Feasibility and accuracy of a computer-assisted self-interviewing instrument to ascertain prior immunization with human papillomavirus vaccine by self-report: Cross-sectional analysis

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Abstract

Background: Ascertaining history of prior immunization with human papillomavirus (HPV) vaccine can be challenging and resource-intensive. Computer-assisted self-interviewing instruments have the potential to address some of the challenges of self-reporting, and may also reduce the time, costs, and efforts associated with ascertaining immunization status. Objective: This study assesses both the feasibility and the accuracy of a computer-assisted self-interviewing instrument to ascertain a patient's history of immunization with the HPV vaccine. Methods: We developed both a survey and a Web-based data collection system using computer-assisted self-interviewing to ascertain self-reported HPV vaccine immunization history. We implemented the instrument in a sample of adult women enrolled in an ongoing study of the HPV vaccine. Vaccine records from prior sources of care were reviewed to verify reported immunization history. Results: Among the 312 participants who provided HPV vaccine immunization history by self-report, almost all (99%) were able to do so using the computer-assisted self-interviewing instrument. The median survey completion time was 10 minutes (IQR 7-17). The accuracy of self-report was 84%, sensitivity was 89%, specificity was 80%, and the negative predictive value was 92%. Conclusions: We found that it is feasible to collect a history of immunization with the HPV vaccine using a computer-assisted self-interviewing instrument. This approach is likely to be acceptable to adult women and is reasonably accurate in a clinical research setting.

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Oliveira, C. R., Avni-Singer, L., Badaro, G., Sullivan, E. L., Sheth, S. S., Shapiro, E. D., & Niccolai, L. M. (2020). Feasibility and accuracy of a computer-assisted self-interviewing instrument to ascertain prior immunization with human papillomavirus vaccine by self-report: Cross-sectional analysis. JMIR Medical Informatics, 8(1). https://doi.org/10.2196/16487

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