The main aim of this study was to explore the sources of consultation that women seek during premenstural syndrome (PMS), and to establish the association between the severity of PMS and how it affects the quality of life.Cross sectional study of 179 female patients, using an Arabic validated version of the shortened premenstrual assessment form, and a 7-item quality of life questionnaire that was developed by the researchers. The questionnaire was tested for validity and reliability via a pilot study before the initiation of data collection. Data was analyzed using SPSS version 19.179 women participated in the study, with more than half of them aged between 20–30 years old. PMS prevalence was 88%; patient's predominantly sought help from their relatives (51%), followed by physicians (34%). There was no association found between the severity of premenstrual symptoms and seeking consultation. PMS symptoms affected women's daily activities , their satisfaction with their general appearance  and weight , and affected their relationships with family members  and other people .PMS is a common condition that affects women and their quality of life in several ways. Physicians and primary health care providers must be more vigilant in detecting the presence of PMS. Premenstrual syndrome (PMS) is a common health problem in women of reproductive age, The American College of Obstetrics and Gynecology defines PMS as a complex set of physical and emotional symptoms that occur repeatedly in a cyclical manner one to two weeks before menstruation, and then disappear after the menstrual cyclePMS symptomatology includes both physical and emotional symptoms; somatic symptoms associated with PMS include feeling overwhelmed, food cravings, insomnia or hypersomnia, headaches, pelvic pain and discomfort, breast tenderness and swelling, joint pain and bloating. In addition, irritability, anxiety, depression, mood swings, hostility, poor concentration, confusion, social withdrawal and interpersonal conflicts are the most commonly described psychological symptomsPMS symptomatology may affect not only the individual but also their family and society as a wholeSevere PMS symptoms typically interfere with the functional capacity of women, thus affecting multiple settings, such as home, school and workIn a recent study conducted by Hamaideh et al. among students and workers in one Jordanian university, the prevalence was found to be 80.2%This cross-sectional study was conducted at a family medicine walk-in clinic in a hospital in Amman, the capital of Jordan. Patients at this hospital are primarily medically insured through the Ministry of Health, universities, and many affiliated public institutions and companies, although there are also some private patients. The clinics serve patients of all age groups who attend the clinic complaining of acute, sub-acute, and chronic complaints, as well as those who attend for health checkups and preventive services.A convenience sample of 179 women was recruited. Women attending the clinic for various reasons between February 2018 and November 2018 were asked to complete a self-administered questionnaire. Inclusion criteria were all women aged 15–45 years who attended the clinic in the aforementioned period and who agreed to participate in the study. Women were excluded from the study if they were pregnant, had given birth in the last 6 months, or were on hormonal contraception, as each of these factors may affect the occurrence and severity of PMSThe questionnaire consisted of three main parts. The first asked about sociodemographic variables, including age, education level, average income, marital status and occupation. The second part of the questionnaire consisted of a modified shortened premenstrual assessment form (SPAF). This form, developed by Allen, McBride, and PirieThe third part of the questionnaire was developed by the researchers and involved questions about seven items to examine the effect of the presence of PMS symptoms of the women's QoL. The seven items included: performance of daily activates, missed work or school days, satisfaction with their general appearance, satisfaction with their weight, satisfaction with their eating habits, and their relationships with family members and with others. The final Arabic version of our modified SPAF, and the supplementary 7 QoL questions, were examined by three full professors and three assistant professors in the appropriate medical departments. All suggested changes were discussed and resolved, then the final Arabic version of our modified SPAF and 7 QoL questions were examined for reliability in a pilot study of 40 patients who were not included in the present analysis. The analysis revealed the questionnaire to be reliable (Cronbach's α of 0.747).Data were analyzed using SPSS (version 19). The χ2 test was used to compare the frequencies of categorical variables; an independent t-test, analysis of variance, and linear correlation were used to compare continuous data as appropriate. P-values were considered significant at p<0.05.In the current study, we found that 88% of our study population suffered from some degree of PMS; 50% had mild PMS, and only 2% suffered from severe PMS symptoms. Regarding the socio-demographics shown in  of our sAs outlined in As illustrated in In addition, when studying relationships with family members and with other people, we found that both were adversely affected by the presence of severe PMS symptoms; in both cases the mean score of the effect of the symptoms on the aforementioned items was 3.5/4 (87.5%), which was statistically significant .On other hand, PMS symptoms do not seem to affect women in terms of days absent from work or school, nor their satisfaction with their eating habits.In the current study, >50 of the sample reported that they asked their mothers and sisters for help regarding PMS symptoms, which may be attributed to cultural issues; where family is still regarded as the first source of consultation in Jordanian families, particularly for menstrual cycle-related concerns related, which are considered embarrassing for females. Sisters sharing the same home environment malead to females depending on their families' experiences of PMS symptomatology. Physicians and pharmacists were found to be the source of consultation in >1/3 of our study group, which may reflect the severity of their symptoms, in that women feel they need to be evaluated by a healthcare worker. Our current findings are consistent with some published data from different parts of the world. One recent study conducted by Anandha et al. on female medical students on India, found that only 9.7% of the study sample would consult a physician or a pharmacist regarding their symptoms18. On the other hand, Tollossa et al6 reported that 48% of their sample, in a study that was conducted in Ethiopia, have sought medical treatment for their symptoms; in a Malaysian study, 19% of the study sample took prescribed treatment from their health professionalsThe findings of this study demonstrated a significant correlation between moderate to severe PMS and limitations in the performance of daily activities, such as shopping, cooking and doing daily domestic activities. These results are consistent with the findings of Johnson 1987 and, Robinson and Swindle 200020, 21 as they confirmed the functional impairment effect of PMS symptomatology. A consistent relationship between premenstrual symptoms and social and occupational impairment was proven in their work; a similar result was also demonstrated in a study conducted in United Arab Emirates by Rizk et al in 2006, which indicated that PMS has a suggestive influence on QoL22. Comparable results were concluded in a study conducted in Korea, which stated that 14.3% of women reported that PMS symptomology had a significant impact on daily life activities23. Similar results were also reported in other studies conducted in India and Turkey18, 24. These results may be explained by the fact that daily activities can be postponed to a period when PMS symptoms have resolved.PMS symptoms were not demonstrated to be associated with missing work or school days in this study, which is not consistent with the findings of a recent Jordanian study conducted by Hamaideh et al. This previous study stated that women with severe premenstrual symptoms reported higher rates of absence from work than those who reported less severe symptoms. Another study conducted in India, which investigated female medical students, reported that ∼16% of the students had symptoms that were severe enough for them to be absent from college18. This discrepancy between our results and those of the aforementioned studies may be attributed to the sample studied. Our study included women from different backgrounds and work environments, whereas the aforementioned studies were both conducted on college students and workers. In our culture, as it is in many developing countries, symptoms without physical evidence, such as fever or menorrhagia, are not considered enough for doctors to give sick leave certificates to patients, which may also explain why women do not miss days from their school or work for such problems.We found that women with moderate to severe PMS were markedly unsatisfied with their general appearance and weight, which may be attributed to fluid retention that affects body weight and appearance. There is scanty literature about the effect of PMS on women's satisfaction with their weight and general appearance, even though it is one of the most frequently encountered symptoms. Our findings may highlight the need for more investigation into these important QoL factors.Women with severe PMS symptoms reported that PMS symptoms affected their relationships with family members and other people; these results were expected, particularly when considering that the most common emotional symptoms of premenstrual syndrome include depression, irritability, anxiety, tension, crying, oversensitivity, feeling out of control, and mood swings1. Social withdrawal and decreased activity levels are also behavioral symptoms of PMS25, 26. One of the most common psycho-behavioral symptoms experienced by the participants of a study conducted on female university students in Ethiopia was loss of interest in doing things 6, these feelings, along with the somatic symptoms of PMS  exert a substantial impact on women's ability to deal with different people throughout their daily life.PMS is not only a chronic, recurrent problem that affect women in their reproductive years, it also has a severe impact on women's productivity and daily living activities. The current study highlighted the importance of this and the low rate of medical consultations sought for such a disruptive issue. These findings should urge healthcare providers to suspect and explore more about the presence of PMS symptoms and to take the initiative to diagnose and offer help for patients at need. Among the general population, urging the initiation of healthcare campaigns to increase the awareness and treatability of PMS would be beneficial.


