Social Risk of Pregnant Women at a Community Health Center: An Application of the PRAPARE Assessment Tool.

Community health centers (CHCs) screen patients for social determinants of health (SDoH). The study's purpose was to assess the relationship between demographic factors and unmet social needs (SDoH risk) among pregnant mothers. Patient data from 345 pregnant women between January 2019-December 2020 assessed SDoH risk, using the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) tool. Chi-square analyses explored relationships between social needs and demographic factors, and a multivariate logistic regression examined associations between these variables controlling for covariates. Hispanic patients and those who preferred to speak Spanish had 2.35 and 5.39 times the odds, respectively as non-Hispanic Whites and English speakers of having moderate/high/urgent SDoH risks. Mothers who had not completed high school had increased odds (aOR = 7.38) of SDoH risk. By identifying indicators that increase social risk level, CHCs can connect patients to essential social services, improving the downstream health of mothers and children.

Using the PRAPARE Tool to Examine Those Tested and Testing Positive for COVID-19 at a Community Health Center.

The PRAPARE (Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences) tool is an instrument that has been used to assess social determinants of health within community health centers in the US. We sought to examine the association between PRAPARE scores and getting tested for and testing positive with the SARS-CoV-2 virus. We used medical record data collected from a community health center in the US between March-August 2020. Employing logistic regression analyzes, we explored the association between demographic factors, history of screening positive for depression, and PRAPARE scores and patients' odds of getting tested and testing positive for COVID-19. While variables such as ethnicity mirrored similar findings from other sources, we found the PRAPARE score to be associated with increased odds of being tested for COVID-19; however, it was not significantly associated with testing positive. These findings can help health care workers and health educators craft messages to explain screening protocols for communicable diseases, such as COVID-19, to best reach vulnerable populations.

College students' reasons for using different e-cigarette products: A mixed methods analysis.

OBJECTIVE: This study examined if college students used particular e-cigarette devices for different reasons. Participants: College students from a large southern university completed an online, close- and open-ended survey. Data were delimited to those 18-25 years of age who had used e-cigarettes (n = 338). Methods: A convergent mixed-methods design was employed by quantifying qualitative responses via an inducting coding method. Next, χ2 analyses examined relationships between use of different products (i.e., cigalikes, vape pens, eGos, mods) and reasons for using e-cigarettes. Results: Emerging themes representing reasons for trying e-cigarettes included: curiosity, peer pressure, recreation, flavors, better than cigarettes, and to quit/reduce tobacco use. Significant relationships existed between use of cigalikes, (p < . 01), eGos (p < . 05), and mods (p < . 05) and use of e-cigarettes to quitting/reducing tobacco use. Conclusions: Health promotion efforts on college campuses should address curiosity about these products and provide scientifically proven therapy to those seeking to quit tobacco.

College Student E-cigarette Use: A Reasoned Action Approach Measure Development.

Objectives: The purpose of this study was to develop and validate an instrument using the reasoned action approach (RAA) to measure recreational electronic cigarette (e-cigarette) use among college students. Methods: Using a multi-phase, cross-sectional design, a 32-item measure was developed, and the factor structure was explored and confirmed using an exploratory factor analysis (EFA; N = 369) and confirmatory factor analysis (CFA; N = 320), respectively. An exploratory structural equation model (ESEM) and SEM also were employed to examine the relationships between latent constructs and to test the application of the RAA. Results: After removing 9 items, the EFA identified 3 RAA constructs (intention, attitude, social norms), and the ESEM established moderate model fit. The CFA confirmed the 3 factors; however, acceptable model fit was not met until a global social norm variable was loaded onto injunctive and descriptive norms. Based on this 5-factor solution, attitudes (ß = .35, p < .001) and social norms (ß = .50, p <.001) significantly predicted intention to use e-cigarettes. Conclusions: Attitudes and social norms influence college students' intention to use e-cigarettes and should be addressed via health education messaging and prevention programs.