Ischemic heart disease and degenerative encephalopathy are two main sources of disease burden for the global elderly population. Coronary heart disease (CHD) and cognitive impairment, as representative diseases, are prevalent and serious illnesses in the elderly. According to recent research, patients with CHD are more likely to experience cognitive impairment and their cognitive ability declines more quickly. Vascular risk factors have been associated with differences in cognitive performance in epidemiological studies, but evidence in patients with CHD is more limited. Inextricably linked between the heart and the brain. Considering the unique characteristics of recurrent cognitive impairment in patients with CHD, we will further study the related risk factors. We tried to investigate the potential predictors of cognitive impairment in patients with CHD through a prospective, cross-sectional study.2 test was selected to describe and evaluate the variation, and logistics regression analysis was employed to fit the prediction model. After that, do the calibration curve and decision curve to evaluate the model. The prediction model will be validated by a validation set.The cross-sectional study design will recruit 378 patients with CHD (≥65 years) from Xiyuan Hospital of China Academy of Chinese Medical Sciences. The subjects' cognitive function is evaluated with MoCA scale, and they are divided into cognitive impairment group and normal cognitive function group according to the score results. Demographic data, disease characteristics , laboratory tests , metabolites , and lifestyle  will be assessed as outcome indicators. Compare the two groups and the correlation analysis will be performed on the development of mild cognitive impairment. Mann-Whitney U or XTo explore the risk factors related to mild cognitive impairment (MCI) in patients with CHD, a new predictive model is established, which can achieve advanced intervention in the occurrence of MCI after CHD. Owing to its cross-sectional study design, the study has some limitations, but it will be further studied by increasing the observation period, adding follow-up data collection or prospective cohort study. The study has been registered with the China Clinical Trials Registry (ChiCTR2200063255) to conduct clinical trials. With the deepening of population aging, the incidence of cardiovascular and cerebrovascular diseases is increasing annually, which brings heavy social and economic burden. Coronary heart disease (CHD) and cognitive impairment are major diseases that endanger human health, especially for the elderly. Cognitive impairment includes varying degrees from mild cognitive impairment (MCI) to dementia. When memory or other cognitive functions are impaired but not to the point of dementia, this is referred to as MCI . EpidemiStudies have shown that those with CHD are more likely to experience cognitive impairment. Compared to the general population, the prevalence rate is much greater at roughly 35–46% . SimilarThe impact of cardiovascular event chain (from cardiovascular risk factors to end-stage heart diseases) characterized by coronary atherosclerosis has expanded to organs outside the heart, particularly the brain, and affects cognitive performance , 12. It This is a prospective, cross-sectional study with 378 participants. After screening according to the inclusion and exclusion criteria, the informed consent of the subjects was obtained. According to whether CHD patients are accompanied by mild cognitive impairment, the researchers will divide them into a cognitive impairment group (observation group) and a normal cognitive function group (control group). It is based on the program “Research on the Transformation and Application of TCM in the Prevention and Treatment of Secondary Cognitive Impairment of Coronary Heart Disease” sponsored by the Chinese Academy of Chinese Medical Sciences (CI2021A01406) to identify the risk factors for cognitive impairment in CHD patients. The fieldwork for this study will be conducted at Xiyuan Hospital of China Academy of Chinese Medical Sciences in China. Both outpatients and inpatients are allowed to be included. Depending on the feasibility and specific implementation, additional hospital sites may be added. In addition, this study has been registered as a clinical trial by the Chinese Clinical Trials Registry (ChiCTR2200063255), which further standardizes our research. The specific overview of study procedure is shown in Eligible patients were identified according to the diagnostic description and the International Classification of Diseases (10th and 11th editions). The recruitment of subjects was carried out through offline and online announcements, focusing on offline treatment process. Eligible patients are expected to be enrolled between September 2022 and December 2023. The diagnostic criteria of CHD refer to “guidelines for diagnosis and treatment of stable coronary heart disease”  and “guiFor the diagnostic criteria of MCI, refer to the Chinese guidelines on mild cognitive impairment . SpecifiAll the above are diagnosed by the attending physician. Under the premise of full informed consent, it will be screened by the researcher or the attending physicians according to the requirements. The inclusion and exclusion criteria for this study are shown in For the exploratory analysis of multiple risk factors, the sample size of this study is set to be >5–10 times the number of observed factors , 17. AccClinical, biological, social and environmental determinants of interest in this study were selected based on the potential or established association with cognitive impairment in patients with CHD and/or the fact that they are modifiable through preventive strategies.Standardized questionnaires will be used to collect demographic, symptom, and medical history data. Social demographic information includes age, gender, race, height, weight, BMI, marital status, education level, nature of work, and type of occupation. Clinical data include past and present diseases (acute and chronic), drugs, and family history of cardiovascular disease. Disease-related information includes the course of CHD, the results of coronary CT/ angiography, the number of coronary stents implanted, cardiac function class, the number of diseased vessels, types of statins, and drug treatment. Previous disease history and drug use also need to be recorded. Vital signs such as temperature, respiration, pulse and blood pressure are also covered.At baseline, all participants underwent cognitive assessment. Global cognitive function will be assessed using the MoCA scale. Neuropsychological scale screening tests are crucial in the identification of cognitive impairment. Currently, the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are the most commonly used cognitive assessment tools. Of the two, MoCA covers a wider variety of cognitive domains than MMSE. In addition, meta-analysis findings  revealedAs a screening tool specially developed to detect MCI, it takes around 10 min to administer MoCA when executed . The MoCAccording to the investigation, researchers found that an insomnia history was associated with an increased risk of MCI, and a sleep disorder history may usefully predict MCI . TherefoLaboratory examination can accept the test results within 7 days before and after screening. It mainly includes the following contents: fasting glucose, glycosylated hemoglobin (HbA1c), total cholesterol, triglyceride, low-density lipoprotein, high-density lipoprotein, total bilirubin, serum creatinine, serum iron level (Fe), coagulation function , vascular ultrasound pulse wave velocity (PWV).In addition to the above-mentioned indexes, in the early morning of the 2nd day after the selection, two tubes of peripheral venous blood of 5 ml will be drawn from a qualified phlebotomist and placed in the EDTA anticoagulant tubes. Centrifuge the blood samples , store them at −80°C, and then conduct untargeted metabolomics detection. 2 g of fresh fecal samples will be collected and put into aseptic collection tube and stored at −80°C immediately for metabolic detection and analysis of intestinal flora.All researchers can enter and conduct this trial only after they have completed the training and obtained the authorization of the principal researcher. The involved researchers were trained in Good Clinical Practice (GCP) prior to the start of this study. Every researcher has received training in research procedure and plan. Including the collection of the MoCA scale, the researchers mastered the relevant questioning skills and evaluation criteria after strict and standardized training in advance. Ensure the rigor and consistency of the implementation process. All investigators have a thorough understanding of the information in this clinical research protocol, master the GCP principles, unify the recording methods and judgment standards, and strictly follow the protocol.t-test is used for comparison between the two groups. The measurement data that don't conform to the normal distribution are expressed in the median (quartile), and the Mann-Whitney U test is used for comparison between the two groups. Counting data were expressed as frequency or percentage, and X2 test was used to compare the two groups. Single factor analysis shall be conducted for all factors. In order to avoid the omission of important variables, the covariates with P <0.1 in the univariate analysis will be included in the multivariate logistic regression analysis. Stepwise forward regression analysis is used to analyze the independent risk factors of cognitive impairment in patients with CHD, and the OR value and 95% CI of each related factor will be estimated. The risk prediction model of cognitive impairment in patients with CHD would be established by adding independent risk factors. ROC curve will be drawn and the area under the curve (AUC) will be calculated to evaluate the effectiveness of the prediction model. Use Bootstrapping method to verify the accuracy of the final model internally. All tests with P<0.05 on both sides indicate that the difference is statistically significant, and other statistical analysis can be carried out by SPSS25.0.Among the outcomes of this study, the measurement data in accordance with normal distribution are expressed by mean ± standard deviation, and independent sample In this study, standardized case report form (CRF) tables will be used to collect data. Each participant will be assigned a unique identifier with the hospitalization number or patient ID code. Medical and other records of the participants will be kept by the researchers. EpiData3.1 software will be used for data entry and establishing the database. Once the data input is completed, the integrity and reasonableness of all data will be evaluated and checked by the researchers item by item. Check the problem with the original survey data and correct it after confirmation.Age-related cognitive decline is a series of natural cognitive changes that may develop into MCI or dementia. MCI is a state of cognitive impairment between healthy aging and dementia, which is considered as the prophase of dementia . But at The objective of this study is to ascertain the relationship between CHD and its risk factors and cognitive impairment in the elderly. At the same time, establish the risk prediction model of cognitive impairment in patients with CHD. The study will make available data regards CHD and MCI risk prediction. We propose leveraging the progress of machine learning to systematically compare different modeling approaches  to develStill, this research is subject to certain limitations. As an observational study, cross-sectional design has limitations e.g., causality cannot be inferred, we can only address the association. However, we try to include more observation factors, which are widely related to basic demographic data, disease characteristics, blood chemistry, metabolites and lifestyle. It is expected that some risk factors with clinical value can be found on the basis of this exploratory analysis. In order to broaden the current knowledge on CHD and its relationship with cognitive impairment in the elderly. Additionally, it will serve as a valuable foundation for hypothesis generation for future longitudinal studies and / or randomized controlled trials. In the future, it is necessary to conduct a larger sample of prospective cohort studies and add follow-up time to determine the incidence of secondary MCI in patients with CHD.The study was approved by the Ethics Committee of Xiyuan Hospital of Chinese Academy of Chinese Medical Sciences (2022XLA060-3). This study involves elderly patients with cognitive impairment and the legitimate rights and interests of the subjects should be fully protected. Trained researchers will provide the subjects with informed consent forms, which are easy to understand and clear. Researchers will patiently and completely explain the purpose, procedure, potential benefits, and risks of this study before each subject is recruited for it. The principles of complete information disclosure and voluntary choice must be adhered to during the informed consent procedure. Subjects have the right to refuse to participate without giving reasons. After participants have voluntarily signed the informed consent form, attention will be paid to the questioning skills during the study, so as to avoid the unfamiliar emotions of the elderly subjects due to their participation in clinical research. Any modification of the research protocol will be submitted to the Research Ethics Committee for approval. Currently, the researchers are recruiting participants. The research results of this study will be published in medical journals in Chinese or English, but the patients' information will be kept private as required by law. When necessary, government administrative departments, hospital Ethics Committees, and their relevant personnel may consult the patient's data according to the regulations.FX and YuL conceived and designed the study protocol, helped to critically revise the draft, and conduct the final manuscript. QW, SX, and FL drafted the manuscript. YaL and QW made critical revision. All authors contributed to this article and approved the submitted version.