Emotional contagion, in particular of happiness, is essential to creating social bonds. The somatic marker hypothesis posits that embodied physiological changes associated with emotions and relayed to the brain by the autonomous nervous system influence behavior. Perceiving others’ positive emotions should thus be associated with activity in brain regions relaying information from and to the autonomic nervous system. Here, we address this question using a unique corpus of brain activity recorded during unconstrained conversations between participants and a human or a humanoid robot. fMRI recordings are used to test whether activity in key brain regions of the autonomic system, the amygdala, hypothalamus, and insula, is differentially affected by the level of happiness expressed by the human and robot agents. Results indicate that for the hypothalamus and the insula, in particular the anterior agranular region strongly involved in processing social emotions, activity in the right hemisphere increases with the level of happiness expressed by the human but not the robot. Perceiving positive emotions in social interactions induces local brain responses predicted by the contagion of somatic markers of emotions only when the interacting agent is a fellow human. Human beings are intrinsically social creatures whose lives are intertwined with others. Engaged in any social interaction, we cannot help but gather information about others’ mental states, in particular their emotions that signal the quality of the ongoing interaction. Facial expressions convey many signals about people’s internal states, which are extremely relevant for smooth social interactions. Our capacity to take into account these signals allows us to adapt our behavior when interacting with others. One adaptation is emotional contagion, which describes the phenomenon that many components, including the autonomous nervous system’s response, of others’ emotions, are shared by the observer . Such coUnderstanding brain mechanisms involved in emotional contagion during naturalistic social interactions is required for the advancement of second-person neuroscience , which aThe insular cortex and the amygdala  are coreInvestigating the mechanisms underlying the processing of others’ emotions during natural interactions is difficult given the incompatibility between the necessary experimental control in experimental research and the freedom associated with natural social behavior. Exceptional circumstances, such as intracerebral sampling of hormones in narcoleptic patients, clearly demonstrate that the amygdala physiology is influenced by social emotions . ArtificFor instance, two fMRI studies comparing brain response to the passive viewing of humans’ and robots’ facial expressions of emotions reported reduced activity for the robot expressions of emotions in the left insula and right amygdala . AnotherConsidering “the six canonical emotions” as distinct categories, following a long trend of research initiated by Charles Darwin  and contAt the brain level, our initial postulate is that the processing of facial expressions of emotions comprises at least two distinct mechanisms , as do mIn practice, we tested this hypothesis by automatically extracting facial happiness expressed by the human and robot agents and using it as a covariate in multivariate analyses of the signal in functional subregions of the insula, in two divisions of the amygdala, and in the hypothalamus, bilaterally. We hypothesized that should emotional resonance yield an autonomic reaction to positive emotions perceived by the participants during a natural conversation, the response in these particular brain structures would correlate with the level of happiness expressed by the human  but not the robot .in extenso in previous publications  arrived at the MRI center, one experimenter presented them with the cover story. To allow participants to have natural conversations despite the experimental setting, they were kept in the dark about the actual purpose of the experiment through a cover story. They were told that they were participating in a neuromarketing experiment. Specifically, a company asked neuroscientists to determine whether two people could guess the meaning of an upcoming advertising campaign simply by discussing the images used to illustrate it. The experimenter then introduced them to the agents with whom they would be discussing. The human partner was a confederate of the experimenter gender-matched with each participant, and the artificial agent was a back-projected conversational robotic head  acquisition, participants discussed online with these two agents alternatively while lying supine in the scanner and having their brain activity recorded. A BOLD signal (blood oxygen level dependent) was recorded in four sessions of fMRI acquisition, each lasting approximately 8 min. Each session comprised 6 experimental trials that proceeded as follows: a picture appeared for 8.3 s, then after a 3-s pause with a white fixation cross on a black background, a 1-min live conversation took place with either the human or the robot agent, alternatively. The participant and interlocutor could hear each other in real time, and the participant additionally saw a live feed of their interlocutor. All audios and videos available were recorded for further analysis. Other variables were recorded, such as the participant’s eye movements or heart rate, but these will not be discussed further here since they are not used in the current analysis. In total, each participant took part in twelve 1-min conversations with the human and twelve 1-min conversations with the robot.Unbeknown to the participants, who believed the robot was autonomous, it was actually controlled remotely by the confederate acting as the human interlocutor. A set of pre-recorded answers stored as text snippets chosen based on a preparatory version of the experimental procedure were selected in real time by pressing virtual buttons on a touch-sensitive tablet. Responses were played using the voice synthesizer provided by the robot. Some answers were generic , and others were specific to an image (“It is a yellow pear”) or to one of the two advertising campaigns . Importantly, emotional expressions by the robot were not actively controlled but happened as part of random movements encoded in the robot to increase its naturalness, except on very rare occasions when happiness expressions were used as non-verbal feedback.3 voxels of the brain. Each volume contains 54 slices of 84 × 84 in-plane voxel and is recorded in 1.205 s. Pre-processing entails a correction of the temporal synchronization of the acquired slices, a realignment of the volumes of each session on the first one, and a correction of the deformations due to the local distortions of the magnetic field and participants’ movements. Normalization uses the DARTEL procedure . According to its developers, it can achieve an accuracy of 66% in the Facial Emotion Recognition (FER-2013) dataset, which consists of manually labeled 35,887 48 × 48 pixels grayscale images. More precisely, the algorithm achieved a correct recognition of 87% of happy faces, with mislabeling below 5%, while the correct recognition was in the range of 41% (for fear) to 77% (for surprise) for the other emotions according to the confusion matrix. We verified that emotions depicted by the robotic device were correctly recognized by the algorithm and found correct detection for the happy and neutral emotions, which were the only facial expressions used in the recording of the corpus. In addition, the recordings used for this classification, 640 × 480 images of the full-screen face of the human or robot interlocutor looking directly at the camera, were particularly well-suited for this automatic classification, in contrast to the more variable faces, in terms of age, orientation, brightness, and occlusion, used for the development of the algorithm. Altogether, these arguments support the use of automatically recognized happy emotions in our analysis. In practice, the probability predicted for happy emotion was extracted frame by frame, then summed over all frames of a trial, therefore providing one happiness score for each trial.Facial emotions were extracted automatically from the videos of the human and robot interlocutors using a freely available machine learning algorithm  availablStatistical analyses were performed in R using the package lme4. Multivariate models were used as the effect of each predictor  was evaluated while holding constant the effect of the other predictors on the dependent variable. We introduced the happiness score