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Parents of children with autism spectrum disorder (ASD) may be at greater risk for developing antivaccine beliefs that lead to vaccine delays and/or refusals for their children. We investigated current parental vaccine hesitancy, parents’ beliefs about causes of children’s developmental delays, and children’s vaccination histories among parents of children with ASD or non-ASD developmental delays. Data were analyzed from 89/511 parents (17.4%) who completed the Parent Attitudes About Childhood Vaccines questionnaire and the Revised Illness Perception Questionnaire; 46.1% had childhood vaccination records available. Overall, 21/89 (23.6%, 95% confidence interval [CI]: 15.0-34.0) of parents were vaccine hesitant (ASD n = 19/21 [90.5%], non-ASD n = 2/21 [9.5%]). Parents of children with ASD were significantly more likely to agree with “toxins in vaccines” as a cause of their child’s developmental delays (28.4% vs 5.0%, P = .034). The odds of being vaccine hesitant were 11.9 times (95% CI 2.9-48.0) greater among parents who agreed versus disagreed that toxins in vaccines caused their children’s developmental delays. Rates of prior vaccine receipt did not differ between hesitant and nonhesitant groups.

Vaccine hesitancy may be more common among parents of children with autism spectrum disorder (ASD). We examined factors associated with ASD-specific vaccine hesitancy among caregivers of children with ASD who participated in the SPARK study (Simons Foundation Powering Autism Research for Knowledge). 225 participants completed an online survey containing the Parent Attitudes About Childhood Vaccines (PACV) questionnaire (measure of vaccine hesitancy) and the Illness Perception Questionnaire revised for parents of children with ASD (IPQ-R-ASD; measure of parents' views about ASD). 65 participants (28.8%) were vaccine hesitant (PACV score ≥ 50); children of vaccine-hesitant parents (VHPs) were less likely to be first born (n = 27, 41.5%), had greater ASD-symptom severity (mean Social Communication Questionnaire score = 23.9, SD = 6.9), and were more likely to have experienced developmental regression (n = 27, 50.9%) or plateau (n = 37, 69.8%). Compared to non-hesitant parents, VHPs significantly more often endorsed accident/injury, deterioration of the child's immune system, diet, environmental pollution, general stress, parents' negative views, parents' behaviors/decisions, parents' emotional state, and vaccines as causes for ASD. VHPs also had higher scores on the Personal Control, Treatment Control, Illness Coherence, and Emotional Representations subscales of the IPQ-R than did non-hesitant parents. In the final model, ASD-related vaccine hesitancy was significantly associated with higher scores on the Emotional Representations subscale (OR = 1.13, p = 0.10), agreement with deterioration of the child's immunity as a cause of ASD (OR = 12.47, p < 0.001), the child not having achieved fluent speech (OR = 2.67, p = 0.17), and the child experiencing a developmental plateau (OR = 3.89, p = 0.002). Findings suggest that a combination of child functioning and developmental history, as well as parents' negative views about and their sense of control over ASD, influence vaccine hesitancy among parents of children with ASD.

Fears persist despite compelling evidence refuting associations between vaccines and autism spectrum disorder (ASD). We compared vaccine hesitancy (VH) and beliefs about illness causes among parents of children in four groups: ASD, non-ASD developmental disorders, rheumatologic conditions, and the general pediatric population. VH was 19.9% overall; parents of children with ASD reported highest VH rates (29.5%) and more frequently attributed ASD to toxins in vaccines (28.9% vs. 15.7%, p=0.004). The odds of VH were increased among parents who attributed their child's condition to diet or eating habits (aOR 4.2; 95% CI: 1.6, 11.2) and toxins found in vaccines (aOR 20, 95% CI: 7.1, 55.9). Parents who attributed the condition to chance or bad luck were less likely to be vaccine hesitant (aOR 0.1; 95% CI: 0.03, 0.5).

Our aim was to characterize health beliefs about the human papillomavirus (HPV) vaccine in a large set of Twitter posts (tweets). We collected a Twitter data set related to the HPV vaccine from 1 January 2014, to 31 December 2017. We proposed a deep-learning-based framework to mine health beliefs on the HPV vaccine from Twitter. Deep learning achieved high performance in terms of sensitivity, specificity, and accuracy. A retrospective analysis of health beliefs found that HPV vaccine beliefs may be evolving on Twitter.

