Quantification of fossil fuel carbon dioxide emissions (CEs) at fine space and time resolution is a critical need in climate change research and carbon cycle. Quantifying changes in spatiotemporal patterns of urban CEs is important to understand carbon cycle and development carbon reduction strategies. The existing spatial data of CEs have low resolution and cannot distinguish the distribution characteristics of CEs of different emission sectors. This study quantified CEs from 15 types of energy sources, including residential, tertiary, and industrial sectors in Shanghai. Additionally, we mapped the CEs for the three sectors using point of interest data and web crawler technology, which is different from traditional methods. At a resolution of 30 m, the improved CEs data has a higher spatial resolution than existing studies. The spatial distribution of CEs based on this study has higher spatial resolution and more details than that based on traditional methods, and can distinguish the spatial distribution characteristics of different sectors. The results indicated that there was a consistent increase in CEs during 2000–2015, with a low rate of increase during 2009–2015. The intensity of CEs increased significantly in the outskirts of the city, mainly due to industrial transfer. Moreover, intensity of CEs reduced in city center. Technological progress has promoted the improvement of energy efficiency, and there has been a decoupling between the economic development and CEs in the city was observed during in 2000–2015. Studies have shown that urban areas account for 2% of the total land area, but produce 80% of the greenhouse gas emissions5. In 2014, the urban population exceeded 65% of the global population6. Cities are the main areas of human activity and greenhouse gas emissions7. To cope with global climate change and protect the environment, greenhouse gas emissions have drawn increasing attention8. However, urban expansion and population growth have driven increasingly intensified carbon dioxide emissions (CEs) in cities, particularly in China9. In recent decades, China has experienced rapid economic growth, environmental damage, and massive energy consumption. In 2014, the CEs of China were 10.29 billion tons, 4.21 times that in 1990, far higher than those of the United States (5.25 billion tons) and other developed countries (https://data.worldbank.org).Greenhouse gas emissions, such as carbon dioxide, contribute to global warming11, and measuring CEs from energy consumption has received increasing attention14. For example, Lu15 quantified and analyzed the impact of CEs from fossil fuel consumption at the national level. Wang16 analyzed the driving factors of CEs in China. Numerous studies have been conducted on carbon dioxide accounting. Methods of measuring CEs from various processes are developed. Three methods are widely used for carbon accounting: bottom-up, top-down, and hybrid approaches19. The top-down method is mainly a production-based accounting approach and is extremely useful for quantifying energy flows between regions and countries4. Although the top-down method requires less time and labor, it is not suitable for carbon accounting of small systems. The bottom-up method is used for a consumption-based accounting method, which is based on resource consumption at each step of human activity and life cycle analysis (LCA)4. The bottom-up method has a relatively high accuracy, but time-consuming and requires a large amount of data4. The hybrid method includes the synthesis of bottom-up, top-down, and other methods, such as environmental input–output analysis (EIOA)/LCA20 These integrated approaches are suitable for carbon dioxide accounting when detailed energy data are not available.To date, extensive validation of CEs and their environmental effects have been conducted22. Moreover, quantifying the changes in spatiotemporal patterns of urban CEs is important to understand carbon cycle and development carbon reduction strategies23. Recent years, researchers payed more attention to mapping CEs. With the development of remote sensing technology, carbon monitoring satellites have realized the dynamic monitoring of large-scale greenhouse gas emissions . GOSAT's sub-satellite spatial resolution is approximately 10.5 km, and it is suitable for monitoring carbon dioxide concentrations on region and global24. So, GOSAT images are not suitable for studying urban-scale CEs. Additionally, nighttime lighting (NTL) data sets are widely used to map CEs28, as there is a close relationship between NTL and population density, where a higher NTL value indicates greater energy consumption30. The spatial CEs distribution of existing studies has relied on spatial proxies to downscale the total CEs to a grid. Linear regression and panel regression models are the two most commonly used methods33. This downscaling method can use multi-source data to obtain the spatial distribution of carbon emissions indirectly34. Shi31 estimated China CEs distribution base on NTL at province level with a spatial resolution of 1 km. However, the map of CEs lacks the details of sectors. Traditional method of mapping CEs based on NTL have the disadvantages of low spatial resolution, larger than 1 km, and inability to distinguish emission sectors. Moreover, Cai35 developed the China high-resolution emission database (CHRED), which was constructed using the bottom-up method and a spatial resolution of 1 km, combined socio-economic data. Most of the existing spatial CEs studies were mapped based on the NTL at a spatial resolution of 1 km. Thus, NTL-based CEs distribution still has limitations. On one hand, the distribution of CEs does not reflect further details of its spatial heterogeneity at the city level. Low spatial resolution cannot satisfy the application of fine urban carbon management and emission reduction strategy development. On the other hand, the existing downscaling method of CEs does not distinguish sectors CEs. Zhang36 developed an approach for mapping urban CEs based on land use data, the method could distinguish sectors CEs. Moreover, this method cannot express the heterogeneity of CEs for each land use type. Shi37 have explored the relationship between NTL and CO2 emissions from different industries, such as service industry CO2 emissions (SC), traffic CO2 emissions (TC), and secondary industry CO2. They point out that Suomi NPP-VIIRS data are better suited to revealing CEs from different sectors. Although the method and Suomi NPP-VIIRS data helps to reveal the CEs of different sectors, its spatial resolution is still 1 km. To improve the spatial resolution of CEs, researchers have set up monitoring sites to accurately monitor CEs, but the human and capital costs are high38. Therefore, this method not suitable for large scale study. In recent years, emerging big data has provided an opportunity to study the spatial characteristics of high-resolution urban CEs. Web crawler technology (WCT) can be used to obtain information about the location and attributes of the CEs. In addition, points of interest (POI), which contain multi-attribute information and location, is an important data source. For example, Gao39 used POI to mapping urban carbon emissions with a high spatial resolution. In addition, power point and industrial facilities were used to map high resolutions CEs40. However, studies on high spatial resolution and spatial distribution of CEs in more sectors are still insufficient. In summary, existing CEs distribution research focus on region and global, based on NTL with 1 km resolution. So, urban and fine resolution CEs data is still rare.Although there is extensive research on carbon dioxide emissions (CEs), they are mainly focused on accounting and analyze the relationship between CEs and socio-economic. However, spatial research on CEs is insufficient. Quantification of fossil fuel CEs at fine spatial resolution is a critical need for climate change research and carbon cycle41.To meet the critical demands of carbon cycle study, urban precision carbon reduction strategies and carbon management, in this study, we developed an improved method and mapped urban CEs with a fine resolution by POI data. The CEs distribution of this study has better accuracy and fine resolution, compare to traditional NTL-based method. Moreover, different sectors CEs distribution is clear. We selected the international city of Shanghai as an example to map the CEs. In this study, we used POI data and GIS technology to map the fine resolution urban CEs. First, according to data availability and accuracy requirements, this study applied the bottom-up method to account urban CEs for residential, tertiary, and industrial sectors from 2000 to 2015. Moreover, this study used the POI data and multi sources data which obtained by web crawler technology (WCT). The method of mapping CEs in this study could clearly identify the CEs spatial patterns of each sector, and different from existing studies. We analyzed the spatial patterns of CE in Shanghai. We believe that this methodology could be applied in other fast-growing cities to understand carbon cycle and develop accuracy urban carbon reduction strategies2. It lies at the front edge of the Yangtze River Delta (YRD). The gross domestic product (GDP) increased more than 31 times from 1990 to 2015. At the same time, rapid urbanization and industrialization caused a sudden surge in energy consumption and an increase in the urban population. The development of the social economy, expansion of the city, and an increase in the population have led to an increase in CEs. Balancing environmental change and socio-economic development is an urgent need for many cities, particularly in mega cities such as Shanghai. As a resource-limited city, Shanghai, its energy mainly depends on imports. Therefore, understanding the distribution of CEs and reducing energy consumption are important ways to reduce urban CEs and achieve sustainable urban development. The findings and methods from this study will help conduct analyses for other cities, particularly developing cities.Shanghai is one of the megacities in the world. At the end of 2018, there were more than 24.24 million people living in Shanghai within the area of 6340.5 kmhttps://ditu.amap.com/) using Application Programming Interface (API) technology. We used 2002 POI data replaced the year of 2000, because Gaode was founded in 2001 and provided services in 2002. The POI data includes the residential, industrial, and tertiary sectors points. Residence community (RC) POI and industrial enterprise (IE) POI contain residential location information and type of enterprises, respectively. The residential area was estimated using statistical data from the Shanghai Statistical Yearbook (SSY) and the website of residential rental companies  by WCT. The land use data were in raster format with a spatial resolution of 30 m, they were obtained from the Resource and Environment Data Cloud Platform . The land use data included cropland, forest, grass, water, construction land, and unutilized land. Statistical data included the energy balance tables (EBTs) of Shanghai, population (POP), GDP, resident consumption, and energy consumption of key energy-consuming industrial enterprises . The EBT contains data on more than 15 types of energy consumption from industrial, tertiary, and residential sectors.To estimate the CEs distribution in Shanghai, geospatial and statistical data were used. Geospatial