Evidencing the impacts of health research: Insights from trials reported in the 2018 Australian Engagement and Impact Assessment

ISSUE ADDRESSED

While definitions of impact may vary, they often refer to the wider benefits of research evidenced beyond academia. We evaluated case studies featuring randomised trials from the 2018 Engagement and Impact Assessment to better understand how the impacts of health research are evidenced and assessed within Australia.

METHODS

We collated and evaluated 'high' scoring case studies submitted by higher education institutions with a focus on randomised trials across all areas of health research. A qualitative coding system was used for manual content analysis to assess the key characteristics of trials reported, subsequent impacts and the methods used to evidence impacts.

RESULTS

A total of 14 case studies were identified citing 35 clinical trials. The majority of interventions were behavioural with a focus on mental, behavioural or neurodevelopmental disorders. Most trials were phase III, focused on the treatment of the indication and were funded by industry. Contribution to clinical guidelines was the highest cited research impact. While there was evidence of researchers seeking to maximise trial impact, case studies lacked details on the role of trial participants and other beneficiaries in generating impact.

CONCLUSIONS

The impacts of health research can be improved through a better understanding of the priorities and agendas of funders, providing evidence of tangible impact rather than information that is contextual or predictive, and through the early development of impact strategies involving both researchers and beneficiaries. SO WHAT?: Large-scale impact exercises intended for a broad range of disciplines may not be reflective of the depth and scope of health sciences research including trials.

The Spatial Niche and Influencing Factors of Desert Rodents

Resource partitioning may allow species coexistence. Sand dunes in the typical steppe of Alxa Desert Inner Mongolia, China, consisting of desert, shrub, and grass habitats, provide an appropriate system for studies of spatial niche partitioning among small mammals. In this study, the spatial niche characteristics of four rodents, Orientallactaga sibirica, Meriones meridianus, Dipus sagitta, and Phodopus roborovskii, and their responses to environmental changes in the Alxa Desert were studied from 2017 to 2021. Using the capture-mark-recapture method, we tested if desert rodents with different biological characteristics and life history strategies under heterogeneous environmental conditions allocate resources in spatial niches to achieve sympatric coexistence. We investigated the influence of environmental factors on the spatial niche breadth of rodents using random forest and redundancy analyses. We observed that the spatial niche overlap between O. sibirica and other rodents is extremely low (overlap index ≤ 0.14). P. roborovskii had the smallest spatial niche breadth. Spatial niche overlap was observed in two distinct species pairs, M. meridianus and D. sagitta, and P. roborovskii and D. sagitta. The Pielou evenness index of rodent communities is closely related to the spatial distribution of rodents, and the concealment of habitats is a key factor affecting the spatial occupation of rodents.

Data-driven estimation of nitric oxide emissions from global soils based on dominant vegetation covers

Soils are a major source of global nitric oxide (NO) emissions. However, estimates of soil NO emissions have large uncertainties due to limited observations and multifactorial impacts. Here, we mapped global soil NO emissions, integrating 1356 in-situ NO observations from globally distributed sites with high-resolution climate, soil, and management practice data. We then calculated global and national total NO budgets and revealed the contributions of cropland, grassland, and forest to global soil NO emissions at the national level. The results showed that soil NO emissions were explained mainly by N input, water input and soil pH. Total above-soil NO emissions of the three vegetation cover types were 9.4 Tg N year-1 in 2014, including 5.9 Tg N year-1 (1.04, 95% confidence interval [95% CI]: 0.09-1.99 kg N ha-1  year-1 ) emitted from forest, 1.7 Tg N year-1 (0.68, 95% CI: 0.10-1.26 kg N ha-1  year-1 ) from grassland, and 1.8 Tg N year-1 (0.98, 95% CI: 0.42-1.53 kg N ha-1  year-1 ) from cropland. Soil NO emissions in approximately 57% of 213 countries surveyed were dominated by forests. Our results provide updated inventories of global and national soil NO emissions based on robust data-driven models. These estimates are critical to guiding the mitigation of soil NO emissions and can be used in combination with biogeochemical models.

[Impacts of Climate Change and Human Activities on NDVI Change in Eastern Coastal Areas of China]

Based on the datasets of normalized difference vegetation index (NDVI), temperature, precipitation, and solar radiation and the methods of trend, partial correlation, and residual analyses, this study explored the spatiotemporal variation in NDVI and its response to climate change from 1982 to 2019 in eastern coastal areas of China. Then, the effects of climate change and non-climatic factors (e.g., human activities) on NDVI trends were analyzed. The results showed that:① the NDVI trend varied greatly in different regions, stages, and seasons. On average, the growing season NDVI increased faster during 1982-2000 (stage I) than that during 2001-2019 (stage Ⅱ) in the study area. Moreover, NDVI in spring showed a more rapid increase than that in other seasons in both stages. ② For a given stage, the relationships between NDVI and each climatic factor varied in different seasons. For a given season, the major climatic factors associated with NDVI change were different between the two stages. The relationships between NDVI and each climatic factor showed great spatial differences in the study period. In general, the increase in growing season NDVI in the study area from 1982 to 2019 was closely related to the rapid warming. The increase in precipitation and solar radiation in stage Ⅱ also played a positive role. ③ In the past 38 years, climate change played a greater role in the change in growing season NDVI than non-climatic factors, including human activities. Whereas non-climatic factors dominated the increase in growing season NDVI during stage I, climate change played a major role during stage Ⅱ. We suggest that more attention should be paid to the impacts of various factors on vegetation cover variation during different periods to promote the understanding of terrestrial ecosystem changes.

