Evidence map›Paper›PMID 28410177›Full record

ArticleJMIR cancer2016

Predictors of Online Cancer Prevention Information Seeking Among Patients and Caregivers Across the Digital Divide: A Cross-Sectional, Correlational Study.

Tamar Ginossar

Open access · goldAbstract read
In one paragraph

Article in JMIR cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
7.7field-weighted citation impact, top 3% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Health information seeking behaviors among individuals with young-onset and average-onset colorectal cancer: an international cross-sectional survey.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2020
    Article
  10. Advances and future directions in the use of mobile health in supportive cancer care: proceedings of the 2019 MASCC Annual Meeting symposium.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2020
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
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

1 author at 1 institution in 1 country.

Tamar GinossarUniversity of New Mexico Cancer Center, Department of Communication and Journalism, University of New Mexico, albuquerque, NM, United States.ORCID http://orcid.org/0000-0002-0136-6675
University of New Mexico · US

Funding

NM MINORITY-BASED COMMUNITY CLINICAL ONC. PROGRAMU10CA086780 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI ROYCE, MELANIE E · 2000 to 2014
$8.8M
NCI NIH HHS U10 CA086780
6 · The paper itself

Abstract

backgroundThe digital divide is a recognized public health problem caused by social determinants that exacerbate health disparities. Despite the "tectonic shift" in how most of the public obtains cancer information, underserved communities are at increased risk of being digitally marginalized. However, research that examines factors underlying eHealth information seeking in diverse health contexts is lacking.

objectiveThe aim of this paper is to explore preferences and use of eHealth cancer prevention information (CPI) among patients and caregivers attending a minority-serving oncology clinic using the comprehensive model of information seeking as a theoretical framework. Specifically, the study examined the role of social determinants and prevention orientation in differences in preference and use of the Internet for CPI seeking among this diverse sample.

methodsSurvey methodology was used to identify social determinants and behavioral factors, including prevention orientation as correlates and predictors of respondents' (n=252) preferences and use of eHealth for CPI seeking.

resultsLess than half (112/252, 44.4%) of respondents said that if faced with the need to seek CPI, they would seek this information online. In the final logistic regression model, education, ethnicity, age, and prevention orientation made significant contributions to the model (P<.05). Specifically, for each year increase in age, participants were 3% less likely to use the Internet for CPI seeking (P=.011). Compared to college graduates, respondents who did not complete high school were 11.75 times less likely to cite the Internet as a CPI carrier (P<.001) and those with a high school education were 3 times (2.99, P=.015) less likely. In addition, the odds that a Spanish speaker would cite the Internet as a CPI carrier were one-fifth (22%) of non-Hispanic whites (P=.032) and about one-quarter (26%) of English-speaking Latinos (P=.036). Finally, with each one point increase on the prevention orientation scale, respondents were 1.83 times less likely to cite online CPI seeking (P=.05).

conclusionsSocial determinants to health have profound influence on eHealth CPI seeking. Providers and policy makers should focus on meeting patients and family members' CPI needs following diagnosis and increase eHealth accessibility and availability of evidence-based CPI to diverse populations. Future research is needed to unravel further differences in eHealth CPI seeking, including those among Native Americans that emerged as an additional digitally underserved racial/ethnic group. Finally, additional factors underlying these differences should be explored to better tailor CPI eHealth information to diverse communities' information needs.

Indexed as

digital divideInternet, information seeking behaviorminority health

Identifiers

PMID28410177
PMCPMC5369630
OpenAlexW2338601989

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.