data included POI and land use data. The POI data for 2000, 2005, 2010, and 2015 were in vector format. This was obtained from the Gaode map . The CEs of each grid cell was mapped according to the CEI based on downscaling method. The distribution of CEs for each sector was mapped according to Eq.  and downscaling theory. Point density mapping has been widely used in spatial mapping researchg to Eq. .2\docume44.D is the CEs density (CEI), W is the weight, S is the search radius, j is the index, and m is the total number of pixels in the search area.The CEI reflect energy consumption and CEs intensity. And the CEI of grid cell for each sector was calculated according to Eq.  and WPD W is the weight, A is the residential area or ECKEIE, i and j are the index of POI, and n is the count of POI of a sector.In order to map CEI, different weights were used for residential, industrial, and tertiary points. Weights of residential and industrial were calculated according to Eq. , and bas2 according to the energy consumption intensity for each sector, mapping the CEs, and then calculated the total carbon dioxide by overlay analysis.According to the above-mentioned equations used to calculate the energy consumption density for the residential, tertiary, and industrial sectors, mapping the CEs see Fig.  involved42.Due to the lack of available high-resolution carbon emission spatial data as precision validation data, this study adopted the widely used NTL based downscaling carbon emission allocation method to produce validation data. More detail about the method was published by45. The global financial crisis triggered a global recession, which had an impact on the economy in Shanghai as well. The total CEs decreased by 11.56%, and the average growth rate of industrial CEs was 1.60% during 2009–2015, mainly due to the global financial crisis.The total CEs in Shanghai increased by 64% from 112.36 to 183.75 Mt, 2000–2015, with a 50% and 331% increase in the population and GDP, respectively . In addition, industrial transfer was mainly associated with high energy consuming factories, whereas labor-intensive factories remained in the city center of Shanghai, such as iron and steel enterprises. Thus, while the CEs increased in non-city center areas, they decreased in the city center areas (http://www.shanghai.gov.cn). Interestingly, the residential CEs increased in both the city center and its surrounding areas, particularly in the western part of the city center , we used CEs obtained by the NTL-based model method (NTL-based CEs), which maps CEs based on statistical model and NTL data, and then compared to POI-based CEs Fig. . There iThe results shown that more than 31.6% of the pixel values based on this study method are higher than those based on the traditional NTL method. The highest value in NTL-based CEs was 122.49 kt. We set the low range as 0–30% of the highest value, which from 0 to 36.75 kt. Moreover, the high range is 80–100% of the highest value, which between 85.75 and 122.49 kt. According to Fig. Figure We compared the CEs distribution of NTL-based and POI-based method, the CEs distribution of POI-based was found to have more details and fine resolution. Additionally, the heterogeneity of CEs distribution in the three sectors could be assessed at a fine resolution Fig. . The spaTo verify accuracy of CEs by POI-based method, we employed a sampling line see Fig. a to extrThe distribution of urban CEs was assessed based on POI data and its energy consumption intensity. The uncertainty of the POI data and attribute data was consistent with the uncertainty of the distribution of CEs. In addition, energy consumption data and CEs parameters obtained from the existing literature and materials also have some limitations. As the energy consumed in city areas is imported from other cities and areas, energy use types and energy tastes are different. Therefore, there are limitations in using statistical data and uniform CEs parameters to calculate CEs. Moreover, because of the lack of high-resolution remote sensing data of CEs as reference data, it is difficult to accurately assess the accuracy of our estimations. The lack of more detail on companies', residential, and tertiary energy consumption limits the accuracy of the spatial allocation of carbon emissions. In conclusion, with the improvement of more details of energy consumption data and the enrichment of spatial data, the accuracy and reliability of spatial distribution data of CEs will be significantly improved.In this study, a downscaling CEs allocation method based on POI method was developed to achieve fine spatial resolution allocation of CEs and draw spatial distribution maps for different sectors. Based on the fine resolution mapping method of carbon dioxide emissions and dataset at the urban scale, which was proposed in this study, several potential uses could be obtained. They include, but are not limited, the following.First, this method could be applied to map the distribution of urban CEs and as a decision support tool for the analysis of spatial–temporal changes in high-resolution urban CEs in other cities. Second, high-resolution urban CEs data could be used to understand the relationship between spatial–temporal changes and social economy. Third, fine-resolution urban CEs data could be used as a data source for urban spatial planning, also useful to develop accurate urban carbon management strategies. In addition, fine resolution CEs data could meet the critical need of carbon cycle, climate change research, and emerging flux inversion.The goal of this study was to propose an improved method for mapping a fine resolution urban CEs. We found that results obtained using our method had a higher resolution than the traditional NTL-based method. In addition, the method of this study is suitable for mapping the CEs of sectors. This case study in Shanghai suggests that the CEs method based on POI is suitable for the high-resolution spatial distribution under province level. The method effectively draws the spatial characteristics and heterogeneity of urban CEs, and its spatial resolution is better than traditional method. It is important to point out that the POI-based method can accurately determine both emission extent and intensity, be able to identify the carbon emissions of different sectors. In addition, POI-based CEs draws more details and close to reality. Therefore, the improved method is better than the traditional method for mapping CEs. We also found that the total CEs in Shanghai witnessed a three-stage increase from 2000 to 2005, and a steady growth from 2005 to 2009. The global financial crisis strongly impacted CEs growth from 2008 to 2009. The global financial crisis markedly decreased CEs from 2008 to 2009, particularly from the industrial sector. A significant relationship between economic growth and CEs was also observed. The industrial sector was found to be the largest CEs contributor, followed by residential and tertiary sectors. Industrial CEs have shaped the trend in total CEs. These industrial CEs slightly decreased in the city center, but increased in the peri-urban areas. The CEs of residence and tertiary areas significantly accumulated in city center regions and increased rapidly in suburbs.


Early detection of children with autism spectrum disorder (ASD) and comorbid intellectual disability (ID) can help in individualized intervention. Appropriate assessment and diagnostic tools are lacking in primary care. This study aims to explore the applicability of machine learning (ML) methods in diagnosing ASD comorbid ID compared with traditional regression models.From January 2017 to December 2021, 241 children with ASD, with an average age of 6.41 ± 1.96, diagnosed in the Developmental Behavior Department of the Children’s Hospital Affiliated with the Medical College of Zhejiang University were included in the analysis. This study trained the traditional diagnostic models of Logistic regression (LR), Support Vector Machine (SVM), and two ensemble learning algorithms [Random Forest (RF) and XGBoost]. Socio-demographic and behavioral observation data were used to distinguish whether autistic children had combined ID. The hyperparameters adjustment uses grid search and 10-fold validation. The Boruta method is used to select variables. The model’s performance was evaluated using discrimination, calibration, and decision curve analysis (DCA).Among 241 autistic children, 98 (40.66%) were ASD comorbid ID. The four diagnostic models can better distinguish whether autistic children are complicated with ID, and the accuracy of SVM is the highest (0.836); SVM and XGBoost have better accuracy ; LR has the best sensitivity (0.939), followed by SVM (0.952). Regarding specificity, SVM, RF, and XGBoost performed significantly higher than LR (0.355). The AUC of ML  is not different from traditional LR (0.858 [95% CI: 0.770–0.944]). Only SVM observed a good calibration degree. Regarding DCA, LR, and SVM have higher benefits in a wider threshold range.Compared to the traditional regression model, ML model based on socio-demographic and behavioral observation data, especially SVM, has a better ability to distinguish whether autistic children are combined with ID. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social disorder and restricted, repetitive, stereotyped behavior . The worThe proportion of ASD combined with intellectual disability (ID) is about 33–35% , 6, withWechsler Intelligence Scale for Children-IV (WISC-IV) is the most commonly used tool for evaluating intelligence levels , and it In the research of disease diagnosis, regression analysis is a commonly used diagnostic method –29, whicThe existing predictive diagnosis of ASD or ASD comorbidities  usually includes four aspects, disease prevention or risk factor identification, disease diagnosis, disease efficacy prediction, and disease prognosis prediction. Most of these diagnostic models use complex diagnostic-related data, such as expensive head MRI, EEG –39, and This article intends to combine the behavioral observations and socio-demographic data of children with ASD, apply ML methods to the diagnosis of ID in autistic children, and optimize the diagnostic model through feature selection. Simultaneously, SVM, RF, and XGBoost models are compared with the traditional LR model. Finally, comprehensive use of discrimination, calibration, and decision curve analysis (DCA) to evaluate and screen the optimal diagnostic model provides a new perspective for early diagnosis of autistic children with ID.This study retrospectively collected ASD data from January 2017 to December 2021 in the department of Developmental and Behavioral Pediatrics, the Children’s Hospital, Zhejiang University School of Medicine. These children with ASD met the diagnostic criteria for ASD in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5). They were also assessed by the WISC-IV and the Adaptive Behavior Assessment System-II (ABAS-II) for adaptive behavior. Those children who scored below 70 on the WISC-IV and had an adaptive disorder were diagnosed with ASD combined with ID. Socio-demographic information and behavioral observation data were used as variables in this study, and the findings were the result of the WISC-IV assessment see the . Socio-dThe choice of variables has a decisive impact on the final model performance. Therefore, this study used the Boruta method to process the variable list, a feature selection method established