Validation and Reliability Assessment of Data Collection Instrument for University Students' Employment Readiness: A Pilot Testing

This research aims to explore the mediating role of personal image in affecting the employment readiness of university students. Personal image can be a key determinant in the perceived employability and overall preparedness of students. We pilot tested our research instruments by studying a sample of 50 university students, assessing their self-reported employment readiness and their perceptions of their own personal image. This study aimed to assess the validity and reliability of a data collection instrument tailored for gauging university students' readiness for employment. Two key validation methodologies were employed: content validity through expert judgment and construct validity using the Pearson correlation coefficient. Expert feedback was systematically collated, revealing that the instrument's items closely align with the intended research constructs. The Fleiss-Cohen test was utilized to assess inter-respondent agreement, and results indicated a high degree of consensus among experts.Further statistical analysis using Cohen's Kappa statistic demonstrated substantial to almost perfect agreement among raters, bolstering the instrument's reliability. The application of Pearson correlation emphasized the tool's ability to elucidate intricate relationships between myriad factors relevant to students' employment preparedness. Pilot testing concluded that the research instrument is both valid and reliable, ensuring its suitability for a broader study on university students' readiness for the professional world

American Twitter Users Revealed Social Determinants-related Oral Health Disparities amid the COVID-19 Pandemic

Objectives: To assess self-reported population oral health conditions amid COVID-19 pandemic using user reports on Twitter. Method and Material: We collected oral health-related tweets during the COVID-19 pandemic from 9,104 Twitter users across 26 states (with sufficient samples) in the United States between November 12, 2020 and June 14, 2021. We inferred user demographics by leveraging the visual information from the user profile images. Other characteristics including income, population density, poverty rate, health insurance coverage rate, community water fluoridation rate, and relative change in the number of daily confirmed COVID-19 cases were acquired or inferred based on retrieved information from user profiles. We performed logistic regression to examine whether discussions vary across user characteristics. Results: Overall, 26.70% of the Twitter users discuss wisdom tooth pain/jaw hurt, 23.86% tweet about dental service/cavity, 18.97% discuss chipped tooth/tooth break, 16.23% talk about dental pain, and the rest are about tooth decay/gum bleeding. Women and younger adults (19-29) are more likely to talk about oral health problems. Health insurance coverage rate is the most significant predictor in logistic regression for topic prediction. Conclusion: Tweets inform social disparities in oral health during the pandemic. For instance, people from counties at a higher risk of COVID-19 talk more about tooth decay/gum bleeding and chipped tooth/tooth break. Older adults, who are vulnerable to COVID-19, are more likely to discuss dental pain. Topics of interest vary across user characteristics. Through the lens of social media, our findings may provide insights for oral health practitioners and policy makers.Comment: Accepted for publication in Quintessence Internationa

Efficiency of electrochemical chloride removal from concrete at different environmental temperatures

Electrochemical chloride removal (ECR) is an effective and curative method to treat existed reinforced concrete structures about to suffer or already suffering from chloride attack, however, its application is still limited due to its side effect and efficiency, including the velocity and maximum capacity of chloride removal. This paper presents a temperature related numerical transport model to study the effect of temperature on efficiency of electrochemical chloride removal from concrete. Based on Fick’s law and Nernst-Planck equation with Gauss’ Law, temperature effect, chloride binding, multi-species coupling, electrochemical reactions were taken into account in this model. Temperature effect was considered on diffusion coefficient, chloride binding, ions migration capacity as well as electrolyte concentration. The model was validated by the comparison between the calculated results and experimental data. The results indicate that temperature dose have a considerable influence on electrochemical chloride removal and controlling temperature during treatment is a practical method to improve the electrochemical chloride removal when applied current density is not amplified