obtained for each trial as a predictive continuous variable for all regions evaluated, with the nature of the agent as the categorical factor of interest. The identity of the participant and sessions were used as random variables. We used Holm’s correction for multiple comparisons  to contrt = 21.08, p < 0.001, CI 95% ), with higher scores for the human. This significant difference argues in favor of the multivariate linear model approach that allows us to evaluate independently each term’s unique contribution to the variation of the average BOLD signal per trial, therefore controlling for the significant difference in happiness between agents.As expected, there is a significant difference between the happiness extracted for the human and robot interlocutors  and of the continuous happiness score (happiness), as well as the interaction between these two terms (happiness by agent) on the BOLD signal in the insula, amygdala, and hypothalamus ROIs. Statistical results for all ROIs are presented in Results provided in Using a multimodal corpus of human–human and human–robot conversations in which participants’ brain activity was recorded with fMRI, we investigated how the emotion expressed by the interlocutor influences activity in central brain areas interacting with the peripheral autonomous nervous system, looking for evidence of emotional contagion at the somatic level. More precisely, the facial expression of happiness of the interlocutor, human or robot, was quantified automatically for each trial and used as a continuous variable against the BOLD response in subregions of the hypothalamus, the amygdala, and the insula. The rest of the discussion focuses on brain regions in which the interaction term between the happiness score and the nature of the agent is significant, as it identifies areas in which the response to the emotion depends on the nature of the agent expressing this emotion. This interaction term was significant in the hypothalamus bilaterally as well as in subregions of the insula but not in the amygdala. Particularly interesting was the activity in the right anterior insula, which increased with happiness expressed by the human, but not the robot, face.The expression of happiness was significantly higher for humans than for robots. This was expected given that the artificial device used in this experiment refer to , left hat-scores > 3 in the two hemispheres) than the medial division (t-scores < 3)—the latter is associated with visceral inputs compared to the former being associated with sensory, including visual and auditory, inputs . As explained in the “Introduction” section, emotions are a complex construct and difficult to investigate, in particular during natural interactions. Fear has been the focus of most attention in animal models thanks to the paradigm of fear conditioning that allows investigating this emotion without verbal assessment of the participant’s feelings. Thanks to these animal studies, it is well known that the amygdala is necessary for fear conditioning, which takes the form of long-term potentiation within fear circuits. Interestingly, the lateral parts of the amygdala depict a larger effect of agent  were correctly recognized, while there were attribution errors on the other, in particular negative, emotions. Importantly, as noted previously, the algorithm makes the same type of errors on human images. Finally, it is important to keep in mind that the robot’s facial emotions, as well as its utterances and intonations, are fully controlled and therefore show less variation from trial to trial. Given all these reasons, we are confident that the rating of happiness on the robot’s face is objective as smiles are the only facial expressions used when recording the corpus. Finally, it should be added that, from a social cognition standpoint, subjective annotation or rating of a robot’s facial expression of emotion is associated with other issues that are research questions of their own; for example, how does the knowledge and vision that the emotion is displayed by an artificial agent cause a top-down bias in the way the emotion is being perceived by a human observer?An important limitation pertains to the automatic extraction of the happiness scores from the videos. The convolutional neural networks were trained and tested with human faces  but not The robotic device used in this experiment had clear limitations in the expression of emotion, both visually and orally. Even though there was no expression of negative emotions, its expression of happiness was restricted to a limited number of smiles, and we cannot rule out that the limited positive emotions depicted by the robot precluded creating more social bonds with the humanoid interlocutor. Efforts are underway to endow the robot with more natural facial expressions of emotion to complement the current corpus and address this question more directly. The statistical analysis was devised to take into account this unbalances between the human and robot agents. Three comments on the results comfort the experimental paradigm and the statistical analysis used here.post hoc relating the activity to conversational characteristics extracted from the recorded behaviors, the analysis allows to reveal brain correlates associated with these characteristics of natural interactions. This is particularly important as such approaches could become a hallmark of second-person neuroscience if its goal is to investigate natural interactions. Second, in all of the regions investigated (sometimes only in one hemisphere), activity is significantly affected by the characteristic under investigation, here the happiness expressed by the human and robot interlocutor. This also supports our choice of regions to investigate the perception of emotions in relation to emotional contagion and homeostasis. Finally, the finding that not only the factor describing the nature of the interlocutor, human or robot, but also the interaction term involving the more subtle happiness score estimated automatically, yields statistically significant results is in direct agreement with one central assumption of this project, that during natural social interactions, the nature of the interacting agent, human or robot, is an outstanding factor influencing the behavior and underlying neural correlates.First, there are statistically significant results, demonstrating that despite difficulties related to the experimental approach chosen, that is, recording brain activity during unconstrained behaviors and The analysis presented here demonstrates how robots can help understand how the human brain processes social information during natural interactions. Focusing on brain regions at the interface between the central and autonomous nervous system—insula, amygdala, and hypothalamus—the results demonstrate that emotional resonance, in relation to homeostasis and the somatic markers hypothesis, is differently affected by the facial expressions of happiness according to the nature of the interlocutor. Positive correlations with the level of happiness expressed by the human interlocutor were found in two key regions for social bonding, namely, the anterior insula and hypothalamus. These correlations are particularly important because they are not found for the robot agent, illustrating the importance of artificial agents to investigate the specificities of human social interactions.The development of robots capable of complex social interactions requires an objective assessment of their social competence. Despite the limitations of the current analysis, its results illustrate how crucial interdisciplinarity—bringing together social cognitive neuroscience, automatic analysis of complex behaviors, and the design of interactive agents—is for social robotics. Considering the fundamental role of emotions in social interactions, the results directly question the acceptability of human-like robots as natural partners. Thus, in addition to providing insights into the brain correlates of human social interactions, such paradigms also help answer the question: “To what extent can human-like robots be treated as social agents?”https://hdl.handle.net/11403/convers). fMRI raw data can be found on OpenNeuro (https://openneuro.org/datasets/ds001740).Publicly available datasets were analyzed in this study. This data can be found here: Transcribed linguistic data can be found on Ortolang  for the publication of any potentially identifiable images or data included in this article.TC provided the corpus. TC and NS analyzed the data and wrote the manuscript. Both authors contributed to the article and approved the submitted version.


