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COVID-19 Knowledge and Pandemic-Associated Distress Among the Hospital Pharmacist Workforce in China
- Dongliang Yang, Xueying Ma, Songnian Fu, Jun Zhao, Aizezijiang Aierken, Liang Teng, Xiaoli Gao
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- Journal:
- Disaster Medicine and Public Health Preparedness / Volume 17 / 2023
- Published online by Cambridge University Press:
- 25 November 2021, e75
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Background:
The unprecedented disruption brought about by the global coronavirus disease 2019 (COVID-19) pandemic had produced tremendous influence on the practice of pharmacy. Sufficient knowledge of pharmacists was needed to deal with the epidemic situation; however, outbreak also aggravated psychological distress among health-care professionals. Therefore, this study aimed to determine knowledge about the pandemic and related factors, prevalence and factors associated with psychological distress among hospital pharmacists of Xinjiang Province, China.
Methods:An anonymous online questionnaire-based cross-sectional study was conducted by means of WeChat, a popular social media platform in China, February 23-27, 2020, during the COVID-19 outbreak. The survey questionnaire consisted of 4 parts, including informed consent section, demographic section, knowledge about COVID-19, and assessment of overall mental health through World Health Organization’s Self-Reporting Questionnaire (SRQ-20). A score of 8 or above on SRQ-20 was used as cutoff to classify the participant as in psychological distress. SRQ-20 score and related knowledge score were used as dependent variables, demographic characteristics (such as gender, age, monthly income, etc.) were used as independent variables, and univariate binary logistic regression was used to screen out the variables with P < 0.05. Then, the filtered variables were used as independent variables, and multivariate logistic regression models were used to analyze associations with sufficient knowledge of COVID-19 and psychological distress.
Results:A total of 365 pharmacists participated in the survey, fewer than half (35.1%; n = 128) of pharmacists attained a score of 6 or greater (out of 10) in overall disease knowledge, and most were able to select effective disinfectants and isolation or discharge criteria. In the multivariable model, age ages 31-40 (odds ratio [OR] = 3.25; P < 0.05), ages 41-50 (OR = 2.96; P < 0.05) versus >50 (referent); primary place of practice in hospitals: drug supply (OR = 4.00; P < 0.01), inpatient pharmacy (OR = 2.06, P < 0.01), clinical pharmacy (OR = 2.17, P < 0.05) versus outpatient pharmacy (referent); monthly income Renminbi (RMB, China’s legal currency) 5000-10,000 (OR = 1.77; P < 0.05) versus < 5000 (referent); contact with COVID-19 patients or suspected cases (OR = 2.27; P < 0.01); access to COVID-19 knowledge remote work+ on-site work (OR = 6.07; P < 0.05), single on-site work (OR = 6.90; P < 0.01) versus remote work (referent) were related to better knowledge of COVID-19. Research found that 18.4% of pharmacists surveyed met the SRQ-20 threshold for distress. Self-reported history of mental illness (OR = 3.56; P < 0.05) and working and living in hospital versus delay in work resumption (OR = 2.87; P < 0.01) were found to be risk factors of psychological distress.
Conclusions:Further training of COVID-19 knowledge was required for pharmacists. As specific pharmacist groups were prone to psychological distress, it was important for individual hospitals and government to consider and identify pharmacists’ needs and take steps to meet their needs with regard to pandemic and other work-related distress.
Can emotional expressivity and writing content predict beneficial effects of expressive writing among breast cancer patients receiving chemotherapy? A secondary analysis of randomized controlled trial data from China
- Yanni Wu, Dongliang Yang, Biao Jian, Chaixiu Li, Liping Liu, Wenji Li, Xiaojin Li, Chunlan Zhou
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- Journal:
- Psychological Medicine / Volume 53 / Issue 4 / March 2023
- Published online by Cambridge University Press:
- 24 August 2021, pp. 1527-1541
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Background
To explore whether emotional expressivity and the patterns of language use could predict benefits from expressive writing (EW) of breast cancer (BC) patients in a culture that strongly discourages emotional disclosure.
MethodsData were obtained from a recent trial in which we compared the health outcomes between a prolonged EW group (12 sessions) and a standard EW group (four sessions) (n = 56 per group) of BC patients receiving chemotherapy. The Chinese texts were tokenized using the THU Lexical Analyser for Chinese. Then, LIWC2015 was used to quantify positive and negative affect word use.
ResultsOur first hypothesis that BC patients with higher levels of emotional expressivity tended to use higher levels of positive and negative affect words in texts was not supported (r = 0.067, p = 0.549 and r = 0.065, p = 0.559, respectively). The level of emotional expressivity has a significant effect on the quality of life (QOL), and those who used more positive or fewer negative affective words in texts had a better QOL (all p < 0.05). However, no significant difference was identified in physical and psychological well-being (all p > 0.05). Furthermore, the patterns of affective word use during EW did not mediate the effects of emotional expressivity on health outcomes (all p > 0.05).
ConclusionsOur findings suggest that the level of emotional expressivity and the pattern of affective word use could be factors that may moderate the effects of EW on QOL, which may help clinicians identify the individuals most likely to benefit from such writing exercises in China.
