28 research outputs found

    Recommending COVID-19 vaccination for adolescents in primary care

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    BACKGROUND: COVID-19 vaccines are available for adolescents in the United States, but many parents are hesitant to have their children vaccinated. The advice of primary care professionals strongly influences vaccine uptake. OBJECTIVE: We examined the willingness of primary care professionals (PCPs) to recommend COVID-19 vaccination for adolescents. METHODS: Participants were a national sample of 1,047 US adolescent primary care professionals. They participated in an online survey in early 2021, after a COVID-19 vaccine had been approved for adults but before approval for adolescents. Respondents included physicians (71%), advanced practice providers (17%), and nurses (12%). We identified correlates of willingness to recommend COVID-19 vaccination for adolescents using logistic regression. RESULTS: The majority (89%) of respondents were willing to recommend COVID-19 vaccination for adolescents, with advanced practice providers and nurses being less likely than paediatricians to recommend vaccination (84% vs. 94%, aOR 0.47, 95% CI 0.23-0.92). Respondents who had received at least one dose of a COVID-19 vaccine were more likely to recommend adolescent vaccination (92% vs. 69%, aOR 4.20, 95% CI 2.56-6.87) as were those with more years in practice (94% vs. 88%, aOR 2.93, 95% CI 1.79-4.99). Most respondents (96%) said they would need some measure of support in order to provide COVID-19 vaccination to adolescents, with vaccine safety and efficacy information being the most commonly cited need (80%). CONCLUSION: Adolescent primary care professionals were generally willing to recommend COVID-19 vaccination. However, most indicated a need for additional resources to be able to administer COVID-19 vaccines at their clinic

    Questions and concerns about HPV vaccine: A communication experiment

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    OBJECTIVES: We sought to identify effective responses to parents’ questions and concerns about human papillomavirus (HPV) vaccine. METHODS: In 2017–2018, we surveyed a national sample of 1196 US parents of children aged 9 to 17 years. We recorded brief videos of a pediatrician providing messages that addressed 7 HPV vaccination topics that commonly elicit questions or concerns (eg, recommended age). We randomly assigned parents to 1 of the message topics; parents then viewed 4 videos on that topic in random order and evaluated the messages. RESULTS: Parents were more confident in HPV vaccine when they were exposed to messages that addressed lack of knowledge about HPV vaccine (b = 0.13; P = .01), messages that included information about cancer prevention (b = 0.11; P < .001), messages that required a higher reading level (b = 0.02; P = .01), and messages that were longer (b = 0.03; P < .001). Parents were less confident in HPV vaccine when exposed to messages in which urgency was expressed (b = −0.06; P = .005). Analyses conducted by using HPV vaccine motivation as an outcome revealed the same pattern of findings. CONCLUSIONS: We provide research-tested messages that providers can use to address parents’ HPV vaccination questions and concerns about 7 common topics. Important principles for increasing message effectiveness are to include information on the benefits of vaccination (including cancer prevention) and avoid expressing urgency to vaccinate when addressing parents' questions or concerns. Additionally, providers may need to be prepared to have longer conversations with parents who express concerns about HPV vaccine, especially regarding safety and side effects

    Stochastic model reduction for robust dynamical characterization of structures with random parameters

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    International audienceIn this paper, we characterize random eigenspaces with a non-intrusive method based on the decoupling of random eigenvalues from their corresponding random eigenvectors. This method allows us to estimate the first statistical moments of the random eigenvalues of the system with a reduced number of deterministic finite element computations. The originality of this work is to adapt the method used to estimate each random eigenvalue depending on a global accuracy requirement. This allows us to ensure a minimal computational cost. The stochastic model of the structure is thus reduced by exploiting specific properties of random eigenvectors associated with the random eigenfrequencies being sought. An indicator with no additional computation cost is proposed to identify when the method needs to be enhanced. Finally, a simple three-beam frame and an industrial structure illustrate the proposed approach
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