using a random forest classifier . It deteP < 0.05 was considered statistically significant).To quantitatively evaluate the impact of feature selection on the model, we separately constructed models based on all variables and the variables of feature selection and evaluated the contribution of feature selection to the diagnostic model using integrated discrimination improvement index (IDI) . PerformThis study compares traditional LR to other ML methods using it as a reference model. The binary logistic regression used in the study had only two possible outcome values (low versus high function). The log-odds of values marked “1” in LR are linear combinations of predictors, and LR can be expressed as:x is the predicted value, y is the result, w is the weight of each predicted value, and b is the intercept.where The final decision function of SVM is only determined by a very small number of support vectors . Thus, iThis study selects RF and XGBoost as representative ensemble learning models. RF is one of the commonly used Bagging methods. Breiman proposed it in 2001 . It can The dataset is divided into the training set and test set with a ratio of 7:3, which are used for modeling and model performance evaluation. In the modeling phase, Boruta’s method filters variables, and 10-fold cross-validation and grid search were used to tune hyperparameters. The subjects’ accuracy, precision, sensitivity, specificity, and area under curve (AUC) were used to evaluate the model’s discrimination. The Bootstrap method was used to calculate the 95% confidence interval (95% CI) of AUC, and De-long test was used to compare AUC between diagnostic models. Additionally, each diagnostic model is evaluated for its agreement with the ground truth using a calibration plot. Finally, we performed DCA to provide a reference for selecting the best diagnostic model and clinical practice. DCA is a simple method for evaluating diagnostic models that consider both accuracy and clinical utility, as Andrew et al. proposed in 2006 .Furthermore, we use the SHapley Additive exPlanations (SHAP) method to evaluate the interpretability of the optimal model. The SHAP method is derived from game theory based on the SHAP value, which shows the importance of variables and determines the direction of effects , 48.2 test or Fisher’s exact test was used to compare the rates, the t-test was used to compare the means of normal distribution, the rank-sum test was used to compare the means of non-normal distribution, and the univariate analysis was used to compare the multi-category distribution. Two-sided P < 0.05 was considered statistically significant. All methods in this study were implemented with R 3.6.0 with a random seed set to 123. The Boruta feature selection method is derived from Boruta version 7.0.0. pROC version 1.17.0.1 is used for pairwise comparison of AUC, ROC calculation, and drawing. PredictABEL version 1.2-2 is used for the implementation of the IDI evaluation method; e1071 version is used for model parameter tuning 1.7-6; randomForest version 4.6-14 is used to build random forest; e1071 version 1.7-6 is used to build SVM; XGBoost version 1.2.0.1 is used to build XGBoost.Continuous variables were expressed as mean ± SD  and median of the interquartile range , and categorical variables were expressed as percentages. The χA total of 241 children with ASD were included, including 98 with ID, with an average age of 6.41 ± 1.96 .Z-score, average Z-score, and minimum Z-score of the shadow feature. Green features are accepted , and red features are rejected . The yellow features are regarded as edge features (age). Finally, we included 10 accepted variables and edge variables  (The Boruta-based feature selection results are displayed in haviors) .P < 0.05). On the other hand, LR model has a certain degree of improvement, but the difference is not statistically significant (P > 0.05). Therefore, this study selects 10 variables for the final modeling.In addition, IDI was calculated to evaluate the contribution of feature processing features . The resThe performance is displayed in The calibration graph evaluates the consistency between the model prediction results and the actual situation. The SVM is more consistent with the actual situation, and the prediction consistency between LR, RF, and XGBoost is poor .X-axis indicates that all autistic children were non-ID and intervened, with a net benefit of 0. The ALL symbol represents the net benefit at various thresholds, with an assumption that all children with ASD have ID. In most cases, we found that the net benefit of LR was higher than that of SVM, RF, and XGBoost models. However, when the threshold exceeded 0.70, the net benefit of the two ensemble methods returned to zero, while LR and SVM still had an enormous net benefit.Decision curve analysis curve results are illustrated in In practice, the threshold is set according to actual requirements. We can use the proportion of non-ID and combined ID in autistic children with different demographic characteristics to calculate and determine the net benefit of different diagnostic models under the set conditions to evaluate the practical value of the model.To summarize, SVM has higher accuracy, precision, sensitivity, better calibration, and higher benefit over a more extensive threshold range. Therefore, combining discrimination, calibration, and clinical decision curve, we finally choose SVM as the predictive model for whether autistic children are combined with ID.The results for the different importance of each model are demonstrated in We further used SHAP plots to understand the interpretability of SVM . The resIn this study, based on the socio-demographic information and behavioral observation data of children with ASD, the ML methods were used to construct a diagnostic model for whether autistic children were combined with ID. The results demonstrated that the ML methods could effectively distinguish whether autistic children combined ID. Before building a model requires sufficient data preprocessing, such as outlier identification, missing value filling, normalization, feature selection, etc. The data integrity in this study was all above 99%, indicating that the quality of the data used for diagnosis was good. For variables, this study uses the methods of outlier identification, missing value imputation, normalization, and feature selection to deal with variables. Some studies have pointed out that sufficient data preprocessing should be carried out before training the diagnostic model .d and Pearson’s rpb , 0.829 (0.738–0.920), 0.845 (0.747–0.944), and 0.845 (0.734–0.937), respectively. In the existing evaluation system, there is no evaluation of AUC. The accepted threshold for assessing good classifiers. Rice et al. proposed that AUC can be converted to effect sizes, such as Cohen’s on’s rpb .d values of LR, SVM, RF, and XGBoost were 1.515, 1.344, 1.436, 1.436, and rpb were 0.604, 0.558, 0.583, and 0.583, respectively. According to Cohen’s d intensity criteria, our diagnostic models are equivalent to high impact levels. According to the standard of impact strength on rpb, traditional LR demonstrated high correlation, and SVM, RF, and XGBoost revealed moderate correlation levels. In addition, some studies also show that the performance of ML and regression models are comparable . Although RRB is one of the two core symptoms of children with ASD, it is not unique to autism. Other neurodevelopmental disorders and even ordinary children may also have RRB manifestations . TherefoAlthough language disorder (LD) is no longer a core symptom of ASD, it is one of the common comorbidities of ASD . About 6The average level of the mother’s educational level ranks third in the four models. That is to say, whether autistic children are combined with ID may have a certain relationship with the mother’s educational level. The higher the mother’s education level, the lower the likelihood of autistic children with ID. The lower education level of parents may affect their awareness of ASD, thereby delaying the diagnosis of children with ASD , and motAssessing the clinical utility of diagnostic models can guide clinical practice. DCA was performed in this study, combining discrimination, calibration, and DCA, and the results showed that SVM was relatively superior in terms of clinical benefit and ability to discriminate against autistic children with ID. Medical and health workers can collect socio-demographic data and behavioral observations of autistic children and use the recommended SVM model for children with autism in grassroots units that cannot conduct systematic intelligence assessments . Preliminary diagnosis of ID is the premise of a stepped care and personalized health approach for children with different types of ASD .Our study may have some potential advantages. First, we used demographic and behavioral observational data from a population cross-section to construct a diagnostic model with low costs of model construction and easy access to diagnostic data. Therefore, initial diagnostic screening may be applicable to primary care physicians. Second, the optimal SVM model is computationally efficient and can be quickly computed in real time during practical application. In addition, we conducted a relatively complete data pre-processing work to ensure the processing effect of the prediction model and provide a solid foundation for the model architecture. Finally, we conducted a comprehensive evaluation of the prediction model, including traditional metrics , and clinical utility analysis (decision curves and prediction curves). The SHAP method was also used with a view to discussing in further depth the interpretability of the ML model. Also we followed the standard reporting procedures for prediction models described in TRIPOD .The limitation of this study is that the sample size is relatively small. If the sample size continues to increase, the model trained by ML will be more convincing. Concurrently, this study only evaluates the generalization ability of the diagnostic model through internal verification. Further research must be conducted in other perform external validation on ASD population in the region or subsequent children on the ASD in the region. The diagnostic model is based on the current behavioral observation to evaluate the current IQ, which solves the current situation that the intelligence test cannot be fully promoted in real situations. However, children with ASD are frequently diagnosed in early childhood, and intelligence evaluation results at this stage are not stable. Therefore, predicting school-age IQ through behavioral observations of children with ASD in early childhood is more in line with clinical reality, which needs to establish a follow-up cohort of autistic children.Based on the data of children with ASD in Zhejiang, China, the ML model can effectively distinguish whether autistic children are combined with ID. Given the degree of discrimination, calibration, and clinical usefulness, we believe SVM is the best model for screening autistic children with ID.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.CS conceived the study and wrote the draft of the manuscript. Z-QJ conducted literature searches and completed the data analysis. L-FH and X-LL engaged in behavioral observation. W-HL, Y-YW, and W-YJ conducted the IQ test. Z-WZ critically revised the manuscript. All authors contributed to the article and approved the submitted version.