Editorial boards play a key role in the production, dissemination, and promotion of scientific knowledge. The cross-presence of scholars in different journals, known as editorial board interlocking, maps the connections between such bodies of governance. Former research on this topic is typically restricted to individual disciplines and has failed to consider the relevance of potential interlocking between related, but different academic fields. Further, although existing studies note a significant lack of diversity in editorial board representation, they mainly focus on a single dimension, such as gender or geography. This study addressed these knowledge gaps by offering a complex cross-disciplinary approach to the geographical, gender, and institutional compositions of editorial boards, with a specific emphasis on within- and between-fields editorial board interlocking. We used graph and social network analysis to examine editorial board connections between 281 top journals  of six disciplines: communication, psychology, political science, sociology, economics, and management. We found substantial differences in terms of field connections, ranging from sociology with 42% interlocking with other fields, to management with only 11%. Psychology is significantly less connected to the other five disciplines. The results also show a clear overrepresentation of American institutions and native English-speaking countries in all fields, with Harvard, Columbia, Cornell, Stanford, UC Berkeley, and New York University forming a well-connected central cluster. Although female scholars are underrepresented, there are no significant differences in terms of positioning in the network. Female scholars are even employed in more central positions than male scholars in psychology, sociology, and management. Our findings extend the literature on editorial board diversity by evidencing a significant imbalance in their gender, geographical, institutional representation, and interlocking editorship both within and between fields. The growing importance of publication output in leading peer-reviewed journals , and theAlthough editorial board (EB) members are typically recruited according to their “measured” academic achievements , researcwithin several research fields of the social sciences [within and between academic fields, nor the scientific structure and institutions of the dominant scholars, thus remaining unclear the power structure that governs major disciplines in social sciences. This study addresses this gap in the literature and examines editorial interlocks in the leading journals of six major fields.Thus far, the growing literature on editorial board interlocking has empirically examined interlocking editorships sciences . This stSpecifically, this study focuses on disciplines that are frequently analyzed in terms of editorial board composition but lack cross-discipline analyses: communication , 11–13, Our empirical results show that a typical central EB member is a male scholar from an elite American university who contributes to many different journals. Women are less likely to be editorial board members across all the analyzed disciplines, and influential affiliations are different for each field, with no central actor but rather a set of strong connections between relevant institutions. Overall, our results indicate a relatively loose but still existing network of notable scholars and elite institutions who occupy gatekeeper positions across analyzed fields. We argue that the uneven distribution of gatekeeping and a considerable interlocking across disciplines might hinder the balanced representation of gender and regions, and, ultimately, it might decrease the diversity of perspectives in the social sciences.Academic journals are typically considered the main spaces for the dissemination of scientific knowledge . ResearcExtant research has shown that positions on the EBs of top-tier journals are typically held by prominent scholars with great expertise and experience . RationaSeveral studies have emphasized the low gender and institutional diversity of editors . For insStudies have demonstrated that there is less female representation on EBs for high impact journals, and that it tends to decrease the higher the position . Metz etThe crossed presence of scholars on more than one EB is a phenomenon referred to as editorial board interlocking . EBI is Moreover, research has suggested that some individuals may also be invited to join editorial boards based on their international excellence and prestige , typicalStudies have suggested that EBI has a greater influence over research production for the social sciences and humanities than for hard-science disciplines . ResearcIn summary, research into scientometrics has highlighted the low diversity of EBs and the connections between journals and editors through EBI e.g., , 8. WhilRQ1: What is the geographic and gender representation of the editorial boards across the six fields?RQ2: What institutions are in central positions in the social networks of the six fields?RQ3: What are the connections a) within, and b) between fields through EBI?The data used in this study comes from the public webpages of the selected journals. We used the Journal Citation Report (JCR) as a source for journals because it has the most influential ranking. We used 2019 for the analysis because it was the most recent data available when we started our research. Journals indexed by the JCR are grouped into categories. We selected six categories of the JCR as the fields examined for this study: communication, psychology, political science, sociology, economics, and management. The fields were selected on the basis of their academic proximity, tradition within the literature of editorial board interlocking, and their reach within the social sciences.Since journals can be listed in more than one category, the field for each journal was determined by selecting the first category listed by the JCR SSCI which was among the fields considered for this study. For instance, if a selected journal was listed under engineering and management, we labeled it as management because engineering is not part of the study. Categories were defined by Clarivate Analytics (formerly known as ISI) on the basis of several indicators, such as the title of the journal and citation patterns , 39. TheJournals are divided into four different quartiles by their impact factor for each category of the JCR. In 2019, the population of the six categories under study included 1,100 JCR-ranked journals: 92 journals for communication, 78 for psychology, 181 for political science, 150 for sociology, 373 for economics, and 226 for management. In order to make such large number of journals and the data collection feasible, we selected a representative, stratified random sample of the 1,100 indexed journals, with a margin of error of 5%, taking 25% of journals evenly distributed between quartiles, so that journals with different degrees of influence were represented in the sample. Accordingly, the journals sample is representative of the journal population. This random selection was implemented by using a random number generator. In total, our proportional random sample consisted of 281 journals of the 1,100: 25 for communication, 20 for psychology, 44 for political science, 36 for sociology, 99 for economics, and 57 for management. It was not reasonably feasible for this study to gather and analyze the data from the complete network of EBs, so sampling was used. The sampling goals for this study were (1) to obtain a representative network that reflects both structural network properties and community structure, and (2) to preserve the distribution of node attributes. Biases in sampling may affect results in different ways, however, and there is no perfect method that accurately balances network structure, communities, and attribute distribution . SeveralSampling methods for graphs include random selection and crawling. Random selection chooses nodes or edges using either uniform, probability (e.g. degree-based) or hybrid distributions. Crawling methods sample the graph by exploring it. Among them, breadth sampling explores all the edges of current nodes, depth sampling prioritizes the first edge of current nodes, and random walks explore edges uniformly at random. Forest Fire Sampling is a probabilistic version of breadth sampling that explores edges with a given probability. Evidence shows that node sampling is better at preserving degree distributions . Edge saGiven the nature of the bipartite network of EBs, it is possible to sample and explore journals if we use a source for journals such as the JCR and then identify the EBs as reported on the journal’s web page. However, it is difficult to sample and explore scholars, since sources of researchers are not as common or widely accepted, and it would be necessary to obtain the journals in which individual scholars serve as EB members in order to explore them all. This may be reported on personal or institutional web pages, requiring specific and unreliable searches. Random sampling of edges was thus not possible for this study.As we can then see, different sampling strategies work for certain goals better than others. We tried to mitigate the limitations of data acquisition and the limitations built-in for each sampling method, while reasonably preserving structural properties and attribute distributions. We thus combined random uniform node sampling and breadth-first sampling. The sampling method used was an adaptation of the Random Node Neighbor (RNN) for a bipartite network. We selected a random set of journals (random-first sampling) and sampled its out-going edges (breadth sampling). RNN keeps the structural properties of the sampled graph for a sample size over 15% . Althoughttps://gender-api.com/). The API returns a prediction of gender based on the name and an estimation of accuracy, which is a measure between 0 and 100 of the reliability based on the API internal database. We coded the gender when the accuracy returned was greater than 75%. Since API prediction is mostly based on the first name, we did not use the API for EB members who were reported in journals using only initials. In total, 14669 entries were “genderized” using the API and the gender of 415 EB members remained undetermined.The final sample included 15,084 scholars and 17,092 memberships. Social network analysis (SNA) investigates the social structure of networks using graph theory. The social network of scholars (EB members) and journals can be represented as a graph in which nodes represent actors  and edges represent their shared EB memberhips. This network is shown in a bipartite graph, in which the edges only connect the nodes of two different sets . Bipartite networks are sometimes called affiliation networks or two-mode networks.SNA provides different metrics with which to quantify the network properties of individual nodes and of complete networks. The individual properties of nodes  were analyzed using degree, closeness centrality and betweenness centrality, as used in previous studies , 45, 46.Closeness centrality represents the distance to the center of the network for a given node. It can be regarded as a measure of how long it takes to spread information from the node. In this study, closeness centrality is normalized . The maxBetweenness centrality measures the number of times that a given node is part of the shortest path between two other nodes. It is a measure of the influence of a node over the resources and the flow of information in the network. Betweenness shows which nodes act as a bridge between different parts of the network. For example, a journal or EB member with high betweenness acts as a connector between two parts of the network that may otherwise be unconnected or distant, and plays a relevant role in whether information and ideas spread through the network. The betweenness centrality of a given node is computed as the sum of the fraction of all pairs of the shortest paths that go through the node. In this study, betweenness is normalized by the maximum possible value, which is total number of pairs of nodes .Since this study collected the social network of EB