Laura Attanasio1, Donna McAlpine1. 1. University of Minnesota, School of Public Health, Division of Health Policy and Management, Minneapolis, MN.
Abstract
OBJECTIVES: Since the introduction of the human papillomavirus (HPV) vaccine in 2006, there have been considerable efforts at the national and state levels to monitor uptake and better understand the individual and system-level factors that predict who gets vaccinated. A common method of measuring the vaccination status of adolescents is through parental recall. We examined how the accuracy of parents' reports of their daughters' HPV vaccination status varied by social characteristics. METHODS: Data were taken from the 2009-2010 National Immunization Survey (NIS)-Teen, which includes a household interview and a provider-completed immunization history. We evaluated concordance between parents' and providers' reports of teens' HPV vaccine initiation (≥1 dose) and completion (≥3 doses). We assessed bivariate associations of sociodemographic characteristics with having a concordant, false-positive (overreporting) or false-negative (underreporting) report, and used multinomial logistic regression to estimate the independent impact of each characteristic. RESULTS: In bivariate analyses, concordance of parent-reported HPV vaccine initiation was associated with each of the sociodemographic characteristics investigated. In regression models, self-reported nonwhite race, lower household income, and lower education level of the teen's mother were associated with a higher likelihood of having a false-negative parental report than a concordant report. CONCLUSION: Our results indicate that, while estimates of overall coverage based on parental report may be unbiased, the differences in the accuracy of parental report could result in misleading estimates of disparities in HPV vaccine coverage.
OBJECTIVES: Since the introduction of the human papillomavirus (HPV) vaccine in 2006, there have been considerable efforts at the national and state levels to monitor uptake and better understand the individual and system-level factors that predict who gets vaccinated. A common method of measuring the vaccination status of adolescents is through parental recall. We examined how the accuracy of parents' reports of their daughters' HPV vaccination status varied by social characteristics. METHODS: Data were taken from the 2009-2010 National Immunization Survey (NIS)-Teen, which includes a household interview and a provider-completed immunization history. We evaluated concordance between parents' and providers' reports of teens' HPV vaccine initiation (≥1 dose) and completion (≥3 doses). We assessed bivariate associations of sociodemographic characteristics with having a concordant, false-positive (overreporting) or false-negative (underreporting) report, and used multinomial logistic regression to estimate the independent impact of each characteristic. RESULTS: In bivariate analyses, concordance of parent-reported HPV vaccine initiation was associated with each of the sociodemographic characteristics investigated. In regression models, self-reported nonwhite race, lower household income, and lower education level of the teen's mother were associated with a higher likelihood of having a false-negative parental report than a concordant report. CONCLUSION: Our results indicate that, while estimates of overall coverage based on parental report may be unbiased, the differences in the accuracy of parental report could result in misleading estimates of disparities in HPV vaccine coverage.
Authors: Lauri E Markowitz; Susan Hariri; Elizabeth R Unger; Mona Saraiya; S Deblina Datta; Eileen F Dunne Journal: Vaccine Date: 2010-02-25 Impact factor: 3.641
Authors: Charlene A Wong; Zahava Berkowitz; Christina G Dorell; Rebecca Anhang Price; Jennifer Lee; Mona Saraiya Journal: Cancer Date: 2011-06-20 Impact factor: 6.860
Authors: Jessica A Kahn; Susan L Rosenthal; Yan Jin; Bin Huang; Azadeh Namakydoust; Gregory D Zimet Journal: Obstet Gynecol Date: 2008-05 Impact factor: 7.661
Authors: Jessica Hughes; Joan R Cates; Nicole Liddon; Jennifer S Smith; Sami L Gottlieb; Noel T Brewer Journal: Cancer Epidemiol Biomarkers Prev Date: 2009-02-03 Impact factor: 4.254
Authors: Serena A Rodriguez; Lara S Savas; Elizabeth Baumler; Alan G Nyitray; Patricia Dolan Mullen; Sally W Vernon; Maria E Fernandez Journal: Vaccine Date: 2018-07-03 Impact factor: 3.641
Authors: Peter G Szilagyi; Christina S Albertin; Dennis Gurfinkel; Alison W Saville; Sitaram Vangala; John D Rice; Laura Helmkamp; Gregory D Zimet; Rebecca Valderrama; Abigail Breck; Cynthia M Rand; Sharon G Humiston; Allison Kempe Journal: Vaccine Date: 2020-08-02 Impact factor: 4.169
Authors: Emiko Y Petrosky; Susan Hariri; Lauri E Markowitz; Gitika Panicker; Elizabeth R Unger; Eileen F Dunne Journal: Int J Infect Dis Date: 2015-01-14 Impact factor: 3.623
Authors: Carlos R Oliveira; Lital Avni-Singer; Geovanna Badaro; Erin L Sullivan; Sangini S Sheth; Eugene D Shapiro; Linda M Niccolai Journal: JMIR Med Inform Date: 2020-01-22