Technology-supported shared decision-making in chronic conditions: A systematic review of randomized controlled trials

OBJECTIVES

To describe the role of patients with a chronic disease, healthcare professionals (HCPs) and technology in shared decision making (SDM) and the use of clinical decision support systems (CDSSs), and to evaluate the effectiveness of SDM and CDSSs interventions.

METHODS

Randomized controlled studies published between 2011 and 2021 were identified and screened independently by two reviewers, followed by data extraction and analysis. SDM elements and interactive styles were identified to shape the roles of patients, HCPs and technology.

RESULTS

Forty-three articles were identified and reported on 21 SDM-studies, 15 CDSS-studies, 2 studies containing both an SDM-tool and a CDSS, and 5 studies with other decision support components. SDM elements were mostly identified in SDM-tools and interactions styles were least common in the other decision support components.

CONCLUSIONS

Patients within the included RCTs mainly received information from SDM-tools and occasionally CDSSs when it concerns treatment strategies. HCPs provide and clarify information using SDM-tools and CDSSs. Technology provides interactions, which can support more active SDM. SDM-tools mostly showed evidence for positive effects on SDM outcomes, while CDSSs mostly demonstrated positive effects on clinical outcomes.

PRACTICE IMPLICATIONS

Technology-supported SDM has potential to optimize SDM when patients, HCPs and technology collaborate well together.

Socio-economic variables improve accuracy and change spatial predictions in species distribution models

In an era marked by increasing anthropogenic pressure, understanding the relations between human activities and wildlife is crucial for understanding ecological patterns, effective conservation, and management strategies. Here, we explore the potential and usefulness of socio-economic variables in species distribution modelling (SDM), focusing on their impact on the occurrence of wild mammals in Poland. Beyond the environmental factors commonly considered in SDM, like land-use, the study tests the importance of socio-economic characteristics of local human societies, such as age, income, working sector, gender, education, and village characteristics for explaining distribution of diverse mammalian groups, including carnivores, ungulates, rodents, soricids, and bats. The study revealed that incorporating socio-economic variables enhances the predictive power for >60 % of species and overall for most groups, with the exception being carnivores. For all the species combined, among the 10 predictors with highest predictive power, 6 belong to socio-economic group, while for specific species groups, socio-economic variables had similar predictive power as environmental variables. Furthermore, spatial predictions of species occurrence underwent changes when socio-economic variables were included in the model, resulting in a substantial mismatch in spatial predictions of species occurrence between environment-only models and models containing socio-economic variables. We conclude that socio-economic data has potential as useful predictors which increase prediction accuracy of wildlife occurrence and recommend its wider usage. Further, to our knowledge this is a first study on such a big scale for terrestrial mammals which evaluates performance based on presence or absence of socio-economic predictors in the model. We recognise the need for a more comprehensive approach in SDMs and that bridging the gap between human socio-economic dynamics and ecological processes may contribute to the understanding of the factors influencing biodiversity.

The potential range of west Asian apple species Malus orientalis Uglitzk. under climate change

The wild relatives of cultivated apples would be an ideal source of diversity for breeding new varieties, which could potentially grow in diverse habitats shaped by climate change. However, there is still a lack of knowledge about the potential distribution of these species. The aim of the presented work was the understand the impacts of climate change on the potential distribution and habitat fragmentation of Caucasian crab apple (Malus orientalis Uglitzk.) and the designation of areas of high interest according to climatic conditions. We used the MaxEnt models and Morphological-Spatial Analysis (MSPA) to evaluate the potential distribution, suitability changes, habitat fragmentation, and connectivity throughout the species range in Turkey, Armenia, Georgia, Russia, and Iran. The results revealed that the potentially suitable range of M. orientalis encompasses 858,877 km², 635,279 km² and 456,795 km² under the present, RCP4.5 and RCP8.5 scenario, respectively. The range fragmentation analysis demonstrated a notable shift in the edge/core ratio, which increased from 50.95% in the current scenario to even 67.70% in the future. The northern part of the range (Armenia, northern Georgia, southern Russia), as well as the central and western parts of Hyrcania will be a core of the species range with suitable habitats and a high connectivity between M. orientalis populations and could work as major refugia for the studied species. However, in the Zagros and central Turkey, the potential range will shrink due to the lack of suitable climatic conditions, and the edge/core ratio will grow. In the southern part of the range, a decline of M. orientalis habitats is expected due to changing climatic conditions. The future outlook suggests that the Hyrcanian forest and the Caucasus region could serve as important refuges for M. orientalis. This study helps to understand spatial changes in species' range in response to climate change and can help develop conservation strategies. This is all the more important given the species' potential use in future breeding programs aimed at enriching the gene pool of cultivated apple varieties.

Refining Ixodes scapularis (Acari: Ixodidae) distribution models: a comparison of current methods to an established protocol

Blacklegged ticks (Ixodes scapularis Say) pose an enormous public health risk in eastern North America as the vector responsible for transmitting 7 human pathogens, including those causing the most common vector-borne disease in the United States, Lyme disease. Species distribution modeling is an increasingly popular method for predicting the potential distribution and subsequent risk of blacklegged ticks, however, the development of such models thus far is highly variable and would benefit from the use of standardized protocols. To identify where standardized protocols would most benefit current distribution models, we completed the "Overview, Data, Model, Assessment, and Prediction" (ODMAP) distribution modeling protocol for 21 publications reporting 22 blacklegged tick distribution models. We calculated an average adherence of 73.4% (SD ± 29%). Most prominently, we found that authors could better justify and connect their selection of variables and associated spatial scales to blacklegged tick ecology. In addition, the authors could provide clearer descriptions of model development, including checks for multicollinearity, spatial autocorrelation, and plausibility. Finally, authors could improve their reporting of variable effects to avoid undermining the models' utility in informing species-environment relationships. To enhance future model rigor and reproducibility, we recommend utilizing several resources including the ODMAP protocol, and suggest that journals make protocol compliance a publication prerequisite.

Investigating the Impact of AI on Shared Decision-Making in Post-Kidney Transplant Care (PRIMA-AI): Protocol for a Randomized Controlled Trial

BACKGROUND

Patients after kidney transplantation eventually face the risk of graft loss with the concomitant need for dialysis or retransplantation. Choosing the right kidney replacement therapy after graft loss is an important preference-sensitive decision for kidney transplant recipients. However, the rate of conversations about treatment options after kidney graft loss has been shown to be as low as 13% in previous studies. It is unknown whether the implementation of artificial intelligence (AI)-based risk prediction models can increase the number of conversations about treatment options after graft loss and how this might influence the associated shared decision-making (SDM).

OBJECTIVE

This study aims to explore the impact of AI-based risk prediction for the risk of graft loss on the frequency of conversations about the treatment options after graft loss, as well as the associated SDM process.

METHODS

This is a 2-year, prospective, randomized, 2-armed, parallel-group, single-center trial in a German kidney transplant center. All patients will receive the same routine post-kidney transplant care that usually includes follow-up visits every 3 months at the kidney transplant center. For patients in the intervention arm, physicians will be assisted by a validated and previously published AI-based risk prediction system that estimates the risk for graft loss in the next year, starting from 3 months after randomization until 24 months after randomization. The study population will consist of 122 kidney transplant recipients >12 months after transplantation, who are at least 18 years of age, are able to communicate in German, and have an estimated glomerular filtration rate <30 mL/min/1.73 m2. Patients with multi-organ transplantation, or who are not able to communicate in German, as well as underage patients, cannot participate. For the primary end point, the proportion of patients who have had a conversation about their treatment options after graft loss is compared at 12 months after randomization. Additionally, 2 different assessment tools for SDM, the CollaboRATE mean score and the Control Preference Scale, are compared between the 2 groups at 12 months and 24 months after randomization. Furthermore, recordings of patient-physician conversations, as well as semistructured interviews with patients, support persons, and physicians, are performed to support the quantitative results.

RESULTS

The enrollment for the study is ongoing. The first results are expected to be submitted for publication in 2025.

CONCLUSIONS

This is the first study to examine the influence of AI-based risk prediction on physician-patient interaction in the context of kidney transplantation. We use a mixed methods approach by combining a randomized design with a simple quantitative end point (frequency of conversations), different quantitative measurements for SDM, and several qualitative research methods (eg, records of physician-patient conversations and semistructured interviews) to examine the implementation of AI-based risk prediction in the clinic.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06056518; https://clinicaltrials.gov/study/NCT06056518.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/54857.

Effects of climate on the distribution and conservation of commonly observed European earthworms

Belowground biodiversity distribution does not necessarily reflect aboveground biodiversity patterns, but maps of soil biodiversity remain scarce because of limited data availability. Earthworms belong to the most thoroughly studied soil organisms and-in their role as ecosystem engineers-have a significant impact on ecosystem functioning. We used species distribution modeling (SDMs) and available data sets to map the spatial distribution of commonly observed (i.e., frequently recorded) earthworm species (Annelida, Oligochaeta) across Europe under current and future climate conditions. First, we predicted potential species distributions with commonly used models (i.e., MaxEnt and Biomod) and estimated total species richness (i.e., number of species in a 5 × 5 km grid cell). Second, we determined how much the different types of protected areas covered predicted earthworm richness and species ranges (i.e., distributions) by estimating the respective proportion of the range area. Earthworm species richness was high in central western Europe and low in northeastern Europe. This pattern was mainly associated with annual mean temperature and precipitation seasonality, but the importance of predictor variables to species occurrences varied among species. The geographical ranges of the majority of the earthworm species were predicted to shift to eastern Europe and partly decrease under future climate scenarios. Predicted current and future ranges were only poorly covered by protected areas, such as national parks. More than 80% of future earthworm ranges were on average not protected at all (mean [SD] = 82.6% [0.04]). Overall, our results emphasize the urgency of considering especially vulnerable earthworm species, as well as other soil organisms, in the design of nature conservation measures.