Many anthropometric parameters  present significant correlations with health variables . We conclude that greater adherence to Mediterranean diet is associated with healthier values of the selected anthropometric and health parameters. Since most of the anthropometric and health parameters present significant correlations among themselves, this finding could be useful in medical diagnosis, health monitoring, and risk detection. Based on the level of adherence to Mediterranean diet and the KIDMED found in the present study, and considering the prevalence of obesity in the Middle East, it is imperative to implement nutritional interventions with the target population of this research to prevent nutrition-related diseases and promote public health.The present study aimed to verify the association between adherence to the Mediterranean diet (MD) and anthropometric and health variables. Four-hundred-and-ninety-five college-aged males aged 18–25 participated in this cross-sectional research. The KIMED  was used to assess the adherence to MD. The following variables were also assessed: body mass (BM), height (HE), body mass index (BMI), body fat percentage (%FAT), lean mass (LEAN), abdominal girth (AG), waist-to-hip ratio (WHR), oxygen saturation (SPO2), systolic blood pressure (SBP), diastolic blood pressure (DBP), double product (DP), and fasting blood glucose (GLU). The results showed that adherence to MD presented a strong negative correlation with most of the anthropometric parameters (BM:  Nowadays, the Mediterranean diet (MD) is one of the healthiest dietary patterns. It provides an adequate quantity and quality of nutrients to improve health conditions and prevent diseases ,2. In adMD is based on a regular and generous consumption of seasonal plant-based foods such as fruits, vegetables, nuts, and whole grains. Olive oil is the main source of fat. The intake of fish, dairy products, poultry, and eggs is moderate, whereas red meat and sausages are consumed infrequently and in small quantities . Thus, MUnfortunately, adherence to MD has declined worldwide, including in Mediterranean countries , and amoFurthermore, many existing articles examined the adherence to MD ,34, and In non-Mediterranean countries, MD is being promoted because its benefits are increasingly recognized. This has been accompanied by increased scientific interest in MD . HoweverA cross-sectional descriptive observational study was carried out. The STROBE  guidelines were followed.(a)Male(b)Aged 18–25 years(c)Resident in Riyadh(d)Do not suffer from nutritional , traumatic , genetic , endocrine , mental , or degenerative  diseases.A total of 495 college-aged individuals were included in the current research. They were duly informed of the objectives, benefits, and risks of participating in the present study and signed an informed consent form indicating their willingness to be included in it. They were also instructed that they could withdraw from the study without penalty. Subjects were granted anonymity when handing the data collected and informed that it would be used only for scientific purposes. Moreover, they receive no academic or monetary compensation for their contribution. The inclusion criteria were: The study was held in Riyadh between 15 May and 30 June 2022. A stratified random sample from the 15 districts that make up the city was used for subject selection. Potential participants were contacted and invited to participate in the current research through Riyadh municipality forum groups available on social media (WhatsApp and Facebook Messenger). Once 600 volunteers expressed their willingness to participate in the study, all of them were summoned to attend the tests and fill out the questionnaire. Finally, a total of 495 subjects completed all assessments. To estimate the sample size required, the following equation :n = Z2p The KIMED index was used to assess the adherence to MD. This questionnaire is based on the principles of the MD pattern. The validity and reliability of this instrument to measure the adherence to MD of college-aged individuals in non-Mediterranean countries has been previously confirmed . The KIDThe KIDMED questionnaire was applied again to all subjects to verify the reliability of the measurement. That is, a test–retest method was used. The interval between both measurements was three weeks, which is the optimal recommended time . The tesAssessments were made following the indications of the ISAK , and usiTo measure the skin folds, a FG1056 Harpenden skinfold  caliper was used. Lean mass (LEAN) was calculated with the following equation:Abdominal girth (AG) and WHR were evaluated using a Seca 203 Ergonomic Circumference Measuring Tape , and it was calculated through the following equation:Oxygen saturation (SPO2) was measured on the index finger, with the patient seated and calm, using a BPL Smart Oxy Lite Pulse Oximeter . Systolic and diastolic blood pressure (SBP and DBP) and heart rate (HR) were assessed with the subject seated and relaxed using an Omron Upper Arm Gold Blood Pressure Monitor . The three measurements were taken with a time interval of 1 min . The douFinally, fasting blood glucose (GLU) was measured with a Benecheck 3 in 1 Meter Kit . Each of the above variables was measured by the same researcher.This study was conducted in accordance with the ethical principles set out in the Helsinki Declaration. It was also approved by the Institutional Review Board of the Bioethics Committee at Prince Sultan University in Riyadh, Saudi Arabia (PSU IRB-2022-06-0115).r = 0 null correlation; 0.01 ≤ r ≤ 0.09 very weak; 0.10 ≤ r ≤ 0.29 weak; 0.30 ≤ r ≤ 0.49 moderate; 0.50 ≤ r ≤ 0.69 strong; and r ≥ 0.70 very strong [p values were found, Tukey’s post hoc test was performed. The effect size was calculated using the partial eta squared (ηp2). Values of ηp2 = 0.01, ηp2 = 0.06, and ηp2 = 0.14 were considered as small, medium, and large effect sizes, respectively [p < 0.05. The statistical analysis was performed using the program IBM SPSS V.26® computing .The results are presented using the format mean SD (standard deviation). The data’s normality and homoscedasticity were verified using Kolmogorov–Smirnov and Levine’s test, respectively. The associations between variables were examined using the Pearson correlation coefficient, and the results were interpreted as follows: y strong . The oneectively . A stepwThe characteristics of study participants and the results they obtained in the anthropometric and health assessments are shown in Of the 495 study participants, 6.46% (n = 32) showed a low level of adherence to the Mediterranean diet, 62.62% (n = 310) a medium adherence, and 30.91% (n = 153) a high adherence. The average KIDMED index was 6.41 (1.87) for the whole sample, and for the cohorts that present a low, medium and high level of adherence to MD was 2.80 (0.20), 5.75 (0.15), and 8.54 (0.13), respectively. Furthermore, once the normality and homoscedasticity of the data had been verified, Pearson’s correlation analysis was conducted see , and thep < 0.0001; ηp2 = 0.211); BMI ; %FAT ; LEAN ; AG ; SBP ; DBP ; GLU ; and DP . The posterior Tukey´s post hoc test revealed that subjects´ with low adherence to MD presented a significantly higher BM ; BMI ; %FAT ; LEAN ; AG ; and GLU  than those subjects with medium adherence to MD. Similarly, subjects with low adherence to MD presented a higher BM ; BMI ; %FAT ; LEAN ; AG ; SBP ; DBP ; GLU ; and DP  than those subjects with high adherence to MD. Finally, subjects with medium adherence to MD presented a significantly higher BM ; BMI ; %FAT ; LEAN ; AG ; SBP ; DBP ; GLU ; and DP  than those subjects with high adherence to MD. Moreover, no significant effect was found for the following variables: AGE, HE, SPO2, and WHR.Comparisons between different levels of adherence to the Mediterranean diet are shown in The multiple regression analysis conducted originated two models see . AccordiThis research analyzed the association between adherence to MD and anthropometric and health variables. To our knowledge, this research is one of the few studies that has analyzed the mentioned association, including a large stratified sample and a comprehensive number of anthropometric and health variables. It is also the only study to do so in the Middle East region with college-age individuals. One of the main findings of the present study was that 6.46% of the study participants showed a low level of adherence to MD, 62.62% a medium adherence, and 30.91% a high adherence. If we compare these data with studies carried out with subjects of similar ages wherein the KIDMED index was used, we can appreciate the level of adherence is similar to that registered by de la Montaña et al. (2012)  and PadiTherefore, considering KIDMED figures found in the present research, there is significant room for improvement in the eating habits of the study participants. To this end, Durá-Travé et al. (2011)  considerAnother important finding of the present study is the significant negative correlation found between adherence to MD and most of the variables analyzed. This correlation is strong with most anthropometric parameters , moderate or weak with many health variables  and LEAN, and very weak in the case of WHR. In addition, it should also be stressed that BMI and %FAT are predictor variables of KIDMED. By contrast, no significant correlation was observed between AGE, HE, and SP02 and adherence to MD. The presence or absence of a correlation between variables is consistent with the results obtained from the one-way ANOVA comparisons established between cohorts according to the level of adherence to MD . Regarding anthropometric variables, the correlations between these variables and greater adherence to the Mediterranean diet are consistent with studies carried out by Galan-Lopez et al. (2020)  with adoFurthermore, it should again be recalled that most of the studies conducted to date to analyze the adherence to MD have examined only a small number of anthropometric parameters, particularly BMI. Therefore, it is recommended that future studies include a comprehensive number of anthropometric variables. As for the present study, it was verified that while BM, BMI, %FAT, and AG have a strong correlation with adherence to MD, this correlation is weak in the case of WHR. This suggests that WHR—although it may be a better predictor for cardiovascular or metabolic disease than BMI, or AG —could beAs expected, study participants with higher levels of MD adherence showed lower SBP and DBP values. These results agree somewhat with the findings of De Pergola and D’Alessandro (2018) . After cAccording to the patterns established by the Mediterranean diet, protein consumption implies increasing the intake of fish, nuts, and low-fat dairy and reducing the intake of red meat. However, this fact does not increase sodium intake, meaning that it positively affects BP. Jennings et al. (2019) , TeunissGLU also maintained a significant correlation with the levels of adherence to the Mediterranean diet in the present study. These results —which coincide with previous research —could beInterestingly, the present study’s results also showed significant correlations between anthropometric  and health variables . These interconnections reveal the possibility that the human organism works as a functional unit so that the different systems that make up the human being interact with each other, and the correct functioning of one organ conditions the health of the others. This circumstance highlights the usefulness of the mentioned variables for evaluating the health status, health risks, and the diagnosis and monitoring of diseases .Furthermore, three variables did not correlate with adherence to MD . As for the AGE, the results of the present study are compatible with most of the previous research conducted with adults, wherein AGE did not significantly determine the levels of adherence to MD . MoreoveFinally, it is necessary to mention the strengths and limitations of the present research. As for the strengths, the study was conducted with a large stratified sample of subjects, in a non-Mediterranean country, and with an age group that—despite not being extensively studied—is interesting to analyze since college-aged individuals are often subject to modifications in their habits and schedules, which may affect their eating patterns. Likewise, a broad set of anthropometric and health parameters was analyzed. Regarding the limitations, women were not included in the study, and the lipid profile was not analyzed. Therefore, it is recommended that future studies include both sexes and different population groups and analyze as many biomarkers as possible, including the lipid profile. Additionally, the KIDMED questionnaire was administered using the digital support of Google Forms to avoid incomplete or partial submissions. However, this circumstance can also be considered a limitation of the study because that is not the format initially envisaged for the questionnaire management.Greater adherence to Mediterranean diet is associated with healthier values of numerous anthropometric and health variables . In contrast, no significant correlation was observed between age, height, and Oxygen saturation and adherence to Mediterranean diet. Many anthropometric parameters  present significant correlations with health variables . This could be useful for medical diagnosis, health monitoring, and health risks detection. Based on the levels of adherence to Mediterranean diet and the KIDMED index found in the present research, there is significant room for improvement in the dietary habits of college-aged citizens residing in Riyadh. Therefore, considering these results and the prevalence of obesity in the Middle East, nutritional interventions should be urgently implemented with the target population of this study to prevent nutrition-related diseases and promote public health.


