The Job Demands-Resources (JD-R) model is an integrative theoretical framework for monitoring workplaces with the aim to increase job engagement and prevent burnout. This framework is of great interest since the management of job resources and demands can negatively affect employees, especially in organisational contexts characterised by high job demands. This study uses the job demands-resources model to investigate the relationships between organisational climate, role stress, and employee well-being (burnout and job satisfaction) in public organisations. This is a descriptive, cross-sectional study. The research participants are 442 public employees. A structural equation model was developed . These confirm that organisational climate is correlated with role stress (−0.594), job satisfaction (0.746), and burnout (−0.408), while role stress is correlated with burnout (0.953) and job satisfaction (−0.685). Finally, there is a correlation between burnout and job satisfaction that is negative and significant (−0.664). The study confirms that a positive organisational climate could lead to less stressed and burned-out workers and, at the same time, to more satisfied employees with improved well-being. Reforms in the public sector have been a constant of the last 20 years, and there has been a particular focus on developing human factors . These cHuman factors are the key to improving public services. Bakker  states tThe emergence in the late twentieth century of the so-called ‘Positive Psychology’, which focuses on the positive side of people , was cruThe Job Demands-Resources (JD-R)  model isThe job resources were defined as ‘those physical, psychological, social, or organisational aspects of the job that are either/or functional in achieving work goals; reduce job demands and the associated physiological and psychological costs; stimulate personal growth and development’ The JD-R model assumes that factors associated with organisations affect employees in two ways: A process of health deterioration, and a motivational process. In the first process, job demands predict the occurrence of burnout, which is associated with negative effects for the organisation and its employees. The motivational process links the existence of labour resources with the emergence of employee engagement, which leads to positive results for both employees and organisations .One of the main job resources is the organisational climate . OrganisRole stress is the most studied job demand involving a natural phenomenon in organisations. It can be defined as a set of expectations, duties and obligations, applied to employees, coming from those who can influence the employees and help to define their roles . It negaIn the study of the relationship between organisational climate and role stress , the buffering hypothesis prevails. It suggests that the impact of job demands on employee well-being is weaker when they have a high level of resources . The relJob satisfaction is certainly the most researched topic in the history of industrial and organisational psychology . The mosThe influence of job resources  on job satisfaction, as an indicator of employee well-being, occurs through a motivational process . Job resBurnout is defined as ‘a syndrome of emotional exhaustion, depersonalization, and reduced personal accomplishment that can occur among individuals who work with other people’ . There iThe relationship between job demands and burnout, as an indicator of employee well-being, occurs through the health deterioration process  and follThe organisational climate can affect employees’ well-being, directly influencing burnout. Under this hypothesis, Winnubst  carried Also, the study of the relationship between role stress and job satisfaction is of major importance. Recently, several studies have presented evidence of this relationship in different country, industry, and labour contexts ,41.The JD-R model also provides a relationship between the consequences of job demands and those of job resources. A recent longitudinal study by Figueiredo-Ferraz et al. , who focOther findings explained that—relative to private sector employees—public servants became the most engaged by intrinsic factors including work-related resources . Work enThe aim of this study is to analyse the relationship between organisational climate, role stress, burnout, and job satisfaction in public employees. For this purpose, our hypotheses are consistent with previous studies:Organisational climate will show a significant and negative reciprocal relationship with role stress (hypothesis 1) and a positive reciprocal relationship with job satisfaction (hypothesis 2). Also, role stress will show a significant and positive reciprocal relationship with burnout (hypothesis 3). Furthermore, organisational climate will show a significant and negative reciprocal relationship with burnout (hypothesis 4) and role stress will show a significant and negative reciprocal relationship with job satisfaction (hypothesis 5). Finally, job satisfaction will have a reciprocal relationship, both significant and negative, with burnout (hypothesis 6).Data were collected through online questionnaires in this cross-sectional study. Most participants in the chosen institution completed the questionnaire, for a total of 442 out of 475 public employees. All participants gave written informed consent in accordance with the Declaration of Helsinki. The Ethical Review Committee at the University of Almería (Spain) approved the study (UALBIO2018/027).In terms of gender, 50.7% of participants were women and 49.3% men. For age, 5.7% of participants were under 36 years old 57.7% were between 36 and 45; 31.2% of them were between 46 and 55; and 5.4% were more than 55 years of age. As for educational level, 11.5% had no formal schooling, primary or secondary education; 25.8% had studied at high school; 61.1% were graduates; and 1.6% held a doctoral degree. In terms of labour status, 96.6% were civil servants and 3.4% were ordinary employees. Their positions at work were as follows: 86.4% were middle managers and workers and 13.6% were head managers. As for work hours, 392 of the participants (88.7 %) worked a morning shift and 50 (11.3%) worked an afternoon shift.A shortened version of the First Organisational Climate/Culture Unified Search 93 (FOCUS-93) questionnaire by Van Muijen et al.  was usedThis variable was measured using CSLPS-EAP/33 , which cThis was measured using an adapted version of the Maslasch Burnout Inventory , translaThis was measured using a questionnaire composed by Rizzo et al.  that wasIn order to verify the reliability of the dimensions, the internal consistency was assessed using Cronbach’s alpha coefficient  for eachStructural equation models were fitted using the diagonalised weighted least squares (DWLS)  or robusp > (p + 1)/2, where p is the number of parameters to be estimated by the structural equation. Therefore, dimensions where the number of items considered in the model was too low could not be fitted using this method. Thus, the method used for those dimensions was RML. Those dimensions were from two variables: Climate and job satisfaction [The DWLS method requires large data sets; specifically, the sample size should be larger than sfaction .The goodness of fit for the proposed models was measured using the Tucker-Lewis Index (TLI) and the Comparative Fit Index (CFI). For both, values greater than 0.9 indicate a good