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OBJECTIVE: Low birthweight is one of the main causes of poor health outcomes among newborns, with Black women having a disproportionately high prevalence. A digital intervention targeted Black women in Orange County, Florida with information on positive pregnancy-related knowledge and attitudes related to low birthweight. This paper reports on campaign methods for the first 2.5 years of implementation. METHODS: Campaign content was tailored toward Black women, around a reproductive empowerment lens. Content focused on emphasizing healthy pregnancy-related behaviors and creating positive representations of Black women throughout the various stages of pregnancy through both static images and a web series. Digital metrics gauged campaign engagement. Three cross-sectional online surveys conducted in the intervention county examined Black women's pregnancy-related knowledge, attitudes, and behaviors. RESULTS: After two years of campaign implementation, social media accounts showed 1784 followers. While Facebook showed more average monthly impressions, Instagram showed more average monthly engagements. Survey results showed some increases in knowledge about prenatal care, weight gain, exercise, and the health impacts of low birthweight. CONCLUSIONS FOR PRACTICE: This study highlights the potential for a culturally-appropriate digital intervention to promote positive pregnancy outcomes among at-risk women. Digital interventions offer a potential way to achieve positive pregnancy-related behavior changes on a larger scale. This may be particularly important given that the COVID-19 pandemic may be changing the ways that pregnant women access information. Studies should examine the impact and feasibility of using culturally-appropriate digital interventions that directly address Black women and their specific experiences during pregnancy.
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Negro ou Afro-Americano/educação , Negro ou Afro-Americano/psicologia , Promoção da Saúde/métodos , Recém-Nascido de Baixo Peso , Gestantes/educação , Cuidado Pré-Natal/métodos , Mídias Sociais , Adulto , Estudos Transversais , Estudos de Viabilidade , Feminino , Florida/epidemiologia , Humanos , GravidezRESUMO
OBJECTIVES: To report on vaccine opposition and misinformation promoted on Twitter, highlighting Twitter accounts that drive conversation. METHODS: We used supervised machine learning to code all Twitter posts. We first identified codes and themes manually by using a grounded theoretical approach and then applied them to the full data set algorithmically. We identified the top 50 authors month-over-month to determine influential sources of information related to vaccine opposition. RESULTS: The data collection period was June 1 to December 1, 2019, resulting in 356 594 mentions of vaccine opposition. A total of 129 Twitter authors met the qualification of a top author in at least 1 month. Top authors were responsible for 59.5% of vaccine-opposition messages. We identified 10 conversation themes. Themes were similarly distributed across top authors and all other authors mentioning vaccine opposition. Top authors appeared to be highly coordinated in their promotion of misinformation within themes. CONCLUSIONS: Public health has struggled to respond to vaccine misinformation. Results indicate that sources of vaccine misinformation are not as heterogeneous or distributed as it may first appear given the volume of messages. There are identifiable upstream sources of misinformation, which may aid in countermessaging and public health surveillance.
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Objectives. To report on vaccine opposition and misinformation promoted on Twitter, highlighting Twitter accounts that drive conversation.Methods. We used supervised machine learning to code all Twitter posts. We first identified codes and themes manually by using a grounded theoretical approach and then applied them to the full data set algorithmically. We identified the top 50 authors month-over-month to determine influential sources of information related to vaccine opposition.Results. The data collection period was June 1 to December 1, 2019, resulting in 356 594 mentions of vaccine opposition. A total of 129 Twitter authors met the qualification of a top author in at least 1 month. Top authors were responsible for 59.5% of vaccine-opposition messages. We identified 10 conversation themes. Themes were similarly distributed across top authors and all other authors mentioning vaccine opposition. Top authors appeared to be highly coordinated in their promotion of misinformation within themes.Conclusions. Public health has struggled to respond to vaccine misinformation. Results indicate that sources of vaccine misinformation are not as heterogeneous or distributed as it may first appear given the volume of messages. There are identifiable upstream sources of misinformation, which may aid in countermessaging and public health surveillance.
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Movimento contra Vacinação , Comunicação , Mídias Sociais/estatística & dados numéricos , Vacinas , Humanos , Saúde PúblicaRESUMO
Obesity is a leading cause of premature death in the U.S., in part due to consumption of sugar sweetened beverages (SSBs). In New Jersey, African Americans, Hispanics, and those of low income have the highest rates of SSB consumption. This study evaluates the impact of NJ Sugarfreed, a campaign designed to reduce sugar-sweetened beverage (SSB) consumption across New Jersey. From 12/1/17-9/30/18, we used a collective impact model to create targeted statewide campaigns that reduce SSB consumption among New Jersey residents, with an emphasis on African American and Hispanic low-income mothers/caregivers who are often gatekeepers to children's SSB consumption. Passaic County, New Jersey received a higher dose intervention. Messages were disseminated through social media, partner organizations, and community partnerships. Campaign impact was examined through evaluation surveys and analysis of beverage sales. Baseline and follow-up surveys (n = 800 baseline; n = 782 follow-up) showed positive trends toward decreased soda consumption and increased knowledge about SSBs. Passaic respondents showed a 5% decrease in those who consume 1+ soda per day, compared to a 1% decrease among New Jersey respondents. Analysis of overall SSB beverage sales showed the most pronounced decreases in Passaic (7% decrease) compared to New Jersey (6%). By drawing upon best practices in message development and the use of various platforms for dissemination, combined with community-based participation, we have provided more evidence to support the use of a collective impact model as a way of reducing unhealthy behaviors that impact health disparities.