memberships of six different fields, it is possible to analyze the similarities and differences between the fields using the SNA metrics that quantify the structural properties of complete networks. It is also possible to analyze and compare fields with the overall network that includes all journals and all scholars from the six fields. The structural properties of the networks for each field, and for the overall network, were compared using the following network metrics: density, the clustering coefficient, average path length, diameter, number of connected components, average degree, average closeness centrality and average betweenness centrality. Density is the ratio between the number of edges in the graph and all possible edges. It is a measure of the overall number of connections. Clustering measures the intensity of local connections with the closest nodes. In our case, density and the clustering coefficient are indicative of the level of a field’s overall cohesion. Fields with low density can still have higher values for clustering coefficients by having tightly connected subgroups working independently which are only sparsely connected through EBIs.Average path length is the average of the shortest path between all possible pairs of nodes. It provides an estimation of the distance between participants. Diameter is the distance between the two farthest nodes in the network . In our case, low values for average path length and the diameter of the network of a given field indicate that information and ideas can spread fast. The combination of all these metrics also provides an estimation of the organic nature of each field. Networks of human activity usually show low density, but also short average path lengths, small diameters, and high clustering coefficients. The networks of EBIs for each field should present these features.A connected component is a set of nodes linked to each other by paths. The number of connected components is the number of such sets in the network. Components represent areas of activity that are unconnected through EBI, and the number of connected components can then provide an estimation of the level of fragmentation of a given network. In our case, a field with a high number of connected components represents a substantial number of groups working independently that do not share any kind of information, ideas, or interests through EBI. Conversely, fields with only one connected component may present a lower level of diversity since interest may be shared across the whole network.The corresponding averaged values of the metrics previously defined for all nodes are average degree, average closeness centrality and average betweenness centrality. An analysis of all network metrics is used in this study to determine the similarities and differences in terms of connectivity, cohesion, and distance both between fields and with the overall network.A projection of a bipartite network is a one-mode network that contains the nodes of one set and the edges between each pair of nodes only if they have a common affiliation in the original bipartite network. A weighted projection includes an integer-valued attribute at each edge to indicate the number of shared affiliations between the connected nodes. For instance, two journals are connected in a projection if they share EB members, and the weight of the edge indicates how many members are common to both journals. EB members and journals have additional properties, such as affiliation, country or field, which can be used to build projections of these relevant features. We used the weighted projections of institutions and fields to find these relevant actors and analyze their connections through EBI.Since projections of institutions may have a significant number of nodes and edges, we used slicing to find the subsets of institutions which have intense ties. A slice is a subgraph that only has edges with a weight equal to or larger than a given parameter, as well as the nodes that connect all those edges. Slices show the presence of cohesive groups in which connections are more intense . We analhttps://networkx.org/) to create and analyze the graphs, compute the network metrics, and create the weighted projections. Graph figures were produced using the Gephi network visualization and exploration software [This study used SNA to analyze the bipartite network of EB memberships formed by scholars and journals. We used the Python’s NetworkX package . Non-parametric tests comparing medians are adequate because network metrics do not usually follow normal distributions.Youth & Society, and Journal Studies on Alcohol and Drugs) and 106 EBs with only one interlocking. The remaining 28 components include only one journal each, comprising a total of 733 EBs do not interlock with any other journal. It is difficult to represent the complete graph here because of its size. The final graph presents 15,365 nodes  and 17,092 edges forming 31 connected components. The main connected component includes 14,255 nodes  and 16,022 edges with 2018 EBIs (1667 scholars interlocking two or more EBs). A second component includes five neuropsychology journals and 236 EBs with 10 interlockings. A third component includes two journals  and may be caused by the differences in the sample sizes between countries, although only instances with more than 100 EB members are considered.108 countries are represented in the sample. The EB members in the sample represent 2850 different institutions. The most prominent institutions for each field in terms of the intensity of the connections of the slice as measured by the number of scholars shared through EBI are as follows: communication, Michigan State, Texas at Austin and Illinois at Urbana-Champaign; psychology, California-San Diego, California-Los Angeles, Columbia and Boston; political science, Columbia, Harvard, Oxford and London School of Economics; sociology, California-Berkeley, California-Los Angeles, New York and Harvard; and economics and management, the projection of institutions  shows thdegree = 0.924, rcloseness = 0.533, rbetweeness = 0.701, p<0.01 in all cases), showing that correlations for the whole dataset are not outweighed by institutions with a small number of scholars who present low values for network metrics. The total number of scholars across all EBs reflects the prominence of the institution, and can be used as an estimator of its influence. Although this result may seem obvious, it may very well be the case that overrepresented institutions only manage to place their scholars in a limited number of peripheral journals that do not have scholars from other prominent institutions in their EBs. Similar results are observed for each individual field, with strong significant correlations in most cases , closeness centrality  and betweenness centrality . Metrics were computed for the projection of institutions in the overall network of all fields. The results are similar when repeating the test only with institutions that have 20 or more members in the dataset  form a well-connected network, while despite having many EB members, the LSE is relatively distanced from the hub of elite US universities.In line with the corresponding literature  we foundAs discussed in the literature of social identity theory , scholarThe density values we observed were low for all disciplines and were similar to the values reported for the same and other fields: communication , economiManagement Communication Quarterly, the International Journal of Advertising and the International Journal of Conflict Management, which strongly connects the field of communication to the field of management with significant EBI. This latter field has a similar structure as that of communication, as it also has some more central journals but lacks journals with strong betweenness centrality positions.Basically, there are several types of interlocking. The first is represented by communication, where both within field and between field interlocking is significant, and there are more central journals surrounded by a set of more minor outlets. In the case of communication, there are several journals with high betweenness centrality, such as Industry and Innovation, and journals that connects economics to political science, such as the Review of International Political Economy. Half a dozen political science journals share a significant number of EB members with economics.Another type is represented by economics and political science, where we did not find a clear differentiation between central and peripheral journals, but where there are journals in strong betweenness centrality positions. There are journals that connect economics to management, such as Finally, sociology forms a dense network with journals that lacks within field interlocking, but shows substantially more between field interlocking, and with journals with strong ties to communication, economics and political science. While these disciplines are all interdisciplinary in terms of EBI, communication typically interlocks with management and sociology, economics has strong ties to management and political science, and sociology is the most balanced in the sense of interdisciplinarity as it interlocks almost equally with the other four disciplines.One unanticipated finding was that psychology is significantly detached from the other five disciplines, with a very limited number of shared EB members. This finding may be explained by several factors. First, it might demonstrate a thematic, theoretical, and methodological divergence between mainstream psychology and the other five disciplines. While the study did not content-analyze journal articles, it is reasonable to suggest that psychology is somehow distanced from more social scientific fields, and that psychologists might use more field-specific methods and theories, meaning that the editorial board composition of psychology journals may be detached from the other analyzed fields.Based on its relative distance from the other analyzed disciplines, we might even assume that contemporary psychology, as represented by the editorial boards of journals, is more closely related to the natural and life sciences than to social scientific disciplines. Second, as reviewers are, in most cases, selected on the basis of their research production and impact , 21, ourAlthough the study has successfully demonstrated a significant gender and geographical imbalance across the analyzed fields and observed a considerable EBI both within and between fields, it has some limitations that should be addressed in future research. First, we selected a particular number of fields within social sciences. Future research may consider other fields to map different disciplinary interlocks. Second, we implemented a representative, proportional random sample to each field. However, covering the full set of journals might provide a more detailed picture of EBI. The amount of data and the need for manual coding meant that a full mapping of all journals in all fields was not feasible, and future research might try to analyze all journals with fewer disciplines. Further, the sampling method presents its own limitations in terms of the representativity of communities and the distribution of attributes. Although this comes from the need to accommodate what is feasible when gathering data, we have to be careful with results and interpretations concerning communities, and gender, geographic and institutional representation. Future research can then focus on obtaining complete networks of EBs with the help computational technologies such as web scraping or selecting all journals within a quartile of the JCR ranking. Third, while working with the JCR journal list is reasonable and well established in the literature, findings may be different should the study focus on other academic rankings. Future research may thus replicate our comparative analysis with a different database, such as Scopus. Fourth, according to recent literature , scientiS1 Appendix(DOCX)Click here for additional data file.S1 FigThe labeled graph of the social network of journals and members is provided as high-resolution image (png) and vector image (svg).(ZIP)Click here for additional data file.