This research seeks to determine mechanisms in developing collaborative networking among agricultural production cooperatives in Iran. The research design was survey method and a network consisting of agricultural cooperatives has been defined as the core of the network. The statistical population of the study included managers of cooperatives which were administrated by the “Ministry of Cooperatives, Labour and Social Welfare” and the “Rural Cooperative Organization” of the Alborz Province (N = 540). From this target population, 176 managers of cooperatives were selected by multi-stage cluster sampling. A questionnaire was developed to determine the technical, economical, educational, legal, social, and policy making mechanisms that presented the collaborative networking model. The validity of the questionnaire was confirmed by experts in the field of Agricultural cooperative. To calculate the reliability coefficient of the questionnaire, Cronbach’s alpha coefficient, which is used for multi-scale questions, was used. The mean of Cronbach’s alpha coefficients in this study was 0.803. The results showed that policy making with a coefficient of 0.539, economic with a coefficient of 0.499, legal with a coefficient of 0.208, and educational mechanisms with a coefficient of 0.130 had the most impact, while technical and social mechanisms had no role in developing the collaborative networking. Network; Agricultural production cooperatives; Mechanism, Iran. To overcome the problems that they face during their existence, organizations must certainly adopt survival strategies, both individually and in group .Networking has several definitions that relate to issues such as formal and informal relationships within and outside the organization between individuals and organizations and display behaviours that play a role in establishing these relationships.Both inter- and intraorganizational networks draw the attention of researchers from various disciplines who view them as the fabric of the socioeconomic world .Organizational networks are often seen as a new way to get things done. In many instances outcomes cannot be realized by an individual organization because the task is complex (in contrast to simple or complicated tasks) and/or when tailor-made services are demanded .Jane Wei-Skillerna professor of business management at Harvard University, examines the role of networking in NGOs, saying the networking deals with a set of actors and the relationships between them .Networking and Linkages focus on very good communications and partnerships with others to serve people with mutual interest. It is another important part of management to strengthen its organization to develop and manage its communications to networking with other organizations or having joint projects with others in assisting vulnerable community .Various studies show the effects of networking on knowledge management and learning in the organization. Collaboration is considered as one of the principles of success in today’s business. The importance of collaboration stems from the fact that it has led to the exchange of information, customer - focus and competition . Dean , scientific identity, commercial identity , economic identity  as well as public and private companies and institutions and trade unions under Ministry of Agriculture.Currently, there are more than 1800 agricultural cooperatives registered in the agricultural sector alone, most of which have been formed in less than two decades . To furtTo strengthen and coordinate among these cooperatives, it will be necessary to develop a systematic network coupled with the support of the government so that producers will be encouraged to participate in this network and simultaneously government services will be provided within the network. This situation necessitates the creation of a comprehensive network or structure to cover multiple different units. Accordingly, it is necessary for all non-governmental organizations or at least organizations affiliated to the agricultural business to be connected to each other as a single network so that they can have maximum efficiency through their collaboration.In another study by A review of the experiences of successful companies shows that networking within the organization and outside the organization has influenced the collective learning and innovative performance of these companies In examining the relationships between networks inside and outside the organization, In this regard, Designing a network of agricultural cooperatives, while increasing efficiency, reducing transaction costs, and facilitating direct access of customers to producers, maximizing retailer farmers and villagers' share of production’s added value, encouraging the producers, empowering farmers by increasing their share and ultimately reducing defective and unfruitful cycles of brokers.Formation of networks is affected by many factors and interaction between these different factors eventually lead to more efficient and effective networks. In this regard, examining the factors that form the networks would improve existing relationship between them and provide the ground for more technical, social, and economic cooperation among organization .Improving economic growth with a focus on increasing cooperation among co-operators requires an impact evaluation of both members and non-members for a respective sector .The main purpose of this study is to determine mechanisms affecting the design of a model for the collaborative networking among agricultural cooperatives in Alborz Province.In this model, all the mechanisms involved in the network are identified and the effectiveness of each is evaluated and measured. Finally, the influential mechanisms are introduced and insignificant one in the measurement model will be eliminated. Furthermore economic, educational, extension, research, social, policymaking, legal and technical mechanisms are examined along with the main objective.We discuss the potential mechanisms that could have contributed to the development of these networks. Such potential mechanisms are economic, social, policy, educational, technical, and legal. With respect to the lack of collaborative networking among agricultural cooperatives, this survey study aims at answering this question: what are determining mechanisms in development of collaborative networking among agricultural cooperatives?2Alborz Province was formed by division of Tehran Province into two provinces, after the Parliamentary approval on June 23, 2010, and was introduced as 31st province of Iran. Situated northwest of Tehran, the Province of Alborz has 6 counties, Karaj, Savojbolagh, Taleqan, Eshtehard, Fardis and Nazarabad. According to the National Census, in 2016 population of Alborz was 2,712,400 million out of which 90,5% lived in urban areas. 3The dependent variable of this study is the development of collaborative networking which consists of network-based behavior, market-oriented behavior, and relationship-based behavior. The mechanisms that contribute to the development of collaborative networking would in six following mechanisms: policy making, economic, legal, social, technical, and educational mechanisms. Moreover, 4This study applies a quantitative case study approach, and a survey method is used to collect the data. The study analysed quantitative data that focused on mechanisms that contribute to development of collaborative networking among agricultural cooperatives by collecting field data.The statistical population of the research consists of managers of agricultural cooperative under the auspices of the Ministry of Cooperative, Labour, and Social Welfare and the Organisation of Rural Cooperatives  located in Alborz province. Multi-stage cluster sampling method is used to determine the size of the sample. The Cochran formula is used to determine the sample size that essential sample carried up by simple random or unsystematic sampling method. In the formula of the Cochran, p and q are the ratio of success and failure that are considered 0.5. Considering the sampling error rate of 5%, the sample size has been estimated as 176 employing the following formula .Table 1TThe value of The error value of d is considered as 0.05.The N - value defines the volume of the community.The formula of Cochran is written as Based on literature review, following hypotheses was presented:Economic mechanisms contribute to the development of collaborative networking.Social mechanisms contribute to the development of collaborative networking.Technical mechanisms contribute to the development of collaborative networking.Legal mechanisms contribute to the development of collaborative networkingPolicy making mechanisms contribute to the development of collaborative networkingEducational mechanisms contribute to the development of collaborative networkingA questionnaire consisting of two parts was designed for collecting data. The first part was about the descriptive data about respondents and second part consisted of questions regarding mechanisms that contribute to development of collaborative networking. Semi-structured interview was used to gather in-depth data from managers of agricultural cooperative.Exogenous latent variables of this research have been measured using technical, economic, legal, social, educational, and policy-making mechanisms while the endogenous latent variables of our structural equation have been evaluated using following indicators production management, inputs, agricultural products, the role of government agencies and financial institutions, law and regulations of producers, distributors and exporters, the role of non-governmental organizations, cultural, educational, promotional and research factors, economic policies and development.In the analytical section, structural equation modeling (SEM) was used to determine the relationship, role, effect and comparison of mean differences. The calculations were performed using Amos software. Structural equation modeling (SEM) is a form of causal modeling that includes a diverse set of mathematical models, computer algorithms, and statistical methods that fit networks of constructs to data. SEM includes confirmatory factor analysis, confirmatory composite analysis, path analysis, partial least squares path modeling, and latent growth modeling. SEM is used to show the causal relationships between variables. The relationships shown in SEM represent the hypotheses of the researchers. Typically, these relationships cannot be statistically tested for directionality. SEM is mostly used for research that is designed to confirm a research study design rather than to explore or explain a phenomenon. SEM produces data in a visual display – and this is part of its appeal. When using SEM, the researcher gets a tidy visual display that is easy to interpret, even if the statistics behind the data are quite complex.The second approach is Partial Least Squares (PLS), which focuses on the analysis of variance and can be carried out using