Global Distribution of Culex tritaeniorhynchus and Impact Factors

Culex tritaeniorhynchus is the primary vector of Japanese encephalitis (JE) and has a wide global distribution. However, the current and future geographic distribution maps of Cx. tritaeniorhynchus in global are still incomplete. Our study aims to predict the potential distribution of Cx. tritaeniorhynchus in current and future conditions to provide a guideline for the formation and implementation of vector control strategies all over the world. We collected and screened the information on the occurrence of Cx. tritaeniorhynchus by searching the literature and online databases and used ten algorithms to investigate its global distribution and impact factors. Cx. tritaeniorhynchus had been detected in 41 countries from 5 continents. The final ensemble model (TSS = 0.864 and AUC = 0.982) indicated that human footprint was the most important factor for the occurrence of Cx. tritaeniorhynchus. The tropics and subtropics, including southeastern Asia, Central Africa, southeastern North America and eastern South America, showed high habitat suitability for Cx. tritaeniorhynchus. Cx. tritaeniorhynchus is predicted to have a wider distribution in all the continents, especially in Western Europe and South America in the future under two extreme emission scenarios (SSP5-8.5 and SSP1-2.6). Targeted strategies for the control and prevention of Cx. tritaeniorhynchus should be further strengthened.

A study of factors impacting disease based on the Charlson Comorbidity Index in UK Biobank

Objective

With advances in medical diagnosis, more people are diagnosed with more than one disease. The damage caused by different diseases varies, so relying solely on the number of diseases to represent multimorbidity is limited. The Charlson comorbidity index (CCI) is widely used to measure multimorbidity and has been validated in various studies. However, CCI's demographic and behavioral risk factors still need more exploration.

Methods

We conduct multivariate logistic regression analysis and restricted cubic splines to examine the influence factors of CCI and the relationship between covariates and risk of CCI, respectively. Our research employs the Multivariate Imputation by Chained Equations method to interpolate missing values. In addition, the CCI score for each participant is calculated based on the inpatient's condition using the International Classification of Diseases, edition 10 (ICD10). Considering the differences in the disease burden between males and females, the research was finally subgroup analyzed by sex.

Results

This study includes 5,02,411 participants (2,29,086 female) with CCI scores ranging from 0 to 98. All covariates differed between CCI groups. High waist-hip ratio (WHR) increases the risk of CCI in both males [OR = 19.439, 95% CI = (16.261, 23.241)] and females [OR = 12.575, 95% CI = (11.005, 14.370)], and the effect of WHR on CCI is more significant in males. Associations between age, Body Mass Index (BMI) and WHR, and CCI risk are J-shaped for all participants, males, and females. Concerning the association between Townsend deprivation index (TDI) and CCI risk, the U-shape was found in all participants and males and varied to a greater extent in males, but it is a J-shape in females.

Conclusions

Increased WHR, BMI, and TDI are significant predictors of poor health, and WHR showed a greater role. The impact of deprivation indices on health showed differences by sex. Socio-economic factors, such as income and TDI, are associated with CCI. The association of social status differences caused by these socioeconomic factors with health conditions should be considered. Factors might interact with each other; therefore, a comprehensive, rational, and robust intervention will be necessary for health.

Taxi drivers' traffic violations detection using random forest algorithm: A case study in China

OBJECTIVE

To effectively explore the impacts of several key factors on taxi drivers' traffic violations and provide traffic management departments with scientific decisions to reduce traffic fatalities and injuries.

METHODS

43,458 electronic enforcement data about taxi drivers' traffic violations in Nanchang City, Jiangxi Province, China, from July 1, 2020, to June 30, 2021, were utilized to explore the characteristics of traffic violations. A random forest algorithm was used to predict the severity of taxi drivers' traffic violations and 11 factors affecting traffic violations, including time, road conditions, environment, and taxi companies were analyzed using the Shapley Additionality Explanation (SHAP) framework.

RESULTS

Firstly, the ensemble method Balanced Bagging Classifier (BBC) was applied to balance the dataset. The results showed that the imbalance ratio (IR) of the original imbalanced dataset reduced from 6.61% to 2.60%. Moreover, a prediction model for the severity of taxi drivers' traffic violations was established by using the Random Forest, and the results showed that accuracy, m_F1, m_G-mean, m_AUC, and m_AP obtained 0.877, 0.849, 0.599, 0.976, and 0.957, respectively. Compared with the algorithms of Decision Tree, XG Boost, Ada Boost, and Neural Network, the performance measures of the prediction model based on Random Forest were the best. Finally, the SHAP framework was used to improve the interpretability of the model and identify important factors affecting taxi drivers' traffic violations. The results showed that functional districts, location of the violation, and road grade were found to have a high impact on the probability of traffic violations; their mean SHAP values were 0.39, 0.36, and 0.26, respectively.

CONCLUSIONS

Findings of this paper may help to discover the relationship between the influencing factors and the severity of traffic violations, and provide a theoretical basis for reducing the traffic violations of taxi drivers and improving the road safety management.