Background The 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. Objective The 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. Methods Reddit 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. Results A 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%). Conclusions ML-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.

Narratives can have a powerful impact on our health-related beliefs, attitudes, and behaviors. The human papillomavirus (HPV) vaccine can protect against human papillomavirus that leads to different types of cancers. However, HPV vaccination rates are low. This study explored the effectiveness of a narrative-based interactive game about the HPV vaccines as a method to communicate knowledge and perhaps create behavioral outcomes. We developed a serious storytelling game called Vaccination Vacation inspired by personal narratives of individuals who were impacted by the HPV. We tested the game using a randomized control study of 99 adult participants and compared the HPV knowledge and vaccine beliefs of the Gamer Group (who played the game, n = 44) and the Reader group (who read a vaccine information sheet, n = 55). We also evaluated the usability of the game. In addition to high usability, the interactive game slightly impacted the beliefs about the HPV vaccine over standard delivery of vaccine information, especially among those who never received the HPV vaccine. We also observed some gender-based differences in perception towards usability and the likelihood of frequently playing the game. A narrative-based game could bring positive changes to players’ HPV-related health beliefs. The combination of more comprehensive HPV vaccine information with the narratives may produce a larger impact. Narrative-based games can be effectively used in other vaccine education interventions and warrant future research.

Key Points Question Can public perceptions of the human papillomavirus (HPV) vaccine be accessed from the perspective of behavior change theories by mining social media data with machine learning algorithms? Findings This cohort study included 1 431 463 English-language posts about the HPV vaccine from 486 116 unique usernames from a social media platform. An increase in HPV vaccine–related discussions was found, and the results suggest temporal and geographic variations in public perceptions of the HPV vaccine. Meaning The findings of this study suggest that social media and machine learning algorithms can serve as a complementary approach to inform public health surveillance and understanding and help to design targeted educational and communication programs that increase HPV vaccine acceptance., This cohort study develops and validates deep learning models to understand public perceptions of human papillomavirus (HPV) vaccines from the perspective of behavior change theories using data from social media., Importance Human papillomavirus (HPV) vaccine hesitancy or refusal is common among parents of adolescents. An understanding of public perceptions from the perspective of behavior change theories can facilitate effective and targeted vaccine promotion strategies. Objective To develop and validate deep learning models for understanding public perceptions of HPV vaccines from the perspective of behavior change theories using data from social media. Design, Setting, and Participants This retrospective cohort study, conducted from April to August 2019, included longitudinal and geographic analyses of public perceptions regarding HPV vaccines, using sampled HPV vaccine–related Twitter discussions collected from January 2014 to October 2018. Main Outcomes and Measures The prevalence of social media discussions related to the construct of health belief model (HBM) and theory of planned behavior (TPB), categorized by deep learning algorithms. Locally estimated scatterplot smoothing (LOESS) revealed trends of constructs. Social media users’ US state–level home location information was extracted from their profiles, and geographic analyses were performed to identify the clustering of public perceptions of the HPV vaccine. Results A total of 1 431 463 English-language posts from 486 116 unique usernames were collected. Deep learning algorithms achieved F-1 scores ranging from 0.6805 (95% CI, 0.6516-0.7094) to 0.9421 (95% CI, 0.9380-0.9462) in mapping discussions to the constructs of behavior change theories. LOESS revealed trends in constructs; for example, prevalence of perceived barriers, a construct of HBM, deceased from its apex in July 2015 (56.2%) to its lowest prevalence in October 2018 (28.4%; difference, 27.8%; P

Background Social media platforms such as YouTube are hotbeds for the spread of misinformation about vaccines. Objective The aim of this study was to explore how individuals are exposed to antivaccine misinformation on YouTube based on whether they start their viewing from a keyword-based search or from antivaccine seed videos. Methods Four networks of videos based on YouTube recommendations were collected in November 2019. Two search networks were created from provaccine and antivaccine keywords to resemble goal-oriented browsing. Two seed networks were constructed from conspiracy and antivaccine expert seed videos to resemble direct navigation. Video contents and network structures were analyzed using the network exposure model. Results Viewers are more likely to encounter antivaccine videos through direct navigation starting from an antivaccine video than through goal-oriented browsing. In the two seed networks, provaccine videos, antivaccine videos, and videos containing health misinformation were all found to be more likely to lead to more antivaccine videos. Conclusions YouTube has boosted the search rankings of provaccine videos to combat the influence of antivaccine information. However, when viewers are directed to antivaccine videos on YouTube from another site, the recommendation algorithm is still likely to expose them to additional antivaccine information.

