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Development of a Plain Language Decision Support Tool for Cancer Clinical Trials: Blending Health Literacy, Academic Research, and Minority Patient Perspectives.

Langford AT, Hawley ST, Stableford S, Studts JL, Byrne MM. Development of a Plain Language Decision Support Tool for Cancer Clinical Trials: Blending Health Literacy, Academic Research, and Minority Patient Perspectives. Journal of Cancer Education : The Official Journal of The American Association For Cancer Education. 2020 Jun 1; 35(3):454-461.

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Abstract:

Despite the promise of clinical trials for improving cancer care, less than 5% of all cancer patients participate. Racial/ethnic minorities continue to be underrepresented in cancer clinical trials (CCTs). To address this gap, we developed a plain language, web-based decision support tool (CHOICES DST) in English and Spanish to support decision-making about CCTs among Blacks and Hispanics. In phase 1 (information collection), we conducted qualitative interviews with 45 cancer patients, completed a thorough literature review, and reviewed results from a telephone survey of 1100 cancer patients. In phase 2 (content generation), we created the first iteration of the CHOICES DST. In phase 3 (usability testing), we gathered user experience and acceptability data from a small sample of cancer survivors (n? = 9). The Knowledge, Empowerment, and Values Clarification (KEV) model of decision-making was developed based on data from phase 1. The KEV model and other phase 1 data allowed us to create the CHOICES DST platform. Usability testing of the CHOICES DST showed highly favorable responses from users, satisfaction with content, ease of navigation, and a desire to use the tool. Qualitative results identified addressable points that would benefit from content and navigation-related alterations. The final version of the CHOICES DST was well received and understood by Black and Hispanic participants, and adheres to the mandates for plain language communication. This research provides preliminary data that CHOICES DST holds promise for improving knowledge of CCTs and potentially improving informed decision-making about participation in trials.





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