Impact Factors in Chinese Construction Enterprises' Carbon Emission-Reduction Intentions

The reduction in carbon emissions in the construction industry plays an important role in the realization of the goal of carbon peaking and carbon neutrality, especially in China. Construction enterprises' personnel's intentions to reduce their carbon emissions are closely related to low-carbon behavior. However, the research on the impact factors of carbon emission-reduction intention (CERI) is still limited. In order to understand the factors that affect the intentions of construction enterprises' personnel to reduce carbon emissions, and to put forward valuable suggestions for reducing construction enterprises' carbon emissions, it is necessary to explore the impact factors in carbon emission-reduction intention through empirical tests. This study adopted the theory of planned behavior (TPB) based on the three impact factors of behavioral attitude (BA), subjective norms (SNs) and perceived behavioral control (PBC), introduced the two potential impact factors of moral obligation (MO) and government supervision (GS), and also uses structural equation modeling (SEM) to test the impact factors in construction enterprises' personnel's carbon emission-reduction intention. The results show that BA, MO and GS have a significant positive impact on carbon emission-reduction intention (CERI). Among them, BA plays an intermediary role between MO and CERI, and BA and MO play a chain intermediary role between GS and CERI. The research conclusions will help to provide a theoretical reference for governments and construction enterprises to implement carbon emission-reduction development strategies and policies.

An updated clinical prediction model of protein-energy wasting for hemodialysis patients

Background and aim

Protein-energy wasting (PEW) is critically associated with the reduced quality of life and poor prognosis of hemodialysis patients. However, the diagnosis criteria of PEW are complex, characterized by difficulty in estimating dietary intake and assessing muscle mass loss objectively. We performed a cross-sectional study in hemodialysis patients to propose a novel PEW prediction model.

Materials and methods

A total of 380 patients who underwent maintenance hemodialysis were enrolled in this cross-sectional study. The data were analyzed with univariate and multivariable logistic regression to identify influencing factors of PEW. The PEW prediction model was presented as a nomogram by using the results of logistic regression. Furthermore, receiver operating characteristic (ROC) and decision curve analysis (DCA) were used to test the prediction and discrimination ability of the novel model.

Results

Binary logistic regression was used to identify four independent influencing factors, namely, sex (P = 0.03), triglycerides (P = 0.009), vitamin D (P = 0.029), and NT-proBNP (P = 0.029). The nomogram was applied to display the value of each influencing factor contributed to PEW. Then, we built a novel prediction model of PEW (model 3) by combining these four independent variables with part of the International Society of Renal Nutrition and Metabolism (ISRNM) diagnostic criteria including albumin, total cholesterol, and BMI, while the ISRNM diagnostic criteria served as model 1 and model 2. ROC analysis of model 3 showed that the area under the curve was 0.851 (95%CI: 0.799-0.904), and there was no significant difference between model 3 and model 1 or model 2 (all P > 0.05). DCA revealed that the novel prediction model resulted in clinical net benefit as well as the other two models.

Conclusion

In this research, we proposed a novel PEW prediction model, which could effectively identify PEW in hemodialysis patients and was more convenient and objective than traditional diagnostic criteria.

[Water Environmental Characteristics and Water Quality Assessment of Lakes in Tibetan Plateau]

Lakes are an important water resource and biological habitat in the Tibetan Plateau. Owing to the combined influence of climate, topography, and other natural factors as well as human factors, the water environment of the lakes on the Tibetan Plateau is facing more and more severe problems and challenges. To clarify the present status, distribution pattern, main characteristic factors of water quality, and important factors affecting the water quality of lakes on the Tibetan Plateau, the water environment of 12 typical lakes on the Tibet Plateau was investigated in summer (July-August) and autumn (October-November) in 2020. The field sampling and laboratory test data comprehensive analysis showed that:① several physical and chemical parameters of typical lakes on the Tibetan Plateau differed in spatiotemporal distribution. ② Salinity was the main characteristic of water quality in the typical lakes on the Tibetan Plateau. ③ The spatiotemporal distribution of lake eutrophication index showed little diversity and basically ranged from poor nutrition to moderate nutrition. The spatial and temporal distributions in the lake water quality index (WQI) were significantly different. The lake WQI grade decreased from "Moderate" to "Very poor" with the increase in salinity area, and the lake water quality in autumn was better than that in summer. ④ The spatiotemporal differences in lake water quality on the Tibetan Plateau were mainly controlled by precipitation, evapoconcentration, and human activities. This study will provide scientific basis for water environment protection and improvement of water ecosystems on the Tibetan Plateau.

Key Factors, Planning Strategy and Policy for Low-Carbon Transport Development in Developing Cities of China

Exploring key impact factors and their effects on urban residents' transport carbon dioxide (CO₂) emissions is significant for effective low-carbon transport planning. Researchers face the model uncertainty problem to seek a rational and better explanatory model and the key variables in the model set containing various factors after they are arranged and combined. This paper uses the Bayesian Model Averaging method to solve the above problem, explore the key variables, and determine their relative significance and averaging effects. Beijing, Xi'an, and Wuhan are selected as three case cities for their representation of developing Chinese cities. We found that the initial key factor increasing transport emissions is the high dependence on cars, and the second is the geographical location factor that much more suburban residents suffer longer commuting. Developing satellite city rank first for reducing transport emissions due to more local trips with an average short distance, the second is the metro accessibility, and the third is polycentric form. Key planning strategies and policies are proposed: (i) combining policies of car restriction based on vehicle plate number, encouraging clean fuel cars, a carbon tax on oil uses, and rewarding public transit passengers; (ii) fostering subcenters' strong industries to develop self-contained polycentric structures and satellite cities, and forming employment and life circle within 5 km radius; and (iii) integrating bus and rail transit services in the peripheral areas and suburbs and increasing the integration level of muti-modes transferring in transport hubs. The findings will offer empirical evidence and reference value in developing cities globally.