This study demonstrates the use of distributed vector representations and Pathfinder Network Scaling (PFNETS) to represent online vaccine content created by health experts and by laypeople. By analyzing a target audience’s conceptualization of a topic, domain experts can develop targeted interventions to improve the basic health knowledge of consumers. The underlying assumption is that the content created by different groups reflects the mental organization of their knowledge. Applying automated text analysis to this content may elucidate differences between the knowledge structures of laypeople (heath consumers) and professionals (health experts). This paper utilizes vaccine information generated by laypeople and health experts to investigate the utility of this approach. We used an established technique from cognitive psychology, Pathfinder Network Scaling to infer the structure of the associational networks between concepts learned from online content using methods of distributional semantics. In doing so, we extend the original application of PFNETS to infer knowledge structures from individual participants, to infer the prevailing knowledge structures within communities of content authors. The resulting graphs reveal opportunities for public health and vaccination education experts to improve communication and intervention efforts directed towards health consumers. Our efforts demonstrate the feasibility of using an automated procedure to examine the manifestation of conceptual models within large bodies of free text, revealing evidence of conflicting understanding of vaccine concepts among health consumers as compared with health experts. Additionally, this study provides insight into the differences between consumer and expert abstraction of domain knowledge, revealing vaccine-related knowledge gaps that suggest opportunities to improve provider-patient communication.

The human papillomavirus (HPV) vaccine protects adolescents and young adults from 9 high-risk HPV virus types that cause 90% of cervical and anal cancers and 70% of oropharyngeal cancers. This study extends our previous research analyzing online content concerning the HPV vaccination in social media platforms used by young adults, in which we used Pathfinder network scaling and methods of distributional semantics to characterize differences in knowledge organization reflected in consumer- and expert-generated online content. The current study extends this approach to evaluate HPV vaccine perceptions among young adults who populate Reddit, a major social media platform. We derived Pathfinder networks from estimates of semantic relatedness obtained by learning word embeddings from Reddit posts and compared these to networks derived from human expert estimation of the relationship between key concepts. Results revealed that users of Reddit, predominantly comprising young adults in the vaccine catch up age-group 18 through 26 years of age, perceived the HPV vaccine domain from a virus-framed perspective that could impact their lifestyle choices and that their awareness of the HPV vaccine for cancer prevention is also lacking. Further differences in knowledge structures were elucidated, with implications for future health communication initiatives.

Objective Our study retrospectively evaluated the implementation of an influenza vaccine best practice alert (BPA) in an electronic medical record within an integrated pediatric health care delivery system. Methods An influenza BPA was implemented throughout a large pediatric health care delivery system in Houston, TX, to improve vaccine uptake. Outcomes were measured retrospectively over 3 years of BPA implementation and compared with a control year prior to BPA implementation. Primary outcomes were influenza vaccine uptake, distribution of influenza vaccines ordered by week, proportion of BPA displays ignored, and missed vaccination opportunities. Results Influenza vaccine uptake declined from the pre-BPA year (47.2%; 95% confidence interval [CI]: 47.0, 47.4) to the last study year (45.1%; 95% CI: 44.9, 45.2). BPA displays were increasingly ignored by clinical staff throughout the study years from 59.6% in 2014–2015 to 72.5% in 2016–2017. For providers, BPA displays were ignored less frequently each year from 53.4% in 2014–2015 to 51.4% in 2017–2017. Within the primary care outpatient group, the proportion of missed vaccination opportunities in sick visits decreased from 86.8% during the pre-BPA year to 81.0, 79.8, and 82.7% during the subsequent study years 2014–2015, 2015–2016, and 2016–2017, respectively. Conclusion Implementation of a widespread influenza BPA in an integrated pediatric health care delivery system did not produce meaningful increases in influenza vaccine uptake. Differences between clinical staff and providers on BPA use warrant further investigation.