In recent years, public hospitals have seen an increasing need for management reform in light of increasing social security costs due to the aging population. This study investigated the relationship between collaboration with neighboring medical institutions and management efficiency in public hospitals. Data envelopment analysis was used to calculate the dependent variable. We used the referral rate for each public hospital as an independent variable to indicate active collaboration. Univariate and multivariate analyses examined the association between the two variables above. The adjustment variables in the multivariate analysis incorporated those variables that were considered significant in the univariate analysis when the significance level was 10% on a two-sided basis. The Tobit regression model was used in both univariate and multivariate analyses. Ultimately, the analysis included 402 public hospitals. Approximately 8% fell into the high-collaboration group. Even after adjusting for significant variables from the univariate analysis, the inefficiency value was significantly lower in the high-collaboration group than in the low-collaboration group; namely, the efficiency value in the high-collaboration group was significantly higher than in the low-collaboration group. Moreover, hospitals with a higher ratio of subsidies to revenue had significantly lower values for management efficiency. The analysis of the relationship between efficiency value and the percentage of referred patients in Japan indicated that higher percentages of referred patients, that is, higher degrees of cooperation, were significantly associated with higher efficiency scores.  Japan’s medical system has universal health insurance and free access to care (5). As with other countries’ healthcare systems, public hospitals in Japan play an important role (7). They provide standardized medical services even in unprofitable rural areas and unprofitable medical services, such as emergency medicine and pediatric care (8). However, in recent years, public hospitals have seen an increasing need for management reform due to increasing social security costs associated with an aging population (12). The Ministry of Internal Affairs and Communications (MIC) issued guidelines for reforming public hospitals in 2007 and 2015, requiring each hospital to formulate a plan for reform and operational efficiency (14).Japan is known worldwide for providing high-quality medical services (18). In the new guidelines for public hospital (PH) reform, reviewing salary structure and reexamining departments were considered measures for improving business conditions, but these measures may be limited. Zhang et al. found no significant difference in management efficiency between PHs that could determine their salary structure and those that could not (19). Additionally, Chen et al. suggest that the provision of unprofitable care does not necessarily correlate with financial status (20).According to a recent study, the factors affecting the management efficiency of public hospitals include the ratio of subsidies to revenue, nurse-to-patient ratio, hospital location, number of doctors and other medical staff, and medical revenueWealth of Nations, Adam Smith concluded that regional cooperation promotes the division of labor and specialization of each entity and increases efficiency (21). To the best of our knowledge, no investigation has been conducted into whether active collaboration with neighboring medical institutions has affected the management efficiency of PHs. This study has examined the relationship between collaboration with neighboring medical institutions and management efficiency in PHs. Moreover, as an indicator of the degree of collaboration (DOC) with other facilities, we adopted the referral rate, which several organizations use to indicate the degree of active collaboration (23).However, in We hypothesize that PHs that actively collaborate with neighboring hospitals (NH) are more efficient in their operations than those that do not.(24) published by the MIC; hospitals that adopt the diagnosis procedure combination (DPC) system charging a fixed amount of medical expenses per day, which accounts for all procedures, medication, etc., at a rate that matches the name of the hospitalized patient’s disease; hospitals preparing for the adoption of the DPC system; hospitals that use a fee-for-service system to submit DPC data to the Ministry of Health, Labor and Welfare (MHLW) (25); and hospitals listed in the survey of medical facilities published by the MHLW for FY2019 (26). The exclusion criteria, in line with previous studies, were: hospitals specializing in tuberculosis, psychiatry, and other specialties  were excluded (19); hospitals with a ratio of general hospital beds to total hospital beds of less than 80%; and hospitals where the average length of stay was longer than 70 days or shorter than 6 days.The inclusion criteria for facilities were: hospitals listed in the FY2019 Local Public Enterprise Yearbook (LPEY) (33). The DEA method is explained in detail in the supplementary file. Further, an efficient PH used the least amount of human, financial, and material resources to care for a certain number of inpatients and outpatients. From this definition and because previous studies have shown that PHs may have increasing returns to scale, we adopted the input-oriented Banker-Charnes-Cooper model to calculate the efficiency value (34).We adopted the technical inefficiency value as the dependent variable, consistent with previous studies. The technical inefficiency value was the inverse of the technical efficiency value minus one, calculated using data envelopment analysis (DEA)―used for calculating efficiency values among decision-making units (DMUs); DEA has been used in many studies in medicine (19). First, the outputs were defined as the number of per day outpatients and inpatients. The inputs were the number of doctors, nurses, and other medical professionals and the number of hospital beds and materials costs. The data came from the FY2019 LPEY and the FY2019 Hospital Bed Function Report published by the MHLW (26). We used these inputs and outputs to calculate the efficiency of each PH. We used DEA Solver Pro 12.1  to perform the calculations. The target hospitals were assigned a technical efficiency value between 0 and 1, and PH with the highest management efficiency was assigned an inefficiency score of 0.Owing to our focus on the management efficiency of PHs, we designated DMUs as the research target hospitals. The outputs and inputs of the DMUs were based on the previous study, which explored the factors that determine the management efficiency of PHs in Japan (35). This data were drawn from MHLW’s report “Survey on the evaluation of the impact of the introduction of DPC in fiscal 2019: Aggregate results” (25).We took the referral rate (RR) of each PH as an independent variable indicating active collaboration. The RR was the number of first-time patients referred from other hospitals per year, divided by the number of all first-time patients minus the number of patients transported by ambulance on holidays and at night, together with the number of first-time emergency patients (36).Facilities with an RR of 80% or higher were the high-collaboration group and assigned a dummy variable value of 1. The other facilities were designated as the low-collaboration group and assigned a value of 0. To create categorical variables, we used the requirement of an 80% or higher RR, which is a requirement for certification as a community medical support hospital in Japan. A community medical support hospital is a medical institution that supports primary care doctors to promote cooperation among medical institutions in the community and should show a significant degree of strong cooperation with NHs Previous studies selected four variables that affected management efficiency in PHs as control variables.(19). The region of the hospital’s location was tracked to derive the results that adjust for these effects. Then, following previous studies, we divided the regions of Japan into three categories (19).This variable was the region where the PH was located. Previous research has found that in some regions of Japan, PHs are the main source of healthcare services, and there, the impact of the reform plan is greater than it would be in other regions (24).The regions were classified into three groups. Japan is usually divided into eight main regions, i.e., Hokkaido, Tohoku, Kanto, Chubu, Kinki, Chugoku, Shikoku, and Kyushu. Hospitals located in Hokkaido and Tohoku were defined as the East Group and assigned the dummy variable value 1 for location. Hospitals located in the Kanto, Chubu, and Kinki regions were defined as the Central Group and assigned 2 for the dummy variable. Finally, Chugoku, Shikoku, and Kyushu hospitals were defined as the West Group and assigned 3. The data used in this study were from the FY2019 LPEY (37). This factor was included in the model to adjust for its effect on efficiency. For this variable, we used data on the ratio of the current account balance to transfers to other accounts in the FY2019 LPEY (24).Subsidies percentage was calculated by dividing the number of government subsidies by the current account balance. Previous studies have found that high levels of financial subsidy from the government lead hospital managers to invest in useless equipment regardless of demand, producing inefficiency (38). This variable was used as an adjustment variable to exclude the effect of this factor. The variable was obtained from the FY2019 LPEY (24).This variable represents the average time between admission and discharge. Previous studies have shown that longer average lengths of stay result in lower bed occupancy and less efficiency 2 of the municipality where the hospital is located. Previous studies showed that high population density and the associated need for a variety of medical care might increase the demand for medical services and result in a greater variety of medical services in PHs, thus increasing the operational efficiency of PHs (39). This variable was adopted to adjust for the effects of population density on efficiency. Data from MIC’s 2015 census, the most recent census before 2019, were used to compute this variable (40).The population density of the municipality variable is the population per 1,000 kmFirst, summary statistics were calculated to investigate the dependent, independent, and adjustment variables. The Mann-Whitney U test was used to assess the continuous variables, and the chi-square test was used for categorical variables to investigate whether there was a significant difference between the values of the high-collaboration group and the low-collaboration group for the collected variables.Next, for each combination, a simple linear regression model was used to conduct univariate analysis. The dependent variable was the technical inefficiency value and the independent variables were dummy variables based on the RR or variables obtained as adjustment variables.