Factors Influencing O3 Concentration in Traffic and Urban Environments: A Case Study of Guangzhou City

Ozone (O₃) pollution is a serious issue in China, posing a significant threat to people's health. Traffic emissions are the main pollutant source in urban areas. NO_X and volatile organic compounds (VOCs) from traffic emissions are the main precursors of O₃. Thus, it is crucial to investigate the relationship between traffic conditions and O₃ pollution. This study focused on the potential relationship between O₃ concentration and traffic conditions at a roadside and urban background in Guangzhou, one of the largest cities in China. The results demonstrated that no significant difference in the O₃ concentration was observed between roadside and urban background environments. However, the O₃ concentration was 2 to 3 times higher on sunny days (above 90 μg/m³) than on cloudy days due to meteorological conditions. The results confirmed that limiting traffic emissions may increase O₃ concentrations in Guangzhou. Therefore, the focus should be on industrial, energy, and transportation emission mitigation and the influence of meteorological conditions to minimize O₃ pollution. The results in this study provide some theoretical basis for mitigation emission policies in China.

Trends and Impact Factors of Mental Health Service Utilization among Resettled Humanitarian Migrants in Australia: Findings from the BNLA Cohort Study

Resettled humanitarian migrants (HMs) have high levels of mental disorders, but factors associated with the utilization of mental health services (MHS) are poorly understood. We aimed to explore trends and impact factors of MHS utilization among HMs in the process of resettlement in Australia. A total of 2311 HMs from the 1st (2013), 3rd, and 5th (2018) waves of a national cohort study were included. MHS utilization in the past year was assessed by two indicators: having MHS contacts and the frequency of MHS contacts. Trends were identified by Cochran-Armitage tests, and generalized linear mixed models and ordered logistic models were fitted to explore impact factors of MHS utilization. The proportion of having MHS contacts significantly rose from 13.0% to 29.4% over the five years. MHS utilization was mainly driven by perceived needs, such as post-traumatic stress disorders and the degree of post-migration stress. Unemployment and strong belongingness to the local community were also associated with having MHS contacts. No significant gender difference was found in having MHS contacts but females tended to contact MHS more frequently. Resettled HMs have a persistent dilemma of high mental illness prevalence and MHS underutilization. Sustainable mental health education and long-term resettlement services targeted at social integration that consider gender difference are urgently needed in host countries.

The impact of diabetes mellitus on pulmonary TB

OBJECTIVE

To compare the clinical characteristics and laboratory results of pulmonary TB (PTB) patients with and without diabetes mellitus (DM) and the relationship between haemoglobin A1C (HbA1c) concentration and mycobacterial load at county level area in Sichuan Province, China.

METHODS

A retrospective study was performed from January 2018 to July 2019 inJianyang People's Hospital, Sichuan Province. Clinical characteristics and laboratory results of newly diagnosed TB patients were collected. Univariable and multivariable logistic regression analyses were performed. The Kruskal-Wallis test was used to compare HbA1c level and mycobacterial load.

RESULTS

The final sample included 415 patients with TB, of whom 45 were diagnosed with DM (10.8%). Uni-variable logistic regression showed that PTB patients with concomitant DM were more likely to present with haemoptysis, positive acid-fast bacilli (AFB) smear, cavity, higher erythrocyte sedimentation rate (ESR), higher serum C-reactive protein (CRP), lower serum albumin (ALB), or higher fasting blood glucose (FBG). Multivariate logistic regression analyses showed that AFB smear positivity (OR 15.81, 95% CI 3.09-80.95) and FBG (OR 1.88, 95% CI 1.53-2.31) were independent risk factors of DMPTB. The mycobacterial load was heaviest when the HbA1c was 7.9 mmol/L (95% CI 7.35-11.1) and declined along with HbA1c rising up. But it has not been significantly associated with HbA1c.

CONCLUSIONS

Patients with PTB over 45 years old, with haemoptysis, positive AFB, cavity, higher ESR, higher CRP, lower ALB or higher FBG are more likely to present with concomitant DM. Patients with PTB with these factors need to be targeted for DM screening. The mycobacterial load has not been significantly associated with HbA1c.

Impacts of Built Environment on Risk of Women's Lung Cancer: A Case Study of China

Built environment factors such as air pollution are associated with the risk of respiratory disease, but few studies have carried out profound investigation. We aimed to evaluate the association between the built environment and Chinese women’s lung cancer incidence data from the China Cancer Registry Annual Report 2017, which covered 345,711,600 people and 449 qualified cancer registries in mainland China. The air quality indicator (PM2.5) and other built environment data are obtained from the China Statistical Yearbook and other official approved materials. An exploratory regression tool is applied by using Chinese women’s lung cancer incidence data (Segi population) as the dependent variable, PM2.5 index and other built environment factors as the independent variables. An apparent clustering region with a high incidence of women’s lung cancer was discovered, including regions surrounding Bohai bay and the three Chinese northeastern provinces, Heilongjiang, Liaoning and Inner Mongolia. Besides air quality, built environment factors were found to have a weak but clear impact on lung cancer incidence. Land-use intensity and the greening coverage ratio were positive, and the urbanization rate and population density were negatively correlated with lung cancer incidence. The role of green spaces in Chinese women’s lung cancer incidence has not been proven.

Temporal and Spatial Heterogeneity of PM2.5 Related to Meteorological and Socioeconomic Factors across China during 2000-2018

In recent years, air pollution caused by PM_2.5 in China has become increasingly severe. This study applied a Bayesian space-time hierarchy model to reveal the spatiotemporal heterogeneity of the PM_2.5 concentrations in China. In addition, the relationship between meteorological and socioeconomic factors and their interaction with PM_2.5 during 2000-2018 was investigated based on the GeoDetector model. Results suggested that the concentration of PM_2.5 across China first increased and then decreased between 2000 and 2018. Geographically, the North China Plain and the Yangtze River Delta were high PM_2.5 pollution areas, while Northeast and Southwest China are regarded as low-risk areas for PM_2.5 pollution. Meanwhile, in Northern and Southern China, the population density was the most important socioeconomic factor affecting PM_2.5 with q values of 0.62 and 0.66, respectively; the main meteorological factors affecting PM_2.5 were air temperature and vapor pressure, with q values of 0.64 and 0.68, respectively. These results are conducive to our in-depth understanding of the status of PM_2.5 pollution in China and provide an important reference for the future direction of PM_2.5 pollution control.