Shared decision-making and its influencing factors among parents of children with cancer in China: A cross-sectional study

PURPOSE

This study aimed at exploring SDM implementation and its influencing factors, and preferences towards SDM among parents of children with cancer in China.

DESIGN AND METHODS

This cross-sectional study recruited 204 participants from 2 grade-A tertiary hospitals in Guangzhou, China. The preferences towards decision-making, the status of SDM were measured by CPS-P and SDM-Q-9. The nurse support were measure by NPST, the needs of parents were measured by Questionnaire for Needs of Parents Whose Children are in PICU, and sociodemographic and disease-related questionnaires were used to investigate general information of children and parents. Descriptive statistics, univariate analysis, and multivariable linear regression were used for data analysis.

RESULTS

Of 204 participants, about half of parents (55.4 %) tended to choose SDM, however, 40.2 % of them still show passive attitudes. The mean SDM-Q-9 score was 31.07 ± 8.74, and the result showed that age (β = 2.480, P＜0.05), relapse (β = 4.407, P＜0.01), course of disease (β = -5.213, P＜0.01), relationships with doctors (β = -4.05, P＜0.05), trust in doctors (β = -2.796, P＜0.05), and communication and information support from nurses (β = 0.651, P＜0.01) were the main factors influencing SDM for parents.

CONCLUSIONS

Over half of Chinese parents tended to choose SDM, but their real participation in SDM is unsatisfactory. Parents who were older, had good relationships with doctors, trusted in doctors, received more communication and information support from nurses, and whose children had shorter course of disease, suffered relapses, participated in SDM better.

Muscling mussels: Understanding the invasive potential of the South American bivalve Mytella strigata (Hanley, 1843) in the Northern Indian Ocean

In past decades, non-native species invasion has emerged as one of the leading drivers of biodiversity loss in terrestrial and aquatic ecosystems globally. In aquatic ecosystems, invasion by bivalve species has increased substantially due to their evolutionary resilience and adaptability. This study aimed to determine the habitat suitability of the South American bivalve Mytella strigata in the northern Indian Ocean using Species distribution modelling. The species occurrence and environmental data for model building were extracted from GBIF, Bio-ORACLE, The World Bank Data Catalogue and GMED. Pearson's correlation (<0.7) and Variance inflation factor (<10) analyses were used to select the environmental covariates. Individual models were built by combining the native range occurrence data of Mytella strigata with the bioclimatic data under the current climatic setting. Ten individual models were built and ensembled to create the final model using the biomod2 package. The variable importance score and the response curve plot were used to identify the most crucial variable and its influence on the models. Distance to port had the highest influence on predicting the distribution of Mytella strigata. The results indicated that the western coast of India as more susceptible to invasion. Our predictions indicate that the species has the potential to become highly invasive in the region, given the vast habitat suitability and documented introduction and presence of the species in the region. This research generated baseline information on the habitat suitability of M. strigata that will aid in managing and restricting its spread in the region. Considering the substantial impact of the species in other introduced ranges worldwide, immediate action should be initiated for the swift management of M. strigata from the Indian coast.

Spatial distribution dynamics for Epimedium brevicornum Maxim. from 1970 to 2020

At different time scales, a species will experience diverse distribution changes. For Epimedium brevicornum Maxim, the phenomenon is obvious, but the understanding of the spatial dynamics of E. brevicornum under distinct time scales is poor. In this study, we modeled the potential distribution for E. brevicornum for five time scales, 1970-1979, 1980-1989, 1990-1999, 2000-2009, and 2010-2019, with different occurrence data, and the Kuenm package was used to optimize the parameter combination. Then, SDM tools and a Venn diagram were utilized to simulate the changes in highly suitable areas and spatial dynamics, respectively. Comprehensive results show that temperature seasonality (BIO4, 37.54%) has the greatest effect on the distribution of E. brevicornum, followed by minimum temperature (TMIN, 21.42%). The areas of distribution for E. brevicornum are 35.06 × 105 km2, 25.7 × 105 km2, 67.64 × 105 km2, 27.29 × 105 km2, and 9.87× 105 km2, which are mainly concentrated in Gansu, Shaanxi, Shanxi, and Henan, respectively. In addition, the largest regions for expansion, stability, and contraction under various time scales are 5.6 × 105 km2, 3.54 × 105 km2, and 3.47 × 105 km2, respectively. These changes indicate that approximately 7.96% of the regions are highly stable, and three critical counties, Wanyuan, Chenggu, and Hechuan, and Xixiang, have become significant areas for migration. Overall, our results indicate that there are different spatial distribution patterns and dynamics for E. brevicornum for different time scales. Given these results, this study also proposes comprehensive strategies for the conservation and management of E. brevicornum, which will further improve the current resource utilization status.

Global potential distribution of mangroves: Taking into account salt marsh interactions along latitudinal gradients

Mangrove is one of the most productive and sensitive ecosystems in the world. Due to the complexity and specificity of mangrove habitat, the development of mangrove is regulated by several factors. Species distribution models (SDMs) are effective tools to identify the potential habitats for establishing and regenerating the ecosystem. Such models usually include exclusively environmental factors. Nevertheless, recent studies have challenged this notion and highlight the importance of including biotic interactions. Both factors are necessary for a mechanistic understanding of the mangrove distribution in order to promote the protection and restoration of mangroves. Thus, we present a novel approach of combining environmental factors and interactions with salt marsh for projecting mangrove distributions at the global level and within latitudinal zones. To test the salt marsh interaction, we fit the MaxEnt model with two predicting sets: (1) environments only and (2) environments + salt marsh interaction index (SII). We found that both sets of models had good predictive ability, although the SII improved model performance slightly. Potential distribution areas of mangrove decrease with latitudes, and are controlled by biotic and abiotic factors. Temperature, precipitation and wind speed are generally critical at both global scale and ecotones along latitudes. SII is important on global scale, with a contribution of 5.9%, ranking 6th, and is particularly critical in the 10-30°S and 20-30°N zone. Interactions with salt marsh, including facilitation and competition, are shown to affect the distribution of mangroves at the zone of coastal ecotone, especially in the latitudinal range from 10° - 30°. The contribution of SII to mangrove distribution increases with latitudes due to the difference in the adaptive capacity of salt marsh plants and mangroves to environments. Totally, this study identified and quantified the effects of salt marsh on mangrove distribution by establishing the SII. The results not only facilitate to establish a more accurate mangrove distribution map, but also improve the efficiency of mangrove restoration by considering the salt marsh interaction in the mangrove management projects. In addition, the method of incorporating biotic interaction into SDMs through establish the biotic interaction index has contributed to the development of SDMs.

Analysis of spatial spillover effects and influencing factors of transportation carbon emission efficiency from a provincial perspective in China

Globally, the transportation industry has become one of the leading sectors in carbon emission, and all countries are committed to environmental protection and energy conservation while experiencing rapid development. Under China's "dual-carbon" goal, the carbon emission problem hinders the construction of China's green transportation system and affects the high-quality development of transportation, so it is of great significance to study the spatial pattern of carbon emission efficiency in the transportation industry and the factors affecting it. Firstly, this paper measures the carbon emission value of transportation in 30 provinces in China from 2010 to 2020 based on the IPCC method and measures the carbon emission efficiency through the super-efficiency slack-based measurement model. Secondly, spatial autocorrelation analysis was conducted to determine the spatial clustering characteristics of the efficiency values. Finally, two spatial Durbin models are constructed to measure the spatial spillover effects and analyze the short-term immediate effects of each influencing factor on the static model and the long-term effects of the dynamic model considering the time lag of the transportation carbon emission efficiency. The results of the study show that (1) the average value of efficiency in the central and eastern regions is basically higher than 0.5; in the western and northeastern regions, it is basically lower than 0.3.The overall efficiency of carbon emission in the region shows a fluctuating upward trend but with increasing regional differences. (2) The number of regions with positive spatial correlation increased from 21 to 25 during the study period, and the degree of provincial transportation carbon emission efficiency agglomeration increased. (3) Although urbanization and energy intensity have a large detrimental influence on transportation carbon emission efficiency, environmental regulation has a major favorable effects on it both long and short term. Population scale, opening level, and urbanization all have significant spatial spillover effects. Accordingly, relevant policy recommendations are put forward to provide theoretical guidance for promoting the realization of low-carbon transportation.

