Previous meta-analyses were conducted during the initial phases of the COVID-19 pandemic, which utilized a smaller pool of data. The current meta-analysis aims to provide additional (and updated) evidence related to the psychological impact among healthcare workers. The search strategy was developed by a medical librarian and bibliographical databases, including Medline, Embase, CINAHL, PsycINFO, and Scopus were searched for studies examining the impact of the COVID-19 pandemic on the psychological health of healthcare workers. Articles were screened by three reviewers. Heterogeneity among studies was assessed by I² statistic. The random-effects model was utilized to obtain the pooled prevalence. A subgroup analysis by region, gender, quality of study, assessment methods, healthcare profession, and exposure was performed. Publication bias was assessed by Funnel plot and Egger linear regression test. Sixty-five studies met the inclusion criteria and the total sample constituted 79,437 participants. The pooled prevalence of anxiety, depression, stress, post-traumatic stress syndrome, insomnia, psychological distress, and burnout was 34.4%, 31.8%, 40.3%, 11.4%, 27.8%, 46.1%, and 37.4% respectively. The subgroup analysis indicated higher anxiety and depression prevalence among females, nurses, and frontline responders than males, doctors, and second-line healthcare workers. This study highlights the need for designing a targeted intervention to improve resilience and foster post-traumatic growth among frontline responders.

Mental health issues among college students is a leading public health concern, which seems to have been exacerbating during the COVID-19 pandemic. While previous estimates related to psychological burden among college students are available, quantitative synthesis of available data still needs to be performed. Therefore, this meta-analysis endeavors to present collective evidence discussing the psychological impact of COVID-19 among college students. Bibliographical library databases, including Embase, Medline, CINAHL, Scopus, and PsycINFO, were systematically searched for relevant studies. Titles, abstracts, and full articles were screened, and two reviewers extracted data. Heterogeneity was assessed by I² statistic. The random-effects model was utilized to obtain the pooled estimates of psychological indicators among college students. Location, gender, level of severity, and quality scores were used as moderator variables for subgroup analyses. Funnel plot and Egger linear regression test was used to assess publication bias. Twenty-seven studies constituting 90,879 college students met the inclusion criteria. The results indicated 39.4% anxiety (95% CI: 28.6, 51.3; I² = 99.8%; p-value < 0.0001) and 31.2% depression (95% CI: 19.7, 45.6; I²= 99.8%, p < 0.0001) among college students. The pooled prevalence of stress (26.0%), post-traumatic stress disorder (29.8%), and impaired sleep quality (50.5%) were also reported. College students bear a disproportionate burden of mental health problems worldwide, with females having higher anxiety and depression levels than males. This study‘’s findings underscore the need to develop appropriate public health interventions to address college students’ emotional and psychosocial needs. The policies should be reflective of demographic and socioeconomic differentials.

With the emergence of the novel SARS-CoV-2 and the disease it causes; COVID-19, compliance with/adherence to protective measures is needed. Information is needed on which measures are, or are not, being undertaken. Data collected from the COVID Impact Survey, conducted by the non-partisan and objective research organization NORC at the University of Chicago on April, May, and June of 2020, were analyzed through weighted Quasi-Poisson regression modeling to determine the association of demographics, socioeconomics, and health conditions with protective health measures taken at the individual level in response to COVID-19. The three surveys included data from 18 regional areas including 10 states (CA, CO, FL, LA, MN, MO, MT, NY, OR, and TX) and 8 Metropolitan Statistical Areas (Atlanta, GA; Baltimore, MD; Birmingham, AL; Chicago, IL; Cleveland and Columbus, OH; Phoenix, AZ; and Pittsburgh, PA). Individuals with higher incomes, insurance, higher education levels, large household size, age 60+, females, minorities, those who have asthma, have hypertension, overweight or obese, and those who suffer from mental health issues during the pandemic were significantly more likely to report taking precautionary protective measures relative to their counterparts. Protective measures for the three subgroups with a known relationship to COVID-19 (positive for COVID-19, knowing an individual with COVID-19, and knowing someone who had died from COVID-19) were strongly associated with the protective health measures of washing hands, avoiding public places, and canceling social engagements. This study provides first baseline data on the response to the national COVID-19 pandemic at the individual level in the US. The found heterogeneity in the response to this pandemic by different variables can inform future research and interventions to reduce exposure to the novel SARS-CoV-2 virus.

Former foster youth are at increased risk of housing instability and sexually transmitted infections (STIs) during the transitional period following foster care. We measured housing stability using sequence analysis and assessed whether a supportive housing program in New York, New York, was effective in improving housing stability and reducing STIs among former foster youth. Matched administrative records identified 895 former foster youth who were eligible for the housing program during 2007–2010. The main outcomes included housing stability (as determined from episodes of homelessness, incarceration, hospitalization, and residence in supportive housing) and diagnosed STI case rates per 1,000 person-years during the 2 years after baseline. Marginal structural models were used to assess impacts of the program on these outcomes. Three housing stability patterns (unstable housing, stable housing, and rare institutional dwelling patterns) were identified. The housing program was positively associated with a pattern of stable housing (odds ratio = 4.4, 95% confidence interval: 2.9, 6.8), and negatively associated with diagnosed STI rates (relative risk = 0.3, 95% confidence interval: 0.2, 0.7). These positive impacts on housing stability and STIs highlight the importance of the supportive housing program for youths aging out of foster care and the need for such programs to continue.

Purpose: Given the increased exposure to e-cigarettes and nicotine among young adults, difficulty in quitting vaping is likely, which supports the need for effective behavioral interventions. Therefore, this cross-sectional study aims to assess the testability of the contemporary multi-theory model of health behavior change in predicting the vaping quitting behavior among young adults in the United States. Methods: A nationally representative sample of 619 young adults engaged in vaping behavior and aged 18–24 years was recruited to complete a 49-item web-based survey. A structural equation model was used to test relationships between MTM constructs. Hierarchical multiple regression was utilized to predict the variance in the initiation and sustenance of vaping quitting behavior by predictor variables, such as demographic characteristics, history of behaviors, and MTM constructs. Results: Of 619 respondents, over 75% were White and nearly 70% had educational attainment equal to high school or some college. In total, 62% of respondents were using nicotine, followed by 33.3% were using cannabis. About 80% of the respondents reported being engaged in drinking alcohol, and nearly 45% were engaged in cigarette smoking. The predictive effect of all MTM constructs on vaping quitting initiation (adjusted R² = 0.417, F (23, 595) = 20.215, p < 0.001) and sustenance (adjusted R² = 0.366, F (23, 595) = 16.533, p < 0.001) was statistically significant. Conclusions: The findings of this study point to the usability and applicability of MTM in operationalizing and developing vaping quitting behavior interventions targeting young adults.