Impact of Neighborhood Environment on Pedestrian Route Selection among Elementary Schoolchildren in Korea

Previous studies on the walking environment of elementary school students have focused on physical factors such as traffic accidents, safety, and the neighborhood environment. However, scholars have yet to consider the behavioral characteristics of elementary school students, particularly in respect to the relationship between environmental factors and behavioral characteristics in pedestrian route selection and safety. Addressing this gap, this study identifies how neighborhood environment factors and behavioral characteristics impact route selection and satisfaction among elementary school students. Accordingly, this study surveyed 251 elementary school students at three elementary schools in Korea and analyzed the spatial forms of the selected sites. In doing so, this study discerns students’ satisfaction with their selection of the shortest or non-shortest route and which environmental factors and behavioral characteristics influenced their selection and satisfaction. Study results have practical implications for policymaking, including valuable insights into the planning of school routes for elementary school students.

The Roles of Sono-induced Nitrosation and Nitration in the Sono-degradation of Diphenylamine in Water: Mechanisms, Kinetics and Impact Factors

The potential risks of sono-induced nitrosation and nitration side reactions and consequent toxic nitrogenous byproducts were first investigated via sono-degradation of diphenylamine (DPhA) in this study. The kinetic models for overall DPhA degradation and the formation of nitrosation byproduct (N-nitrosodiphenylamine, NDPhA) and nitration byproducts (2-nitro-DPhA and 4-nitro-DPhA) were well established and fitted (R² > 0.98). Nitrosation contributed much more than nitration (namely, 43.3 - 47.3 times) to the sono-degradation of DPhA. The contribution of sono-induced nitrosation ranged from 0.4 to 56.6% at different conditions. The maximum NDPhA formation rate and the contribution of sono-induced nitrosation were obtained at 600 and 200 kHz, respectively, as ultrasonic frequencies at 200 to 800 kHz. Both NDPhA formation rate and the contribution of sono-induced nitrosation increased with increasing power density, while decreased with increasing initial pH and DPhA concentration. PO₄^3-, HCO₃^-, NH₄⁺ and Fe²⁺ presented negative impacts on sono-induced nitrosation in order of HCO₃^- >> Fe²⁺ > PO₄^3- > NH₄⁺, while Br^- exhibited a promoting effect. The mechanism of NDPhA formation via sono-induced nitrosation was first proposed.

Evaluating Fertilizer Use Efficiency and Spatial Correlation of Its Determinants in China: A Geographically Weighted Regression Approach

Improving fertilizer use efficiency (FUE) is an effective means to reduce fertilizer use and environmental contamination. Few studies have considered the spatial effects of FUE and its determinants. This paper calculated the FUE of agricultural production by adopting panel data on 31 provinces in China from 2007 to 2017 using a stochastic frontier method with a heteroscedastic inefficiency term, and discussed the spatial characteristics. Further, the geographical weighted regression model (GWR) was employed to examine the spatial impact of factors on FUE and revealed the spatial dispersion and agglomeration effect. The results show that averaged FUE in China was 0.722, and had a significantly decreasing trend with a significant regional difference and spatial positive correlation in different provinces. The non-agricultural employment ratio was the leading factor for increasing FUE, and its degree of influence showed a decreasing trend from eastern to western China. The different agricultural industry development modes, crop planting patterns adjustment, labor transfer, and policy incentive systems for increasing the non-agricultural employment ratio should be developed for different regions. Farmers’ income had a negative impact on FUE, but the influence degree decreased annually. Education level had a negative impact on FUE and was relatively weak, but the influence degree was increasing. This should strengthen the exploration of a scientific and practical technical training system for farmers on fertilizer use while improving educational levels in different regions on the basis of local characteristics. The impact of disasters on FUE depended on their severity, and a combined weather and disaster forecasting mechanism should be developed.

The residents' mental health status and community's role during the COVID-19 pandemic: a community-based cross-sectional study in China

Background

The related research of coronavirus disease 2019 (COVID-19) pandemic on the mental health of community residents is still lacking. Here we reported the mental health status of Chinese residents as well as the community’s prevention and control during the pandemic period of COVID-19 and further explored the influencing factors of mental status.

Methods

In this cross-sectional study, convenience sampling and snowball sampling methods were adopted from February 16 to February 23, 2020, and Chinese community residents were included according to the inclusion and exclusion criteria. Three questionnaires, including General Anxiety Disorder 7 (GAD-7), Patient Health Questionnaire 9 (PHQ-9), and a self-designed “Community prevention and control questionnaire”, were used. A multivariate linear regression analysis was conducted to analyze the impact factors of anxiety and depression.

Results

A total of 3,001 community residents were included in this study. In total, 85.6% and 83.7% of participants had minimal anxiety and depression, respectively. Among all the community residents, 16.6% of participants proved that the communities they lived in had confirmed cases. 95.3% of participants reported that the residents were screened for mobility and contact history. 97.8% of participants reported the entrance and exit of the community were managed in their communities. There were 97.5% and 99% of participants needed to take body temperature and wear masks in their communities. Ninety-two percent (92%) of communities have their public areas and facilities disinfected daily, and 95.4% of communities have conducted health education about COVID-19. Factors including gender, education level, chronic illness, the frequency of going out, achieving information about COVID-19 by community and newspaper, and confirmed cases in the community, show association with community residents’ anxiety and depression.