Results indicate that CE strongly associates with Individual Emotions –in particular, Self-Transcendent Emotions– and Communal Sharing constructs , providing construct validity. Among the distal effects of CE, it is associated with Collective Positive Emotions, long-term Social Integration , Social Values and Beliefs and Empowerment-related variables . Among the moderation analyses carried out , the effects of CE in demonstrations are noticeable, where this variable is a factor that favors other variables that make collective action possible, such as Group Identity (rpooled = 0.52), Collective Efficacy (rpooled = 0.37), Negative and Self-Transcendent Emotions (rpooled = 0.14 and 0.58), and Morality-related beliefs (rpooled = 0.43).In this article, we review the conceptions of Collective Effervescence (CE) –a state of intense shared emotional activation and sense of unison that emerges during instances of collective behavior, like demonstrations, rituals, ceremonies, celebrations, and others– and empirical approaches oriented at measuring it. The first section starts examining Émile Durkheim's classical conception on CE, and then, the integrative one proposed by the sociologist Randall Collins, leading to a multi-faceted experience of synchronization. Then, we analyze the construct as a process emerging in collective encounters when individuals contact with social ideal and values, referring to the classical work of Serge Moscovici as well as those more recent empirical approaches. Third, we consider CE as a set of intense positive emotions linked to processes of group identification, as proposed by authors of the Social Identity Theory tradition. Finally, we describe CE from the perspective of self-transcendence , and propose a unified description of this construct. The second section shows the results of a meta-analytical integration ( At the dawn of the twentieth century, a series of researchers and theorists tried to understand and explain the human experience in social rituals and gatherings —based on the ethnographies conducted by Spencer and Gillen  their first effect is to bring individuals together, to multiply the relations between them, and to make them more intimate with one another. By this very fact, the contents of their consciousnesses are changed. (p. 348)Under these conditions, the utilitarian and individual preoccupations that dominate in profane life are eclipsed and the parcel of social being that each person carries within is revived and emerges to the forefront of consciousness. Thoughts focus on common beliefs, common traditions, and collective ideals. Homogeneous manifestations then develop in the assembly. By uttering the same cries, the same words, and the same gestures, individuals nourish the group feeling. Strong emotional experiences arise because every feeling expressed resounds in other consciences. Each of them echoes the others and vice versa, resulting in a reciprocal amplification. Progressively, participants enter into communion and CE takes place. Durkheim argued that once individuals are assembled, a “sort of electricity is formed by their collecting which quickly transports them to an extraordinary degree of exaltation” (p. 212). He insisted that the CE is independent of the type of emotion involved. Whatever the emotion, the key point is that it has to be shared. The social sharing of emotions in itself represents the decisive condition for a state of effervescence to arise. This point is made particularly clear in the author's descriptions of mourning rituals which are framed around negative emotions  as theorized above . In their view, cultural practices such as collective gatherings and rituals can evoke in witnesses and participants the sudden intensification and salience of the Communal Sharing mode. In turn, this triggers kama muta, characterized by feeling moved or touched, positive affect, bodily responses such as tears, chills, or warmth, and action tendencies such as approach behavior, affiliation, prosocial behavior, and social bonding  and collective  levels. It is a process that implies attentional  and behavioral  convergence and, above all, emotional synchronization . When these criteria are met, CE usually implies a beyond-normal emotional intensification or emotional feedback. In other words, after the convergence of attention, as well as that behavioral and emotional, participants of a collective gathering will feel emotions of greater-than-normal intensity and an enhanced sense of unison with others.Here, we briefly summarize the major effects of CE that recur among authors  Affective reactions or the emotions felt by participants as individuals during collective gatherings. These emotions—which are proximal from a time perspective—include (a) general activation or emotional arousal; (b) negative emotions in negatively valenced events; (c) positive emotions, which are often reported when individuals come together even when their meeting involves negative emotions ; (d) self-transcendent positive emotions which include elevation, compassion, admiration, gratitude, kama muta or moved by love, and social awe;(2) Communal sharing. These proximal effects refer to the individual relationship with her co-participants of the collective gatherings and includes (a) social identification or self-categorization as a member of the group or collective; (b) feeling the individual self as less important than the collective self, or feeling that the individual self and the collective overlap, merge, or are fused into one; and (c) an increased sensation of social support with the group.Outcomes that are more distal may include:(3) Collective emotions or emotions perceived as dominant in the group during a given period, and organized broadly into negative or positive climate.(4) Social integration. This group of outcomes consists on those variables that reflect a psychological connection with those represented in the gathering but not necessarily present. It includes: (a) an enhanced feeling of commitment toward the group, and (b) an identification with those that are not in the gathering .(5) Social values and beliefs. According to what is being enacted, represented, celebrated, etc., in the collective gathering, CE can facilitate greater agreement with (a) social values  and (b) self-transcendent beliefs, spirituality- and religion-related beliefs, as well as those related to purpose or meaning of life.(6) Empowerment among those who participate. Finally, CE can boost the subjective perception of (a) vitality and wellbeing among those who take part in the collective event, as well as (b) self-esteem and efficacy. The latter, could be related to co-participants  or to an extended group .Specifically, in order to analyze the role of CE in the fueling of social movements, we will examine its association with factors that are both conducive and explanatory of the participation in collective action or social movements. Demonstrations as a protest ritual are not only aimed to change the social milieu, but are also symbolic performance with an expressive purpose. Demonstrations “provide participants with the sense of being engaged in a common cause with a large number of like-minded people who share similar feelings about an issue, mass gatherings also work as opportunities to cement a given social group” , but rather an emotional phenomenon that implies jointly experienced affect. In addition, it is not subjected to positive affect solely; rather, it can also be the result from negatively valenced emotions, such as the common pain, sadness and grief present at a funerary ritual.So far, we have reviewed theories and research related to CE. We will now consider available empirical studies and datasets addressing collective events and report a meta-analytic examination of the relationship between their various measures and operationalizations of this construct, as well as its relationship with several criterion variables. For the latter, we considered variables that came up repeatedly throughout the review of the theoretical and empirical literature. The meta-analytic review will allow an accurate assessment of the association of each of these variables with measures of CE.Accordingly, we organize the associations of CE with a series of dependent variables from empirical studies, similarly as presented above  and in two levels of analyses: proximal and distal outcomes (see Section Procedure). In further detail, we examine the effects of participation in demonstrations to examine whether they reinforce explanatory principles of social movements, such as collective or social identity, social efficacy, negative emotions linked to relative deprivation and injustice, as well as positive moral emotions.https://osf.io/wb8c5/?view_only=~da9c179483f64d229a29ff5397bb9930.Following the American Psychological Association (APA) Meta-Analysis Reporting Standards (MARS) and more biological related PRISMA guidelines  quantitative measurement of CE, (b) at least one criterion variable, (c) individual-level responses or aggregated data, and (d) report at least one correlation or beta coefficient between (a) and (b) see .Mage = 30.8, SD = 9.15; 58.8% female) (see N = 10), demonstrations (N = 15), religious events (N = 10), sports gatherings (N = 4), music festivals (N = 3), others . The studies involved various designs , types of collective gatherings , and measurements of collective effervescence .The final selection comprised 41 articles encompassing 50 studies that have included in total 182,738 participants  see . These sFollowing Lipsey and Wilson's  guidelinOne widely-used measure of CE consisted of scales comprising from 5 to 18 items inspired by the concept of PES described earlier in this article. These items assess mutual entrainment of intense emotions, their coordination and sharing with others, and feelings of unity with others  individual emotions felt by participants, (2) communal sharing or immediate social integration, (3) collective emotions, (4) social integration, (5) social values and beliefs, and (6) empowerment. We made a distinction between immediate effects  and more or less long term effects . In addition, immediate effects represent facets or features that conform the construct of CE.In this category, we included variables addressing either the participants' own states and feelings, or how they feel with regard to co-present participants. Such effects can therefore directly affect the course of the collective situation namely, by intensifying emotional arousal and positive emotions or by feeding up an experience of self-transcendence. Other proximal variables are related to situated or immediate social integration, like altering the perception of individual boundaries, enhancing openness to others. In all, these variables also serve as construct validity criteria, since they are constructs that cover the two essential elements of CE found in the literature review: emotional reactions and a sense of union with others. The variables included here  are considered by scholars as criteria or indexes of a state of CE Draper, . VariablThis class comprised self-reported individually-felt emotional states . Other distal outcome variables were assessed in follow-up measurements and thus regarded effects that participants carry with them in the period after the collective event. The following variables were considered under this second category see .Several studies included a Perceived Emotional Climate scale assessing the emotional atmosphere as currently perceived by respondents .r = 0.18 and 0.16), and included in the fourth or highest quartile  brought a much robust result and neither the rank correlation nor the regression