Psychological impact of 2019 novel coronavirus (2019-nCoV) outbreak in health workers in China
- Dandan Sun, Dongliang Yang, Yafen Li, Jie Zhou, Wenqing Wang, Quanliang Wang, Nan Lin, Ailin Cao, Haichen Wang, Qingyun Zhang
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- Journal:
- Epidemiology & Infection / Volume 148 / 2020
- Published online by Cambridge University Press:
- 20 May 2020, e96
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The first case of 2019-nCoV pneumonia infection occurred in Wuhan, Hubei Province, South China Seafood Market in December 2019. As a group with a high probability of infection, health workers are faced with a certain degree of psychological challenges in the process of facing the epidemic. This study attempts to evaluate the impact of 2019-nCoV outbreak on the psychological state of Chinese health workers and to explore the influencing factors. During the period from 31 January 2020 to 4 February 2020, the ‘Questionnaire Star’ electronic questionnaire system was used to collect data. The 2019-nCoV impact questionnaire and The Impact of Event Scale (IES) were used to check the psychological status of health workers in China. A total of 442 valid data were collected in this study. Seventy-four (16.7%) male and 368 (83.3%) female individuals participated in this study. The average score of high arousal dimension was 5.15 (s.d. = 4.71), and the median score was 4.0 (IQR 2.0, 7.0). The average score of IES was 15.26 (s.d. = 11.23), and the median score was 13.5 (IQR 7.0, 21.0). Multiple regression analysis showed that there were critical statistical differences in high arousal scores among different gender groups (male 3.0 vs. female 5.0, P = 0.075). Whether being quarantined had significant statistical differences of IES scores (being quarantined 16.0 vs. not being quarantined 13.0, P = 0.021). The overall impact of the 2019-nCoV outbreak on health workers is at a mild level. Chinese health workers have good psychological coping ability in the face of public health emergencies.
11 - Social influence analysis in the big data era: a review
- from Part III - Big data over social networks
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- By Jianping Cao, National University of Defense Technology, China, Dongliang Duan, University of Wyoming, USA, Liuqing Yang, Colorado State University, USA, Qingpeng Zhang, City University of Hong Kong, China, Senzhang Wang, Beihang Univerisity, China, Feiyue Wang, National University of Defense Technology, China
- Edited by Shuguang Cui, Texas A & M University, Alfred O. Hero, III, University of Michigan, Ann Arbor, Zhi-Quan Luo, University of Minnesota, José M. F. Moura, Carnegie Mellon University, Pennsylvania
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- Book:
- Big Data over Networks
- Published online:
- 18 December 2015
- Print publication:
- 14 January 2016, pp 301-334
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Summary
Social influence is a widely accepted phenomenon in social networks, and it has been studied by researchers from various perspectives, including social psychology, sociology, marketing, and computer science, just to name a few. During the past decade, the emergence and fast growth of social media sites (such as Facebook and Twitter) have enabled the measurement, quantitative analysis, and modeling of social influence at a large scale. Therefore, it is essential to re-evaluate these developed algorithms and models in the new era of big data. In this chapter, we review research on social influence analysis in the big data era, with a focus on the computational perspective.We first present the statistical measurements of social influence. Then, we introduce the algorithms and models to characterize the propagation of social influence. Next, we present the issues related to the optimization of the propagation of social influence. In addition, we review research on the diffusion of network influence, which is closely related to the studies of the forecasting and influencing/contagion of information. Towards the end of this chapter, we also discuss the envisioned opportunities and challenges.
Introduction
Social influence analysis is an intuitive and well-accepted phenomenon by researchers for decades [1, 2]. Since social influence plays a key role in social life and decision making, as discovered by Katz and Lazarsf in the 1950s [3], theories and models have been developed from various perspectives by researchers in many different areas, including sociology, computer science, and management science, etc. With the popularity of social network services, increasing computer science researchers are paying more attention to this field. Social influence has extensive qualitative and quantitative applications, which have been well studied in sociology and computer science. For example, public opinion leaders affect numerous fans, and their opinions are quickly spread to a large population. Since they play an essential role in information dissemination, many studies focused on the identification of those users [4–6]. Social influence analysis has also been applied to other fields, such as recommendation systems [7], information propagation in social networks [1, 8–11], link prediction [12–14], viral marketing [15–21], public health [22, 23], expert discovery [24, 25], detection of emergent events [26], and advertising [27], just to name a few. In this chapter, we focus on the “social influence analysis” based on social networks such as Twitter, Facebook, and Weibo.
Study of Intermetallic FeAl—Alumina Wettability Affected by Microalloying Y and Nb
- Dong Xu, Dening Wang, Weimin Zhou, Hong Yang, Dongliang Lin, (T. L. Lin)
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- Journal:
- MRS Online Proceedings Library Archive / Volume 288 / 1992
- Published online by Cambridge University Press:
- 01 January 1992, 817
- Print publication:
- 1992
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The effects of microalloying elements, Y(0.02at%, 0.04at% and 0.06at%) and Nb(0.2at%, 0.5at% and 0.8at%) on the wettability of intermetallic Fe-40A1 with polycrystalline α-Al2O3 were investigated experimentally by means of sessile drop method. The addition of 0.02at%Y and 0.04at%Y showed no significant effects on the wettability. However, the addition of 0.06at%Y improved the wettability in temperature range from 1673K to 1823K. The addition of different amount of Nb were not beneficial to the FeAl-Al2O3 wettability under conditions investigated. The SEM study of the shear fractured surfaces showed that the additions of Y and Nb coursed Al2O3 particles more adherent to FeAl matrix, compared with the case of pure Fe-40A1. The degree of adherence varied with the amount of Y and Nb. These phenomena are discussed in terms of interfacial reactions and interfacial bonding.