Technology, community, and equity: Considerations for collecting social determinants data
| dc.contributor.author | Singh, Aditi | |
| dc.contributor.author | Ding, Eric Y. | |
| dc.contributor.author | Mehawej, Jordy | |
| dc.contributor.author | Joshi, Shiksha | |
| dc.contributor.author | Soni, Apurv | |
| dc.contributor.author | Mujahid, Mahasin S. | |
| dc.date | 2022-08-11T08:08:11.000 | |
| dc.date.accessioned | 2022-08-23T15:45:38Z | |
| dc.date.available | 2022-08-23T15:45:38Z | |
| dc.date.issued | 2022-02-12 | |
| dc.date.submitted | 2022-03-31 | |
| dc.identifier.citation | <p>Singh A, Ding EY, Mehawej J, Joshi S, Soni A, Mujahid MS. Technology, community, and equity: Considerations for collecting social determinants data. Cardiovascular Digital Health Journal. 2022 Feb 12. V<a href="https://doi.org/10.1016/j.cvdhj.2022.01.003" target="_blank" title="view article on publisher's site">iew article on publisher's site</a></p> | |
| dc.identifier.doi | 10.1016/j.cvdhj.2022.01.003 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.14038/27572 | |
| dc.description.abstract | Gathering detailed information on an individual’s neighborhood environment is becoming increasingly recognized as a crucial component of understanding the impact that social determinants have on individual and public health, and this has been further highlighted by the ongoing COVID-19 pandemic. Emerging research clearly demonstrates COVID-19’s differential impact on underserved and rural communities, and it is imperative to adequately capture important neighborhood-level predictors of health outcomes to better understand the extent to which these communities have been affected, and to equitably promote their recovery and healing. mHealth tools have drastically transformed the framework of data collection within clinical and population health research and can significantly reduce accessibility barriers for research participants to allow for convenient, continuous real-time health and activity space assessments. Digital interventions leveraging remote data collection, and providing study participants with requisite devices when necessary, serves to bridge the digital divide that would otherwise preclude rural populations’ participation in key research opportunities for advancing health equity. | |
| dc.language.iso | en_US | |
| dc.rights | © 2022 Heart Rhythm Society. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Cardiovascular disease | |
| dc.subject | Rural health | |
| dc.subject | Wearable devices | |
| dc.subject | Social determinants of health | |
| dc.subject | Technology | |
| dc.subject | Biomedical Devices and Instrumentation | |
| dc.subject | Cardiology | |
| dc.subject | Cardiovascular Diseases | |
| dc.subject | Community-Based Research | |
| dc.subject | Community Health and Preventive Medicine | |
| dc.subject | Health Information Technology | |
| dc.subject | Health Services Administration | |
| dc.subject | Infectious Disease | |
| dc.subject | Virus Diseases | |
| dc.title | Technology, community, and equity: Considerations for collecting social determinants data | |
| dc.type | Journal Article | |
| dc.source.journaltitle | Cardiovascular Digital Health Journal | |
| dc.identifier.legacyfulltext | https://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=1380&context=covid19&unstamped=1 | |
| dc.identifier.legacycoverpage | https://escholarship.umassmed.edu/covid19/372 | |
| dc.identifier.contextkey | 28460694 | |
| refterms.dateFOA | 2022-08-23T15:45:38Z | |
| html.description.abstract | <p>Gathering detailed information on an individual’s neighborhood environment is becoming increasingly recognized as a crucial component of understanding the impact that social determinants have on individual and public health, and this has been further highlighted by the ongoing COVID-19 pandemic. Emerging research clearly demonstrates COVID-19’s differential impact on underserved and rural communities, and it is imperative to adequately capture important neighborhood-level predictors of health outcomes to better understand the extent to which these communities have been affected, and to equitably promote their recovery and healing. mHealth tools have drastically transformed the framework of data collection within clinical and population health research and can significantly reduce accessibility barriers for research participants to allow for convenient, continuous real-time health and activity space assessments. Digital interventions leveraging remote data collection, and providing study participants with requisite devices when necessary, serves to bridge the digital divide that would otherwise preclude rural populations’ participation in key research opportunities for advancing health equity.</p> | |
| dc.identifier.submissionpath | covid19/372 | |
| dc.contributor.department | Graduate School of Biomedical Sciences | |
| dc.contributor.department | Department of Medicine |