Conclusions

The vast majority of Chinese residents have little anxiety and depression, and most communities have adopted standardized control measures following the government’s regulations and policy, which plays a vital role in the control of COVID-19 and improving residents’ anxiety and depression.

How do sustained birth tears after vaginal birth affect birth tear patterns in a subsequent birth?

Background Tears are common after vaginal birth, and different impact factors are known. However, the impact of tears from a previous birth to the tears of a subsequent birth is unknown. Therefore, we aimed to evaluate the distribution of birth tear patterns according to the sustained tears in a previous birth, in addition to other impact factors. Methods In a retrospective cohort study, we evaluated all women up to parity 4 with subsequent vaginal, singleton births of vertex presentation at ≥37 + 0 gestational weeks between 1/2005 and 12/2016. Their tears were grouped into tear patterns and were analyzed by parity. Tear patterns in the subsequent births were analyzed in association to the patterns of the previous births and impact factors were evaluated. Results We counted 4017 births in 1855 women [P1: 1368 (34.1%), P2: 1730 (43.1%), P3: 741 (18.4%), P4: 178 (4.4%)]. The frequency of tears and episiotomies decreased with higher parity, whereas the frequency of intact perineum increased. Twenty-eight different unique tear patterns were found. We could show that birth tear patterns changed with increasing parity and were associated with sustained tears in a previous birth. In addition, some impact factors on tear patterns could be identified. Conclusion The distribution of the single tear types is in accordance with the current literature. However, it is new that distinct tear patterns are associated to sustained tear patterns of previous births. Furthermore, we demonstrated some weak associations of tear patterns to certain impact factors, such as more episiotomies, low-grade perineal or vaginal tears isolated or in combination with other tears with increasing fetal weight and head circumference in the higher parities, and with a longer duration of the second stage and the pushing phase in lower parities.

Does the Connectivity of Urban Public Green Space Promote Its Use? An Empirical Study of Wuhan

A high greenness level can enhance green space use and outdoor physical activity. However, rapid urbanization and high-density development have led to the loss or fragmentation of green space, especially urban public green space (PGS). With the aim of increasing the health benefits from PGS, some planners and researchers suggest connecting existing PGSs to encourage urban residents to use the PGS, and thus, to improve public health. Does this suggestion stand with robustness? By taking 42 sub-districts in the inner area of Wuhan as the study objects, this paper examines the correlation between the connectivity of PGS and its use. We also explore how the characteristics of PGS and the facilities/functions in the neighboring areas influence this relationship by using Location Based Service data (WeChat-Yichuxing data), point of interest (POI) data, and remote-sensing image, etc. Using Regression Analysis, we found that there is no high correlation between PGS use and its connectivity. The possible causes might be attributed to the fact that PGS use is profoundly influenced by multifaceted competing impact factors, and no one can stand dominantly. It is interesting to see that the density of companies is positively, but slightly, related to PGS use.

Games academics play and their consequences: how authorship, h-index and journal impact factors are shaping the future of academia

Research is a highly competitive profession where evaluation plays a central role; journals are ranked and individuals are evaluated based on their publication number, the number of times they are cited and their h-index. Yet such evaluations are often done in inappropriate ways that are damaging to individual careers, particularly for young scholars, and to the profession. Furthermore, as with all indices, people can play games to better their scores. This has resulted in the incentive structure of science increasingly mimicking economic principles, but rather than a monetary gain, the incentive is a higher score. To ensure a diversity of cultural perspectives and individual experiences, we gathered a team of academics in the fields of ecology and evolution from around the world and at different career stages. We first examine how authorship, h-index of individuals and journal impact factors are being used and abused. Second, we speculate on the consequences of the continued use of these metrics with the hope of sparking discussions that will help our fields move in a positive direction. We would like to see changes in the incentive systems, rewarding quality research and guaranteeing transparency. Senior faculty should establish the ethical standards, mentoring practices and institutional evaluation criteria to create the needed changes.

Induced complete remission faster in adult patients with acquired pure red cell aplasia by combining cyclosporine A with corticosteroids

To evaluate whether the adult patients with acquired pure red cell aplasia (PRCA) could benefit more from cyclosporine A (CsA) combined with corticosteroids (CS) than CsA or CS alone.Seventy-three patients were evaluated in 2 institutions (6 patients lost to follow-up).The induction therapy included CsA (n = 21), CS (n = 21), or CsA combined with CS (n = 31), and remission was achieved in 16/21 (76.2%), 10/21 (47.6%), and 21/31 (71.0%) patients, respectively. Higher complete remission (CR) rate was achieved in CsA combined with CS group than in CS group (61.3% vs 19.0%, P = .003). Patients achieved CR faster in CsA combined with CS group than in CS group or CsA group (median time, 1 month vs 2 month vs 3 month, P = .010). By multivariate analysis, CsA combined with CS therapy and primary PRCA were the influence factors for CR rate. Twenty-seven patients relapsed due to discontinuation or tapering therapy, and 19 patients regained response by increasing the dose of original regimens or changing to other immunosuppressive therapy. Complete remission to induction therapy was a correlative factor for death (P = .035).CsA combined with CS produced faster and higher CR rate in treating adult patients with PRCA than did CsA or CS alone.