A contentious theory espoused by some parents is that regressive-onset of autism spectrum disorder (ASD) is triggered by vaccines. If this were true, then vaccine receipt should be higher in children with regressive-onset ASD compared with other patterns of onset. Parental report of rate of receipt for six vaccines (DPT/DTaP, HepB, Hib, polio, MMR, varicella) was examined in children with ASD (N=2755) who were categorized by pattern of ASD onset (early onset, plateau, delay-plus-regression, regression). All pairwise comparisons were significantly equivalent within a 10% margin for all vaccines except varicella, for which the delay-plus-regression group had lower rates of receipt (81%) than the early-onset (87%) and regression (87%) groups. Findings do not support a connection between regressive-onset ASD and vaccines in this cohort.

Objectives. Immunization forecasting systems evaluate patient vaccination histories and recommend the dates and vaccines that should be administered. We described the conceptualization, development, implementation, and distribution of a novel immunization forecaster, the Texas Children’s Hospital (TCH) Forecaster. Methods. In 2007, TCH convened an internal expert team that included a pediatrician, immunization nurse, software engineer, and immunization subject matter experts to develop the TCH Forecaster. Our team developed the design of the model, wrote the software, populated the Excel tables, integrated the software, and tested the Forecaster. We created a table of rules that contained each vaccine’s recommendations, minimum ages and intervals, and contraindications, which served as the basis for the TCH Forecaster. Results. We created 15 vaccine tables that incorporated 79 unique dose states and 84 vaccine types to operationalize the entire United States recommended immunization schedule. The TCH Forecaster was implemented throughout the TCH system, the Indian Health Service, and the Virginia Department of Health. The TCH Forecast Tester is currently being used nationally. Conclusions. Immunization forecasting systems might positively affect adherence to vaccine recommendations. Efforts to support health care provider utilization of immunization forecasting systems and to evaluate their impact on patient care are needed.

Objective Nonmedical exemptions continue to rise because of increasing proportions of vaccine-hesitant parents. The proportion of expectant parents who are vaccine-hesitant is currently unknown. We assessed the prevalence of vaccine hesitancy among expectant parents receiving care at an obstetrics clinic in Houston, Texas. Methods We conducted a cross-sectional survey of expectant parents between 12 and 31 weeks gestation who received care at Texas Children's Pavilion for Women between July 2014 and September 2015. Using convenience sampling, participants completed a questionnaire that included questions on demographic items, self-assessed pregnancy risk, receipt of annual influenza vaccine, and the 15-item Parents Attitudes About Childhood Vaccines survey, a validated tool to identify vaccine-hesitant parents. We used multivariable logistic regression to determine the association of demographic characteristics, pregnancy risk, and influenza vaccine receipt with vaccine hesitancy after controlling for variables significant in univariable analyses. Results Six hundred ten expectant mothers and 38 expectant fathers completed the Parents Attitudes About Childhood Vaccines survey. Overall, 50 of 610 expectant mothers (8.2%; 95% confidence interval [CI], 6.1%–10.7%) were vaccine-hesitant. Expectant mothers were primarily non-Hispanic white, 30 years old or older, and married. The odds of being vaccine-hesitant were 2.2 times greater (95% CI, 1.2–4.1) among expectant mothers with a college level of education or less compared with those with more than a 4-year degree. The odds of being vaccine-hesitant were 7.4 times greater (95% CI, 3.9-14.0) among expectant mothers who do not receive an annual influenza vaccine compared with those who do. Conclusions Our findings suggest the need to identify and address vaccine hesitancy among expectant parents before birth.