Global spatial distribution of Prosopis juliflora - one of the world's worst 100 invasive alien species under changing climate using multiple machine learning models

Climate change is one of the factors contributing to the spread of invasive alien species. As a result, it is critical to investigate potential invasion dynamics on a global scale in the face of climate change. We used updated occurrence data, bioclimatic variables, and Köppen-Geiger climatic zones to better understand the climatic niche dynamics of Prosopis juliflora L. (Fabaceae). In this study, we first compared several algorithms-MaxEnt, generalized linear model (GLM), artificial neural network (ANN), generalized boosted model (GBM), generalized additive model (GAM), and random forest (RF)-to investigate the relationships between species-environment and climate for mesquite. We identified the global climate niche similarity sites (NSSs) using the coalesce approach. This study focused on the current and future climatic suitability of P. juliflora under two global circulation models (GCMs) and two climatic scenarios, i.e., Representative Concentration Pathways (RCPs), 4.5 and 8.5, for 2050 and 2070, respectively. Sensitivity, specificity, true skill statistic (TSS), kappa coefficient, and correlation were used to evaluate model performance. Among the tested models, the machine learning algorithm random forest (RF) demonstrated the highest accuracy. The vast swaths of currently uninvaded land on multiple continents are ideal habitats for invasion. Approximately 9.65% of the area is highly suitable for the establishment of P. juliflora. Consequently, certain regions in the Americas, Africa, Asia, Europe, and Oceania have become particularly vulnerable to invasion. In relation to RCPs, we identified suitable area changes (expansion, loss, and stability). The findings of this study show that NSSs and RCPs increase the risk of invasion in specific parts of the world. Our findings contribute to a cross-border continental conservation effort to combat P. juliflora  expansion into new potential invasion areas.

Can green finance and environmental regulations promote carbon emission reduction? Evidence from China

Carbon reduction has become a major challenge for China's economy in its transition toward sustainability. The government has been monitoring the behavior of enterprises through regulations to protect the environment, while green finance has rapidly developed in recent years as a new tool to reduce carbon emissions. Despite these measures, few studies have explored the interaction between these two drivers of carbon reduction. Therefore, this study aimed to examine the impact of green finance and environmental regulations on carbon emissions. To determine whether their coordination can lead to greater carbon reduction, the spatial spillover effect of this impact was also investigated. The results show that green finance can reduce carbon emissions and that the interaction of green finance with environmental regulations plays a significant positive role in reducing carbon emissions. Finally, this study concludes that the carbon reduction effects of green finance and environmental regulations have positive spillover effects on adjacent areas.

Predicting Disparity between ASF-Managed Areas and Wild Boar Habitats: A Case of South Korea

African swine fever (ASF) is a highly contagious viral disease affecting both domestic and wild boars. Since its first outbreak in South Korea in 2019, substantial efforts have been made to prevent ASF transmission by reducing the wild boar population and eliminating infected carcasses; however, the persistence of ASF transmission has posed challenges to these efforts. To improve ASF management strategies, the limitations of current management strategies must be identified by considering disparities between wild boar habitats and ASF-managed areas with environmental and anthropogenic characteristics of wild boars and their management strategies. Here, ensemble species distribution models were used to estimate wild boar habitats and potential ASF-managed areas, with elevation, distance to urban areas, and Normalized Difference Vegetation Index as important variables. Binary maps of wild boar habitats and potential ASF-managed areas were generated using the maxSSS as the threshold criterion. Disparity areas of ASF management were identified by overlying regions evaluated as wild boar habitats with those not classified as ASF-managed areas. Dense forests near urban regions like Chungcheongbuk-do, Gyeongsangbuk-do, and Gyeongsangnam-do were evaluated as disparity areas having high risk of ASF transmission. These findings hold significant potential for refining ASF management strategies and establishing proactive control measures.

Analysis of spatial distribution and drivers of gaseous energy combustion pollution in China based on SDM

Air pollution is an important part of ecological environment problems. Gaseous energy combustion pollution is a key part of air pollution. Analysis of its spatial distribution and drivers is important to effectively manage air quality and promote regional green development. This paper uses panel data of 30 provinces in China from 2006 to 2019 to analyze the spatial distribution and drivers of gaseous energy combustion pollution in each province of China through a combination of quantitative and qualitative analysis based on the spatial Durbin model, and further decompose the spatial effects of each influencing factor. The empirical results show, firstly, that inter-provincial gaseous energy combustion pollution in China shows significant spatial differences and cluster characteristics. Secondly, most areas are located in high-high aggregation area and low-low aggregation area. Finally, population, energy consumption and other independent variables have different impacts on gaseous energy combustion pollution in different regions. The changes of these variables will affect the adjacent areas through spatial transmission while affecting a region. According to the empirical results, this study proposes policy recommendations to balance the pollution degree of gaseous energy combustion in various regions and effectively reduce the emissions of various pollution sources. The research results are helpful to understand the spatial distribution of gaseous energy combustion pollution in various regions of China, provide reference for the future development of various regions, and have important practical significance for the reduction and balance of pollution levels.

How does an innovative decision-making scheme affect the high-quality economic development driven by green finance and higher education?

This research examines the various elements that contribute to the achievement of high-quality economic development (HQED) in China. Specifically, it explores the influence of several major indices, such as the Green Finance Index, Energy Development Index, Higher Education, Technology Market Environment, and Human Capital. In this study, we utilize a Spatial Durbin Model to examine the interdependencies and spatial linkages between various variables, and their combined impact on China's efforts towards achieving HQED. The Green Finance Index serves as an indicator of a nation's dedication to the implementation of financially sustainable practices and investments that align with environmental objectives. The Energy Development Index assesses the extent to which the energy sector contributes to both economic growth and sustainability. The significance of education and skill development in promoting economic advancement is underscored by Higher Education and Human Capital measures. The Technology Market Environment Index examines the impact of the innovation ecosystem on fostering economic growth. The empirical analysis in our study utilizes extensive data sets collected from 30 provinces and regions throughout China. In this study, we analyze the spatial and temporal interactions of the indices, considering the potential spillover effects from adjacent locations. The findings offer significant contributions to understanding the intricate interconnections among green financing, energy development, education, technology, and human capital, and their combined influence on China's continuous endeavor towards achieving high-quality economic growth. Comprehending the intricate interconnections and spatial dynamics holds paramount importance for policymakers and stakeholders who aspire to foster sustainable, inclusive, and ecologically conscientious economic development in China. The results obtained from this study possess the potential to provide valuable insights for evidence-based policy decisions and strategies aimed at promoting the nation's pursuit of HQED objectives.

The role of agricultural machinery in improving green grain productivity in China: Towards trans-regional operation and low-carbon practices

Agricultural machinery is effective in improving food production and labor productivity, but it also raises environmental concerns. The impacts of agricultural machinery on the green total factor productivity (GTFP) of grain in China are still under debate in the scientific literature. This study proposed an integrated framework for confronting this issue. The findings suggest that both agricultural mechanization and the GTFP of grain demonstrate a consistent upward trend with moderate fluctuations between 2001 and 2019. By expanding the spatial pattern, there is a positive spatial correlation between them. In addition, we compared the results in three grain functional areas by using the spatial Durbin model (SDM). There were significantly positive spatial spillover effects in major grain-producing areas, which were attributed to the trans-regional operation of agricultural machinery and its carbon reduction effects on neighboring provinces. Notably, the direct effects in major grain-marketing areas and producing-marketing balance areas were significantly positive because agricultural machinery has played a critical role in filling the gap in local labor shortages in grain production. Accordingly, adaptive strategies including building the "Internet + agricultural machinery operation" platform, implementing the land consolidation suitable for machinery, and developing low-carbon agricultural machinery should be fully considered by Chinese policy-makers to promote mechanized agriculture and a low-carbon economy. The findings of this study can help us better understand the role of agricultural machinery in improving green grain productivity in China and thus have significance for the modern and green transformation of agricultural production systems.

Climate change and carnivores: shifts in the distribution and effectiveness of protected areas in the Amazon

Background

Carnivore mammals are animals vulnerable to human interference, such as climate change and deforestation. Their distribution and persistence are affected by such impacts, mainly in tropical regions such as the Amazon. Due to the importance of carnivores in the maintenance and functioning of the ecosystem, they are extremely important animals for conservation. We evaluated the impact of climate change on the geographic distribution of carnivores in the Amazon using Species Distribution Models (SDMs). Do we seek to answer the following questions: (1) What is the effect of climate change on the distribution of carnivores in the Amazon? (2) Will carnivore species lose or gain representation within the Protected Areas (PAs) of the Amazon in the future?

Methods

We evaluated the distribution area of 16 species of carnivores mammals in the Amazon, based on two future climate scenarios (RCP 4.5 and RCP 8.5) for the year 2070. For the construction of the SDMs we used bioclimatic and vegetation cover variables (land type). Based on these models, we calculated the area loss and climate suitability of the species, as well as the effectiveness of the protected areas inserted in the Amazon. We estimated the effectiveness of PAs on the individual persistence of carnivores in the future, for this, we used the SDMs to perform the gap analysis. Finally, we analyze the effectiveness of PAs in protecting taxonomic richness in future scenarios.

Results

The SDMs showed satisfactory predictive performance, with Jaccard values above 0.85 and AUC above 0.91 for all species. In the present and for the future climate scenarios, we observe a reduction of potencial distribution in both future scenarios (RCP4.5 and RCP8.5), where five species will be negatively affected by climate change in the RCP 4.5 future scenario and eight in the RCP 8.5 scenario. The remaining species stay stable in terms of total area. All species in the study showed a loss of climatic suitability. Some species lost almost all climatic suitability in the RCP 8.5 scenario. According to the GAP analysis, all species are protected within the PAs both in the current scenario and in both future climate scenarios. From the null models, we found that in all climate scenarios, the PAs are not efficient in protecting species richness.