(41). A two-tailed significance level of 5% was used for analysis, conducted using STATA 14.0 .Finally, a multivariable linear regression model was used for a multivariate analysis using the technical inefficiency value as the dependent variable, RR as the independent variable, and a variable found to be significant when the significance level of the univariate analysis was P < 0.1 as adjustment variable. A logarithmic transformation was performed if the Shapiro-Wilk test did not normally distribute the adjustment variables. Furthermore, in both the multivariate and univariate analyses, the dependent variable drew on censored data; hence, the Tobit model was used in line with previous studies Because all data in this study were publicly available, the application for ethical approval was waived.There were 693 PHs listed in the FY2019 LPYE that submitted DPC data and responded to the FY2019 Hospital Bed Function Report. After applying the exclusion criteria, 254 facilities were excluded. Moreover, assuming that the missing data occurred randomly, 37 facilities with missing data in one or more variables were excluded from the analysis. Ultimately, 402 PHs were included in the analysis, as shown in The characteristics of the hospitals subjected to analysis are shown in In this retrospective cohort study in Japan, using DEA, we observed a significant relationship between the DOC with NHs and the operational efficiency of PHs, even after adjusting for the factors suggested by previous studies as possible influences on the operational efficiency of PHs. In other words, our results suggest that increased percentages of referred patients and increased degrees of collaboration with NHs may improve management efficiency in PHs.(19). Similar studies have been conducted in other countries; for example, a study that explored the factors determining the efficiency of PHs in Uganda found that bed utilization and the number of beds affected efficiency scores (42). Furthermore, a study that examined the impact of the transfer of PHs in Germany to private operators on management efficiency found that the transfer to the private sector resulted in significantly more efficient management (43). However, as far as we know, in Japan and elsewhere, few studies have investigated the relationship between the DOC with NHs and management efficiency in PHs.To the best of our knowledge, this is the first study to investigate whether collaboration with NHs affects management efficiency in PHs. Although the results may not be universally applicable due to differences in healthcare delivery systems and institutions among countries and regions, many studies have investigated factors affecting the management efficiency of PHs in Japan and other countries. In Japan, one study concluded that the hospital’s region affects the management efficiency of PHs and the operational efficiency of their dispensing departments (37). In this study, hospitals with a higher ratio of subsidies to revenue had significantly lower values for management efficiency. Moreover, as with previous studies, the regional location of the hospital had a significant effect on operating efficiency (19). However, unlike these studies, we conclude that the average length of stay, a factor found to most affect efficiency in our study, may not have had a significant impact (38). We speculate this is mostly because there was little difference in the average length of stay among the facilities in our study. The target was hospitals had adopted or were planning to adopt the DPC system, designed to limit profitability as the number of days spent in the hospital increases.The results herein are in line with the findings of previous work in that the ratio of subsidies to revenue has been found to affect management efficiency in PHs (39). We believe that this may be due to the free access provided by the Japanese healthcare system. Previous studies have concluded that high population densities and related needs for various medical care trigger the accelerated use of medical services. Existing hospitals in the area have increased their production of medical services to respond to these needs, resulting in higher management efficiency. However, even if a wide range of demands for medical services occurs in a densely populated area, if this principle of free access exists, the place to receive medical services may fall outside the area where the demand occurs. If this happens, hospitals in the region where the demand occurs need not increase their production of medical services, and productivity will not increase. Therefore, the relationship between location in high population density areas and efficiency, shown in previous studies, did not hold because the demand for medical services generated in high population density areas was then met in other areas. The supply of medical services in high population density areas did not change due to the existence of the free access system.Further, population density, which showed a significant relationship to efficiency in a previous study conducted in a PH in Saudi Arabia, was not found to be significantly associated with efficiency Our study has important implications for future policy considerations regarding PHs in Japan. Around 92% of Japanese PHs have an RR lower than 80%. Increasing this rate, even if only slightly, and increasing the level of cooperation between NHs may increase the management efficiency of PHs. To improve management efficiency, making large-scale changes, such as investing in new medical equipment or changing operating forms of operation, is inessential; instead, management can be improved by strengthening cooperation with similar facilities in the neighboring areas. Furthermore, according to the results of the multivariate analysis, a decrease in the ratio of subsidies to revenues may also create improved management efficiency in PHs.It is important to investigate whether other indicators of the DOC with other medical institutions affect management efficiency in PHs. Some potential indicators would include the reverse RR, or the percentage of first-time patients referred to other appropriate medical institutions due to their disease status; the number of patients using the community collaborative clinical path developed to create medical treatment plans for multiple facilities within the same region, from acute care hospitals to recovery hospitals, and to share them among all medical institutions providing treatment; the number of collaborating doctors; and the amount of expensive medical equipment shared with other institutions. An important tool for hospital managers to check the management efficiency of their hospitals could be created if the relationship between these variables and management efficiency could be clarified.(44). Future research should verify these detailed mechanisms after an empirical analysis of how resources, such as material costs and the number of staff, can be input to provide medical services and how the services have changed due to functional differentiation.We expected higher efficiency values through functional differentiation and specialization in medical services, exploiting comparative advantage through collaboration with NHs. A field of comparative advantage is one where productivity is relatively high within an entity, and specializing in this field can increase productivity (45). In another study, which investigated the management efficiency of PHs by province―defining each DMU as a province―the inputs were the total number of medical personnel, the total number of hospital beds, and number of PHs in the province. The outputs were the number of outpatients and inpatients and the occupancy rate of the beds (46).There are several limitations of this study. First, the definition of efficiency value may change the results. In this study, the inputs for calculating efficiency values were defined as the number of doctors, nurses, and other medical professionals, total hospital beds, and material costs. The outputs were defined as the daily number of inpatients. However, an exploratory study of the factors that determine the management efficiency of Palestinian PHs set the outputs to the total number of inpatient days per year, the number of outpatients per year, and the number of emergency patients received, while the inputs were the number of beds, doctors, and other staff Second, we ignored patients’ images of the hospitals. While calculating efficiency values and in univariate and multivariate analyses, the patient profile of each hospital was considered to be the same. In general, hospitals at smaller scales tend to treat relatively easier cases; thus, fewer resources are needed to treat one patient. Therefore, efficiency values may have been overestimated at smaller relative to larger hospitals.Third, we may have missed some unexpected confounders. We determined the confounding factors for multivariate analysis based on an extensive review of the existing literature, but it is possible that we did not cover all of them. If such factors are present and considered in the analysis, the results of this study would change.(47). In other words, active collaboration and an increase in RR may not be equivalent for small- and medium-sized hospitals. We may have underestimated the DOC in small hospitals.Fourth, for small-sized PHs, RR may not accurately reflect the DOC with surrounding hospitals. This is because some small-sized hospitals provide general practitioner medical care, and in such cases if they actively collaborate with NHs, the aforementioned reverse RR will increase The fifth limitation is that RR may be an intermediate factor. In other words, environmental factors, such as location, may have an impact on RR. Even if RR is an intermediate factor, we believe that this study is very meaningful in clarifying the mechanism through which environmental factors affect the management efficiency of PHs.As a result of analyzing the relationship between the efficiency value calculated using DEA and the percentage of referred patients in Japan, which indicates the DOC with NHs in PHs, we show that the higher the percentage of referred patients. The higher the DOC is, the higher the efficiency score, to a significant degree. This result provides important evidence for planning policies to improve the business condition of PHs, which has become an important issue in Japanese society in recent years.Dr. Tanimoto reports personal fees from Medical Network Systems, MNES Inc., and Bionics Co., Ltd., outside the submitted work.Motoi Miura: conception of the study design, analysis of the data, interpretation of the analysis results, draft of the article, and final approval of the article; Tetsuya Tanimoto: critical revision of the article about the interpretation of analysis results and final approval of the article; Satoshi Miyata: analysis and interpretation of the data and final approval of the article; Masayasu Murakami: critical revision of the article about the interpretation of analysis results and final approval of the article; and Yoshinori Nakata: conception of the study design, critical revision of the article about the interpretation of analysis results and final approval of the article.Because all data in the present study comprised publicly available data, the ethical approval application was waived.Supplementary Material 1Click here for additional data file.Supplementary figure 1Click here for additional data file.Supplementary figure 2Click here for additional data file.