Bibliometrics in a digital age: help or hindrance

Bibliometrics are a range of techniques and quantitative measures that provide an analysis of written publications such as books and articles, and which assess the impact of research outputs. They are commonly applied to individual authors in the form of citation metrics but can also be used to assess the influence of research groups or even entire institutions. With the increased importance of social media as a means of communicating and publicising research findings, additional alternative measures of impact (altmetrics) are now being used. In addition to analysing the reach of a research output, bibliometrics can also be used as search tools to identify related and updated research, author networks and connections between institutions. This review summarises the range of tools and services that are available, their advantages and disadvantages, and some of the challenges and issues presented by the existence of multiple digital versions of research outputs.

Impact factors on fetal descent rates in the active phase of labor: a retrospective cohort study

AIM

To assess fetal descent rates of nulliparous and multiparous women in the active phase of labor and to evaluate significant impact factors.

METHODS

In a retrospective cohort study at the University Hospital of Zurich, Switzerland, we evaluated 6045 spontaneous vaginal deliveries with a singleton in vertex presentation between January 2007 and July 2014 at 34 0/7 to 42 0/7 gestational weeks. Median fetal descent rates and their 10th and 90th percentiles were assessed in the active phase of labor and different impact factors were evaluated.

RESULTS

Fetal descent rates are exponentially increasing. Nulliparous women have slower fetal descent than multiparous women (P<0.001), ranging from 0 to 5.81 cm/h and from 0 to 15 cm/h, respectively. The total duration of fetal descent in labor is 5.42 h for nulliparous and 2.71 h for multiparous women. Accelerating impact factors are a lower fetal station, multiparity, increasing maternal weight and fetal occipitoanterior position, whereas epidural anesthesia decelerates fetal descent (P<0.001).

CONCLUSIONS

Fetal descent is a hyperbolic increasing process with faster descent in multiparous women compared to nulliparous women, is highly inter individual and is associated with different impact factors. The diagnosis of labor arrest or prolonged labor should therefore be based on such rates as well as on individual evaluation of every parturient.

Impact Factors for Perioperative Morbidity and Mortality and Repercussion of Perioperative Morbidity and Long-term Survival in Pancreatic Head Resection

Background

The focus of the present study was to reveal any impact factors for perioperative morbidity and mortality as well as repercussion of perioperative morbidity on long-term survival in pancreatic head resection.

Patients and methods

In a retrospective study, clinic-pathological factors of 240 patients after pancreatic head (PD) or total resection were analyzed for correlations with morbidity, 30- and 90-day mortality, and long-term survival. According to Clavien–Dindo classification, all complications with grade II and more were defined as overall complications (OAC). OAC, all surgical (ASC), general (AGC) and some specific types of complications like leaks from the pancreatoenteric anastomosis (PEA) or pancreatic fistula (PF, type A, B and C), leaks from other anastomoses (OL), bleeding (BC) and abscesses (AA) were studied for correlation with clinic-pathological factors.

Results

In the 9-year period, altogether 240 patients had pancreatic resection. The incidence of OAC was 37.1%, ASC 29.2% and AGC 15.8%. ASC presented themselves as PL, OL, BC and AA in 19% (of 208 PD), 5.8%, 5.8%, and 2.5% respectively. Age, ASA score, amylase on drains, and pancreatic fistulas B and C correlated significantly with different types of complications. Overall 30- and 90-day mortalities were 5 and 7.9% and decreased to 3.5 and 5% in P2.

Conclusions

High amylase on drains and higher mean age were independent indicators of morbidity, whereas PL and BC revealed as independent predictor for 30-day mortality, and physical status, OAC and PF C for 90-day mortality.

Impact factors on cervical dilation rates in the first stage of labor

AIMS

To assess cervical dilation rates of nulliparous and multiparous women in the active first stage of labor and to evaluate significant impact factors.

METHODS

In a retrospective cohort study between January 2007 and July 2014 at the University Hospital of Zurich in Switzerland, we analyzed 8378 women with singleton pregnancies in vertex presentation with a vaginal delivery at 34+0 to 42+5 gestational weeks. Median cervical dilation rates were calculated and different impact factors evaluated.

RESULTS

Cervical dilation rates increase during labor progress with faster rates in multiparous compared with nulliparous women (P<0.001). Dilation rates exceed 1 cm/h at a dilatation of 6-7 cm, but are very individual. Accelerating impact factors are multiparity, a greater amount of cervical dilation and fetal occipitoanterior position, whereas the use of epidural anesthesia, a higher fetal weight and head circumference decelerate dilation (P<0.001).

CONCLUSION

Cervical dilation is a hyperbolic increasing process, with faster dilation rates in multiparous compared to nulliparous women and a reversal point of labor around 6-7 cm, respectively. Besides, cervical dilation is highly individual and affected by several impact factors. The diagnosis of labor arrest or prolonged labor should therefore be based on such rates and on the individual evaluation of every woman.

Factors Associated with the Competencies of Public Health Workers in Township Hospitals: A Cross-Sectional Survey in Chongqing Municipality, China