Geospatial analysis to assess distribution patterns and predictive model for endangered Lilium mackliniae Sealy: to support management decisions

Lilium mackliniae Sealy is a species endemic to the Indo-Myanmar Biodiversity Hotspot with confined occurrence in the Shirui hills of Manipur (India). A rapid fragmentation of the species resulted in enlisting the remaining population as endangered. Tribal communities have managed this population in national parks for in situ conservation because of its sacred value. Maximum entropy-based modeling was performed with 19 bioclimatic and six geospatial variables on 65 true presence data to assess the threat on its only habitat. The accuracy of modeling was confirmed by an AUC value of 0.989. Among the variables used for habitat modeling, elevation range was a key predictor of the species distribution, followed by land use class and annual temperature range. Additionally, the model projected a similar habitat for the species in the same district. This study, therefore, provides essential information for the conservation and management of the species.

Impacts of logistics agglomeration on carbon emissions in China: a spatial econometric analysis

Logistics industry relies heavily on fossil fuels and has drawn significant attention for its environmental impact. With a focus on the effect of logistics agglomeration, this paper examines the spatial spillover effects of the Chinese logistics industry on carbon emissions by using the spatial Durbin model based on panel data of 30 Chinese provinces from 2000 to 2019. The results indicate that the logistics agglomeration can positively influence emission reduction in both local and surrounding areas. Additionally, the environmental externalities from transportation structure and logistics scale are estimated; it finds that the scale of logistics also plays a significant role on carbon emissions. As to the heterogeneity of regions, the logistics agglomeration of the eastern area has positive externalities on carbon reduction, and the total spatial spillover effects on environmental pollution in the eastern area are much stronger than western area. The research findings indicate the potential benefits of promoting logistics agglomeration to reduce carbon emissions in China and can provide policy recommendations for green logistics reform and emission governance.

Shared decision-making in multiple sclerosis physical symptomatic care: a systematic review

Background

Multiple sclerosis (MS) is a chronic autoimmune inflammatory, demyelinating, and neurodegenerative disease affecting young adults. People with MS are highly interested in engaging in physical symptom management and decision-making but are often not actively engaged in symptom management discussions. Research examining the benefit of shared decision-making in the management of physical MS symptoms is sparse.

Objectives

This study aimed to identify and synthesize the evidence on the use of shared decision-making in physical MS symptom management.

Design

This study is a systematic review of published evidence on the use of shared decision-making in physical MS symptom management.

Data sources and methods

MEDLINE, CINAHL, EMBASE, and CENTRAL databases were searched in April 2021, June 2022, and April 2, 2023, for primary, peer-reviewed studies of shared decision-making in the management of MS physical symptoms. Citations were screened, data extracted, and study quality assessed according to Cochrane guidelines for systematic reviews, including risk of bias assessment. Statistical synthesis of the included study results was not appropriate; results were summarized in a nonstatistical manner using the vote-counting method to estimate beneficial versus harmful effects.

Results

Of 679 citations, 15 studies met the inclusion criteria. Six studies addressed shared decision-making in the management of pain, spasms, neurogenic bladder, fatigue, gait disorder, and/or balance issues, and nine studies addressed physical symptoms in general. One study was a randomized controlled trial; most studies were observational studies. All study results and study author conclusions indicated that shared decision-making is important to the effective management of physical MS symptoms. No study results suggested that shared decision-making was harmful or delayed the management of physical MS symptoms.

Conclusion

Reported results consistently indicate that shared decision-making is important in effective MS symptomatic care. Further rigorous randomized controlled trials are warranted to investigate the effectiveness of shared decision-making associated with MS physical symptomatic care.

Registration

PROSPERO: CRD42023396270.

Comparison of Structural Diagnosis and Management (SDM) approach and MyoFascial Release (MFR) for improving plantar heel pain, ankle range of motion and disability: A randomized clinical trial

[Purpose] The purpose of this study was to compare the effectiveness of the Structural Diagnosis and Management (SDM) approach with Myofascial Release (MFR) in improving plantar heel pain, ankle range of motion, and disability. [Subjects] Sixty-four subjects, aged 30-60 years, with a diagnosis of plantar heel pain, plantar fasciitis, or calcaneal spur by a physician according to ICD-10, were equally allocated to the MFR (n = 32) and SDM (n = 32) groups by hospital randomization and concealed allocation. [Methods] In this assessor-blinded randomized clinical trial, the control group performed MFR to the plantar surface of the foot, triceps surae, and deep posterior compartment calf muscles, while the experimental group performed a multimodal approach utilizing the SDM concept for 12 sessions over 4 weeks. Both groups also received strengthening exercises, ice compression, and ultrasound therapy. Pain, activity limitations and disability were assessed as primary outcomes using the Foot Function Index (FFI) and Range of motion (ROM) assessment of the ankle dorsiflexors and plantar flexors using a universal goniometer. Secondary outcomes were measured using the Foot Ankle Disability Index (FADI) and a 10-point manual muscle testing process for the ankle dorsiflexors and plantar flexors. [Results] Both MFR and SDM groups exhibited significant improvements from baseline in all outcome variables, including pain, activity level, disability, range of motion, and function after the 12-week intervention period (p < .05). The SDM group showed more improvements than MFR for FFI pain (p < .01), FFI activity (p < .01), FFI (p < .01) and FADI (p = <.01). [Conclusion] Both MFR and SDM approaches are effective in reducing pain, improving function, ankle range of motion, and reducing disability in plantar heel pain, however, the SDM approach may be a preferred treatment option.

Digitally supported shared decision-making and treat-to-target in rheumatology: a qualitative study embedded in a multicenter randomized controlled trial

Patient-reported outcomes (PRO) represent a cornerstone in the management of patients with rheumatoid arthritis (RA). However, PRO are currently recorded mainly on paper and only during on-site appointments. Electronic PRO (ePRO) enable continuous remote monitoring and could improve shared decision-making (SDM) and implementation of a treat-to-target (T2T) approach. This study aims to investigate patient and physician experiences, perceived drawbacks and benefits of using an ePRO web-app (ABATON RA) to digitally support SDM and T2T. A qualitative study embedded in a multicenter randomized controlled trial (RCT) consisting of interviews with RA patients and physicians that were subsequently analyzed using deductive-inductive qualitative content analysis. Between August 2021 and May 2022, interviews with ten RA patients and five physicians were completed. Three key themes emerged in the analysis: (i) App user experiences; (ii) perceived drawbacks of app-supported rheumatology care; and (iii) perceived benefits of app-supported rheumatology care. Continuous ePRO collection and a high level of standardization strained some RA patients. Certain ePRO seemed outdated and were hard to understand. Patients and physicians appreciated having an improved overview of disease activity, capturing disease flares and continuous remote monitoring. Paper- and time-saving were associated with using ePRO. Physicians feared to become too focused on ePRO data, stressed the lack of ePRO monitoring reimbursement and app interoperability. For RA patients and physicians, benefits seemed to outweigh observed drawbacks of the digitally supported SDM using ePRO. The software was easy to use and could lead to a better understanding of the individual disease course, resource allocation and treatment of rheumatoid arthritis.

Informing the development of a decision aid: Expectations and wishes from service users and psychiatrists towards a decision aid for antipsychotics in the inpatient setting

OBJECTIVES

Decision aids (DAs) are promising tools to foster evidence-based shared decision-making between practitioners and service users. Nevertheless, it is still obscure how an evidence-based DA for people with severe mental illness, especially psychosis, should look in an inpatient treatment setting to be useful and feasible. Therefore, we conducted focus groups with psychiatrists and service users to collect and assess their expectations and wishes regarding an evidence-based DA. From these findings, we derived immediate recommendations for the future development of DAs.

METHODS

We held two group interviews with service users (n = 8) and three group interviews with psychiatrists (n = 10). We used an open, large-scale topic guide. First, we presented data from a current meta-analysis on antipsychotics to the interviewees and, in a second step, asked for their expectations and wishes towards a DA that integrates these data.

RESULTS

Our thematic analysis revealed six key themes addressed by the respondents: (1) general considerations on the importance and usefulness of such a DA, (2) critical comments on psychiatry and psychopharmacotherapy, (3) communicative prerequisites for the use of a DA, (4) form and content of the DA, (5) data input, data processing and output as well as (6) application of the DA and possible obstacles.

CONCLUSIONS

Participants identified several important features for the development of DAs for selecting antipsychotics in inpatient psychiatric treatment. The digital format was met with the greatest approval. Especially the adaptability to different needs, users and psychopathologies and the possibility to outsource information dissemination via app seemed to be a decisive convincing argument. Further research is required to test specific features of DAs to be developed in clinical settings.

Effects of a shared decision making intervention for older adults with multiple chronic conditions: the DICO study

BACKGROUND

To evaluate the effects of a shared decision making (SDM) intervention for older adults with multiple chronic conditions (MCCs).

