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Effective pain management is closely related to nurses' knowledge and attitudes toward pain. Limited studies have been performed related to nurses' knowledge and attitudes toward pain in hospitals in low-income areas. This study surveyed the knowledge and attitudes of nurses toward pain management in county hospitals from low-income areas in Hunan Province, China. The study included 4,668 registered nurses working in 48 county hospitals in low-income areas in China. A cross-sectional study examined the knowledge and attitudes of nurses with regard to pain using the Chinese version of the Knowledge and Attitude Survey Regarding Pain (KASRP) via the WeChat application. The 4,668 registered nurses completed the survey; of these, 43.6% indicated they had never received continuing education for pain. The mean percentage score for KASRP was (40.3 ± 7.95), and none of the respondents achieved a percentage score of >80%. Further, of the 40 items, only two had a correct rate of >80%. Continuing pain education did not significantly affect KASRP. Multiple stepwise linear regression showed that education level, ethnicity, professional title, position, and department were independent influencing factors for KASRP scores. Almost all nurses in county hospitals of low-income areas had deficiencies in various aspects of pain management knowledge. Better educated nurses with higher professional title or management position, those from the Han ethnicity, and those from the oncology department had higher mean KASRP scores. Current continuing education programs for pain did not improve the pain management capability of the nurse. High-quality and standardized pain educational programs should be implemented to improve pain management. [ABSTRACT FROM AUTHOR]

It is a great challenge to identify the many and varied sources of soil heavy metal pollution. Often little information is available regarding the anthropogenic factors and enterprises that could potentially pollute soils. In this study we use freely available geographical data from a search engine in conjunction with machine learning methodologies to identify and classify potentially polluting enterprises in the Yangtze Delta, China. The data were classified into 31 separate and four integrated industry types by five different machine learning approaches. Multinomial naive Bayesian (NB) methods achieved an accuracy of 87% and Kappa coefficient of 0.82 and were used to classify the geographic data from more than 260,000 enterprises. The relationship between the different industry classes and measurements of soil cadmium (Cd) and mercury (Hg) concentrations was explored using bivariate local Moran's I analysis. The analysis revealed areas where different industry classes had led to soil pollution. In the case of Cd, elevated concentrations also occurred in some areas because of excessive fertilization and coal mining. This study provides a new approach to investigate the interaction between anthropogenic pollution and natural sources of soil heavy metals to inform pollution control and planning decisions regarding the location of industrial sites. Image 1 • Potentially polluting enterprises are identified and classified. • Spatial correlation of Cd and Hg with polluting enterprises is observed. • Industry pollution affects the distribution of Cd and Hg pollution in soils. • High contents of Cd occur in some areas due to fertilization and coal mining. • Hg pollution caused by chemical industry is more serious than other industries. Capsule: This work provides a new way based on machine learning methods using geographic dataset for pollution source identification and risk mitigation. [ABSTRACT FROM AUTHOR]

Purpose This study aimed to examine the psychometric properties and performance of a Chinese version of the Female Sexual Function Index (FSFI) among a sample of Chinese women with cervical cancer. Methods A cross-sectional survey design was used. The respondents included 215 women with cervical cancer in an oncology hospital in China. A translated Chinese version of the FSFI was used to investigate their sexual functioning. Psychometric testing included internal consistency reliability (Cronbach's alpha coefficient and item–total correlations), test-retest reliability, construct validity (principal component analysis via oblique rotation and confirmatory factor analysis), and variability (floor and ceiling effects). Results The mean score of the total scale was 20.65 ± 4.77. The Cronbach values were .94 for the total scale, .72–.90 for the domains. Test-retest correlation coefficients over 2–4 weeks were .84 (p < .05) for the total scale, .68–.83 for the subscales. Item-total correlation coefficients ranged between .47 and .83 (p < .05). A five-factor model was identified via principal component analysis and established by confirmatory factor analysis, including desire/arousal, lubrication, orgasm, satisfaction, and pain. There was no evidence of floor or ceiling effects. Conclusions With good psychometric properties similar to its original English version, this Chinese version of the FSFI is demonstrated to be a reliable and valid instrument that can be used to assess sexual functioning of women with cervical cancer in China. Future research is still needed to confirm its psychometric properties and performance among a large sample. [ABSTRACT FROM AUTHOR]

In this study we systematically reviewed 1203 research papers published between 2008 and 2018 in China and recorded related data on eight kinds of soil heavy metals (Cr, Pb, Cd, Hg, As, Cu, Zn, and Ni). Based on that, the pollution levels, ecological risk and health risk caused by soil heavy metals were evaluated and the pollution hot spots and potential driving factors of different heavy metals in different provinces were also identified. Results indicated accumulation of heavy metals in soils of most provinces in China compared with background values. Consistent with previous findings, the most prevalent polluted heavy metals were Cd and Hg. Polluted regions are mainly located in central, southern and southwestern China. Hunan, Guangxi, Yunnan, and Guangdong provinces were the most polluted provinces. For the potential health risk caused by heavy metals pollution, children are more likely confront with non-carcinogenic risk than adults and seniors. And children in Hunan and Guangxi province were experiencing relatively larger non-carcinogenic risk. In addition, children in part of provinces were undergoing potentially carcinogenic risks due to soil heavy metals exposure. Furthermore, in our study the 31 provinces in mainland China were divided into six subsets according to corresponding potential driving factors for heavy metal accumulation. Our study provide more comprehensive and updated information for contributing to better soil management, soil remediation, and soil contamination control in China. Image 1 • Cd and Hg were the most polluted heavy metals in soil across China. • The ER values for Cd in 30 provinces varied from moderate to very high risk. • Hunan, Guangxi, Yunnan and Guangdong were confirmed as priority control provinces. • Children are undergo larger health risk than adults and seniors in China. • Controlling factors of heavy metals accumulation in different provinces were mapped. [ABSTRACT FROM AUTHOR]