Objective To construct a comprehensive vaccine information ontology that can support personal health information applications using patient-consumer lexicon, and lead to outcomes that can improve patient education. Methods The authors composed the Vaccine Information Statement Ontology (VISO) using the web ontology language (OWL). We started with 6 Vaccine Information Statement (VIS) documents collected from the Centers for Disease Control and Prevention (CDC) website. Important and relevant selections from the documents were recorded, and knowledge triples were derived. Based on the collection of knowledge triples, the meta-level formalization of the vaccine information domain was developed. Relevant instances and their relationships were created to represent vaccine domain knowledge Results The initial iteration of the VISO was realized, based on the 6 Vaccine Information Statements and coded into OWL2 with Protégé. The ontology consisted of 132 concepts (classes and subclasses) with 33 types of relationships between the concepts. The total number of instances from classes totaled at 460, along with 429 knowledge triples in total. Semiotic-based metric scoring was applied to evaluate quality of the ontology.

It is essential that the medical and public health communities respond to vaccine concerns and make every effort to maintain and improve vaccination coverage rates. As increasing numbers of providers encounter parents with vaccine concerns, they are faced with the challenge of how to best communicate with such parents while caring for their children. One method that has been suggested for organizing conversations with vaccine-concerned parents is the C.A.S.E approach.

Parents who delay or refuse vaccination tend to share common characteristics such as maternal age over 30, white race, higher income levels, and higher educational levels. These parents are also more likely to report distrust in their medical provider and more likely to seek care from a complementary and alternative medical (CAM) professional. Parents who delayed or refused vaccines are significantly less likely to believe vaccines are safe and effective. In addition, they are more likely to report misconceptions about vaccines such as beliefs about dangerous side effects, overload to the immune system, excessive number of doses, and causation of developmental disorders. In order to appropriately tailor vaccine education, it is important to understand the characteristics and beliefs of parents with strong vaccine concerns.

Vaccine concerns date back to the eighteenth century during a time of smallpox epidemics in colonial America. Despite increased survival rates among those who were inoculated by variolation, opposition to this procedure was strong. Modern day vaccine fears were fueled by the Cutter Incident when incompletely inactivated polio vaccine was inadvertently administered to children resulting in significant morbidity and mortality. This incident was followed in the 1980s by the release of “DPT: Vaccine Roulette,” a television documentary that engendered fears about the DTP vaccine and galvanized the formation of a well-known anti-vaccine group, National Vaccine Information Center. Parental vaccine safety concerns were fueled by this group and further strengthened with the publication of a controversial paper by Dr. Andrew Wakefield in which he suggested that the MMR vaccine was linked to autism. Despite the retraction of this paper and the discovery that many of its findings were fraudulent, others joined the anti-vaccine movement, including actress Jenny McCarthy and Dr. Bob Sears. These outspoken individuals have influenced many parents by suggesting that parents choose non-scientifically based alternative vaccination schedules that delay or omit vaccines.

Increasing numbers of parents demonstrate high levels of vaccine concerns. Concurrently, increasing numbers of states allow personal belief exemptions for school required vaccinations. Unvaccinated individuals and communities with high rates of nonmedical vaccine exemptions are at greater risk for vaccine-preventable diseases. Rates of nonmedical vaccine exemptions have continually increased during the last two decades resulting in outbreaks of vaccine-preventable diseases such as measles and pertussis.

In this paper, we explore the benefits of storytelling in health communication and, in particular, immunization education. During the mid-20th century polio epidemic, both personal stories and scientific information abounded in the media. However, as rates of vaccine-preventable diseases declined, narratives about the dangers of such diseases faded as did the public fear of them. Meanwhile, anti-vaccine advocates flooded the media and Internet with stories of injured children and tied those injuries, such as autism, to vaccines. Medical experts often counter anti-vaccine concerns with scientific information which can fail to persuade parents. Furthermore, evidence suggests that many people misunderstand quantitative information resulting in a misinterpretation of risk. Compared to scientific information, stories relate life lessons and values. They are effective because they are memorable and relatable. Evidence also suggests that storytelling can effectively improve health knowledge and behaviors. Inspired by In Harm's Way--True Stories of Uninsured Texas Children by the Children's Defense Fund and Faces of Influenza by the American Lung Association, we published Vaccine-Preventable Disease: The Forgotten Story, a collection of photographs and personal stories of families affected by vaccine-preventable diseases. We have found that the stories included in our booklet capture all the benefits of storytelling. Given the many benefits of storytelling, providers should strive to include stories along with medical facts in their daily practice.