METHODS

A pragmatic trial evaluated the effects of the SDM^MCC intervention, existing of SDM training for nine geriatricians in two hospitals and a preparatory tool for patients. A prospective pre-intervention post-intervention multi-center clinical study was conducted in which an usual care group of older patients with MCC and their informal caregivers was included before the implementation of the intervention and a new cohort of patients and informal caregivers after the implementation of the intervention. SDM was observed using the OPTION^MCC during video-recorded consultations. Patient- and caregivers reported outcomes regarding their role in SDM, involvement, perceived SDM and decisional conflict were measured. The differences between groups regarding the level of observed SDM (OPTION^MCC) were analyzed with a mixed model analysis. Dichotomous patient-reported outcomes were analyzed with a logistic mixed model.

RESULTS

From two outpatient geriatric clinics 216 patients with MCCs participated. The mean age was 77.3 years, and 56.3% of patients were female. No significant difference was found in the overall level of SDM as measured with the OPTION^MCC or in patient-reported outcomes. However, at item level the items discussing 'goals', 'options', and 'decision making' significantly improved after the intervention. The items discussing 'partnership' and 'evaluating the decision-making process' showed a significant decrease. Fifty-two percent of the patients completed the preparatory tool, but the results were only discussed in 12% of the consultations.

CONCLUSION

This study provides scope for improvement of SDM in geriatrics. Engaging older adults with MCCs and informal caregivers in the decision making process should be an essential part of SDM training for geriatricians, beyond the SDM steps of explaining options, benefits and harms. More attention should be paid to the integration of preparatory work in the consultation.

Predictive Modeling of Kudzu (Pueraria montana) Habitat in the Great Lakes Basin of the United States

Kudzu (Pueraria montana [Lour.] Merr. var. lobata [Willd.] Maesen & S.M. Almeida ex Sanjappa & Predeep) is an invasive woody vine widespread throughout much of the southeastern United States. New occurrences and recent studies using climatic parameters suggest that the Midwestern region of the United States is at the greatest risk of kudzu invasion. As there are already multiple reports of kudzu within the Great Lakes basin and no previous landscape models exist specifically for the basin, we developed probability models from existing spatial data (forest type, geology, land cover, precipitation, temperature, and known kudzu locations) by using maximum entropy methods at the national, regional, and basin scales. All three models had relatively high accuracy and strong positive correlation between predicted and observed values. Based on evaluation of the models using a testing data set, we determined a presence threshold and categorized areas within each model as suitable or unsuitable habitat. We pooled the models and calculated mean habitat suitability within the Great Lakes basin. Much of the southern half of the basin was suitable for kudzu. Continuing management and further monitoring of kudzu spread are likely necessary to limit further introduction and mitigate spread of kudzu within the Great Lakes region.

How do "Young-old" Adults Project their Self? A Study of Self-defining Future Projections in Normal Ageing

BACKGROUND

Self-defining future projections (SDFP) are mental representations of plausible and highly significant future events that provide core information of one's understanding of self.

OBJECTIVE

We explored SDFPs in a large sample of older adults and aimed to target the interrelations between the main dimensions of SDFPs. Moreover, correlations between these dimensions and clinical and cognitive variables were examined.

METHODS

We recruited 87 young-old adults (60-75 years) with normal cognitive functioning who were asked to generate three SDFPs.

RESULTS

We found integrative meaning as a salient dimension and older individuals preferentially generated projections containing leisure or relationship events. Anxiety and self-esteem were correlated with integrative meaning and high executive functioning was found to be protective towards the simulation of future events containing dependence and death or end-of-life events.

CONCLUSION

This study will contribute to the understanding of personal goals and identity in normal ageing.

Comprehensive Implementation of Shared Decision Making in a Neuromedical Center Using the SHARE TO CARE Program

PURPOSE

SHARE TO CARE (S2C) is a comprehensive, multi-module implementation program for shared decision making (SDM). It is currently applied at the University Hospital Schleswig-Holstein in Kiel, Germany, and among general practitioners at the Federal State of Bremen. This study examines the results of the full implementation of S2C in terms of effectiveness within the Kiel Neuromedical Center comprising the departments of neurology and neurosurgery.

METHOD AND DESIGN

The S2C program consists of four combined intervention modules: 1) multimodal training of physicians; 2) a patient activation campaign including the ASK-3 method; 3) digital evidence-based patient decision aids; and 4) SDM support by nurses, e.g., as decision coaches. The SDM level before and immediately after implementation was retrospectively assessed in consecutively selected patients on the subscale "Patient Decision Making" of the Perceived Involvement in Care Scale (PICS_PDM). Mean scores were compared with t-tests.

RESULTS

Eighty-nine percent of all physicians (N = 56) completed the SDM training. We developed a total of 12 evidence-based digital decision aids in the center, educated two decision coaches to support patients' decision processes by using decision aids. Physicians adjusted patients' pathways to incorporate the use of decision aids. Patients (n = 261) reported a significant increase in participation (p<0.001; Hedges' g = 0.49) in medical decision making.

CONCLUSION

The S2C program has been successfully implemented within the entire Neuromedical Center. Patients reported a medium to small increase of perceived involvement in decision making demonstrating the effectiveness of the implementation. For future research, it might be interesting to investigate the sustainability of the effects of S2C. In addition, it seems useful to complement the patient-based evaluation with observer-based data.

Is the Lesser Khingan Suitable for the Amur Tiger Restoration? Perspectives with the Current State of the Habitat and Prey Base

The Amur tiger (Panthera tigris) has a status of being endangered on the world's IUCN red list. The northwestern part of its range is situated in Russia and China, where tigers were exterminated by humans in the 1950-1970s. To restore tiger population within a historical range, an estimation of the habitat suitability is firstly needed. The Lesser Khingan mountains (Heilongjiang) was analyzed. Habitat types were mapped by satellite images analysis and field proven. The potential habitats of the main tiger's prey species (wild boar (Sus scrofa), roe deer (Capreolus pygargus), and red deer (Cervus elaphus xanthopygus) were also assessed. Maximum entropy and linear discriminant analysis methods were applied and compared for species distribution modeling (SDM). Species distribution maps were used to design an ecological network. The fragmentation of habitat patches was evaluated by spatial ecological metrics. The habitat patches with the best metrics were assigned as cores for the ecological network, which were connected by calculated corridors. The least cost distance method (based on distance to roads and settlements) was used. The recovery of the Amur tiger in habitats of China's Lesser Khingan is shown to be possible. Types of habitats were calculated as natural corridors for moving tigers. They are mainly located at the forests' edges and characterized with various canopy structures and high variability in the tree species composition. Three potential transboundary corridors are described: (a) foothills and low mountains of the northern Lesser Khingan; (b) connection between the southeast Lesser Khingan and the western part of the Wandashan mountain system; and (c) corridor within foothills and low mountains of the eastern part of Lesser Khingan. It is recommended to establish protected areas for the important tiger core habitats, and the main optimal ways for their migrations are described during the current investigation. Moreover, it is necessary to implement habitat recovery activities for key areas.

Problem-based shared decision making: The role of canonical SDM steps

OBJECTIVE

To evaluate the extent to which the canonical steps of shared decision making (SDM) take place in clinical encounters in practice and across SDM forms.

METHODS

We assessed 100 randomly selected video-recorded primary care encounters, obtained as part of a randomized trial of an SDM intervention in patients with type 2 diabetes. Two coders, working independently, noted each instance of SDM, classified it as one of four problem-based forms to SDM (weighing alternatives, negotiating conflicting issues, solving problems, or developing existential insight), and noted the occurrence and timing of each of the four canonical SDM steps: fostering choice awareness, providing information, stating preferences, and deciding. Descriptive analyses sought to determine the relative frequency of these steps across each of the four SDM forms within each encounter.

RESULTS

There were 485 SDM steps noted (mean 4.85 steps per encounter), of which providing information and stating preferences were the most common. There were 2.7 (38 steps in 14 encounters) steps per encounter observed in encounters with no discernible SDM form, 3.4 (105 steps in 31 encounters) with one SDM form, 5.2 (129 steps in 25 encounters) with two SDM forms, and 7.1 (213 steps in 30 encounters) when ≥3 SDM forms were observed within the encounter. The prescribed order of the four SDM steps was observed in, at best, 16 of the 100 encounters. Stating preferences was a common step when weighing alternatives (38%) or negotiating conflicts (59.3%) but less common when solving problems (29.2%). The distribution of SDM steps was similar to usual care with or without the SDM intervention.

CONCLUSION

The normative steps of SDM are infrequently observed in their prescribed order regardless of whether an SDM intervention was used. Some steps are more likely in some SDM forms but no pattern of steps appears to distinguish among SDM forms.

CLINICAL TRIAL REGISTRATION

ClinicalTrial.gov: NCT01293578.

Are chromosome number and genome size associated with habit and environmental niche variables? Insights from the Neotropical orchids

BACKGROUND AND AIMS

The entangled relationship of chromosome number and genome size with species distribution has been the subject of study for almost a century, but remains an open question due to previous ecological and phylogenetic knowledge constraints. To better address this subject, we used the clade Maxillariinae, a widely distributed and karyotypically known orchid group, as a model system to infer such relationships in a robust methodological framework.

