A data-driven social network intervention for improving organ donation awareness among minorities: analysis and optimization of a cross-sectional study
dc.contributor.author | Murphy, MD | |
dc.contributor.author | Pinheiro, D | |
dc.contributor.author | Iyengar, R | |
dc.contributor.author | Lim, G | |
dc.contributor.author | Menezes, R | |
dc.contributor.author | Cadeiras, M | |
dc.date.accessioned | 2020-03-27T11:21:51Z | |
dc.date.issued | 2020-01-14 | |
dc.description.abstract | BACKGROUND: Increasing the number of organ donors may enhance organ transplantation, and past health interventions have shown the potential to generate both large-scale and sustainable changes, particularly among minorities. OBJECTIVE: This study aimed to propose a conceptual data-driven framework that tracks digital markers of public organ donation awareness using Twitter and delivers an optimized social network intervention (SNI) to targeted audiences using Facebook. METHODS: We monitored digital markers of organ donation awareness across the United States over a 1-year period using Twitter and examined their association with organ donation registration. We delivered this SNI on Facebook with and without optimized awareness content (ie, educational content with a weblink to an online donor registration website) to low-income Hispanics in Los Angeles over a 1-month period and measured the daily number of impressions (ie, exposure to information) and clicks (ie, engagement) among the target audience. RESULTS: Digital markers of organ donation awareness on Twitter are associated with donation registration (beta=.0032; P<.001) such that 10 additional organ-related tweets are associated with a 3.20% (33,933/1,060,403) increase in the number of organ donor registrations at the city level. In addition, our SNI on Facebook effectively reached 1 million users, and the use of optimization significantly increased the rate of clicks per impression (beta=.0213; P<.004). CONCLUSIONS: Our framework can provide a real-time characterization of organ donation awareness while effectively delivering tailored interventions to minority communities. It can complement past approaches to create large-scale, sustainable interventions that are capable of raising awareness and effectively mitigate disparities in organ donation. | en_GB |
dc.description.sponsorship | Rosenfeld Heart Foundation | en_GB |
dc.identifier.citation | Vol. 22, no. 1, article e14605 | en_GB |
dc.identifier.doi | 10.2196/14605 | |
dc.identifier.uri | http://hdl.handle.net/10871/120432 | |
dc.language.iso | en | en_GB |
dc.publisher | JMIR Publications | en_GB |
dc.rights | ©Michael Douglas Murphy, Diego Pinheiro, Rahul Iyengar, Gene Lim, Ronaldo Menezes, Martin Cadeiras. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. | en_GB |
dc.subject | organ donation | en_GB |
dc.subject | social media | en_GB |
dc.subject | digital sensor | en_GB |
dc.subject | tailored intervention | en_GB |
dc.title | A data-driven social network intervention for improving organ donation awareness among minorities: analysis and optimization of a cross-sectional study | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-03-27T11:21:51Z | |
dc.identifier.issn | 1439-4456 | |
dc.description | This is the author accepted manuscript | en_GB |
dc.identifier.eissn | 1438-8871 | |
dc.identifier.journal | Journal of Medical Internet Research | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2019-11-12 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019-11-12 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-03-27T11:16:30Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-03-27T11:21:56Z | |
refterms.panel | B | en_GB |
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Except where otherwise noted, this item's licence is described as ©Michael Douglas Murphy, Diego Pinheiro, Rahul Iyengar, Gene Lim, Ronaldo Menezes, Martin Cadeiras.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.