Branding has been a key factor for the software houses, mainly customers’ expectations for a predicted product and real-time experience. The identity and knowledge of brands set a certain set of expectations in the mind of the consumers and the organization’s employees. This study mainly investigates the effects of brand identity and brand knowledge on the employee-based brand equity (EBBE) and consumer-based brand equity (CBBE). Further, it examined the mediating role of EBBE among these variables. To complete this empirical study, a quantitative survey was conducted using a 30-item survey method to collect data from 243 respondents from China’s software houses. The participants were selected based on purposive sampling. Results show that brand identity and brand knowledge are the main constituents of EBBE, which significantly predicts the CBBE. The study highlights the importance of employees in building overall brand equity. Training and brand promotion activities would help the organizations build a brand identity that positively contributes to the EBBE. Further, brand identity and brand knowledge are needed to improve the human capital, engagement of employees, and their emotional affiliations with the organizations, ultimately making the brand equity of employees stronger. Branding has become an important aspect for software companies, particularly in terms of consumer expectations for an anticipated product and also real-time experience. The identity and knowledge of brands create a set of expectations in the customer’s mind and also workers of the firm. The competition among service brands has intensified. The problem of gaining and maintaining customers is made more difficult by the increasingly fragmented market caused by growing consumer knowledge and experience . Brand lvia organic interactions between the different components that constitute a brand. Understanding these relationships within the integrated frameworks of CBBE is critical for measuring branding success and effectively managing the brand. In recent years, the idea of CBBE has gained traction among academics. CBBE and its many characteristics are significant for businesses because of its impact on customer’s satisfaction, perceived benefits, and loyalty . CBBE, or the overall instrumental value that customers give to a specific brand, is important in assessing long-term brand value . Because loyalty . Quality loyalty .Customer-based brand equity is viewed as a multidimensional concept in brand management, despite debates about whether the ideas underpinning brand awareness development can be applied directly to brands like hotels, food, and beverage enterprises, where the service aspect is dominating . BecauseAs a result, brand love may be seen as a catalyst for brand loyalty, which influences customers’ behavioral intentions and attitudes and their steadfast allegiance to the brand . The previa strong marketing and human resource activities. EBBE is the value that a brand adds to a company by influencing the attitudes and behaviors of its workers  . Second,H3. Brand identification has an association with EBBEH4. Brand identification has an association with CBBEThe entire foundation for understanding CBBE is the idea of brand knowledge . SimilarThe idea of EBBE has recently been a hot issue in the realm of brand equity literature and theories . The EEBvia brand knowledge and brand identification  modeling. Through SEM analysis, the data had been analyzed in two steps. The first step checks the validity and reliability of the data obtained, whereas in the second step, the hypotheses developed in the study have been checked to identify whether the data support or does not support them. PLS-SEM analysis is robust with model estimation, especially for theory development. This study has used this statistical tool as it has proposed certain hypothesis forming the basis for the theory.The common method variance, in the study, has been checked with Harman’s one-factor test using SPSS 26. Initially, the biases in the responses have been checked with Harman’s one-factor test since the responses obtained through convenience sampling can create biasness. This can be considered as under control if the survey method has been ensured for the understanding of the respondents p-Values, R-square, and f-square statistics have been employed.This study has employed the PLS-SEM through Smart-PLS and SPSS software for analyzing the data. This is a statistical tool that analyzes the complex causal effects in the form of path models. It provides less contradiction among the results than regression analysis . QuantitIn this study, the questionnaires were used as the survey instrument. It consisted of 30 items in total relating to each variable of the study. There were four variables, which include two independent variables, one mediating variable, and one dependent variable. The acceptable value for Cronbach’s alpha is reported as 0.7 in the literature . All theThe scale for the first independent variable of brand knowledge consisted of five items, and it has been adapted from the study of The other independent variable (brand identity) consisted of eight items that have been adapted from the study of The mediating variable of EBBE consists of thirteen items that have been adapted from The CBBE, the dependent variable, consists of four items that were also adapted from the study of The demographic information of the respondents had been collected from the last part of the questionnaire that consisted of four categories, namely, gender, age, education, and nature of the job. The question on gender was categorized into two main streams, men and women. Among the respondents, 53.9% were men and 46.1% were women. Of the age categories, the highest numbers of respondents were between the ages of 21–25 years, followed by the category of 26–30 years, and the least number of respondents fell under the category of 31 and above. Considering the education factor of the respondents, around 15% of the respondents had Ph.D. or other diplomas or certifications, whereas the rest of the respondents were bachelor’s and master’s degrees holders, that is, 42% and 43%, respectively. Regarding the nature of the job of the respondents, 37.5% of respondents were software developers, 48.55% were web developers whereas the rest of them were from the human resource department. The results of the demographic profile can be seen in In the first stage, measurement model outcomes are used for checking the validities, reliabilities, average variance extracted (AVE), and factor loads for the initial screening to check whether the data are fit for hypothesis testing or not. For reliability of the data, Cronbach’s alpha and composite reliabilities are used whereas for validities, heterotrait–monotrait (HTMT) ratios and Fornell and Larcker criterion have been used. The algorithm obtained for the measurement model from the Smart-PLS software has been given in The results obtained for factor loadings and AVE have been reported in The other measures for validity used in this study are the HTMT ratio and Fornell and Larcker criterion . The accR-square, also known as the coefficient of determination, indicates the fitness of the proposed model by explaining the variance explained by each endogenous variable in the context of regression analysis. The R-square values obtained for the dependent variables in this study are all good. The variance of the variable EBBE has been 59.9% explained by the independent variables brand identity and brand knowledge. Similarly, the CBBE has been 31% explained by EBBE. Q-square shows the predictive relevance if the model shows predictive relevancy or not (the endogenous variables indicate any predictive relevance). A value of Q-square above zero shows that variables and the model possess predictive relevance. The endogenous variables in this study shows good predictive relevance with CBBE that shows 0.436 and EBBE that shows 0.373 values, thus meeting the criteria for predictive relevance of the model. The outer variance inflation factor values have been mentioned in p-values. The results obtained from the structural model have been reported in p < 0.05. The third hypothesis showed a significant impact of brand identity on the EBBE , thus accepting H3 whereas fourth direct effect (H4) has been rejected, which indicates no significant impact of brand identity on the CBBE.The analysis obtained from Smart-PLS software gives the output for the results of the structural model. Based on the results obtained from the structural model, the decision for acceptance or rejection is taken considering the t-statistics and 5) is regarding the mediation of EBBE between brand knowledge and CBBE, which has been accepted at p < 0.05  and shows partial mediation (VAF = 41%) as the obtained values lie between 0.20 and 0.80. Similarly, the second mediation of the study has also been accepted, which shows a significant mediating effect of EBBE between the brand identification and CBBE , which shows full mediation, VAF > 0.80.This research has been conducted to evaluate the directional relationship of brand knowledge and brand identification with CBBE. Moreover, the indirect role of EBBE was also evaluated among brand knowledge, brand identification, and CBBE. It is understood that EBBE assists workers in developing a link between their organization’s perceived financial cost and advantages and how it will influence them in the future. Whether there is an EBBE among the employees, the organization can profit from it in a variety of ways. This study demonstrated that software houses may effectively establish their CBBE with the support of a strong brand knowledge among the industry and stakeholders by taking use of the consumer-provided facilities. Similarly, good brand knowledge among software engineers inside software businesses may assist in enhancing their EBBE. Internally (EBBE) and externally (CBBE) brand equity is equally vital for the success of any brand in the IT business, which requires a combination of experience, abilities, and implementation.This study empirically tested the mediating effect of EBBE on CBBE based on two critical variables to understand how brand identification and brand knowledge could contribute toward CBBE. These findings indicated that the first two hypotheses were accepted, which suggests that brand knowledge had a substantial influence on CBBE along with having a significant impact on EBBE. Basically, employees play a critical role in establishing total brand equity. Employees’ brand knowledge aids in their comprehension of the brand, which in turn aids in the reinforcement of their brand equity. Similar kinds of results have been reported in the past which suggests that knowledge or information about the brands among employees and consumers has a positive contribution toward creating equity of the brands whether it be employee-based or consumer-based. This is due to the fact that brand knowledge has such a strong impact on people’s thinking, customers may recollect their memories based on it .Employee brand internalization guarantees that employees have a thorough understanding of brands and a strong commitment to them, which reflects cognitive and emotive pathways to EBBE . EmployeThe possible reason behind developing such internal organizational equity among employees is the fact that if employees are well equipped with the information about brand and brand imagery or the conception of the brand, then it develops a stronger sense of ownership among themselves. This could lead to a better EBBE, whereas the identification of brands by the consumers did not have