METHODS

Based on the literature and new data, we gathered the chromosome number and genome size for 93 and 64 species, respectively. We built a phylogenetic hypothesis and assessed the best macroevolutionary model for both genomic traits. Additionally, we collected together ecological data (preferences for bioclimatic variables, elevation and habit) used as explanatory variables in multivariate phylogenetic models explaining genomic traits. Finally, the impact of polyploidy was estimated by running the analyses with and without polyploids in the sample.

KEY RESULTS

The association between genomic and ecological data varied depending on whether polyploids were considered or not. Without polyploids, chromosome number failed to present consistent associations with ecological variables. With polyploids, there was a tendency to waive epiphytism and colonize new habitats outside humid forests. The genome size showed association with ecological variables: without polyploids, genome increase was associated with flexible habits, with higher elevation and with drier summers; with polyploids, genome size increase was associated with colonizing drier environments.

CONCLUSIONS

The chromosome number and genome size variations, essential but neglected traits in the ecological niche, are shaped in the Maxillariinae by both neutral and adaptive evolution. Both genomic traits are partially correlated to bioclimatic variables and elevation, even when controlling for phylogenetic constraints. While polyploidy was associated with shifts in the environmental niche, the genome size emerges as a central trait in orchid evolution by the association between small genome size and epiphytism, a key innovation to Neotropical orchid diversification.

Shared decision making process measures and patient problems

OBJECTIVES

Purposeful SDM posits four modes of shared decision making (SDM). The use of each mode depends on the type of problem of care that is being addressed. We sought to identify how current observer-based SDM measures apply to each mode of Purposeful SDM.

METHODS

Four coders, working independently, evaluated 192 items pertaining to 12 observer-based SDM process measures. They classified the items into 6 themes that vary across Purposeful SDM modes and then into one of the four modes (weighing, negotiating, problem-solving, developing insight). Disagreements were resolved by consensus.

RESULTS

The items were classified as pertaining to the following themes: problem (28), roles/participation (84), options (62), preferences (21), decision (15), and evaluation (6). They were then classified as pertaining particularly to the SDM modes of weighing (54), negotiating (5), problem-solving (0), and developing insight (0) modes, with 191 items applying broadly to all modes of Purposeful SDM.

CONCLUSIONS

Observer-based SDM measures describe behaviors pertinent to all modes but lack items sensitive to behaviors particular to some modes of SDM.

PRACTICE IMPLICATIONS

New or revised observer-based measures of the SDM process could help estimate the extent to which the appropriate SDM mode is being used to address the patient's problem.

Evidence-based Shared-Decision-Making Assistant (SDM-assistant) for choosing antipsychotics: protocol of a cluster-randomized trial in hospitalized patients with schizophrenia

BACKGROUND

Choosing an antipsychotic medication is an important medical decision in the treatment of schizophrenia. This decision requires risk-benefit assessments of antipsychotics, and thus, shared-decision making between physician and patients is strongly encouraged. Although the efficacy and side-effect profiles of antipsychotics are well-established, there is no clear framework for the communication of the evidence between physicians and patients. For this reason, we developed an evidence-based shared-decision making assistant (SDM-assistant) that presents high-quality evidence from network meta-analysis on the efficacy and side-effect profile of antipsychotics and can be used as a basis for shared-decision making between physicians and patients when selecting antipsychotic medications.

METHODS

The planned matched-pair cluster-randomised trial will be conducted in acute psychiatric wards (n = 14 wards planned) and will include adult inpatients with schizophrenia or schizophrenia-like disorders (N = 252 participants planned). On the intervention wards, patients and their treating physicians will use the SDM-assistant, whenever a decision on choosing an antipsychotic is warranted. On the control wards, antipsychotics will be chosen according to treatment-as-usual. The primary outcome will be patients' perceived involvement in the decision-making during the inpatient stay as measured with the SDM-Q-9. We will also assess therapeutic alliance, symptom severity, side-effects, treatment satisfaction, adherence, quality of life, functioning and rehospitalizations as secondary outcomes. Outcomes could be analysed at discharge and at follow-up after three months from discharge. The analysis will be conducted per-protocol using mixed-effects linear regression models for continuous outcomes and logistic regression models using generalised estimating equations for dichotomous outcomes. Barriers and facilitators in the implementation of the intervention will also be examined using a qualitative content analysis.

DISCUSSION

This is the first trial to examine a decision assistant specifically designed to facilitate shared-decision making for choosing antipsychotic medications, i.e., SDM-assistant, in acutely ill inpatients with schizophrenia. If the intervention can be successfully implemented, SDM-assistant could advance evidence-based medicine in schizophrenia by putting medical evidence on antipsychotics into the context of patient preferences and values. This could subsequently lead to a higher involvement of the patients in decision-making and better therapy decisions.

TRIAL REGISTRATION

German Clinical Trials Register (ID: DRKS00027316 , registration date 26.01.2022).

Functional Neural Alterations in Pathological Internet Use: A Meta-Analysis of Neuroimaging Studies

Previous resting-state functional MRI (fMRI) studies found spontaneous neural activity in the brains of Pathological Internet Use (PIU) subjects. However, the findings were inconsistent in studies using different neuroimaging analyses. This meta-analytic study aimed to identify a common pattern of altered brain activity from different studies. Resting-state fMRI studies, based on whole-brain analysis methods published before July 1, 2021, were searched in multiple databases (PubMed, EMBASE, MEDLINE, and Web of Science). A voxel-based signed differential mapping (SDM) method was used to clarify brain regions, which showed anomalous activity in PIU subjects compared with healthy controls (HCs). Ten eligible publications consisting of 306 PIU subjects and 314 HCs were included in the SDM meta-analysis. Compared with HCs, subjects with PIU showed increased spontaneous neural functional activity in the left temporal pole of the superior temporal cortex, left amygdala, bilateral median cingulate cortex, and right insula. Meanwhile, a decreased spontaneous neural activity was identified in the left dorsolateral superior frontal gyrus and right middle frontal gyrus in the subjects with PIU. These abnormal brain regions are associated with cognitive executive control and emotional regulation. The consistent changes under different functional brain imaging indicators found in our study may provide important targets for the future diagnosis and intervention of PIU.

Systematic Review Registration:www.crd.york.ac.uk/PROSPERO, identifier: CRD42021258119.

Climate change and niche unfilling tend to favor range expansion of Moina macrocopa Straus 1820, a potentially invasive cladoceran in temporary waters

Non-native species' introductions have increased in the last decades primarily due to anthropogenic causes such as climate change and globalization of trade. Moina macrocopa, a stress-tolerant cladoceran widely used in bioassays and aquaculture, is spreading in temporary and semi-temporary natural ponds outside its natural range. Here, we characterize the variations in the climatic niche of M. macrocopa during its invasions outside the native Palearctic range following introduction into the American continent. Specifically, we examined to what extent the climatic responses of this species have diverged from those characteristics for its native range. We also made predictions for its potential distribution under current and future scenarios. We found that the environmental space occupied by this species in its native and introduced distribution areas shares more characteristics than randomly expected. However, the introduced niche has a high degree of unfilling when displacing its original space towards the extension to drier and hotter conditions. Accordingly, M. macrocopa can invade new areas where it has not yet been recorded in response to warming temperatures and decreasing winter precipitation. In particular, temporary ponds are more vulnerable environments where climatic and environmental stresses may also lower biotic resistance.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10750-022-04835-7.

Spatial Spillover Effects of Renewable Energy on Carbon Emissions in Less-developed Areas of China

The purpose of this paper is to determine the spatial spillover effects of renewable energy on carbon emissions in China's less-developed areas. However, few studies have considered this issue from the perspective of less-developed areas. Based on panel data of 21 provinces in China from 2000 to 2017, this paper analyzes the spatial spillover effects of renewable energy on carbon emissions using Moran's I and Spatial Durbin Model (SDM). The results suggest that, first, Moran's I ranges from 0.378 to 0.519, Moran scatter plot presents that provinces are located in the high-high (HH) and low-low (LL) quadrants, indicating provincial carbon emissions in the study area have a significant spatial correlation and agglomeration. Second, under the three matrices, the direct effect coefficients of renewable energy are -0.2522, -0.2639 and -0.2601, this shows that renewable energy is beneficial to local carbon emissions reduction. In contrast, the indirect effect coefficients of renewable energy are 0.0605, 0.1012 and 0.1125, which means higher renewable energy consumption in a single area is conducive to the improvement of carbon emissions to neighbouring areas. Third, urbanization, industrialization, physical capital and other variables have different impacts on local and nearby carbon emissions. This study provides empirical evidence to achieve carbon emission reduction targets by government policymakers.

Study on the impact of comprehensive urbanization on urban civil building CO2 emissions in China

With the rapid development of China, urbanization has become an important research topic of China's CO2 emissions. To fill the gap in considering the spatial correlation of the comprehensive urbanization that includes multi-dimensional factors on CO2 emissions from urban civil buildings (UBEC), this study constructs a comprehensive evaluation indicator of urbanization from four aspects including population, economy, society, and land urbanization by using the entropy method. The spatial spillover effect of UBEC and the impact of comprehensive urbanization on UBEC are also studied by using the spatial panel model in this paper. This study finds out that UBEC has obvious spatial spillover effects. During the early years of the study period, the eastern coastal areas had greater carbon emissions, while in recent years, they have gradually transitioned to the northwestern regions. Comprehensive urbanization has a significant promotion effect on it. And foreign direct investment and per capita energy consumption also have positive impact on UBEC. This study provides a reference for measuring the effects of urbanization on sector-specific CO2 emissions and may be useful for energy efficiency and emission abatement efforts in China.

