the Internet use index as the predictor and health information seeking as the outcome. Next, models were fitted with low, medium, and high Web usage in capital-enhancing, entertainment, and social network categories to determine their associations with health information seeking.

resultsParticipants used the Web for diverse purposes, with 63.6% (75/118) accessing the Internet for all defined types of Internet use. Each additional category of Internet use was associated with 2.12 times the rate of health information seeking (95% CI 1.84-2.44, P<.001). Higher use of each type of capital-enhancing information was associated with higher rates of health information seeking, with high uses of government (incident rate ratio [IRR] 8.90, 95% CI 4.82-16.42, P<.001) and news (IRR 11.36, 95% CI 6.21-20.79, P<.001) websites associated with the highest rates of health information seeking compared to their lowest use categories. High entertainment website use (IRR 3.91, 95% CI 2.07-7.37, P<.001) and high social network use (IRR 2.06, 95% CI 1.08-3.92, P=.03) were also associated with higher health information seeking.

conclusionsThese data clearly show that familiarity and skills in using the Internet enhance the capacity to use it for diverse purposes, including health and to increase capital, and that Internet usage for specific activities is not a zero sum game. Using it for one type of topic, such as entertainment, does not detract from using it for other purposes. Findings may inform ways to engage low SEP groups with Internet resources.

Indexed as

Information Seeking BehaviorLeisure ActivitiesAdultComputer LiteracyConsumer Health InformationFemaleHumansInternetMaleMiddle AgedPovertyRandomized Controlled Trials as TopicSocial ClassSocial NetworkingUrban PopulationVideo Gameshealth communicationinformation-seeking behaviorInternetsocioeconomic factors

Identifiers

PMID26940637
PMCPMC4796406

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.