a significant impact on CBBE due to the possible reasoning that employees are more concerned with their brands compared to the loyal consumers with brands which develops into a non-significant type of interaction between brand identification and CBBE. Some contrasting results are obtained in the previous studies, which indicate that brand identification could have a positive impact on developing CBBE . The indAs reported in many studies that brand knowledge has an association with EBBE as an internal protocol, it was evident that EBBE could further strengthen the relationship of brand knowledge with CBBE. It is only possible due to the upholding ability of knowledge about the brand by the employees which helps in strengthening the brand equity at the consumer level. Even though the term brand knowledge refers to customers, the idea is also applicable to employees of software houses because brand awareness is the cornerstone for building brand equity. Likewise, employees who are familiar with the brand are more likely to grasp their responsibilities and execute the brand promise . The dirEmployee-based brand equity helps the employees to develop a relationship between the perceived costs and benefits of their organization and how it will affect them in the future. If there exists an EBBE among the employees, the organizations can reap certain benefits from it. (i) First of all, this study provides evidence that software houses can successfully build their CBBE with the help of a strong brand knowledge among the industry and stakeholders by taking advantage of the facilities provided to the consumers. (ii) Similarly, within the software houses, adequate brand knowledge among the software engineers can help strengthen their EBBE providing attractive compensations for their services.(iii) Moreover, the management of other organizations can use this empirical evidence given by this study that the availability of brand knowledge among the employees and consumers can add value in the intensification of EBBE and CBBE, respectively. (iv) Turnover has been a challenge for the software industry which can affect the EBBE and consequently the CBBE. To cope with this challenge, continuous investment in the training, brand identity, and brand knowledge is needed so to improve the human capital, engagement of employees, and their emotional affiliations, which would ultimately make the brand equity of employees stronger. Training and brand promotion activities would help the organizations in building a brand identity that positively contributes to the EBBE.This study contributes in theory as it has found that EBBE’s role as a mediator between the brand knowledge, brand identification, and CBBE conveys the value of the brand from the organization to the final consumers, which leads to CBBE. Despite contributions to the literature, there are few limitations in the study that open new avenues for future research. First of all, the sample size is relatively smaller which is 243, and the results can be checked for generalizability with bigger sample size. Second, the software houses’ employees have been taken as the sample in this study; it is highly encouraged to conduct this study in other fields of professions, which considers different cultures for comparison and contrast to this study. Finally, some possible variables are expected to moderate the relationship between EBBE and CBBE ; hence, future studies should consider these variables as the moderators and check their effects on this kind of relationships.In the IT industry which needs a blend of expertise, skills, and execution, both internal (EBBE) and external (CBBE) brand equities are equally important for the success of any organization. This study has investigated the two key variables, that is, brand identity and brand knowledge to understand the mechanism of how these independent variables influence the EBBE and CBBE. The results of the study have indicated that brand identity positively and significantly affects the EBBE; however, it could not find any effect on the CBBE. Furthermore, brand knowledge has been found as a significant predictor of EBBE and CBBE. In addition, EBBE has been found as a significant mediator among the independent variables of brand identity and CBBE. Among the second relationship of the study between brand knowledge and CBBE, the EBBE has been found to partially mediate the relationship.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The studies that involve human participants were reviewed and approved by the Liaoning University, China. The patients or participants provided their written informed consent to participate in this study. The study was conducted in accordance with the Declaration of Helsinki.ZH conceived, designed the concept, collected the data, wrote the manuscript, and read and agreed to the published version of the manuscript.The author declares 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.


Successful recruitment of participants into clinical research has always been challenging and is affected by many factors. This systematic review aimed to explore the perceptions and attitudes as well as identify the factors affecting the participation in clinical research among the Eastern Mediterranean Regional Office countries’ population.A systematic search of the literature was conducted to explore attitudes or perceptions of the general public or patients towards participation in clinical research. PubMed, Pro-Quest Central, World Health Organizations Index Medicus for the Eastern Mediterranean Region, and Google Scholar were searched. Studies were considered eligible for inclusion if they presented primary data and were conducted in one of the Eastern Mediterranean Regional Office countries. A data extraction sheet was used to record the following: year, country, aim, population, sample size, study design, data collection, and setting. The identified factors from the included studies were categorized into motivators and barriers.In total, 23 original research articles were identified that addressed perceptions or attitudes towards clinical research participation. Six main motivators and barriers of research participation among patients, the general public, and patient family members were identified. The most common cited motivators included personal benefits to the individual, altruism and the desire to help others, the research process, the influence of the physician, family encouragement, and religion. Concerns regarding safety, confidentiality, and other factors in addition to the research process, lack of trust in healthcare providers or healthcare system, lack of interest in research and no perceived personal benefit, religious concerns, and family/cultural concerns were the most cited barriers to participation.The identified motivators and barriers are essential to tackle during clinical research planning among the population of Eastern Mediterranean Regional Office countries. Further research is needed to assess the attitudes and perceptions of individuals approached to participate in trials. Such evidence is made available through the different types of research, including interventional and observational studies. This might result in failing to meet recruitment targets, and sometimes, failure or termination of trials. The literature shows that >50% of oncology trials were terminated prematurely due to a low recruitment rate.,5Successful recruitment and retention of participants into clinical research have always presented as a challenge since the general public and patients might lack the awareness about the importance of clinical research for the advancement in healthcare and many other influencing factors.,7The World Health Organization (WHO) Eastern Mediterranean Region Office (EMRO) comprises a diverse population from 22 countries. This population shares numerous similar demographics, religious, and cultural characteristics, yet diverse socioeconomic, racial, and ethnic backgrounds. Additionally, this region is changing population size and health-related characteristics. Hence, the need for expanding clinical research is crucial to face the challenges relating to healthcare provision. However, participation in clinical research in the EMRO countries is yet underdeveloped. A study by Nair et al showed that the participants from the region countries accounts for <1% of the global research participants’ size and 0.5% of the total global sites of clinical trial.In order to improve participation in clinical research, there is a need to explore the perceptions and attitudes of the general public to tackle their concerns when intending to recruit them to clinical research. Hence, this systematic review aimed to explore the perceptions and attitudes and identify the factors affecting the participation in clinical research among the EMRO countries population. The following databases were searched: PubMed, Pro-Quest Central, World Health Organizations Index Medicus for the Eastern Mediterranean Region (IMEMR), and Google Scholar. The databases were searched up to October 2021 using the following MeSH terms and keywords that were agreed upon by the authors: “research” AND “attitude” AND “involvement” OR “participation” AND the individual countries of the Eastern Mediterranean Region, a total of 22 countries . As the search terms were broad, the search yielded many studies. Hence, we limited it to studies conducted in humans and published in English. Additionally, a manual search of the references list of the identified relevant articles was done to supplement the search.This review is registered on PROSPERO International Prospective Register of Systematic Reviews (registration number CRD42020195763). A comprehensive systematic literature search was conducted and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.Studies were included if they met the following criteria: presented original and primary research; explored attitudes or perceptions towards participation in clinical research among patients or the general public; conducted in one of the 22 countries of the EMRO region; and using a recognized method for data collections, such as questionnaire and structured interviews.Studies were excluded if they: did not meet all inclusion criteria or did not present original/primary research, such as reviews. and Critical Appraisal Skills Programme (CASP) for qualitative studies, aiming to ensure the quality of the included studies. In the case of disagreement, it was resolved through discussion among the authors. A coding template was developed to extract the data and categorize it into motivators and barriers to research participation among patients and the general public in the countries of the EMRO region.The titles of the articles retrieved by the initial search Fig.  were indThe systematic literature search across the databases yielded a total of 2041 studies, in addition to 9 articles that were identified through the supplemental search of the bibliographies of relevant articles  of the studies, clinical research in the EMRO region was motivated by the desire to help other patients and improve society and its healthcare system. This is driven by a sense of duty and commitment to the country, community, and volunteerism.,16,24 Additionally, participation in research was positively influenced by the adequacy of information provided to participants regarding the disease/condition being investigated, the importance of the research and its impact on patient’s health outcomes, the procedures being taken as part of the research, the benefits and potential hazards to expect, and the plan of monitoring the patients during