PLS-Graph, VisualPLS, SmartPLS, and WarpPLS. In this study the SmartPLS software was used to analyse the data. Kolmogorov-Smirnov test was also applied to test the normality of the data.2 criterion, Q2 criterion, Redundancy criterion and GOF criterion were applied.To test the reliability of the measurement model factor loadings, combined reliability (CR), convergent validity (AVE), divergent validity, RSignificance coefficients of Z  were also used to determine the nature of the relationships between the constructs and to see whether the research hypotheses are confirmed or rejected.5A brief descriptive statistical analysis of sample showed that the average age of the managers was 45 and more than 80 percent were male. It was also observed that 68% of the respondents had at least a bachelor’s degree and the average of work experience in cooperative was 18 years.In the structural model analysis, considering the significance level being smaller than 0.05, which was measured by Kolmogorov-Smirnov test, it is indicated that the variables have not been normal. Regarding size of the sample, the researcher concluded to use the structural equation modelling method (PLS) to analyse the data.1.Factor loadings analysis: Factor loadings are measured by calculating the correlation value of the indicators of a construct with the construct itself. If this value is equal to or greater than 0.4, the model will be reliable. Based on the output of software, this value is greater 0.4, so the reliability of the model is approved.2.Composite reliability: this criterion measures the reliability of constructs not in an absolute way and the correlation of constructs with each other shows the value is greater than 0.7 : Convergence Validity (Average Variance Extraction) indicates the degree of correlation of a construct with its characteristics and the higher the correlation, the greater the fit of the model. Convergent validity is acceptable if its values are greater than 0.5  variable of the model and for exogenous constructs, this value is zero. Three values of 0.19, 0.33, 0.67 are considered as weak, medium, and strong impacts, respectively.6.Q2criterion: This criterion determines the goodness of predication of model and the values of 0.02, 0.15 and 0.35 indicate weak, medium, and strong goodness of predication of the variables, respectively. This value is only Calculated for endogenous variables of the model.7.Redundancy criterion: This criterion indicates the amount of variability of the indicators of an endogenous construct which is influenced by one or more exogenous constructs and the higher the average of Red, the more appropriate the fit of the structural model of the study.8.GOF criterion: this criterion could be examined for both measurement and structural models. Values of 0.01, 0.20 and 0.36 will be described as weak, medium, and strong, respectively.9.t-values: This is the most basic criterion to measure the relationship between variables in the model. If the value is greater than 1.96 the accuracy of the relationship between the constructs is confirmed and thus the research hypothesis is valid at a 95% confidence level. Of course, it should be noted that this criterion indicates the correctness of the relationships while the intensity of the relationship between the constructs cannot be measured through it.To examine the reliability and validity of the model, these criteria were evaluated:Based on the results of the study, in examining policy-making factor and, two substantial indicators of development policies and economic policies, the development policies in comparison with economic policies was a stronger determining factor in the development of collaborative networking in cooperatives.To analyse the economic mechanisms, four indicators of inputs, role of government agencies, role of financial institutions, and agricultural products have been identified. According to the view of the respondents in this study, the input variable had the highest factorial loading, and the variable of credit institutions had the lowest factorial loading in the economic factor.Regarding the legal indicator, two variables of the laws related to producers as well as the laws related to distributors and exporters have been examined. The results showed that the factorial loading for the laws related to producers had the greatest impact in our structural analysis.Among the three indicators of education, extension, and research, it was reported that extension indicator had highest factorial loading and research indicators had the lowest factorial loading.Based on the results of study, two social and technical factors have not had much effect on collaborative networking among cooperatives.According to the results of the structural equation test illustrated in It was also observed that values for social and technical mechanisms have been greater than 0.05 and there was no significant relationship between social and technical mechanisms with development of collaborative networking. The results also showed that the social factors and technical mechanisms had weakest structural relationship among all factors.6National governments pursue strategies in which strengthening the cooperative sector is seen as a priority for sustainable economic development. This study examines the mechanisms that can be involved in development of collaborative networking among agricultural cooperatives in the Karaj Province. The results of descriptive analysis of the data show that 68% of the population have bachelor’s degrees. Furthermore, having an average of 18 years of experience in working in cooperatives shows that the members of the population have had enough experience in their profession. The results also show that the target population in this study was dominated by the male population (80%).This study specifically explored the relationship between independent variables (mechanisms) and dependent variable (collaborative networking). The results indicated a significant relationship between educational, economical, policy making and legal mechanisms and collaborative networking.One potential mechanism that develop the collaborative networking among cooperatives is economic. That’s because this mechanism has been considered by agricultural policy makers to provide financial services and inputs to the target population. In the context of economic policies, respondents indicated that insurance and emergency policies, subsidies, and guaranteed purchases, could be enhanced establishing collaborative networking among cooperatives. From respondent’s perspective, the input indicator has had the greatest impact on our proposed network model due to its significant role in reducing the end-user price. The result of study by In regard to the role of legal mechanisms in development of collaborative networking, it was found out that rules and regulation which create and facilitate the ground to develop collaboration among cooperative needs to be approved and modified by the government to make the process easier and more efficient. The results of study by Three variables are used to capture the collaborative networking mechanism namely, network-based behavior, market-oriented behavior, and relationship-based behavior. Considering the role of behaviour, market-oriented behaviour may have more positive ramification in establishing networks among cooperative. This is in line with the study of The policy making mechanisms was found to play an important role in developing collaborative networking among agricultural cooperatives. This finding is in accordance with the study by The proposed network has the potential in offering educational services such as training courses required by network members. Educational services have direct and indirect benefits for organizations and their members in the networks and enhance collaboration among them . SurprisThe results indicated a non-significant relationship between social mechanisms and development of collaborative networking. Therefore, it can be concluded that social mechanisms have not influenced the development of networking in production cooperatives. Such a result is not in accordance with a study done by 7There are very limited studies on networking in cooperatives and it is expected that such studies can fill in the gap. In addition, due to the structural and functional differences between cooperatives and other organizations, it seems that the findings of this study can make a significant contribution to providing a ground for building networks between cooperatives.The results of this study show that economic, educational, policy and legal mechanisms are identified factors that play a role in collaborative networking cooperatives. The result confirmed the hypothesis because it shows that there is a relationship between the variables involved. However, social, and technical mechanisms are not considered as the main factors affecting the collaborative networking among cooperatives, because the results showed a weak positive relationship between the variables.One of the main outcomes of this study is the promise of cooperative networking to deliver positive consequences for the efficiency and effectiveness of agricultural production cooperatives as well as better service.Findings of this study by focusing on the role of networking would improve the performance of cooperatives and indirectly helping the government in achieving the economic goals.The findings of this study will also help policy makers and planners to identify weaknesses and shortcomings to improve the performance of cooperatives and to achieve the goals of the cooperative sector.The analysis of factors in this study would allow practitioner and policy makers to understand the current pattern of relationships between cooperatives and develop model to improve the collaboration between cooperative through networking.8The practical consequences of this study are limited to agricultural production cooperatives in Karaj province, so the networking in these cooperatives is probably different from other specialized cooperatives as well as agricultural cooperatives in other provinces.9This study has provided results that contributed to cooperation and collaboration among cooperative societies, however there are certain limitations about its applicability in other cooperatives and further research is needed to test its validity.It is also recommended that studies should be conducted to examine the factors that contribute to the development of informal networks among cooperatives.The results of this study emphasize that there is need for future studies about internal characteristics of cooperative networks. Furthermore, more research is needed on the critical determinants of the success of these networks.Mohammad Alimohammad, Seyed Jamal Farajallah Hosseini, Seyed Mehdi Mirdamadi, Sahar Dehyoori: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Data will be made available on request.The authors declare no conflict of interest.No additional information is available for this paper.


