The Association Between Dating Violence and Student Absenteeism Among a Representative Sample of U.S. High School Students: Findings From the 2019 Youth Risk Behavior Survey Survey.

Student absenteeism affects students' engagement in school and academic and professional success. While research documents a significant association between school bullying/fighting and student absenteeism due to fear of being at school or getting to school, little research has examined the association of adolescent dating violence (ADV) victimization with this type of absenteeism. This study examined the relationship between physical and/or sexual ADV victimization in the past year (dichotomized as yes or no), and number of days of student absenteeism due to feeling unsafe at school or on the way to school in the past month (dichotomized as any vs. none). We analyzed cross-sectional data from the 2019 Youth Risk Behavior Survey (YRBS), a nationally representative survey of U.S. high school students (n = 9507). We conducted crude and multivariate regression models for the total sample and stratified by sex to assess our hypothesized association of ADV victimization and absenteeism; sex, grade, race/ethnicity, and sexual identity were included as covariates in adjusted models. Findings demonstrate that students reporting past year ADV victimization had 3.69 times the odds of student absenteeism due to feeling unsafe, when compared to students who did not report ADV victimization (95% CI: 3.06-4.45, p < 0.001). Sex-stratified models reveal that this effect is significantly stronger for males than for females, as indicated by non-overlapping confidence intervals (male AOR: 5.67, 95% CI: 4.18-7.68; female AOR: 2.95, 95% CI: 2.32-3.74). The multivariate models also show that Black and Latinx compared with White students, and lesbian/gay/bisexual/unsure compared with heterosexual students, had higher odds of student absenteeism due to feeling unsafe. Findings indicate the need to address ADV victimization and student absenteeism with integrated and gender-tailored responses, and with consideration of greater vulnerabilities for queer students and students of color.

Breastfeeding Communication Strategies, Challenges and Opportunities in the Twitter-Verse: Perspectives of Influencers and Social Network Analysis.

Using social media is one important strategy to communicate research and public health guidelines to the scientific community and general public. Empirical evidence about which communication strategies are effective around breastfeeding messaging is scarce. To fill this gap, we aimed to identify influencers in the largest available Twitter database using social network analysis (n = 10,694 users), inductively analyze tweets, and explore communication strategies, motivations, and challenges via semi-structured interviews. Influencers had diverse backgrounds within and beyond the scientific health community (SHC; 42.7%): 54.7% were from the general public and 3% were companies. SHC contributed to most of the tweets (n = 798 tweets), disseminating guidelines and research findings more frequently than others (p < 0.001). Influencers from the general community mostly tweeted opinions regarding the current state of breastfeeding research and advocacy. Interviewees provided practical strategies (e.g., preferred visuals, tone, and writing style) to achieve personal and societal goals including career opportunities, community support, and improved breastfeeding practices. Complex challenges that need to be addressed were identified. Ideological differences regarding infant feeding may be hampering constructive communication, including differences in influencers' interpretation of the WHO International Code of Marketing of Breast-milk Substitutes and in perspectives regarding which social media interactions encompass conflict of interest.

Real-time Twitter interactions during World Breastfeeding Week: A case study and social network analysis.

Using Twitter to implement public health awareness campaigns is on the rise, but campaign monitoring and evaluation are largely dependent on basic Twitter Analytics. To establish the potential of social network theory-based metrics in better understanding public health campaigns, we analyzed real-time user interactions on Twitter during the 2020 World Breastfeeding Week (WBW) as an exemplar case. Social network analysis (SNA), including community and influencer identification, as well as topic modeling were used to compare the activity of n = 29,958 campaign participants and n = 10,694 reference users from the six-months pre-campaign period. Users formed more inter-connected relationships during the campaign, retweeting and mentioning each other 46,161 times compared to 10,662 times in the prior six months. Campaign participants formed identifiable communities that were not only based on their geolocation, but also based on interests and professional background. While influencers who dominated the WBW conversations were disproportionally members of the scientific community, the campaign did mobilize influencers from the general public who seemed to play a "bridging" role between the public and the scientific community. Users communicated about the campaign beyond its original themes to also discuss breastfeeding within the context of social and racial inequities. Applying SNA allowed understanding of the breastfeeding campaign's messaging and engagement dynamics across communities and influencers. Moving forward, WBW could benefit from improving targeting to enhance geographic coverage and user interactions. As this exemplar case indicates, social network theory and analysis can be used to inform other public health campaigns with data on user interactions that go beyond traditional metrics.