fit. Another measure used was the Root Mean Square Error of Approximation, (RMSEA) where values lower than 0.08 indicate a good model fit and the upper limit of the 90% confidence interval should be below the 0.1 cut-off value for a good model fit . The StaFirst, we performed a confirmatory analysis of the dimensions for each of the variables used in the study, and later we presented a structural equation model for testing the relations between variables.Cronbach’s alpha for climate was 0.95. The RMSEA and SRMR obtained in the confirmatory analysis for climate were 0.079  and 0.076, respectively, indicating an acceptable data fit.The estimated correlation for the dimension ranged from 0.824 between rules and innovation to 0.916 between goal orientation and innovation, indicating strong relationships between them. For rule dimension, item 7 had the lowest impact. Regarding the innovation dimension, items 8 and 28 had the lowest effects in the construct of the dimension. For the support and goal orientation dimension, all items had similar impacts on the constructs.For the job satisfaction variable, the value of Cronbach’s alpha was 0.91. The goodness of fit values of the model were as follows: RMSEA = 0.057  and SRMR = 0.048. In addition, the values for CFI and TLI were 0.913 and 0.913, respectively, showing a good fit.The estimated correlations between dimensions ranged from 0.319, between objects and means and conditions, to 0.826 between equipment and workload. The associations between intrinsic, firm, workload, autonomy, and objects were stronger than those between team retribution and conditions. Regarding the salary, autonomy and object dimensions, all items had similar impacts on their constructs. Within the environment/conditions and workload dimensions, the lower parameter estimated was associated with items 15 and 27.For role stress, the value of Cronbach’s alpha was 0.79. The RMSEA value was 0.034  and the SRMR value was 0.055. The values of CFI and TLI were 0.99 and 0.988, respectively, showing a good fit for the model. The correlations between the dimensions of the construct were positive, with a value of 0.167 for the dimensions of ambiguity and overload, and 0.508 for overload and conflict. Within the ambiguity dimension, the lower parameter estimate was associated with item 1; this item had a weaker impact on the dimension than the rest of them. Regarding the conflict dimension, item 7 had the weakest effect in the construct of the dimension. For the overload dimension, all items had a similar impact.For the burnout variable, Cronbach’s alpha was 0.80. The RMSEA was almost 0 , and the SRMR value was 0.038. The CFI and TLI values were both 1, indicating a perfect fit. The correlations between dimensions were positive, with a value of 0.16 for exhaustion and lack of personal accomplishment, and 0.459 for depersonalisation and exhaustion. Within the depersonalisation and lack of personal accomplishment dimensions, the lowest parameter estimated was associated with items 3 and 9; those items had a weaker impact on their respective dimensions than the rest of the items. For the exhaustion dimension, all items had a similar impact.The standardised estimates of the structural equation model testing the relations between all variables are presented in The aim of this work was to study the reciprocal relationships between a job resource , a job demand (role stress) and indicators of employee well-being (burnout and job satisfaction). The results confirmed that organisational climate is significantly and negatively linked to role stress (−0.594), which suggests that the existence of a positive climate would buffer role stress in workers.In the JD-R model, the direct relationships between demands (role stress) and labour resources  are not specified as positive or negative correlations. Bakker and Demerouti  considerIn this study, climate showed a significant and positive reciprocal influence on job satisfaction (0.746), confirming the motivational process of the JD-R model. Furthermore, previous studies showed that when employees perceive their organisational climate in a more positive way, they are more satisfied . Also, wThe results confirmed that job demands and resources could interact to positively or negatively affect well-being in two cross-linked relationships . On the Finally, the results confirmed that job satisfaction has a significant and negative relationship with burnout. In a recent longitudinal study, Figueiredo-Ferraz et al.  analysedThis study represents a step towards understanding the relationships between variables that affect the well-being of employees in public service. These results will be of great interest in the POP field as they will help to promote this viewpoint in the field of human resource management in public administration. The effects of job resources could enhance employees’ well-being, increasing satisfaction and preventing burnout .The results obtained in this study have important practical implications for managing the employees of public universities. A positive climate is key to enhancing and fostering the well-being of public employees, as the perception of a positive organisational climate leads to more satisfied employees. Such employees are less stressed and suffer from less burnout in their work, which should encourage those responsible for managing people to invest in creating comfortable and positive organisational climates. Such policies would not only help produce more positive results at work, but they would also enhance the development of work in a healthy environment. Furthermore, as was already mentioned when discussing the JD-R model, when a professional job is developed in a job environment characterised by the existence of role stressors, it will have negative effects on the health of employees. Therefore, it is important to establish policies in public administration that help employees have control over their demand level and increase their resources.However, the results of our study should be considered with the following limitations in mind. First, the results were obtained from self-reports and might be affected by common method variance. Second, the sample was very specific and limited to public employees in a Spanish context; thus, the results cannot be generalised to other types of organisation or public administration. Third, the design of the study had a cross-sectional nature, which prevented us from drawing conclusions about the temporal order of effects and causality relationships. To avoid such limitations, future research should utilise a longitudinal methodology within a multi-method approach .In our changing world, priority should be given to the study of how the well-being of employees in the public sector affects the execution of their duties. Also, the study of different mediating and moderating links in the relation between job demands, resources and well-being in the public context is important. Thus, a more inclusive approach should be taken to examining how work variables affect performance . It willThe study confirms that a positive organisational climate could lead to less stressed and burned-out workers and, at the same time, a higher role stress can lead to lower job satisfaction and, therefore, to worse employee well-being. Organisational climate showed a significant and positive influence on job satisfaction, confirming the motivational process of the JD-R model.