Identifying and Aligning Ecosystem Services and Beneficiaries Associated with Best Management Practices in Chesapeake Bay Watershed

Ecosystem restoration may require implementing programs or best management practices (BMPs) in areas that are geographically far from the target ecosystem. Stakeholders in these areas may feel disconnected from the target ecosystem or may not have a clear understanding of local benefits from implemented practices. To achieve widespread participation in restoration efforts, it is important to engage stakeholders located where BMPs need to be implemented to identify and consider their local priorities and impacts. Here, we demonstrate use of a structured decision-making approach to identify ecosystem services associated with BMPs in the Chesapeake Bay watershed and connect them with the priorities of stakeholders they benefit. We follow a four-step approach to define the bounds of the decision context, identify ecosystem services and beneficiaries relevant to that decision context, engage stakeholders to understand priorities, and identify potential metrics and indicators. Our approach highlights the utility of different tools, such as ecosystem service classification systems and the Final Ecosystem Goods and Services (FEGS) Scoping Tool, in engaging stakeholders to identify, communicate, and prioritize ecosystem services. The results demonstrate a method by which to connect large-scale regional restoration efforts, and the managers overseeing such efforts, with the priorities of local communities where programs will be implemented. This work will help Chesapeake Bay restoration partners identify and promote management actions that will provide the most value for communities throughout the watershed, while also benefiting restoration of Chesapeake Bay.

Analysis of spillover effects of regional environmental pollution: an interprovincial study in China based on spatiotemporal lag model

Based on 2004-2017 Chinese interprovincial panel data, we construct the regional environmental pollution indicators, analyze the influencing factors and spillover effects of environmental pollution under the conditions of time lag, spatial lag, and spatiotemporal lag by using the STIRPAT model and dynamic spatial Durbin model, and discuss the spatiotemporal characteristics of regional environmental pollution in China. The results show that the overall regional environmental pollution in China is on the decline. Environmental pollution has strengthened the characteristics of strong in the East and weak in the West, and the characteristics of strong in the South and weak in the North began to appear. Population scale, economic growth, and industrial scale will increase environmental pollution in the region, and the environmental regulation intensity and pollution control investment will reduce environmental pollution in the region. The spillover effects of the influencing factors of regional environmental pollution in China are different. In the short term, the influencing factors have a greater impact on the neighboring areas, while in the long term, they have a greater impact on the region. Hence, the critical approach to achieving sustainable development is to give full play to the factors which can reduce environmental pollution and to effectively control the factors which will promote environmental pollution.

Modelling the occurrence and spatial distribution of screwworm species in Northern Pakistan

We use binomial kriging to model the spatial distribution of myiasis by three species namely Chrysomya bezziana, Wohlfahrtia magnifica and Lucilia cuprina in the livestock of Khyber Pakhtunkhwa, Pakistan. Traditional species distribution models are usually based on assumption of independence of observations. Species data often come in presence-only form for which background points are generated based on some covariates using statistical and machine learning techniques such as MaxEnt. We assume a symmetric binomial distribution based on the principle of maximum entropy in order to decide the number of pseudo-absences. Our results showed that the spatial models fitted very well and prediction distributions were estimated with excellent accuracy. Moreover kriging maps were more accurate as most of the non-spatial variation has been picked up by external drift with higher values of the sensitivity focusing partial AUC for all the three species. Land-use-land-cover was a common factor significantly affecting spatial distribution of all the three species suggesting that for established species anthropogenic factors such as land use become a strong determinant of their spatial distribution. Our results also revealed that for invading species like W. magnifica elevation acts as a barrier to species dispersal and therefore is more limiting to distribution. Furthermore the higher overall prediction accuracy demonstrated that our models performed well in predicting the distributions of the three species, which would lead to better understanding and management of the larval infestation.

Land use as an effective factor on the occurrence of chromosomal diseases in Brazil

BACKGROUND

The occurrence of chromosomal diseases is a worldwide health problem. The use of agrochemicals, urbanization processes, and solar radiation can be predictive factors of the elevated risk of congenital malformations. In this sense, predicting the geographical potential of the distribution of chromosomal diseases has high relevance for public health.

OBJECTIVES

This study aimed to describe chromosomal prevalence in Brazil regions, from 2005 to 2015, to model a potential distribution of chromosomal disease occurrence probability associated with land use.

METHODS

We used chromosomal prevalence to model a potential distribution of chromosomal diseases using machine learning algorithms. As the predictors of the models, we used the variables global forest canopy height, distance from the built-up area, and solar radiation. We characterized the predictive areas as potential occurrence of chromosomal diseases by land use and occupation.

RESULTS

Georeferenced data of 43,672 karyotypes detected 7,237 cases of chromosomal diseases and used 5,362 to build the models. The models generated were accurate (TSS>0.5).

DISCUSSION

The areas with greater occurrence of chromosomal diseases present a significant association with pasture areas, crops and agroforestry systems, and urbanized areas. This research is the first Brazilian study with this approach that seems promising in predicting the potential distribution of chromosomal diseases. Therefore, it can be an excellent management tool in public health.

Environmental determinants of Batrachochytrium dendrobatidis and the likelihood of further dispersion in the face of climate change in Texas, USA

One of the major drivers of amphibian population declines is Batrachochytrium dendrobatidis (Bd). We sought to identify the major environmental drivers of Bd prevalence in Texas, USA, by drawing results from museum specimens. We sampled one of the largest museum collections in Texas, the Biodiversity Research and Teaching Collections at Texas A&M University. Our sampling focused on the 9 amphibian species with the widest geographical distribution within the state, where we sub-sampled 30% of each species per decade from 1930 to present via skin swabs, totaling 1501 independent sampling events, and used quantitative real-time PCR (qPCR) to detect pathogen presence. We analyzed several geo-referenced variables describing climatic conditions to identify potential factors influencing the likelihood of presence of Bd using boosted regression trees. Our final model suggests the most influential variables are mean temperature of driest quarter, annual mean temperature, temperature annual range, and mean diurnal range. The most likely suitable range for Bd is currently found in the Blackland Prairie and Cross Timbers ecoregions. Results of our future (to the year 2040) projections suggest that Bd could expand its current distribution. Our model could play an important role when developing an integrated conservation plan through (1) focusing future field work on locations with a high likelihood of presence, (2) assisting in the choice of locations for restoration, and (3) developing future research plans including those necessary for projecting reactions to climate change. Our model also could integrate new presence data of Bd when they become available to enhance prediction precision.

The impact of artificial light at night on taxonomic, functional and phylogenetic bird species communities in a large geographical range: A modelling approach

Artificial light at night (ALAN) is currently recognised as an important environmental disturbance that influences habitats, fitness and behaviour of numerous organisms. However, its effect on bird community distribution on a large spatial scale still remains unclear. Therefore, I decided to use a predictive approach to test an assumption that artificial nightlight, as one of 73 predictors, determines taxonomic, functional and phylogenetic levels of an avian community. In order to safeguard inference from any inconsistency, I used not one but four indices describing functional diversity, two measures showing phylogenetic species richness, and one reflecting taxonomic diversity. For all these measures of species communities I developed two sets of Random Forest models: one set included ALAN as an additional predictor, while the other did not. Following cross validation tests as well as an independent evaluation of models, I demonstrated that artificial night light improved the performance of predictive models. Taxonomic species richness decreased linearly along with increasing artificial luminescence. Moreover, functional diversity showed a unimodal relation to ALAN, which meant that most niches were occupied on a moderate level of artificial lighting. Finally, phylogenetic diversity was under the highest pressure of ALAN, because even a minimal amount of artificial night lighting radically reduced this measure of biodiversity. On the basis of predictive maps, I also found that models which did not include urbanisation processes showed high values of avian biodiversity in regions where in fact they were low. Thus, I conclude that ALAN as a human footprint can play a key role when analysing the distribution of bird communities on large spatial scales.

Assessing climate change risks to the geographical distribution of grass species

There is extensive evidence showing the impact of climate change on the biology and biogeography of species. Adopting drought-tolerant plants to conserve water is a potential adaptation to reduce the consequences of climate change. Accordingly, it was hypothesized that climate change would not affect potential distributions of drought-tolerant species. Here, this hypothesis was tested to model the potential distribution of three drought-resistant plant. Here, the potential distribution of Agropyron cristatum, Agropyron desertorum, and Festuca arundinacea was studied in Iran under current and future climate conditions, using 10 species distribution models. Sixty-two climate change scenarios (19 global climate models (GCMs) under four Representative Concentration Pathways (RCPs)) were used to model the potential distribution of the three plants in Iran in the future. The three species have different responses to predicted climate change due to species-environment interactions, species morphological and physiological advancement. The three species showed different responses to predicted climate change due to species-environment interactions. Festuca arundinacea and Agropyron cristatum will, respectively, experience the most and least severe decline in suitable habitats in the next 50 years. This result is because decreased annual precipitation caused an increase in habitat suitability for A. cristatum, while the same variable had the opposite effect for A. desertorum and F. arundinacea. On the other hand, F. arundinacea grows on moist soils that decreased annual precipitation caused a decrease in habitat suitability. Also, our results have clearly shown that plant species drought-stress tolerant are not immune to climate change and their current distributions undergo significant changes as a result of the changing of climate.

