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The Use of Cancer-Specific Patient-Centered Technologies Among Underserved Populations in the United States: Systematic ReviewWill L Tarver et al. J Med Internet Res. 2019.
. 2019 Apr 23;21(4):e10256. doi: 10.2196/10256. AffiliationsItem in Clipboard
AbstractBackground: In the United States, more than 1.6 million new cases of cancer are estimated to be diagnosed each year. However, the burden of cancer among the US population is not shared equally, with racial and ethnic minorities and lower-income populations having a higher cancer burden compared with their counterparts. For example, African Americans have the highest mortality rates and shortest survival rates for most cancers compared with other racial or ethnic groups in the United States. A wide range of technologies (eg, internet-based [electronic health, eHealth] technologies, mobile [mobile health, mHealth] apps, and telemedicine) available to patients are designed to improve their access to care and empower them to participate actively in their care, providing a means to reduce health care disparities; however, little is known of their use among underserved populations.
Objective: The aim of this study was to systematically review the current evidence on the use of cancer-specific patient-centered technologies among various underserved populations.
Methods: Computer-based search was conducted in the following academic databases: (1) PubMed (cancer subset), (2) MEDLINE, (3) PsycINFO, and (4) CINAHL. We included studies that were peer-reviewed, published in the English language, and conducted in the United States. Each study was individually assessed for relevance, with any disagreements being reconciled by consensus. We used a 3-step inclusion process in which we examined study titles, abstracts, and full-text papers for assessment of inclusion criteria. We systematically extracted information from each paper meeting our inclusion criteria.
Results: This review includes 71 papers that use patient-centered technologies that primarily targeted African Americans (n=31), rural populations (n=14), and Hispanics (n=12). A majority of studies used eHealth technologies (n=41) finding them to be leading sources of cancer-related health information and significantly improving outcomes such as screening among nonadherent individuals and increasing knowledge about cancer and cancer screening. Studies on mHealth found that participants reported overall favorable responses to receiving health information via short message service (SMS) text message; however, challenges were experienced with respect to lack of knowledge of how to text among some participants. More complex mobile technologies (eg, a tablet-based risk assessment tool) were also found favorable to use and acceptable among underserved populations; however, they also resulted in more significant barriers, for example, participants expressed concerns regarding security and unfamiliarity with the technology and preferred further instruction and assistance in its use.
Conclusions: There is a growing body of literature exploring patient-centered technology and its influence on care of underserved populations. In this review, we find that these technologies seem to be effective, especially when tailored, in improving patient and care-related outcomes. Despite the potential of patient-centered technologies and the receptivity of underserved populations, challenges still exist with respect to their effective use and usability.
Keywords: cancer; medical informatics; underserved populations.
©Will L Tarver, David A Haggstrom. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 23.04.2019.
Conflict of interest statementConflicts of Interest: None declared.
FiguresFigure 1
Venkatesh et al's [44] consumer…
Figure 1
Venkatesh et al's [44] consumer acceptance model of the unified theory of acceptance…
Figure 1Venkatesh et al's [44] consumer acceptance model of the unified theory of acceptance and use of technology.
Figure 2
Systematic review flowchart. pop: population.
Figure 2
Systematic review flowchart. pop: population.
Figure 2Systematic review flowchart. pop: population.
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