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Abstract Background Despite the human papillomavirus (HPV) vaccine being a safe, effective cancer prevention method, its uptake is suboptimal in the United States (U.S.). Previous research has found a variety of intervention strategies (environmental and behavioral) to increase its uptake. The purpose of the study is to systematically review the literature on interventions that promote HPV vaccination from 2015 to 2020. Methods We updated a systematic review of interventions to promote HPV vaccine uptake globally. We ran keyword searches in six bibliographic databases. Target audience, design, level of intervention, components and outcomes were abstracted from the full-text articles in Excel databases. Results Of the 79 articles, most were conducted in the U.S. (72.2%) and in clinical (40.5%) or school settings (32.9%), and were directed at a single level (76.3%) of the socio-ecological model. Related to the intervention type, most were informational (n = 25, 31.6%) or patient-targeted decision support (n = 23, 29.1%). About 24% were multi-level interventions, with 16 (88.9%) combining two levels. Twenty-seven (33.8%) reported using theory in intervention development. Of those reporting HPV vaccine outcomes, post-intervention vaccine initiation ranged from 5% to 99.2%, while series completion ranged from 6.8% to 93.0%. Facilitators to implementation were the use of patient navigators and user-friendly resources, while barriers included costs, time to implement and difficulties of integrating interventions into the organizational workflow. Conclusions There is a strong need to expand the implementation of HPV-vaccine promotion interventions beyond education alone and at a single level of intervention. Development and evaluation of effective strategies and multi-level interventions may increase the uptake of the HPV vaccine among adolescents and young adults.

BackgroundThe rapid growth of social media as an information channel has made it possible to quickly spread inaccurate or false vaccine information, thus creating obstacles for vaccine promotion. ObjectiveThe aim of this study is to develop and evaluate an intelligent automated protocol for identifying and classifying human papillomavirus (HPV) vaccine misinformation on social media using machine learning (ML)–based methods. MethodsReddit posts (from 2007 to 2017, N=28,121) that contained keywords related to HPV vaccination were compiled. A random subset (2200/28,121, 7.82%) was manually labeled for misinformation and served as the gold standard corpus for evaluation. A total of 5 ML-based algorithms, including a support vector machine, logistic regression, extremely randomized trees, a convolutional neural network, and a recurrent neural network designed to identify vaccine misinformation, were evaluated for identification performance. Topic modeling was applied to identify the major categories associated with HPV vaccine misinformation. ResultsA convolutional neural network model achieved the highest area under the receiver operating characteristic curve of 0.7943. Of the 28,121 Reddit posts, 7207 (25.63%) were classified as vaccine misinformation, with discussions about general safety issues identified as the leading type of misinformed posts (2666/7207, 36.99%). ConclusionsML-based approaches are effective in the identification and classification of HPV vaccine misinformation on Reddit and may be generalizable to other social media platforms. ML-based methods may provide the capacity and utility to meet the challenge involved in intelligent automated monitoring and classification of public health misinformation on social media platforms. The timely identification of vaccine misinformation on the internet is the first step in misinformation correction and vaccine promotion.