Dataset Information

Mining Twitter to assess the determinants of health behavior toward human papillomavirus vaccination in the United States.

ABSTRACT: OBJECTIVES:The study sought to test the feasibility of using Twitter data to assess determinants of consumers' health behavior toward human papillomavirus (HPV) vaccination informed by the Integrated Behavior Model (IBM). MATERIALS AND METHODS:We used 3 Twitter datasets spanning from 2014 to 2018. We preprocessed and geocoded the tweets, and then built a rule-based model that classified each tweet into either promotional information or consumers' discussions. We applied topic modeling to discover major themes and subsequently explored the associations between the topics learned from consumers' discussions and the responses of HPV-related questions in the Health Information National Trends Survey (HINTS). RESULTS:We collected 2 846 495 tweets and analyzed 335 681 geocoded tweets. Through topic modeling, we identified 122 high-quality topics. The most discussed consumer topic is "cervical cancer screening"; while in promotional tweets, the most popular topic is to increase awareness of "HPV causes cancer." A total of 87 of the 122 topics are correlated between promotional information and consumers' discussions. Guided by IBM, we examined the alignment between our Twitter findings and the results obtained from HINTS. Thirty-five topics can be mapped to HINTS questions by keywords, 112 topics can be mapped to IBM constructs, and 45 topics have statistically significant correlations with HINTS responses in terms of geographic distributions. CONCLUSIONS:Mining Twitter to assess consumers' health behaviors can not only obtain results comparable to surveys, but also yield additional insights via a theory-driven approach. Limitations exist; nevertheless, these encouraging results impel us to develop innovative ways of leveraging social media in the changing health communication landscape.

SUBMITTER: Zhang H

PROVIDER: S-EPMC7025367 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mining Twitter to assess the determinants of health behavior toward human papillomavirus vaccination in the United States.

Zhang Hansi H Wheldon Christopher C Dunn Adam G AG Tao Cui C Huo Jinhai J Zhang Rui R Prosperi Mattia M Guo Yi Y Bian Jiang J

Journal of the American Medical Informatics Association : JAMIA 20200201 2

<h4>Objectives</h4>The study sought to test the feasibility of using Twitter data to assess determinants of consumers' health behavior toward human papillomavirus (HPV) vaccination informed by the Integrated Behavior Model (IBM).<h4>Materials and methods</h4>We used 3 Twitter datasets spanning from 2014 to 2018. We preprocessed and geocoded the tweets, and then built a rule-based model that classified each tweet into either promotional information or consumers' discussions. We applied topic mode ...[more]

PMID: 31711186

Similar Datasets

Project description:BackgroundAs one of the serious public health issues, vaccination refusal has been attracting more and more attention, especially for newly approved human papillomavirus (HPV) vaccines. Understanding public opinion towards HPV vaccines, especially concerns on social media, is of significant importance for HPV vaccination promotion.MethodsIn this study, we leveraged a hierarchical machine learning based sentiment analysis system to extract public opinions towards HPV vaccines from Twitter. English tweets containing HPV vaccines-related keywords were collected from November 2, 2015 to March 28, 2016. Manual annotation was done to evaluate the performance of the system on the unannotated tweets corpus. Followed time series analysis was applied to this corpus to track the trends of machine-deduced sentiments and their associations with different days of the week.ResultsThe evaluation of the unannotated tweets corpus showed that the micro-averaging F scores have reached 0.786. The learning system deduced the sentiment labels for 184,214 tweets in the collected unannotated tweets corpus. Time series analysis identified a coincidence between mainstream outcome and Twitter contents. A weak trend was found for "Negative" tweets that decreased firstly and began to increase later; an opposite trend was identified for "Positive" tweets. Tweets that contain the worries on efficacy for HPV vaccines showed a relative significant decreasing trend. Strong associations were found between some sentiments ("Positive", "Negative", "Negative-Safety" and "Negative-Others") with different days of the week.ConclusionsOur efforts on sentiment analysis for newly approved HPV vaccines provide us an automatic and instant way to extract public opinion and understand the concerns on Twitter. Our approaches can provide a feedback to public health professionals to monitor online public response, examine the effectiveness of their HPV vaccination promotion strategies and adjust their promotion plans.

Project description:BackgroundRacial and ethnic minorities are disproportionately affected by human papillomavirus (HPV)-related cancer, many of which could have been prevented with vaccination. Yet, the initiation and completion rates of HPV vaccination remain low among these populations. Given the importance of social media platforms for health communication, we examined US-based HPV images on Twitter. We explored inconsistencies between the demographics represented in HPV images and the populations that experience the greatest burden of HPV-related disease.ObjectiveThe objective of our study was to observe whether HPV images on Twitter reflect the actual burden of disease by select demographics and determine to what extent Twitter accounts utilized images that reflect the burden of disease in their health communication messages.MethodsWe identified 456 image tweets about HPV that contained faces posted by US users between November 11, 2014 and August 8, 2016. We identified images containing at least one human face and utilized Face++ software to automatically extract the gender, age, and race of each face. We manually annotated the source accounts of these tweets into 3 types as follows: government (38/298, 12.8%), organizations (161/298, 54.0%), and individual (99/298, 33.2%) and topics (news, health, and other) to examine how images varied by message source.ResultsFindings reflected the racial demographics of the US population but not the disease burden (795/1219, 65.22% white faces; 140/1219, 11.48% black faces; 71/1219, 5.82% Asian faces; and 213/1219, 17.47% racially ambiguous faces). Gender disparities were evident in the image faces; 71.70% (874/1219) represented female faces, whereas only 27.89% (340/1219) represented male faces. Among the 11-26 years age group recommended to receive HPV vaccine, HPV images contained more female-only faces (214/616, 34.3%) than males (37/616, 6.0%); the remainder of images included both male and female faces (365/616, 59.3%). Gender and racial disparities were present across different image sources. Faces from government sources were more likely to depict females (n=44) compared with males (n=16). Of male faces, 80% (12/15) of youth and 100% (1/1) of adults were white. News organization sources depicted high proportions of white faces (28/38, 97% of female youth and 12/12, 100% of adult males). Face++ identified fewer faces compared with manual annotation because of limitations with detecting multiple, small, or blurry faces. Nonetheless, Face++ achieved a high degree of accuracy with respect to gender, race, and age compared with manual annotation.ConclusionsThis study reveals critical differences between the demographics reflected in HPV images and the actual burden of disease. Racial minorities are less likely to appear in HPV images despite higher rates of HPV incidence. Health communication efforts need to represent populations at risk better if we seek to reduce disparities in HPV infection.