test indicated any funnel plot asymmetry .As displayed in r = 0.55, and with Self-Transcendent Emotions, r = 0.58. Fail-safe N tests returned values of 28,425 and 21,636, respectively. For the association with Positive Emotions, Egger's regression test showed a significant value , but no the rank correlation test (p = 0.129 and 0.393). In the case of negative emotions, CE was not significantly associated with negative affect.CE was also significantly associated with individual Positive Emotions, rpooled = 0.33–0.69. Specifically, it was associated with every form of ingroup identification, namely with Ingroup Identity (r = 0.47) as well as with the verbal (r = 0.69) and pictorial measures of Fusion of Identity (r = 0.35). In all cases, fail-safe N tests , and regarding asymmetry of the funnel plot, neither the rank correlation nor the regression test indicated asymmetry for Ingroup Identity , for the verbal measure  of for the pictorial measure of Fusion of Identity .CE was significantly and positively associated with every measure of social integration that involved a relationship between the participant and their ingroup or people participating in the collective gathering, with large effect-size correlations ranging from r = 0.33, with a large fail-safe N and a non-significant rank correlation nor the Egger's regression .Finally, CE was also associated with the perception of receiving social support from ingroup members, r = 0.25), or the perception that people feel shared positive emotions for a given period. The fail-safe N test (Nfs = 99) and a non-significant rank correlation and Egger's regression  indicated robust effects and absence of publication bias. Pooled rs revealed that collective effervescence was not significantly associated with Negative Emotional Climate.CE was associated with Positive Emotional Climate .CE correlates with self-reported participants' investment in the group  with r = 0.45), Schwartz's Self-Transcendent Values (r = 0.34), Purpose in Life (r = 0.36) and Spirituality (r = 0.37).N tests returned values of 3,046, 206, 2,182, and 489 (respectively). In addition, all p-values of the rank correlations and Egger's regression tests were non-significant , indicating and absence of publication bias for all analyses in this dimension.We also found positive and significant associations between CE and Self-Transcendent Beliefs (r = 0.24) with robust results and no evidence of publication bias . The same was the case for its association with wellbeing , Self-Esteem (r = 0.15), Collective Efficacy (r = 0.46), and Collective Self-Esteem (r = 0.42), revealing stronger associations for variables at the collective level  than the individual level . However, analyses revealed some indication of possible asymmetry in the funnel plot for the variables Collective Efficacy and Collective Self-Esteem, since the Egger's regression test was significant in both cases (ps <0.001) but not the rank correlation tests . In the case of Self-Esteem, finally, both tests were significant (p = 0.017 and p < 0.001), suggesting strong asymmetry in the funnel plot.For the final dimension, we found that CE was significantly associated with all the variables included. First, it was associated with Vitality , around 30% were medium , and around 13% were small . In addition, and as it was expected, the largest effects were found in the associations with proximal outcomes—also considered validity criteria—with variables such as Self-Transcendent Emotions and Fusion of Identity. Conversely, the weakest associations, were with Self-Esteem , and only two associations were non-significant: those with Negative Emotions and with Negative Emotional Climate. In addition, an examination of the pooled effects from the real correlations  and that residual heterogeneity was decreased noticeably in 11 out of the 12 associations explored. In addition, and while there were no significant differences in the levels of the mediator for the analyses, we found a positive and significant association of CE and Negative Emotions , which was previously non-significant in the main results. Finally, it is worth noting that the relationship between CE and outcome variables did not change dramatically across the types of rituals; in fact, there were only significant differences in the association with Collective Efficacy. Specifically, CE associates with this variable more strongly in across Celebrations (r = 0.52) than Demonstrations (r = 0.38).This analysis allows us to examine the specific association of CE with the outcomes during different type of collective gatherings see . Regardir = 0.52), Collective Efficacy (r = 0.37), Social Beliefs (r = 0.43) and specifically, on Negative Emotions, as previously mentioned. Overall, this supports the hypothesis that demonstrations are socialization instances that fuel factors conducive to long-term participation in collective action.Further, when the gathering in question was a demonstration  see , we founWhen the effect sizes of the association between CE and outcome variables were moderated by the type of design . In addition, rank correlations and Egger's regressions suggested a lack of asymmetry in the funnel plots in 20 out of the 21 analyses performed and we found similar overall effects concerning the methodology . Altogether, these findings suggest little evidence of publication bias and overall robust results.Overall, CE was significantly but heterogeneously associated with, and predicted, the vast majority of criterion variables. More specifically, observed effects were stronger for proximal variables, compared to the distal ones. Confidence intervals excluded zero and Fail-safe First, CE was found to be related to proximal or immediate emotional outcomes: General Arousal, Positive Emotions, and Self-Transcendent Emotions. A strong result was found for General Arousal, which was associated with CE with a large effect size. These results confirmed that this variable was associated with a proximal or immediate intensification of emotions. CE was also strongly associated with positive emotions, supporting the “joy of gathering” or the essentially positive affective nature of effervescent states  that play a role in social mobilization , which in turn were reviewed by all authors. All authors reviewed and commented on the final version of this study. All authors contributed to the article and approved the submitted version.This research was supported by grants given to the research team Culture, Cognition and Emotion , the Spanish Ministry of Economy and Competitiveness ([Ref.: PSI2017-84145-P and Ref.: PID2020-115738GB-I00), the Basque Government , and a post-doc grant from the UPV/EHU to JP (DOCBERRI 20/23).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Mechanical horse-riding simulator (HRS) exercises are a type of therapy based on the use of robotic or mechanical devices that produces movement similar to a real horse with the aim of simulating hippotherapy. This review analyses the effectiveness of HRS therapies in patients with cerebral palsy (CP). Methods: A systematic review and a meta-analysis were carried out by searching studies in PubMed Medline, SCOPUS, Web of Science, CINAHL, PEDro and SciELO up until October 2022. We selected clinical trials that assessed the effectiveness of HRS therapy, compared to other interventions, in patients with CP. The main variables were gross motor function , functional balance, spasticity, hip range of motion (ROM), posturographic balance and satisfaction. The risk of bias was assessed using the Cochrane Risk of Bias Tool. The pooled effect was calculated using Cohen’s Standardized Mean Difference (SMD) for a 95% confidence interval (95% CI). Results: Twelve studies were included in the systematic review, and 10 were included in the meta-analysis, providing data from 343 patients with spastic diplegic CP. Our findings revealed that HRS plus physiotherapy is more effective than physiotherapy in improving the total gross motor function , sitting ability of the gross motor function  and functional balance , and HRS therapy is better than sham to improve pelvic abduction ROM . Conclusions: Horse-riding simulator-based therapy is an effective therapy to improve gross motor function, functional balance and abduction pelvic ROM in children with CP, in comparison to physiotherapy or sham. Cerebral palsy (CP) is the most common physical disability in children, affecting 17 million people worldwide , which hCurrently, there is a wide variety of medical, physiotherapeutic and animal-assisted therapy approaches to reduce motor, balance and gait disorders in children with CP . The tecAs a complement to these therapies, hippotherapy represents a complementary novel approach used in children with CP. Hippotherapy or horse riding therapy is an equine-assisted therapy that uses horse movements in the rehabilitation of neurological diseases ,28 due tTo date, reviews have assessed the effect of HRS therapy in other neurological conditions such as stroke , musculoCochrane Handbook of Systematic Reviews of Interventions (Second Edition) [This systematic review with meta-analysis was carried out following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) , the A MEdition) . FurtherTwo authors (D.M.-C. and E.O.-G.) independently carried out a bibliographic search in the following databases: PubMed Medline, Web of Science (WOS), Scopus, CINAHL Complete, Physiotherapy Evidence Database (PEDro) and SciELO. In order to find studies not published in these databases, we searched in the reference section of studies previously published and in the gray literature . The search strategy was developed based on the PICOS tool proposed by the Cochrane Library ,43: popuThe selection process of the studies included in this meta-analysis was carried out by 2 authors (D.M.-C. and I.C.-P.) independently, who were responsible for reviewing all the records found in each database by title and abstract. In addition, discrepancies in this phase were resolved by a third author (M.C.O.-P.). A study was only included in this review if it met all the inclusion criteria: (1) clinical trials; (2) that the study population was diagnosed with CP; (3) that the study had at least 2 intervention groups, 1 of which underwent HRS therapy and it was compared to another type of therapy different to HRS or no intervention; (4) studies that evaluated variables of interest for this study see ; and (5)The data extraction process of the included studies was carried out by two authors (D.M.-C. and E.O.-G.) independently, using a Microsoft Excel data collection form. All possible disagreements were resolved with a third author (M.C.O-P.). The following data were extracted from each study: (1) general characteristics ; (2) patient characteristics ; (3) characteristics of the experimental group and the control group ; (4) outcome data of the variables of interest ; and (5) assessment time (post-intervention). When a study did not provide standard deviations, it was estimated using standardized transformations through the standard error, range, interquartile range and median ,44.The variables of interest to assess the effectiveness of HRS therapy in patients with CP were gross motor function and its five dimensions , functional balance, spasticity, hip ROM and posturographic parameters and satisfaction.Grading of Recommendations Assessment, Development and Evaluation (GRADE) [The evaluation of the risk of bias in each study included and of the quality of evidence of the main findings was carried out by 2 authors (D.M.-C. and M.C.O.-P.) independently. Any doubts were resolved by a third author (E.O.-G.). At first, the Cochrane Collaboration Bias Tool Risk was used to assess the risk of bias in the studies included in the review. This scale assesses 6 bias domains  through seven items . Each item can be categorized as “+” (high risk of bias), “−“ (low risk of bias), and “?” (uncertain risk of bias) . Secondl (GRADE) . Further (GRADE)  were folIntroduction to Meta-Analysis by Borenstein et al. [The Handbook of Research Synthesis and Meta-Analysis” by Cooper et al. [p-value for the Egger test (p < 0.1 indicates the risk of publication bias) [2) and the p-value for the Q-test (p < 0.01 indicates the risk of heterogeneity). The heterogeneity could be null (I2 0%), low (I2 < 25%), moderate (I2 25–50%) or large (I2 < 50%) [The meta-analysis was carried out by 2 authors (E.O.-G. and I.C.-P.) using the software Comprehensive Meta-Analysis v3.0  . To perfn et al.  and of Tr et al. . Accordir et al. . Cohen’sr et al. . Effect r et al. . Additior et al. . The finr et al. . The risr et al. ; the p-von bias) ; and theon bias) ,59. If von bias) . Finally2 < 50%) ,62.To assess the contribution of each study to the overall pooled effect, we performed a sensitivity analysis using the leave-one-out method. In addition, we performed the following subgroup analyses: HRS plus PT (physiotherapy) vs. PT, HRS vs. PT, and HRS vs. sham.The PRISMA flow chart  shows thThe studies included in this review were conducted between 1998 and 2022 in India ,67, SoutTo assess gross motor function, the studies included reported data from the Gross Motor Function Measure-66 (GMFM-66), GMFM-88 and Gross Motor Function Classification System (GMFCS). To analyze gross motor function, we obtained data from the total score and/or its five dimensions . Secondly, postural balance was assessed with data from the Pediatric Balance Scale (PBS). Thirdly, spasticity in different lower limb muscles was assessed with data from the Modified Modified Ashworth Scale (MMAS) and Modified Ashworth Scale (MAS). Later, hip and tilt pelvic ROM was evaluated with a goniometer.Furthermore, other secondary variables included posturographic parameters of static balance using Pedoscan Sensor and F-mat sensor platform and F-scan system, posturographic spinal posture using ABW Mapper, seated trunk control with SATco and satisfaction with the therapy using the Autoquestionnaire Qualité de Vie Enfant image (AUQEI).The results of this review are presented in two ways: first, a meta-analysis of the variables gross motor function, functional balance, spasticity and ROM and, then, a qualitative synthesis for pelvic tilt, posturographic balance assessment in stand-up or sitting positions (trunk control) and satisfaction with HRS therapy. For gross motor function, we assessed the effect of HRS therapy on each dimension  and on the global total score.p 0.35), C , D  and E dimensions  favors HRS (p for Egger 0.07) due to trim-and-fill and showed a variation of 15%  with respect to the original pooled effect . Subgroup analysis revealed that the use of HRS plus physiotherapy was better  than physiotherapy alone, showing an improvement in the sitting ability of the GMF-88 test of 7.64 points . However, no statistically significant differences were found between HRS vs. sham  in favor of HRS therapy . A subgroup analysis revealed a large effect  favoring HRS plus physiotherapy vs. physiotherapy (p 0.001) and the GMF-88 by 11.21 points . However, no statistically significant differences were found between HRS vs. physiotherapy  and HRS vs. sham  of HRS plus physiotherapy in comparison to physiotherapy (p 0.015). No risk of publication bias or heterogeneity was found. Sensitivity analysis did not report substantial variations in the pooled effect when the studies were excluded.Two studies ,67 with otherapy . In addip 0.008) that favored HRS therapy (p 0.004), compared to sham. The risk of publication bias could not be studied, and heterogeneity was moderate .Two studies ,72 with  therapy , being aThe effect of HRS therapy in reducing spasticity was assessed in hip adductors, knee extensors and ankle dorsiflexors.p 0.122; p 0.642) and between HRS vs. sham  or of the knee extensors .Finally, the spasticity of the ankle dorsiflexors and of the knee extensors was assessed in one study  with twop < 0.05). Furthermore, we found two studies [p 0.004). Choi H.J. et al. (2014) and Silva-Borges et al. (2011) found statistically significant differences in medial-lateral sway [Regarding the qualitative synthesis of the studies included in our systematic review, we were able to reach the following conclusions. Two studies ,72 compa studies ,74 that ral sway ,73 in thAlthough the use of HRSs in the management of motor, balance and gait disorders in different neurological and musculoskeletal diseases is increasing in physiotherapy approaches, only six reviews have compiled the published evidence about HRS therapy on chronic pain ,75, autiRegarding gross motor function, we assessed the effect of HRS therapy on the total score and on each dimension. We found statistically significant differences favoring HRS therapy in improving sitting ability and total gross motor function in comparison to other therapies such as physiotherapy or sham. In addition, the effectiveness of HRS therapy on sitting ability (SMD 0.84) and total gross motor function (SMD 0.98) was large when it was used in combination with physiotherapy compared to physiotherapy. Our meta-analysis identified two important benefits of HRS plus physiotherapy on these variables. On the one hand, the effect of HRS plus physiotherapy was unknown until this study was conducted. On the other hand, we calculated the mean difference between therapies, showing that HRS plus physiotherapy was able to increase the sitting ability and global total score in the GMF-88 test by 7.64 points and 11.21 points, respectively, compared with physiotherapy. Currently, no study has published the MCID for sitting ability in this test, so our data cannot be compared to this MCID, but we consider that an increase of almost 8 points for sitting ability may have relevance for clinical practice, helping these patients to better carry out their activities of daily living in the sitting position. However, on the global total score, our findings exceed the MCID value in GMF-88, calculated in 2020 by Storm et al. . These tSecondly, our findings showed that the inclusion of HRSs in physiotherapy protocols is effective for improving functional balance in comparison to physiotherapy only (SMD 0.6). We determined that the combination of HRS plus physiotherapy increased the total score in PBS by 6.21 points. Chen et al. (2013) reported that the MCID value for the total score of PBS in children with CP was 5.83 points . Our finThe last meta-analysis assessed the effectiveness of HRS therapy on abduction hip ROM and lower limb spasticity. Our results showed that HRS therapy was effective in increasing the hip abduction ROM by 7.5 degrees in a goniometry assessment, in comparison to sham. Regarding spasticity, HRS plus physiotherapy was not better than physiotherapy only in reducing hip adductor, knee extensor and ankle dorsiflexor spasticity. However, in the hip adductor spasticity meta-analysis, our findings were underestimated as a result of publication bias, and when the pooled effect was calculated, taking into account this possible bias (trim-and-fill variation of 100%), we found that HRS therapy could have a large effect (adjusted SMD −0.81) in reducing spasticity in adductor muscles. This last result highlights the importance of performing future research with the aim of confirming this possible finding without the risk of publication bias. The improvement in hip abduction ROM and possible reduction in adductor spasticity can be explained by the continuous riding position of the equine simulator, in which both hips are abducted, keeping the adductor muscles continuously stretched, reducing its shortening and helping to prevent the neuromuscular hip dysplasia which is common in these children [Finally, our review highlights an important finding in the study of Silva–Borges et al. (2011), in which the level of satisfaction in the HRS therapy was assessed in comparison to conventional therapy . ChildreHRSs have some benefits that allow their easy inclusion within the clinical practice, including the lower costs of maintenance of the machine compared to the costs of care and training of horses ,75. MoreAlthough the findings presented in this systematic review and meta-analysis are interesting and relevant for clinical practice, it is important to note some limitations. First, the small number of studies that are included for each variable in which the meta-analysis has been carried out should be highlighted. This is not a limitation of our literature search process unless, due to the scarcity of studies that assess the effect of HRS therapy in CP that have been published to date, they did not meet the inclusion criteria. The second is related to the precision of the results, which is derived from the number of participants. The included studies comprise small sample sizes, and this may lead to underestimation of the results when combining the studies with meta-analysis, as has occurred. The low number of studies conducted to date and their small sample size may make it difficult to generalize the results and reduces the quality of the evidence from the overall analyses; however, no other reviews have been published to date. Third, it is important to highlight the moderate risk of bias in the included studies. Furthermore, the heterogeneity in the HRS therapy protocols used  does not help determine which type of HRS therapy is the most effective. It is also important to highlight the risk of publication bias present in some studies. However, at this point, it is necessary to point out that the risk of publication bias meant that there were no statistically significant differences between HRS plus physiotherapy vs. physiotherapy in increasing spasticity hip adductors, and the trim-and-fill estimation determined that, without publication bias, HRS therapy would improve this variable. Finally, the last limitation is that this review only assessed the immediate effect of HRS therapy because the studies included did not provide follow-up data.This is the first systematic review with a meta-analysis that quantitatively assesses the effect of HRS therapy on gross motor function, functional balance, spasticity and hip ROM and reports a qualitative synthesis of other secondary outcomes such as posturographic parameters and satisfaction of the participants, in comparison to physiotherapy or sham. Our meta-analysis reported that HRS therapy is effective in improving overall gross motor function and sitting ability, functional balance and hip abduction ROM in children with CP. More specifically, we reported that when HRS is combined with physiotherapy, the improvements found in gross motor function, sitting ability and functional balance are higher, but no differences between these therapies were found to reduce spasticity in hip adductors, knee extensors or ankle dorsiflexors. More studies that assess the effectiveness of HRS therapy in these variables and in others, such as quality of life or functional independence, are needed to carry out in the future. An increase in the sample size of these studies will help obtain more robust and accurate results and enable the HRS therapy findings to be generalized. Finally, to guarantee the comparison between therapies in future studies, it would be necessary to homogenize the duration and intensity of the HRS protocols and to evaluate the variables in different follow-up times, in addition to immediate post-intervention, to verify the efficacy of HRS over time.