Asthma remains the most prevalent chronic respiratory disease of childhood. Severe asthma accounts for a minority group of patients but with substantial morbidity burden. It may reflect disease which is resistant to treatment or that which is difficult to treat, or a combination of both. The adolescent patient cohort denote a unique group and are the focus of this review. This group of patients embody transitioning priorities and evolving health beliefs, all of which may influence the management and burden of disease. Factors of importance include the influence of physiological parameters such as sex and race, which have confer implications for medical management and non-physiological factors, such as adherence, risk-taking behavior, and vaping. The holistic approach to management of severe asthma within this group of patients must acknowledge the evolving patient independence and desire for autonomy and strive for a collaborative, patient tailored approach. This review will focus on the factors that may pose a challenge to the management of severe adolescent asthma whilst offering suggestions for changes in practice that might harness patient priorities and shared clinical decision-making. Asthma is the most prevalent chronic lung disease of childhood . Most chsevere asthma in those over 6 years of age, as that which obligates treatment with high dose ICS and another maintenance agent, or use of systemic steroids, for more than half of the previous year to achieve control (The European Respiratory Society (ERS) /American Thoracic Society (ATS) defines  control .Along with high treatment burden, severe asthma confers significant morbidity and mortality. Within pediatrics, the National Review of Asthma deaths in the UK revealed that mortality in this population remains alarmingly high . Asthma adolescence to be within the ages of 10 and 19 years  defines 19 years  whilst o19 years . CertainMarked differences can exist in the manifestation, exacerbating factors, and management strategies for asthma at different age groups . FurtherThis review will explore the multifaceted parameters that bear significance to the management of severe asthma in the adolescent group.The WHO categorizes severe asthma into three groups; (1) inadequately treated (2) that which is difficult-to-treat and (3) severe treatment-resistant asthma (STRA), the last of which represents asthma for which the highest level of management is necessitated to achieve control, or which does not despite this .A crucial initial step is in ensuring the diagnostic labeling is accurate and should begin with addressing the basics. A multidisciplinary approach is paramount  in diagnSTRA may warrant the use of biologics and in the UK currently omalizumab and mepolizumab are licensed for use in children aged above 6 years and dupilumab for children aged above 12 years, with the caveat that the patient has not shown an adequate response or is not eligible for mepolizumab . The US A thorough history and appropriate investigations facilitate diagnostic clarity. Investigations include blood tests for full blood count, total IgE and specific IgE to aeroallergens, as severe childhood asthma has associations with atopy and increased blood eosinophilia . SpiromeSeveral comorbidities may confound the presentation and diagnosis of asthma and should be considered. Of note are breathing pattern disorders. These are best described as chronic or recurrent changes in breathing pattern that cause respiratory symptoms such as breathlessness and non-respiratory symptoms such as anxiety, light-headedness, and fatigue. The prevalence of some breathing pattern disorders in adolescents with asthma may be as high as 25% . DisruptObesity, a global health concern, is a significant risk factor for severe asthma and is associated with poor asthma control and increased health care utilization . SystemiThe aim of any asthma management strategy should be to achieve symptom control, with minimal therapeutic intervention. The WHO suggests adherence to be “the extent to which a person's behavior—taking medication, following a diet, and/ or executing lifestyle changes, corresponds with agreed recommendations from a health care provider” . ContrarA compendium of factors sway adherence in adolescents  and in tConflicting and changing priorities and attitudes to health play a key role in this age group , 26 and initiation (taking the first dose), implementation  and persistence   . In the eatment) . Adhereneatment)  and a steatment) . It is ieatment) , creatinFurthermore, monitoring adherence may itself pose a challenge. A combination of history and investigations, including trends in spirometry and FeNO measurements, and prescription uptakes offer some indication. Subjective tools to ascertain treatment observance include self-reporting questionnaires, such as the Medicine's Adherence Report Scale . HoweverPost-hoc analysis of the IDEAL study noted that 81% of the patients with severe asthma had uncontrolled disease, which was associated with reduced lung function and worsened health related quality of life  study reiterate the deleterious impact of smoking on symptomology, noting the association of exhaled smoke with severe wheeze . HoweverWhilst extensive research is lacking, the present understanding on vaping effects on the lungs highlights the associations with increased severe asthma attacks, airway inflammation, increased risk of acute lung injury and reduction in lung function . Two casrisk factor for future smoking, not simply a marker for future smoking  may be employed, exploring individual priorities and promoting positive health behavior . It has Creating a bridge between patient held beliefs and accurate knowledge of disease and treatment is an important next step. Experiencing episodes of severe asthma exacerbations and decline in asthma control, has shown to emphasize the importance of maintenance therapy and motivate greater adherence in adolescents . This ofA further example where collaborative working may yield a more effective outcome may be seen in school attendance and symptom perception. School and educational establishments are likely to play an integral role in adolescent lives and educational accomplishments are recognized as a priority for adolescents . HoweverTherefore, collaborative working with the adolescent patient and their families, one which endeavors to codesign clinically appropriate but patient-focused management regimens, may offer a bridge to more effective management of severe, difficult to manage asthma.Transition from pediatric to adult services is an important phase in the management of severe adolescent asthma and should endeavor to acknowledge the influence of the various aspects discussed in this review. The transition process should involve a named asthma nurse and consultant from the pediatric and adult services for better outcomes. Whilst a consensus on a set age for transition is lacking, it usually between the ages of 16 and 18. However, the conversations around transition should start early , 55, aimDespite greater understanding, asthma mortality remains high and there are associations that need further exploration. The authors recognize that one such area is the contribution of ethnic differences in asthma subtypes and outcomes, with recent findings suggesting the influence of race and ethnic differences in asthma outcomes and severity . These fSevere asthma in the adolescent requires a broader perspective and demands recognition of the components that are relevant to this unique age group. SW wrote the first draft. Both authors reviewed, revised, made contributions to all subsequent drafts, and contributed to the work of this manuscript.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.