Project description:BackgroundLimited data are available describing human papillomavirus (HPV) genotype distributions in cervical cancer in the United States. Such studies are needed to predict how HPV vaccination and HPV-based screening will influence cervical cancer prevention.MethodsWe used the New Mexico Surveillance, Epidemiology, and End Results Registry to ascertain cases of in situ (n = 1213) and invasive (n = 808) cervical cancer diagnosed during 1985-1999 and 1980-1999, respectively, in the state of New Mexico. HPV genotyping was performed using two polymerase chain reaction-based methods on paraffin-embedded tissues from in situ and invasive cancers and on cervical Papanicolaou test specimen from control subjects (ie, women aged 18-40 years attending clinics for routine cervical screening [n = 4007]). Relative risks for cervical cancer were estimated, and factors associated with age at cancer diagnosis and the prevalence of HPV genotypes in cancers were examined.ResultsThe most common HPV genotypes detected in invasive cancers were HPV type 16 (HPV16, 53.2%), HPV18 (13.1%), and HPV45 (6.1%) and those in in situ cancers were HPV16 (56.3%), HPV31 (12.6%), and HPV33 (8.0%). Invasive cancer case subjects who were positive for HPV16 or 18 were diagnosed at younger ages than those who were positive for other carcinogenic HPV genotypes (mean age at diagnosis: 48.1 [95% confidence interval {CI} = 46.6 to 49.6 years], 45.9 [95% CI = 42.9 to 49.0 years], and 52.3 years [95% CI = 50.0 to 54.6 years], respectively). The proportion of HPV16-positive in situ and invasive cancers, but not of HPV18-positive cancers, declined with more recent calendar year of diagnosis, whereas the proportion positive for carcinogenic HPV genotypes other than HPV18 increased.ConclusionsHPV16 and 18 caused the majority of invasive cervical cancer in this population sample of US women, but the proportion attributable to HPV16 declined over the last 20 years. The age at diagnosis of HPV16- and HPV18-related cancers was 5 years earlier than that of cancers caused by carcinogenic HPV genotypes other than HPV16 and 18, suggesting that the age at initiation of cervical screening could be delayed in HPV-vaccinated populations.

Project description:This study is the first to examine associations between several area-based socioeconomic factors and human papillomavirus (HPV) vaccine uptake among boys in the United States (U.S.).Data from the 2012-2013 National Immunization Survey-Teen restricted-use data were analyzed to examine associations of HPV vaccination initiation (receipt of ?1 dose) and series completion (receipt of three doses) among boys aged 13-17 years (N = 19,518) with several individual-level and ZIP Code Tabulation Area (ZCTA) census measures. Multivariable logistic regression was used to estimate the odds of HPV vaccination initiation and series completion separately.In 2012-2013 approximately 27.9% (95% CI 26.6%-29.2%) of boys initiated and 10.38% (95% CI 9.48%-11.29%) completed the HPV vaccine series. Area-based poverty was not statistically significantly associated with HPV vaccination initiation. It was, however, associated with series completion, with boys living in high-poverty areas (?20% of residents living below poverty) having higher odds of completing the series (AOR 1.22, 95% CI 1.01-1.48) than boys in low-poverty areas (0-4.99%). Interactions between race/ethnicity and ZIP code-level poverty indicated that Hispanic boys living in high-poverty areas had a statistically significantly higher odds of HPV vaccine initiation (AOR 1.43, 95% CI 1.03-1.97) and series completion (AOR 1.56, 95% CI 1.05-2.32) than Hispanic boys in low-poverty areas. Non-Hispanic Black boys in high poverty areas had higher odds of initiation (AOR 2.23, 95% CI 1.33-3.75) and completion (AOR 2.61, 95% CI 1.06-6.44) than non-Hispanic Black boys in low-poverty areas. Rural/urban residence and population density were also significant factors, with boys from urban or densely populated areas having higher odds of initiation and completion compared to boys living in non-urban, less densely populated areas.Higher HPV vaccination coverage in urban areas and among racial/ethnic minorities in areas with high poverty may be attributable to factors such as vaccine acceptance, health-care practices, and their access to HPV vaccines through the Vaccines for Children Program, which provides free vaccines to uninsured and under-insured children. Given the low HPV vaccination rates among boys in the U.S., these results provide important evidence to inform public health interventions to increase HPV vaccination.

Dataset Information

Mining Twitter to assess the determinants of health behavior toward human papillomavirus vaccination in the United States.

Publications

Mining Twitter to assess the determinants of health behavior toward human papillomavirus vaccination in the United States.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets