Training in Public Health Informatics and Technology Leveraging a Multi-institutional Partnership Model and Emphasizing Experiential Learning.

BACKGROUND AND OBJECTIVE: Though public health is an information-intense profession, there is a paucity of workforce with Public Health Informatics and Technology (PHIT) skills, which was evident during the coronavirus disease 2019 (COVID-19) pandemic. This need is addressed through the PHIT workforce program (2021-2025) by the Office of the National Coordinator for training and to increase racial and ethnic diversity in the PHIT workforce. The objective is to share details on the Training in Informatics for Underrepresented Minorities in Public Health (TRIUMPH) consortium, funded by the PHIT workforce program. METHODS: The TRIUMPH consortium is a collaboration between academic and practice partners with a commitment to training 879 students in PHIT. The Schools of Public Health and Nursing at the University of Minnesota, Jiann-Ping Hsu College of Public Health at Georgia Southern University, Morehouse School of Medicine, and Public Health Informatics Institute offer PHIT training through various programs. Academic institutions focus on student recruitment, developing courses/curriculum, and granting degrees/certificates, and the role of practice partners is to support experiential learning through internships/practicums. RESULTS: The TRIUMPH consortium is progressing toward its goals, with 692 students (79%) already trained in a PHIT modality as of December 2023. The learners comprise diverse race/ethnicity, including White (48%), Black/African American (32%), Asian (10%), White Hispanic (5%), American Indian/Alaska Native (2%), and Black Hispanic (1%). Numerous internships have been completed in settings ranging from state/local public health agencies to health care delivery systems. Diversity initiatives were supported by partnering with existing programs (e.g., the AMIA First Look program and the Nursing Knowledge Big Data Science conference). CONCLUSION: This consortium model is an excellent approach to informatics training and sharing expertise across partners. It provides scalability and broader geographic outreach while presenting opportunities to students from underrepresented backgrounds. Lessons learned have implications for overall informatics training (e.g., partnerships models, promoting racial/ethnic diversity).

Factors Predicting In-School and Electronic Bullying among High School Students in the United States: An Analysis of the 2021 Youth Risk Behavior Surveillance System.

BACKGROUND: Bullying is a global public health problem with severe adverse effects on behavioral health. Understanding the predictors of victimization by bullying is essential for public policy initiatives to respond to the problem effectively. In addition to traditional in-person bullying, electronic bullying has become more prevalent due to increasing social interaction and identity formation in virtual communities. This study aims to determine the predictors of in-school and electronic bullying. METHODS: We employed multivariable logistic regression to analyze a nationally representative sample of 17,232 high school students in the United States, the 2021 Youth Risk Behavior Surveillance System national component. The survey was conducted during the COVID-19 pandemic, from September through December 2021. The factors examined included sociodemographic characteristics (age, gender, race), appearance (obesity), physically active lifestyles (being physically active, spending a long time on digital games), and risk-taking behavior (using marijuana). RESULTS: Our results indicated that sociodemographic characteristics were strong predictors of being bullied in school and electronically. Being obese is more likely to result in bullying in school (AOR = 1.32, p = 0.003) and electronically (AOR = 1.30, p = 0.004). Adolescent students showing marijuana use had higher odds of being bullied in school (AOR = 2.15, p < 0.001) and electronically (AOR = 1.81, p < 0.001). While spending a long time on digital devices raises the risk of being electronically bullied (AOR = 1.25, p = 0.014), being physically active is not associated with being bullied. Neither of the two lifestyle factors was associated with in-school bullying. CONCLUSIONS: Interventions addressing violence among adolescents can benefit from empirical evidence of risk factors for bullying victimization in high school.

Demographic and Clinical Characteristics Predicting Missed Clinic Visits among Patients Living with HIV on Antiretroviral Treatment in Kinshasa and Haut-Katanga Provinces of the Democratic Republic of Congo.

BACKGROUND: Patients living with HIV (PLHIV) often face challenges that contribute to missed clinical care which can impact their health outcomes. METHODS: This retrospective quantitative study comprised 5338 adults living with HIV who received antiretroviral treatment (ART) for 12 months, from July 2018 to June 2019 in Kinshasa and Haut-Katanga provinces of the Democratic Republic of Congo. Descriptive statistics were computed to show the level of missed appointments for ART. Multivariable associations of clinical and sociodemographic factors with a tendency to miss scheduled visits after adjusting for the covariates were examined using multivariable logistic regression analysis. RESULTS: Six percent of PLHIV experienced at least one missed visit while 94% did not miss any visits. A small proportion (20%) of PLHIV had a viral load ≥1000 copies/mL. PLHIV receiving ART from urban clinics showed significantly higher odds of missed visits compared to those from rural areas (AOR = 4.18, 95% CI [1.84-9.511]; p < 0.0001). Similarly, patients from semi-rural/semi-urban clinics showed significantly higher odds of missed visits compared to those from rural areas. (AOR = 2.57, 95% CI [1.08-6.141]; p = 0.03). Additionally, older PLHIV (18-34 years old) demonstrated increased odds of missed visits (AOR= 1.71, 95% CI [1.0078-2.697]; p = 0.02) compared to those under 18 years old. CONCLUSIONS: The findings from this study strongly suggest that there is a significant association between certain demographic factors, such as age and rurality-urbanicity, and missed visits. The study findings have implications for policy and interventions targeting PLHIV at higher risk of missed visits.

Social and Structural Determinants of Health Associated with COVID-19 Vaccine Hesitancy among Older Adults in the United States.

State-level COVID-19 vaccination rates among older adults have been uneven in the United States. Due to the immunocompromised nature of older adults, vaccine hesitancy increases the risk of morbidity and mortality. This study aims to determine the association between the social determinants of health, the structural determinants of health, and COVID-19 vaccine hesitancy among older adults in the United States. Secondary data from the Health and Retirement Study (HRS) dataset were used. A descriptive analysis and multinomial multivariable logistic regression were performed to examine the association of the independent variables-gender, age, race, immigration status, marital status, broadband internet access, social security income, Medicare coverage, education, and frequency of religious service-with the dependent variable, vaccine hesitancy. Compared to the respondents with no vaccine hesitancy and without the specific predictor, the respondents who reported religious attendance at least once/week were more likely to be "somewhat hesitant", divorced respondents had higher odds of being "somewhat hesitant", and older adults aged 65-74 years were more likely to be "very hesitant" or "somewhat hesitant" about the COVID-19 vaccine. Compared to the respondents with no vaccine hesitancy and without the specific predictor, females had higher odds of being "very hesitant", "somewhat hesitant", or a "little hesitant", and African Americans were more likely to be "very hesitant", "somewhat hesitant", or a "little hesitant" about the COVID-19 vaccine. Addressing these factors may limit the barriers to vaccine uptake reported among older adults and improve herd immunity among the immunocompromised population.