How does environmental education affect environmental quality? There is no consensus among theorists. This paper is devoted to exploring the influence mechanism of environmental education and environmental quality under the background of a low-carbon economy from a theoretical model and empirical analysis.The research method of this paper includes two aspects. First, from the consideration of the central planner, this paper draws on and improves the Ramsey Model to explore the interaction mechanism among environmental education, environmental quality and green growth. Second, this paper uses provincial panel data from China from 2011 to 2017 for empirical analysis, which mainly verifies the impact mechanism of environmental education on environmental quality.The theoretical model shows that environmental education enhances green consumption intention through residents' environmental awareness and enhances enterprises' cleaner production motivation through environmental pressure. Correspondingly, the pressure to improve environmental quality will also promote the economy's endogenous growth through the digital economy's transformation and the accumulation of human capital. The empirical analysis confirms that environmental education can improve environmental quality through green consumption and pollution control. Still, the effect of improving environmental quality only through pollution control is not apparent, and pollution control needs to be combined with environmental education, especially in high-pollution areas. Finally, this paper puts forward some suggestions for optimizing environmental education. Global climate change has become one of the most significant challenges to human development, dramatically promoting global political consensus and significant actions to address climate change. At the first World Summit on Sustainable Development (WSSD) in Johannesburg in 2002, delegates called for “encouraging and promoting the development of a 10-year framework for Sustainable Consumption and Production Plans (SCP) to support regional and national initiatives to accelerate the transition to SCP”. Promoting sustainable development through pollution control and green consumption is increasingly becoming the international community's consensus. When the level of economic development reaches a certain stage, the government should pay more attention to sustainable development in public life, education, and environmental protection . τ is the output elasticity of environmental investment, τ ∈ . γ is the coordination between production and consumption, γ ∈ . When the consumption structure is upgraded, the production or industrial structure is also upgraded and γ is larger. Thus, we assume that Investment in environmental education can be regarded as an input element of production. The products are used for current consumption, investment in expanded reproduction in the next period, and investment in environmental quality in the next period. The investment accumulation will not be used for the next production period. From the consideration of the central planner, we draw on the Ramsey Model  and conskt+1 and kt in Bellman Equation:et+1 and et in Bellman Equation from formula (3):We construct the Bellman Equation:we have:δ=AγβαγSotection , 21 and otection  but alsootection , 26.Formulas (10)–(12) also show that the performance of environmental education investment is highly correlated with the coordination degree of production and consumption; When the product  structure upgrading is more consistent with the consumption structure upgrading, that is, when the value of γ is larger, the investment in environmental education is more conducive to the upgrading of household consumption, economic growth, and the improvement of environmental quality.pl) serves as the explanatory variable in this study. Existing studies have mainly used single pollutant emission indicators as a substitute for environmental pollution, such as nitrogen oxides and sulfur dioxide  = 0.If Step 4: We calculate the information utility value of each pollution index.Step 5: We calculate the weight of each pollution index.Step 6: We calculate the comprehensive pollution index.Comprehensive Pollution Index ( dioxide . Industr dioxide –35. Entreedu) is the core explanatory variable. Since environmental education is not listed in China's statistical data, we will use the fiscal expenditure for education as an alternative indicator of environmental education. The choice of proxy variable is based on two aspects. First, the Ministry of Education and the Ministry of Environmental Protection of the People's Republic of China jointly formulated the National Measures for the Application and Management of Social Practice Bases of Environmental Education in Primary and Secondary Schools, which is committed to standardizing the construction and management of social practice bases of environmental education in primary and secondary schools. Second, the Ministry of Education of the People's Republic of China issued the Notice on Implementing the Xi Jinping Thought of Ecological Civilization and Enhancing the Awareness of Ecological Environment in Primary and Secondary schools, requiring educational administrative departments at all levels and primary and secondary schools to reflect entirely thrives, green and low-carbon consumption in the teaching of relevant subjects, in-class and extra-curricular activities and all links of school management, so that students can effectively enhance awareness of the ecological environment. Improve the ability to protect the ecological environment. This means that all kinds of schools relying on fiscal education expenditure will carry environmental education through the whole education process; that is, education expenditure is an appropriate proxy variable for environmental education expenditure.Environmental education (nedu) as a substitute indicator of environmental education. In the theoretical analysis, we find that environmental education will affect the environmental pollution index through residential consumption and pollution control. So other independent variables are resident consumption (rc) and investment in pollution control (pci). The level of household consumption expresses resident consumption, and pollution control is measured by the amount of investment completed in industrial pollution control.In the robustness test, we use the number of environmental publicity and education (tp), the proportion of the secondary industry (psi), amount of electricity consumption (aec), the degree of openness (open), and the fiscal and taxation capabilities (ftc). The global environmental change caused by humans has accelerated unprecedentedly, and the continued population growth has a particular relationship with environmental degradation . The data in this article comes from the “China Statistical Yearbook” and “China Environmental Statistical Yearbook” from 2011 to 2017. i and t represent province and year, respectively. pl stands for pollution index, rc stands for household consumption, pci stands for pollution control investment, and eedu stands for environmental education investment. control contains other variables . year represents the time effect of the province, and province represents the individual fixed effect of the province. ε denotes random disturbance terms.Based on theoretical analysis and research hypotheses, the baseline model is set as follows:pl and pci is not statistically significant, pl is negatively correlated with eedu, rc, and pci. eedu has a significant positive correlation with rc and pci. Population, electricity consumption, economic openness, and tax revenue negatively correlate with the environmental pollution index. The development of the secondary industry has aggravated environmental pollution. Initially, the investment in environmental education is conducive to environmental quality, and residents' consumption and pollution control are also conducive to environmental quality. Environmental education positively impacts residents' consumption upgrades and pollution control. Environmental education may affect environmental quality through two channels, influencing residents' consumption upgrade and pollution control. Of course, the conclusion is that the influence of other factors has not been considered. Next, we consider other influencing factors for further empirical verification.The correlation coefficients between variables and their significance levels are shown in H1.eedu × rc = 0.019) but insignificant. It does not indicate that the impact of environmental education on environmental quality will decrease as the level of resident consumption increases. Meanwhile, the coefficients of environmental education, resident consumption, and pollution control are all significantly negative, indicating that the three have a promoting effect on improving environmental quality. The impact of environmental education and pollution control on environmental quality is consistent with the existing research conclusions. The reason resident consumption can improve environmental quality may be that with the deepening of environmental education, resident consumption pays more and more attention to green consumption (H2a.Model (2) shows that the interaction between environmental education and residents' consumption level is positive  is significantly negative. That is, with the increase of pollution control efforts, the impact of environmental education on environmental quality gradually increases. The