their participation period.,27,31 Allowing the participants time to think before enrolling them in research motivated their participation and adequate explanation on their rights to sign an informed consent emphasizing that they will not be subjected to research without their approval and signature of a consent form. In addition to that, they preferred to learn that withdrawal from research is allowed and that the researchers have obtained the necessary governmental approvals.,27,30,32 Informing participants about vital confidentiality and privacy measures throughout the study was an essential component in enrolling in research.,15,27The research process and design were the third common factors influencing the decision of participation in research, which was reported in 12 (52%) of the included studies. Participants were more likely to consent to participate in observational studies in which data are collected through an interview, survey or questionnaire; and in studies that include minimally invasive procedures such as blood sample collection.,26,28,30 Other factors played a role in motivating research participation, such as family encouragement, having a family member around during recruitment, religious permission of research participation, and knowing that God will reward them for this good deed.,21,25–28Interestingly, participants in 8 (35%) of the studies reported that they were more likely to enroll in research if this was recommended by their physician, if they had a chance to consult them, or if their physician approached them during the initial recruitment process. Others were motivated by the fear of jeopardizing the relationship with their physicians and healthcare providers or receiving suboptimal medical care if they refused research participation.–27,30–33 Moreover, participants’ fear of discovering they have a disease when they enroll in the study was among the identified barriers.The main barriers to research participation include fear, the research process, trust, lack of interest or personal benefit, religious concerns, and family or cultural concerns Table . In addi,18,20–33The research process played a role and was one of the main barriers in 18 (78%) of the 23 studies. Some study designs were conceived demoralizing by research participants for the same safety concerns, for example, drug clinical trials. Additionally, studies that included randomization and blinding were considered alienating. Time was another main barrier to participation and concerns regarding the logistical issues such as multiple visits and the need for transportation or being re-contacted by the researchers.–28,30–33In 13 (57%) studies, views reflecting lack of trust in the healthcare system and providers were observed. Some patients believed that their left-over specimens and samples  were collected for research purposes without their consent, which demotivated their participation. Others believed that the samples they provide for research might be exploited or stored indefinitely, and hence they prefer not to participate. Furthermore, some believed that research, especially research conducted in EMRO countries, lacks regulatory supervision, and they believed it is only of interest to clinicians as it is crucial for their career advancement.,26,27,33 Last, religious and cultural concerns had a role in discouraging research participation, as observed in a few of the included studies.,20,21,27Additionally, a trend of lack of interest in research participation due to a stable health condition or lack of personal benefit was observed.In this review, we identified 6 main motivators and barriers to research participation among the population of the EMRO region. This population is unique in its diversity as it includes 22 countries with different ethnic and racial backgrounds and economic statuses. However, this complex population shares enormous similarities due to shared religious and cultural characteristics. Interestingly, some identified factors were interpreted as both motivators and barriers to research participation.,16,24 They were mainly resistant to participating in drug trials, including invasive procedures such as tissue biopsy.,24,31,32An essential factor that was perceived as a motivator and a barrier is the study design, including the method used for data collection. Participants were most likely to enroll in studies of observational nature, such as questionnaires, and in studies that include minimally invasive procedures. Resistance to participate in such trials can be attributed to multiple factors: fear and safety concerns, lack of awareness on concepts of clinical research and its regulations, and mistrust in healthcare providers and in the system. This was confirmed by a global survey about attitudes and experiences of the public toward participation in clinical research. The study included more than twelve thousand individuals, representing 68 countries from North America, South America, Europe, Asia Pacific, and Africa. This study found that the top perceived risk to research participants included the fear of adverse drug events and risks to overall health. Additionally, while >80% of the respondents believed in the importance of research, only 30% were willing to participate.This was opposed by study findings that reported a high proportion of patients considered participation in trials involving repeat biopsies. However, the study included patients with gastrointestinal malignancies or lymphoma only, and their views on biopsies may differ from other patients.The consenting process is another factor that was perceived as critical by many participants; however, some found the written informed consent complex enough to hinder the participation. Furthermore, we found that some participants believed that they were recruited into research without their knowledge and consent. This was consistent with the findings from a study conducted in Canada. The authors found that about 30% of their study participants were uncertain or believed that clinical research participants are rarely or never informed of their participation.The reimbursement for research participation was another area of controversy. It was encouraging to some, offensive or unfamiliar to others, and some found it scary. “So, all parents will be scared, especially because the vaccine is provided for free when we know it is expensive! When we come here, they give us money for our transportation! This is scary, you know!!” a mother stated regarding her children’s participation in clinical research.In contrast, a qualitative study by Breitkopf et al involved thirty women from Texas, United States of America, who were interviewed following their participation in a clinical trial to explore their perceptions regarding reimbursement in clinical research. The participants perceived it as a positive addition that would encourage participation. They also believed that the time spent, the inconvenience and sensitivity of the research topic and the possible hazards reimbursement amount should be reflected on the monetary amount being reimbursed. It was not perceived that offering monetary compensation is likely to coerce participation in research if the individual believed the research to be unacceptable or of high associated risks.Religion was a motivator for participation in research for those who viewed their participation as essential to advance science and help others and for those who perceived it as a means of pleasing God through a good deed act. On the other hand, some were doubtful that their samples might be used in research that is not permitted by religion. Another study conducted in the United States assessing the attitudes of Muslim immigrant women toward cervical cancer screening showed that many participating women expressed their resistance to practices that challenge their religious and cultural values.Our review also showed that effective communication with potential participants was an important factor in encouraging their enrollment in clinical research. This includes providing adequate information about the importance of research and its impact on patient’s health outcomes, research procedures, benefits and potential hazards, and the participants’ rights throughout the process. This is likewise shown in a study conducted in California, United States of America, which evaluated awareness level and willingness to participate in cancer clinical trials among 1188 patients and their families. They reported a significant positive correlation between awareness and willingness to participate in the trials. In Burns et al study, it was reported that only about 70% of participants were adequately informed about the risks and benefits of study.Despite that, effective communication was not always practiced to its best. There was an inconsistent across studies regarding the provided information to participants. In a study conducted in the United Kingdom and included 486 cancer patients, most of the participants (95%) reported that they were provided with enough information about the trial.Evaluating the factors influencing the perception and attitude towards participation in clinical research is crucial for the research in the region. Nevertheless, this could be challenging to be assessed precisely. In our review, there are several important strengths and limitations. This review comprehensively addressed the factors affecting participation in clinical research from studies conducted in the region. Among the limitations is the quality of data due to the observational cross-sectional design of the included studies.Additionally, all the studies depended on self-reporting methods, which might bias the results depending on the participant’s ability to recall or the desire to share what they believe they prefer to hear with the researchers. The majority of the included studies were based on approaching the participants giving a hypothetical scenario asking about their perceptions of participation in clinical research if they were contacted to be enrolled. This creates a gap between the hypothesis and the real world. However, these studies elucidate the factors that motivate or discourage participation in clinical research.The included studies identified the motivators and barriers to clinical research participation among the patients and the general public in the EMRO countries. The identified factors are essential to consider when planning for future research. As they explain what motivates participation and explore some of the fears of the target population, these factors are important to address during the planning stage. There might be a gap between theory and practice due to the hypothetical design of most studies included in this review. Hence, future research to assess the perceptions and attitudes of patients who are actually enrolled in clinical research or those who are rejected to participate is further needed. Moreover, it is important to investigate the association of these factors and the likelihood of individuals participation in clinical research.All authors of this review have participated to this article with different roles. M.A. provided the idea for the article and prepared the review proposal. B.I. provided supervision and guidance for the review concept, proposal, planning, and execution. I.A. and M.A. performed the literature search, data analysis, and initial draft. T.S. validated the review findings through a final assessment discussion with M.A. regarding the search strategy, selection criteria, data extraction and analysis, and quality assessment. M.I.B., I.A., and M.A. prepared the final manuscript version through critical review.