Mild traumatic brain injury (mTBI) or concussion is a complex injury that is difficult to diagnose and assess. There are negative impacts on cognition, balance, and mobility after a concussion. The Gait Disorientation Test (GDT) is an objective measure that assesses a person's balance ability by comparing the walking time with eyes open and the walking time with eyes closed in a standardized walking task. The purpose of this study was to assess the validity and the diagnostic properties of the GDT in children with concussions.Thirty-six children with concussions, and 91 controls aged between 9 and 18 years old participated in the study. Participants completed demographics, the GDT, the Functional Gait Assessment (FGA), the Pediatric Vestibular Symptom Questionnaire (PVSQ), and the Pediatric Visually Induced Dizziness Questionnaire (PVID).M = 2.18 ± 1.93 s) than healthy controls (M = 1.13 ± 0.95 s), which was statistically significant (P = 0.014).Children with concussions showed higher (worse) GDT scores (The GDT was able to distinguish between children with concussions and healthy controls. Given the simplicity of the GDT, it can be used to assist in discriminating between children with and without concussion. A concussion is a common brain injury, which may lead to multiple health impairments including physical and cognitive symptoms, such as headache, dizziness, balance impairments, and visual problems , 2. In tThe purpose of this study was to assess the validity and the diagnostic properties of the GDT in children with and without concussions.Thirty-six children with concussion/mTBI and 91 controls between 9 and 18 years of age participated in the study. Participants with concussions who were seeking medical attention for their concussion were recruited after a neurologic and neuro-otologic examination from a tertiary balance center at the University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, USA. Controls were recruited from middle and high schools in Pittsburgh, PA, USA. Informed consent was obtained from all participants and their guardians. The study was approved by the institutional review board from the University of Pittsburgh and was conducted in accordance with the Declaration of Helsinki.Participants from both groups completed demographics and the Functional Gait Assessment (FGA), which is a performance-based test that include 10 walking and stair-climbing tasks . The perThe Pediatric Visually Induced Dizziness Questionnaire (PVID) is a self-reported questionnaire comprising 11 questions about the frequency of feeling dizzy and unsteady in different places and situations during the past month using a 4-point Likert scale that ranged from “never” to “most of the time”. The totThe GDT is measured in seconds and was calculated by subtracting the time needed to complete the 10-m gait speed test with eyes closed (GS-EC) and the time needed to complete the normal 10-m gait speed test with eyes open (GS). Both GS and GS-EC were timed during the FGA tasks similar to Grove et al. , 13. Allt-tests or the Man–Whitney U-test. Group comparisons were further examined using a one-way ANCOVA to adjust for age, gender, and height differences. The GDT, GS, and GS-EC were tested, as appropriate, using Person or Spearman correlation coefficients against the FGA, PVSQ, and PVID to assess their concurrent validity. The receiver operator characteristic (ROC) analysis was used to assess the diagnostic ability of GDT, GS, and GS-EC to discriminate between the concussed and control children. The optimal cut-off values were calculated using Youden's Index  and 91 healthy children aged between 14 and 18 years old  completed the study. Significant differences between groups were found in age, weight, and height  children with concussions reported having symptoms of dizziness, 17 children reported spinning sensation (47%), and 17 children reported migraine (47%). Thirty-four (94%) children with concussion tested positive on the PVSQ  or the PVID  tests using the cut-off scores reported for children with concussion (Children with concussion were recruited 4–434 days after injury [interquartile range (IQR) = 115 days; ncussion .M = 2.18 ± 1.93 s) and healthy controls , indicating that children with concussion demonstrated larger changes compared to healthy controls in walking speed when walking with eye closed compared to eyes open. Gait speed did not differ between the groups (P = 0.108), while gait speed with eyes closed was significantly slower in children with concussions than healthy controls (P < 0.001). The FGA demonstrated a statistically significant difference between groups demonstrating better performance by the healthy controls (P = 0.003). Results from One-way ANCOVA showed that the GDT, the GS-EC, and the FGA were significantly different between the groups with better performance in the control group compared to the concussion group  = 8.305, P = 0.005; GS-EC, F = 11.201, P = 0.001; and FGA, F = 5.600, P = 0.020. There was no significant effect of group on GS after controlling for age, height, and gender, F = 3.164, P = 0.078 . Gait speed significantly correlated with the FGA, PVSQ, and PVID demonstrating better outcomes with increased gait speed (P < 0.05). Gait speed with eyes closed significantly correlated with the FGA and the PVID demonstrating better outcomes with faster gait speed while walking with eyes closed (P < 0.01). Time since injury did not show a significant correlation with the functional tests GS, GS-EC, GDT, and FGA or the questionnaires PVSQ and PVID , which may explain the small difference between the groups seen in this study , 12.In addition to the GDT, walking with eyes closed and the FGA score were able to differentiate between healthy participants and participants with a concussion, whereas normal walking speed was not different between children with and without concussion. The GDT, walking with closed eyes, and the FGA include tasks that require the participant to close their eyes during walking, which forces a participant to rely more on the somatosensory and vestibular system, which may be affected because of the concussion injury . In contPrevious studies have compared differences in walking speed during various dual-task conditions with concussed and healthy adolescents , 21. HowChildren with concussions who reported having dizziness demonstrated worse performance in all the functional tests in this study , while the presence of spinning sensation or migraine did not show differences in those functional tests. Consistent with this finding, Lue et al., in their study about the signs and symptoms that predict a protracted concussion recovery, found that between 12 different post-concussion signs and symptoms, only dizziness indicated a protracted recovery of concussion .Although GDT was able to distinguish between children with and without concussion, a more useful validation of the GDT is to assess the ability of the GDT to distinguish between children with different diagnoses. Time since the concussion is an important factor in managing individuals with a concussion. Although concussed participants in this study were from a wide range of injury onset, they were recruited while they were seeking medical intervention for their concussion symptoms –25.Another limitation was the difference in gender between the children with a concussion and the healthy children. Although we managed to have an equal number of male and female children in the control group, we recruited all available children with concussions, which resulted in imbalanced gender distribution. However, the one-way ANCOVA analysis was used to adjust for demographic differences between the groups, and neither gender, height, nor age affected the differences in the GDT scores.The GDT is a feasible, valid, and objective test to discriminate between children with and without concussions. It is a simple test that requires a stopwatch and a marked 20-ft hallway and can be performed within 1–2 min.a.alkathiry@mu.edu.sa.IRB approval must be obtained from the University of Pittsburgh to share patients' information. Requests to access the datasets should be directed at: Abdulaziz Alkathiry, The studies involving human participants were reviewed and approved by the institutional review board at the University of Pittsburgh, PA, USA. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.Conceptualization and visualization: SW and AA. Data curation, methodology, validation, and writing: AA, SW, SA, and BA. Formal analysis: AA and SA. Project administration, software: AA. Resources and supervision: SW. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.