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Evaluation of an Online Decision Aid for Selection of Contraceptive Methods
Molly Redman1, Jennifer Brian2, Dongwen Wang1
1College of Health Solutions, Arizona State University, Tempe, Arizona, United States.
Objectives:
Knowledge gaps in contraceptives led to their low adoption rates and misuse in young women. The existing online contraception decision aids missed certain decision factors deemed important to college-aged women and did not consistently provide clear and accurate recommendations. To address the needs of young women and the limitations in current tools, we developed a prototype contraception decision aid, My Contraceptive Choice (MCC). This article reports an evaluation study of the MCC tool.
Methods:
We conducted a mixed methods study: (1) to assess MCC's usefulness and usability through an online survey and a follow-up focus group, and (2) to provide a quantitative examination on the recommendations generated by MCC to match with individual user's needs and preferences through simulated test cases.
Results:
The survey of 150 college-aged women showed very positive responses (reflecting personal preferences, 75%; helping people learn more about birth control methods, 88%; easy to navigate, 91%). The follow-up focus group of 10 survey participants reconfirmed most findings from the survey and provided detailed feedback on certain system functions, such as the inclusion of an important decision factor of weight gain and the efficient hybrid design to integrate the customized recommendations with the side-by-side comparison of all contraceptive methods. Simulated test cases showed that the MCC tool achieved an accuracy of 72% in addressing user preferences and an accuracy of 72% in satisfying user needs, which were significantly better than the existing Planned Parenthood tool.
Conclusion:
The initial evaluations suggest that the MCC tool has achieved good levels of usefulness, usability, and appropriate recommendations to address user needs and preferences. Future research is required to assess the performance of the MCC tool in naturalistic settings and to examine the generalizability of the findings to other user populations.
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