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Bebidas Adoçadas com Açúcar , Bebidas , Bebidas Gaseificadas , Criança , Humanos , New Jersey , Inquéritos e QuestionáriosRESUMO
OBJECTIVE(S): Moderate alcohol consumption has been found to be associated with lower risk of coronary heart disease and myocardial infarction, which share similar risk factors and pathophysiology with chronic kidney disease (CKD). However, there is inconsistent evidence on the association between alcohol consumption and CKD. DESIGN AND METHODS: We conducted a prospective analysis of 12,692 participants aged 45-64 years from the Atherosclerosis Risk in Communities (ARIC) study. We categorized participants into 6 alcohol consumption categories: never drinkers, former drinkers, ≤1 drink per week, 2 to 7 drinks per week, 8 to 14 drinks per week, and ≥15 drinks per week based on food frequency questionnaire responses at visit 1 (1987-1989). Incident CKD was defined as estimated glomerular filtration rate <60 mL/minute/1.73 m2 accompanied by ≥25% estimated glomerular filtration rate decline, a kidney disease-related hospitalization or death or end-stage renal disease. RESULTS: During a median follow-up of 24 years, there were 3,664 cases of incident CKD. Current drinkers were more likely to be men, whites, and to have a higher income level and education level. After adjusting for total energy intake, age, sex, race-center, income, education level, health insurance, smoking, and physical activity, there was no significant association between being a former drinker and risk of incident CKD. Participants who drank ≤1 drink per week, 2 to 7 drinks per week, 8 to 14 drinks per week, and ≥15 drinks per week had, respectively, a 12% (hazard ratio [HR]: 0.88, 95% confidence interval [CI]: 0.79-0.97), 20% (HR: 0.80, 95% CI: 0.72-0.89), 29% (HR: 0.71, 95% CI: 0.62-0.83), and 23% (HR: 0.77, 95% CI: 0.65-0.91) lower risk of CKD compared with never drinkers. CONCLUSION(S): Consuming a low or moderate amount of alcohol may lower the risk of developing CKD. Therefore, moderate consumption of alcohol may not likely be harmful to the kidneys.
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Consumo de Bebidas Alcoólicas/epidemiologia , Insuficiência Renal Crônica/epidemiologia , Causalidade , Comorbidade , Escolaridade , Etnicidade , Feminino , Seguimentos , Taxa de Filtração Glomerular , Humanos , Renda/estatística & dados numéricos , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Fatores de Risco , Fatores Sexuais , Estados Unidos/epidemiologiaRESUMO
Seasonal influenza affects millions of people across the United States each year. African Americans and Hispanics have significantly lower vaccination rates, and large-scale campaigns have had difficulty increasing vaccination among these two groups. This study assessed the feasibility of delivering a flu vaccination promotion campaign using influencers, and examined shifts in social norms regarding flu vaccine acceptability after a social media micro influencer campaign. Influencers were asked to choose from vetted messages and create their own original content promoting flu vaccination, which was posted to their social media pages. Content was intentionally unbranded to ensure that it aligned with the look and feel of their pages. Cross-sectional pre- and post-campaign surveys were conducted within regions that received the campaign and control regions to examine potential campaign impact. Digital metrics assessed campaign exposure. Overall, 117 influencers generated 69,495 engagements. Results from the region that received the campaign showed significant increases in positive beliefs about the flu vaccine, and significant decreases in negative community attitudes toward the vaccine. This study suggests that flu campaigns using a ground-up rather than top-down approach can feasibly reach at-risk groups with lower vaccination rates, and shows the potentials of using an influencer-based model to communicate information about flu vaccination on a large scale.
