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An Iterative Process for Developing and Evaluating a Computer-Based Prostate Cancer Decision Aid for African American
Otis L Owens1, Daniela B Friedman2, Heather M Brandt2
1University of South Carolina, Columbia, SC, USA owenso@email.sc.edu sowens06@gmail.com.
This study developed a culturally relevant computer-based decision aid (CBDA) to improve prostate cancer (PrCA) knowledge for African American men. The iterative development process ensured the CBDA meets the needs of this priority population.
Area of Science:
- Health Informatics
- Public Health
- Cancer Research
Background:
- Prostate cancer (PrCA) disproportionately affects African American (AA) men, highlighting the need for informed screening decisions.
- Developing culturally appropriate decision aids is crucial for this population.
- A computer-based decision aid (CBDA) was designed to enhance prostate knowledge, self-efficacy, and informed decision-making intentions.
Purpose of the Study:
- To develop and evaluate a culturally appropriate computer-based decision aid (CBDA) for African American men regarding prostate cancer (PrCA) screening.
- To increase prostate cancer knowledge, decision self-efficacy, and intention for informed decision-making.
Main Methods:
- An iterative development approach was used, incorporating feedback from focus groups with 21 African American men.
- A prototype CBDA with interactive elements was refined based on participant input.
- Expert reviewers and usability interviews were conducted to further evaluate the CBDA.
Main Results:
- Consensus was reached on many CBDA features between participants and expert reviewers.
- Suggestions for improving format and graphics were provided to enhance CBDA effectiveness.
- The development and evaluation process, along with implications, are discussed.
Conclusions:
- Computer-based decision aids (CBDAs) show potential for supporting informed decision-making among African American men.
- Community and expert engagement in an iterative development process is vital for creating relevant decision aids for priority populations.
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