The effect of a scalable online training module for shared decision making based on flawed video examples - a randomized controlled trial

OBJECTIVE

Shared Decision Making (SDM) is considered the gold standard of medical decision making as it provides a method to systematically integrate the patient's preferences, evidence-based medicine and the experience of health care professionals. Therefore, evidence-based training methods for a broad implementation into healthcare are needed. A new online training was designed, based on the concept of flawed/flawless video examples and additional educational concepts.

METHODS

In a single-blind randomized-controlled trial, medical students were randomly assigned to intervention group receiving the online training (n = 82) or waiting control group (n = 105). SDM-related knowledge and the ability to judge distinct levels of SDM were compared between both groups. Additionally, feedback regarding the intervention was collected.

RESULTS

SDM-related knowledge and judging ability increased significantly in the intervention group compared to controls (SDM knowledge: mean difference: 12 %; 95 % CI: 7.3-18.5; p < 0.001; SDM judging ability (inter-rater concordance displayed by weighted t): mean difference: 0.07; 95 %CI: 0.03-0.11; p = 0.001). Feedback was positive.

CONCLUSION

The online training with its distinctive methodology prove effective. As it shares the theoretical and didactical background with an already existing face-to-face training, both approaches may also be used complementarily.

PRACTICE IMPLICATIONS

SDM can be trained effectively and efficiently with this easily scalable online training.

Shared clinical decision-making experiences in nursing: a qualitative study

Background

Shared decision making (SDM) is a patient-centered nursing concept that emphasizes the autonomy of patients. SDM is a co-operative process that involves information exchange and communication between medical staff and patients for making treatment decisions. In this study, we explored the experiences of clinical nursing staff participating in SDM.

Methods

This study adopted a qualitative research design. Semistructured interviews were conducted with 21 nurses at a medical center in northern Taiwan. All interview recordings were transcribed verbatim. Content analysis was performed to analyze the data.

Results

The findings yielded the following three themes covering seven categories: knowledge regarding SDM, trigger discussion and coordination, and respect of sociocultural factors.

Conclusions

The results of this study describe the experiences of clinical nursing staff participating in SDM and can be used as a reference for nursing education and nursing administrative supervisors wishing to plan and enhance professional nursing SDM in nursing education.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12912-021-00597-0.

Will predicted positive effects of climate change be enough to reverse declines of the regionally Endangered Natterjack toad in Ireland?

The global amphibian crisis is driven by a range of stressors including disease, habitat loss, and environmental contamination. The role of climate change remains poorly studied and is likely to influence environmental suitability, ranges, reproduction, and phenology. This study aimed to characterize the bioclimatic-habitat niche space of the Natterjack toad (Epidalea calamita) throughout its European range and to assess the impact of climate on the toad's environmental suitability and breeding behavior in Ireland, where declines in recent decades have resulted in it being regionally Red-Listed as Endangered. To address these questions, we first identified which climate variables best predict the current bioclimatic niche, fecundity (number of eggs deposit), and phenology. We then used future climate projections for two time periods (2041-2060 and 2061-2080) and two greenhouse gas emission scenarios (RCP 4.5 and RCP 8.5) to predict how the species range, fecundity, and phenology would change. The European range of the species was found to be limited by winter temperatures while its bioclimatic niche varied markedly throughout its range. Species distribution models suggested projected climate change will increase environmental suitability for the species throughout its range, including Ireland, but most notably in Scandinavia and the Baltic. Fecundity in Ireland was greatest during the cool temperatures of spring and after wet winters associated with ephemeral breeding pool availability. Warm, dry summers in the preceding year influenced fecundity the following spring indicative of carryover effects. Initiation of spawning was driven by spring temperatures, not rainfall. Projections suggested future climate change may increase fecundity in Ireland while spawning may commence earlier throughout the 21st century especially under a high greenhouse gas emission scenario (RCP 8.5). Despite recent range contraction and population declines due to habitat deterioration, the Natterjack toad, if subject to a suitable species conservation strategy, has the potential to be a climate change winner, notwithstanding unpredictable habitat and land-use change, sea-level rise inducing coastal erosion, changes in invertebrate prey abundance, and disease.

Patient, clinician and independent observer perspectives of shared decision making in adult orthodontics

OBJECTIVES

To investigate and compare the extent of shared decision making (SDM) in orthodontics from the perspective of patients, clinicians and independent observers.

DESIGN

A cross-sectional, observational study.

SETTING

NHS teaching hospital.

PARTICIPANTS

A total of 31 adult patients and their treating clinicians were included in the study.

METHODS

The extent of SDM in new patient orthodontic consultations was measured using three versions of a validated instrument: the self-administered patient dyadic-OPTION scale; the self-administered clinician dyadic-OPTION scale; and an independent observer-rated OPTION¹² scale. Patients and clinicians completed the 12-item dyadic-OPTION questionnaire independently at the end of the consultation to rate their perceived levels of SDM. The consultations were also audio-recorded and two calibrated raters independently rated the extent of SDM in these consultations using the OPTION¹² scale.

RESULTS

There was excellent inter-rater reliability between the two independent raters using the OPTION¹² scale (intraclass correlation coefficient (ICC) = 0.909). The mean patient, clinician and independent observer OPTION scores for SDM were 90.4% (SD 9.1%, range 70.8% to 100%), 76.2% (SD 8.95%, range 62.5% to 95.8%) and 42.6% (SD 17.4%, range 13.5% to 68.8%), respectively. There was no significant correlation between the OPTION scores for the three groups (ICC = -0.323).

CONCLUSIONS

The results showed that generally high levels of SDM were perceived by patients and clinicians but lower levels of SDM were scored by the independent observers. However, it could be argued that the patient's perception of SDM is the most important measure as it is their care that is affected by their involvement.

Video-Based Education in Lung Cancer Screening

Lung cancer (LC) is the leading cause of cancer mortality in the USA; the American Cancer Society (ACS) estimates upwards of 220,000 new cases will be diagnosed this year. Recently, the Center for Medicare/Medicaid Services (CMS) agreed to cover LC screening with low-dose computed tomography (CT) for patients; however, CMS requires prior documentation of a shared decision-making (SDM) visit between the patient and the referring clinician to inform them about risks of screening. LC screening programs have begun to use YouTube for patient recruitment, education, and marketing of screening. The objective of this study is to shed light on the role of YouTube in lung cancer screening in terms of guidelines, screening options, target population, steps after screening, and risks and benefits of screening. We searched YouTube.com ™ to identify videos dealing with lung screening using the keywords: lung cancer screening. Videos without sound, uploaded before 2009, longer than 20 min, duplicate videos, and videos in a language other than English were excluded. This method yielded 123 videos that fit criteria. Videos were coded for inclusion of LC screening process, risks and benefits of screening, screening guidelines, risk factors for LC, and treatment options after LC diagnosis. One hundred twenty-three videos had a cumulative 261,261 views across all videos. A total of 38.7% of the videos included no mention of United States Preventive Services Task Force (USPSTF) or CMS guidelines for LC screening. Only 30% included any mention of the risks associated with screening: 14% mentioned false positives, 12% radiation, and 4% anxiety associated with screening. Ninety-two percent of all videos sampled were intended for patients, and the majority of videos were created by medical institutions (66%) and news channels (17%). Lung cancer screening videos on YouTube's platform have garnered a substantial amount of views. While all videos sampled highlighted the benefits of LC screening, the majority fail to discuss the risks associated with the screening process. Most videos were produced for marketing purposes rather than educational and therefore should not be used as a substitute for SDM visits.

Predicting seasonal movements and distribution of the sperm whale using machine learning algorithms

Implementation of effective conservation planning relies on a robust understanding of the spatiotemporal distribution of the target species. In the marine realm, this is even more challenging for species rarely seen at the sea surface due to their extreme diving behavior like the sperm whales. Our study aims at (a) investigating the seasonal movements, (b) predicting the potential distribution, and (c) assessing the diel vertical behavior of this species in the Mascarene Archipelago in the south-west Indian Ocean. Using 21 satellite tracks of sperm whales and eight environmental predictors, 14 supervised machine learning algorithms were tested and compared to predict the whales' potential distribution during the wet and dry season, separately. Fourteen of the whales remained in close proximity to Mauritius, while a migratory pattern was evidenced with a synchronized departure for eight females that headed towards Rodrigues Island. The best performing algorithm was the random forest, showing a strong affinity of the whales for sea surface height during the wet season and for bottom temperature during the dry season. A more dispersed distribution was predicted during the wet season, whereas a more restricted distribution to Mauritius and Reunion waters was found during the dry season, probably related to the breeding period. A diel pattern was observed in the diving behavior, likely following the vertical migration of squids. The results of our study fill a knowledge gap regarding seasonal movements and habitat affinities of this vulnerable species, for which a regional IUCN assessment is still missing in the Indian Ocean. Our findings also confirm the great potential of machine learning algorithms in conservation planning and provide highly reproductible tools to support dynamic ocean management.