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Conhecimentos, Atitudes e Prática em Saúde , Vacinas contra Influenza/imunologia , Influenza Humana/prevenção & controle , Otimismo , Mídias Sociais , Adolescente , Adulto , Estudos de Viabilidade , Feminino , Humanos , Programas de Imunização , Masculino , Pessoa de Meia-Idade , Normas Sociais , Inquéritos e Questionários , Estados Unidos , Adulto JovemRESUMO
[RESUMEN]. Objetivo. Informar sobre la oposición a las vacunas y la información errónea fomentadas en Twitter, destacando las cuentas de Twitter que dirigen estas conversaciones. Métodos. Utilizamos el aprendizaje automático supervisado para codificar todos los mensajes publicados en Twitter. En primer lugar, identificamos manualmente los códigos y los temas mediante un enfoque teórico fundamentado y, a continuación, los aplicamos a todo el conjunto de datos de forma algorítmica. Identificamos a los 50 autores más importantes un mes tras otro para determinar las fuentes influyentes de información relacionadas con la oposición a las vacunas. Resultados. El período de recopilación de datos fue del 1 de junio al 1 de diciembre del 2019, lo que dio lugar a 356 594 mensajes opuestos a las vacunas. Un total de 129 autores de Twitter reunieron los criterios de autor principal durante al menos un mes. Los autores principales fueron responsables del 59,5% de los mensajes opuestos a las vacunas y detectamos diez temas de conversación. Los temas se distribuyeron de forma similar entre los autores principales y todos los demás autores que declararon su oposición a las vacunas. Los autores principales parecían estar muy coordinados en su promoción de la información errónea sobre cada tema. Conclusiones. La salud pública se ha esforzado por responder a la información errónea sobre las vacunas. Los resultados indican que las fuentes de información errónea sobre las vacunas no son tan heterogéneas ni están tan distribuidas como podría parecer a primera vista, dado el volumen de mensajes. Existen fuentes identificables de información errónea, lo que puede ayudar a contrarrestar los mensajes y a fortalecer la vigilancia de la salud pública.
[ABSTRACT]. Objectives. To report on vaccine opposition and misinformation promoted on Twitter, highlighting Twitter accounts that drive conversation. Methods. We used supervised machine learning to code all Twitter posts. We first identified codes and themes manually by using a grounded theoretical approach and then applied them to the full data set algorithmically. We identified the top 50 authors month-over-month to determine influential sources of information related to vaccine opposition. Results. The data collection period was June 1 to December 1, 2019, resulting in 356 594 mentions of vaccine opposition. A total of 129 Twitter authors met the qualification of a top author in at least 1 month. Top authors were responsible for 59.5% of vaccine-opposition messages. We identified 10 conversation themes. Themes were similarly distributed across top authors and all other authors mentioning vaccine opposition. Top authors appeared to be highly coordinated in their promotion of misinformation within themes. Conclusions. Public health has struggled to respond to vaccine misinformation. Results indicate that sources of vaccine misinformation are not as heterogeneous or distributed as it may first appear given the volume of messages. There are identifiable upstream sources of misinformation, which may aid in countermessaging and public health surveillance.
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Gestão da Informação , Rede Social , Saúde Pública , Vacinas , Vacinação , Infodemia , InfodemiologiaRESUMO
RESUMEN Objetivo. Informar sobre la oposición a las vacunas y la información errónea fomentadas en Twitter, destacando las cuentas de Twitter que dirigen estas conversaciones. Métodos. Utilizamos el aprendizaje automático supervisado para codificar todos los mensajes publicados en Twitter. En primer lugar, identificamos manualmente los códigos y los temas mediante un enfoque teórico fundamentado y, a continuación, los aplicamos a todo el conjunto de datos de forma algorítmica. Identificamos a los 50 autores más importantes un mes tras otro para determinar las fuentes influyentes de información relacionadas con la oposición a las vacunas. Resultados. El período de recopilación de datos fue del 1 de junio al 1 de diciembre del 2019, lo que dio lugar a 356 594 mensajes opuestos a las vacunas. Un total de 129 autores de Twitter reunieron los criterios de autor principal durante al menos un mes. Los autores principales fueron responsables del 59,5% de los mensajes opuestos a las vacunas y detectamos diez temas de conversación. Los temas se distribuyeron de forma similar entre los autores principales y todos los demás autores que declararon su oposición a las vacunas. Los autores principales parecían estar muy coordinados en su promoción de la información errónea sobre cada tema. Conclusiones. La salud pública se ha esforzado por responder a la información errónea sobre las vacunas. Los resultados indican que las fuentes de información errónea sobre las vacunas no son tan heterogéneas ni están tan distribuidas como podría parecer a primera vista, dado el volumen de mensajes. Existen fuentes identificables de información errónea, lo que puede ayudar a contrarrestar los mensajes y a fortalecer la vigilancia de la salud pública.
ABSTRACT Objectives. To report on vaccine opposition and misinformation promoted on Twitter, highlighting Twitter accounts that drive conversation. Methods. We used supervised machine learning to code all Twitter posts. We first identified codes and themes manually by using a grounded theoretical approach and then applied them to the full data set algorithmically. We identified the top 50 authors month-over-month to determine influential sources of information related to vaccine opposition. Results. The data collection period was June 1 to December 1, 2019, resulting in 356 594 mentions of vaccine opposition. A total of 129 Twitter authors met the qualification of a top author in at least 1 month. Top authors were responsible for 59.5% of vaccine-opposition messages. We identified 10 conversation themes. Themes were similarly distributed across top authors and all other authors mentioning vaccine opposition. Top authors appeared to be highly coordinated in their promotion of misinformation within themes. Conclusions. Public health has struggled to respond to vaccine misinformation. Results indicate that sources of vaccine misinformation are not as heterogeneous or distributed as it may first appear given the volume of messages. There are identifiable upstream sources of misinformation, which may aid in countermessaging and public health surveillance.