conclusion verifies the H2b. It is worth noting that the coefficient of pollution control on environmental quality is significantly positive, which means that the investment in environmental control will increase the pollution level. The possible reason is that pollution control is relatively passive; that is, areas with more investment in pollution control often have more severe pollution. In Section 4.5 of this paper, quantile regression will be conducted according to the regional pollution degree to explore the reasons for this phenomenon further. In consideration of the coefficient value of eedu is not significantly negative. Similarly, we use Formula  can also support H2b.Model (3) shows that the interaction between environmental education and pollution control  shows that environmental education, residents' consumption level, and pollution control significantly negatively impact the pollution index. Environmental education, residents' consumption level, and pollution control are all conducive to environmental quality. The robustness test verifies H1.nedu × rc) is significantly positive. It means that with the increase in residents' consumption, the inhibitory effect of environmental education on environmental pollution will gradually weaken. This makes it even more necessary to improve consumers' awareness of green consumption and achieve environmental protection through green consumption. The conclusion verifies the H2a. Consistent with the benchmark regression, the influence coefficient of environmental education on environmental quality can also be verified by calculating the partial effect of environmental education. The calculation formula of the partial effect of environmental education incorporated into residents' consumption level is as follows: H1.In model (5), The inhibitory effect of environmental education on environmental pollution is significantly negative (−0.358), but the interaction between environmental education and residents' consumption level , the interaction between environmental education and pollution control is considered, and it is found that To further analyze the results of model (3) and model (6) and verify the impact of pollution control on the environmental pollution index, we conducted quantile regression analysis according to the size of the pollution control investment. H3.It is worth noting that with the improvement of the region's pollution index, the pollution control role is getting smaller and smaller. The possible reason is that the increase in investment in pollution control is a passive choice. First, in areas with severe pollution, investment in pollution control has to be increased to meet the environmental protection requirements of the central government. Second, improving residents' environmental awareness will also encourage government departments to increase investment in environmental governance. Residents' emphasis on the ecological environment and protests against polluting companies or behaviors have forced local governments to increase their control of environmental pollution . QuantilThe low-carbon economy is the dominant choice for human society to solve the dilemma of environmental governance. The high-quality natural environment provides a good production and consumption atmosphere for economic growth. This paper's theoretical and empirical research can provide the following four conclusions. First, environmental education will significantly reduce the environmental pollution index, which can be supported by the benchmark regression coefficient of environmental education and its partial effect coefficient.Second, from the perspective of green consumption and cleaner production channels, with the improvement of residents' consumption level, the promotion effect of environmental education on the progress of environmental quality shows a downward trend, so it is more necessary to truly enhance residents' awareness of green consumption through environmental education. It will also push companies toward cleaner production through technological innovation and environmental investment.Third, from the perspective of pollution control channels, pollution control investment cannot effectively promote environmental quality because there is a paradox of positive correlation between regional pollution degree and pollution investment amount. In areas with higher pollution degrees, more pollution control costs need to be invested in meeting environmental protection standards or residents' willingness to protect environmental protection. The conclusion of quantile regression verifies this phenomenon.In addition, we find that there is uncertainty about pollution control in improving environmental quality. With the improvement of the pollution index of the region itself, the role of pollution control is getting smaller and smaller. This indicates that the environmental governance issues in areas with higher pollution levels are more passive. It also means that environmental education should be carried out first to avoid passive responses when environmental pollution is severe.First of all, it is necessary to form a consensus on environmental protection in the whole society through environmental education from a strategic perspective. Chinese local governments should respond to the unified deployment of the CPC Central Committee and the State Council of the People's Republic of China, distinguish between different objects such as state organs, enterprises, public institutions, social organizations, schools, families, and the public, and penetrate environmental education into family education, primary education, higher education, vocational education, cadre education, and training and other links. Environmental education should penetrate all stages of citizens' lives according to its purpose and tasks, combined with its universality and life-long characteristics. This is an important measure to implement the concept that clear waters and lush mountains are gold and silver mountains and also a necessary choice for a low-carbon economy and sustainable development.Secondly, from the perspective of the channel mechanism of environmental education. Environmental education should emphasize its role in promoting citizens' environmental awareness and reflect the positive role of environmental education in promoting residents' green consumption and enterprises' green production. At the same time, local environmental protection and environmental education departments should actively respond to hot environmental issues concerned by the people with a scientific and pragmatic attitude, guide the public to participate in environmental protection work in a mature, rational, orderly, and effective manner, gather the people's hearts, wisdom and strength to the greatest extent, and jointly promote the steady improvement of environmental quality.Finally, environmental education legislation should be accelerated from the perspective of legal regulation. Currently, the connection between environmental education and legislation in China exists only in single words and sentences of individual legal provisions. For example, the Environmental Protection Law only stipulates the principles of environmental education. According to the Environmental Protection Law of the People's Republic of China, the Education Law of the People's Republic of China and other laws and regulations, Jiangsu Province has formulated the Measures for the Promotion of Ecological Civilization Education of Jiangsu Province, which also defines the scope and implementation subjects of ecological civilization education in schools, families, and society. However, it is still only an administrative document of the local government. It has not yet risen to the level of the legal system. In fact, environmental education legislation can regulate the behavior of citizens and enterprises and provide a legal system guarantee for the government's environmental education and environmental governance.There are two marginal contributions in this paper. Firstly, this paper improves the Ramsey model and finds that the fit between consumption structure and industrial structure is an important factor for environmental education to improve environmental quality, which provides a factual basis for environmental protection practice. Secondly, this paper conducts theoretical analysis and empirical tests on the transmission mechanism of environmental education to environmental quality and finds that environmental education can improve environmental quality through pollution control and green consumption, especially for heavily polluted areas. Environmental protection and environmental education should be strengthened, especially for heavily polluted areas, which is an expansion of the research on the transmission mechanism of environmental education.There are a few shortcomings in this paper. For example, due to data availability, this paper uses the data at the provincial level in China and does not analyze the city and county levels. This paper also fails to explore how environmental education affects citizens' environmental awareness and, thus, environmental quality. It does not explore the influencing mechanism of environmental education on high-quality economic and social development, which are future research directions.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.YW, JW, and WY conceived the study and drafted the manuscript. YW designed the model. All authors contributed to the article and approved the submitted version.