Human Papillomavirus Vaccination and Physical and Mental Health Complaints Among Female Students in Secondary Education Institutions in Denmark

Factors Associated With Psychological Outcomes Among Vaccinated and Unvaccinated Health Care Workers Against COVID-19 Infection in Bangladesh

Background

Vaccination of healthcare workers (HCWs) is recommended during the COVID-19 pandemic to reduce the risk of infection for themselves and their patients, as well as to encourage their patients to get immunized. The present study aimed to investigate the psychological outcomes and associated factors among vaccinated and unvaccinated HCWs against COVID-19 infection in Bangladesh.

Methods

From March to August 2021, an online nationwide survey was conducted with a total of 2,038 Bangladeshi HCWs. The frequency of symptoms of general health problems, depression, anxiety, stress, post-traumatic stress disorder, insomnia, and loneliness was assessed using the Bangla versions of the GHQ-12, PHQ-2, GAD-2, PSS-4, PC-PTSD-5, ISI, and UCLA-LS scales, respectively.

Results

Compared with unvaccinated HCWs (n = 1,058), vaccinated HCWs (n = 980) had a statistically significant lower prevalence of general health problems (16.7 vs. 59.1%), depression (15.6 vs. 31.9%), post-traumatic stress disorder (22.3 vs. 30.8%), insomnia (23.8 vs. 64.9%), and loneliness symptoms (13.9 vs. 21.8%). Among vaccinated HCWs, females were significantly associated with a higher risk of symptoms of general health problems (AOR, 2.71; 95% CI, 0.97-7.60), anxiety (AOR, 2.17; 95% CI, 1.14-4.13), and loneliness (AOR, 2.52; 95% CI, 1.11-5.73). Except for anxiety and post-traumatic stress disorder symptoms, participants living in urban areas had a significantly lower risk of all psychological outcomes (e.g., depression: AOR, 0.43; 95% CI, 0.27-0.67; stress: AOR, 0.64; 95% CI, 0.47-0.88). Respondents who were married were significantly less likely to experience symptoms of general health problems (AOR, 0.10; 95% CI, 0.02-0.39), depression (AOR, 0.31; 95% CI, 0.22-0.82), insomnia (AOR, 0.46; 95% CI, 0.20-1.03), and loneliness (AOR, 0.31; 95% CI, 0.10-0.92). Participants who worked as doctors were significantly less chance of experiencing symptoms of general health problems (AOR, 0.18; 95% CI, 0.08-0.37), depression (AOR, 0.51; 95% CI, 0.30-0.87), and anxiety (AOR, 0.54; 95% CI, 0.37-0.78). On the other hand, unvaccinated HCWs who were 18-29 years old and had <5 years of work experience were significantly associated with a higher risk of all psychological outcomes except anxiety and insomnia symptoms (e.g., depression among 18-29 years old: AOR, 1.83; 95% CI, 0.27-2.60; stress among those with <5 years of work experience: AOR, 2.37; 95% CI, 0.93-6.07). Participants who worked as nurses were significantly more likely to suffer from depression (AOR, 1.44; 95% CI, 0.84-2.46), anxiety (AOR, 1.42; 95% CI, 0.24-1.73), and stress (AOR, 1.55; 95% CI, 0.31-0.89) symptoms. Except for anxiety and stress symptoms, respondents who worked as frontline workers and provided direct care to infected patients were the significantly higher chance of experiencing all psychological outcomes (e.g., depression among who worked as frontline workers: AOR, 2.41; 95% CI, 0.23-3.73; insomnia among those who provide direct care to infected patients: AOR, 2.60; 95% CI, 0.34-3.06). Participants who were infected with COVID-19 had a significantly less chance of experiencing symptoms of general health problems (AOR, 0.89; 95% CI, 0.65-1.22), depression (AOR, 0.66; 95% CI, 0.48-0.92), and anxiety (AOR, 0.63; 95% CI, 0.46-0.87).

Conclusions

To control the infection and improve psychological outcomes, this study suggests emphasizing the vaccinated to unvaccinated HCWs as soon as possible. They also required special attention, health-related education, and psychological support.

Changes in Mental Health and Preventive Behaviors before and after COVID-19 Vaccination: A Propensity Score Matching (PSM) Study

Mass vaccination against the COVID-19 pandemic is ongoing worldwide to achieve herd immunity among the general population. However, little is known about how the COVID-19 vaccination would affect mental health and preventive behaviors toward the COVID-19 pandemic. In this study, we conducted a cross-sectional survey to address this issue among 4244 individuals at several COVID-19 vaccination sites in Guangzhou, China. Using univariate analysis and multiple linear regression models, we found that major demographic characteristics, such as biological sex, age, education level, and family per capita income, are the dominant influencing factors associated with health beliefs, mental health, and preventive behaviors. After propensity score matching (PSM) treatment, we further assessed the changes in the scores of health belief, mental health, and preventive behaviors between the pre-vaccination group and the post-vaccination group. When compared to individuals in the pre-vaccination group, a moderate but statistically significant lower score was observed in the post-vaccination group (p = 0.010), implying possibly improved psychological conditions after COVID-19 vaccination. In addition, there was also a moderate but statistically higher score of preventive behaviors in the post-vaccination group than in the pre-vaccination group (p < 0.001), suggesting a higher probability to take preventive measures after COVID-19 vaccination. These findings have implications for implementing non-pharmaceutical interventions combined with mass vaccination to control the rebound of COVID-19 outbreaks.

Prediction Algorithm of Young Students' Physical Health Risk Factors Based on Deep Learning

Young people's physical and mental health is the foundation of society's overall development and the key to improving people's health quality. Middle school students' physical examinations and monitoring work are a surefire way to ensure their healthy development. Poor vision, dental caries, overweight and obesity, and high blood pressure are the most common adverse health outcomes of students caused by adolescent health risk behavior factors. Researchers have been concerned about the retinal fundus vascular system, which is the only internal vascular system that can be observed in a noninvasive state of the human body. Fundus images contain a wealth of disease-related information. Fundus images have been widely used in the field of medical auxiliary diagnosis because many important systemic diseases of the human body cause specific reactions in the fundus. Aiming to solve the problem of inseparable tiny blood vessels, this paper proposes a model of retinal vessel segmentation based on attention mechanisms. In light of the retinal arteriovenous division of discontinuous challenges, the topological structure of the constraint system along with overcoming the network and topology restrictions is monitored. Finally, simulation experiments were conducted on two publicly available datasets. The findings show that the proposed method is reliable, effective, and accurate in predicting physical health risk factors in adolescent students.