Purpose: This study aimed to explore the competencies of public health workers (PHWs) of township hospitals in Chongqing Municipality (China), and determine the related impact factors of the competencies of PHWs; Methods: A cross-sectional research was conducted on 314 PHWs from 27 township hospitals in three districts in Chongqing Municipality (China), from June to August 2014. A self-assessment questionnaire was established on the basis of literature reviews and a competency dictionary. The differences in competencies among the three districts were determined by adopting the chi-square test, t-test, analysis of variance (ANOVA) method, and the impact factors of the competencies of PHWs were determined by adopting stepwise regression analysis. Results: (1) Results of the demographic characteristics of PHWs in three sample districts of Chongqing Municipality showed that a significant difference in age of PHWs (p = 0.021 < 0.05) and the majors of PHWs (p = 0.045 < 0.05); (2) In terms of the self-evaluation competency results of PHWs in township hospitals, seven among the 11 aspects were found to have significant differences in the three districts by the ANOVA test; (3) By adopting the t-test and ANOVA method, results of the relationship between the characteristics of PHWs and their competency scores showed that significant differences were found in the economic level (p = 0.000 < 0.05), age (p = 0.000 < 0.05), years of working (p = 0.000 < 0.05) and title of PHWs (p = 0.000 < 0.05); (4) Stepwise regression analysis was used to determine the impact factors of the competencies of PHWs in township hospitals, including the economic level (p = 0.000 < 0.001), years of working (p = 0.000 < 0.001), title (p = 0.001 < 0.005), and public health major (p = 0.007 < 0.01). Conclusions: The competencies of the township hospital staff in Chongqing Municipality (China), are generally insufficient, therefore, regulating the medical education and training skills of PHWs is crucial to improve the competencies of PHWs in the township hospitals of Chongqing Municipality. The results of this study can be mirrored in other areas of China.

Bibliometric Analyses of Physical and Occupational Therapy Faculty across Canada Indicate Productivity and Impact of Rehabilitation Research

PURPOSE

This study examines physical and occupational therapy faculty across Canada, using bibliometrics and federal funding as indicators of academic impact, and considers the validity of various bibliometric indices.

METHODS

Faculty members were identified and their rank, professional designation, and department obtained from faculty Web sites. Bibliometric indicators were determined using Publish or Perish software. An independent author (not a faculty member) inspected the data to remove any incorrectly attributed publications. The h-index, citation years, g-index, and total number of citations for each faculty member were retrieved. The Canadian Institutes of Health Research (CIHR) funding database was used to determine the amount of research funding provided to each faculty member as a principal investigator (PI) and his or her total CIHR funding received. Mean faculty indicators by university, rank, gender, and profession were determined. Analysis of variance (ANOVA) was used to detect differences by rank and gender, and measures of association (Pearson correlation coefficients and multiple regression) were used to identify factors that affected h-index and PI funding received.

RESULTS

A total of 347 physical and occupational therapy faculty were identified. The median h-index was 5 (inter-quartile range [IQR] 2-8) for assistant professors, 11 (IQR 7-15) for associate professors, and 18 (IQR 12-26) for full professors. ANOVA indicated no significant differences between male and female faculty in terms of h-index or funding received. Regression analysis indicated that 58% of h-index variance could be explained by gender (p=0.039), appointment within a department that provides a (rehabilitation science) PhD programme (p<0.001), rank (p<0.001), CIHR PI funding (p=0.001), or total CIHR funding (p<0.001). Significant predictors of the amount of CIHR funding received as a PI included h-index (p<0.001) and total number of citations (p=0.023), which together explained 27% of the variation in funding received.

CONCLUSION

The h-index, although not without flaws, provides a useful metric that indicates that physical and occupational faculty in Canada are productive scientists having a measurable impact and that this impact increases with rank and greater funding.

Nine criteria for a measure of scientific output

Scientific research produces new knowledge, technologies, and clinical treatments that can lead to enormous returns. Often, the path from basic research to new paradigms and direct impact on society takes time. Precise quantification of scientific output in the short-term is not an easy task but is critical for evaluating scientists, laboratories, departments, and institutions. While there have been attempts to quantifying scientific output, we argue that current methods are not ideal and suffer from solvable difficulties. Here we propose criteria that a metric should have to be considered a good index of scientific output. Specifically, we argue that such an index should be quantitative, based on robust data, rapidly updated and retrospective, presented with confidence intervals, normalized by number of contributors, career stage and discipline, impractical to manipulate, and focused on quality over quantity. Such an index should be validated through empirical testing. The purpose of quantitatively evaluating scientific output is not to replace careful, rigorous review by experts but rather to complement those efforts. Because it has the potential to greatly influence the efficiency of scientific research, we have a duty to reflect upon and implement novel and rigorous ways of evaluating scientific output. The criteria proposed here provide initial steps toward the systematic development and validation of a metric to evaluate scientific output.

Continuously variable rating: a new, simple and logical procedure to evaluate original scientific publications

OBJECTIVE

Impact Factors (IF) are widely used surrogates to evaluate single articles, in spite of known shortcomings imposed by cite distribution skewness. We quantify this asymmetry and propose a simple computer-based procedure for evaluating individual articles.

METHOD

(a) Analysis of symmetry. Journals clustered around nine Impact Factor points were selected from the medical ''Subject Categories'' in Journal Citation Reports 2010. Citable items published in 2008 were retrieved and ranked by granted citations over the Jan/2008 - Jun/2011 period. Frequency distribution of cites, normalized cumulative cites and absolute cites/decile were determined for each journal cluster. (b) Positive Predictive Value. Three arbitrarily established evaluation classes were generated: LOW (1.3≤IF<2.6); MID: (2.6≤IF<3.9); HIGH: (IF≥3.9). Positive Predictive Value for journal clusters within each class range was estimated. (c) Continuously Variable Rating. An alternative evaluation procedure is proposed to allow the rating of individually published articles in comparison to all articles published in the same journal within the same year of publication. The general guiding lines for the construction of a totally dedicated software program are delineated.

RESULTS AND CONCLUSIONS

Skewness followed the Pareto Distribution for (1<K<2). Observed Positive Predictive Values ranged from 24 - 43% for over 98% of the selected journals in the ISI database. Continuously Variable Rating is shown to be a simple computer based procedure capable of accurately providing a valid rating for each article within the journal and time frame in which it was published.