The purpose of this study was to investigate the relationship between anxiety proneness and aggressive behavior in adolescents.A quantitative, large scale cross-sectional study was conducted in Korea. The survey questionnaire included general health behavior and scales for assessing anxiety  and aggressive behavior  in adolescents.A total of 2432 students participated in the survey, and 1933 individuals completed the questionnaire, indicating a response rate of 79.5%. Based on RCMAS, 163 (8.4%) subjects were classified as the anxiety group. Aggressive behavior was significantly associated with higher anxiety scores. In particular, among four subdomains of aggression, anger and hostility had a stronger relationship with anxiety than did physical and verbal aggression. Multivariate analysis demonstrated that anxiety was independently associated with gender, age, headache, constipation, asthma, and aggression score. Adolescents with total aggression scores of 69 or higher showed a 9-fold  higher risk of anxiety compared to those with under 69.Aggression and anxiety are important aspects of mental health in adolescents. Our results demonstrated that higher risk of anxiety was associated with total aggression scores. In particular, indirect aggression (i.e. anger and hostility) was more closely associated with anxiety than direct aggression. Adolescence is a critical developmental period by which social, emotional, and physical changes to the body can build up negative self-perceptions . PreviouCumulative prevalence by age 16 is estimated to be 9.9% for adolescents meeting the diagnostic criteria for anxiety and 23% for behavioral disorders in the U.S . BehavioWhile aggression and anxiety have been studied separately as two distinct properties, researchers have begun to suspect that anxiety may be one of the key emotional underpinnings of childhood aggression and their link is not unidirectional. Several studies have reported the link between anxiety and aggression in childhood. It was revealed that reactively aggressive children at age six were significantly more anxious than their non-aggressive counterparts . Also, iAdolescence is a unique period in human development, with rapid physiological and psychological changes. Due to these changes, adolescents often face a number of crises and dilemmas, especially in the areas of mental and emotional health. Kim et al. revealed that Korean middle and high-school students experience high level of stress related to general studying demands and preparations for college admission that may lead to serious physical or psychological problems . ResearcAdolescent stress has been linked to negative mental health outcomes such as anxiety and depression . AnxietyTherefore, the purpose of this study was to examine the associations among subdomains of aggression and anxiety disorders and investigate associated factors with anxiety disorders among Korean adolescents.A cross-sectional study was conducted with randomly selected students from middle schools (7th–9th grade) and high schools (10th–12th grade) in Gwangju, South Korea, April–May 2016. With the assistance of statisticians at the Office of Education of the region, six clusters in Gwangju city were formed based on the socio-demographic characteristics of each cluster. In addition, the questionnaire was distributed during researchers’ on-site visit to schools. Each participant voluntarily completed the survey. Once completed, unique study identification was assigned to each participant to ensure confidentiality and anonymity. A total of 2432 students participated in the survey, and 1933 individuals completed the questionnaire, showing a response rate of 79.5%. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.The survey was comprised of the following questionnaires: Revised Children’s Manifest Anxiety Scale (RCMAS) , 21 and Demographic information included age, gender, caffeine intake, alcohol consumption, smoking, history of medical symptoms such as headache, muscle pain, scoliosis, constipation, indigestion, heartburn, atopic dermatitis, sinusitis and asthma, and medication history of consuming painkillers, digestants and sleeping pills within 30 days.P value of less than 0.05 was considered statistically significant. Statistical analysis was conducted using SPSS Statistics for Windows 20.0 .The independent t-test was used to compare continuous variables between participants with and without anxiety or aggression propensity. The chi-square test was used for categorical variables, and data were expressed as percentages. A multivariate analysis of variance (MANOVA) was conducted to examine differences in the subdomains of aggression propensity , since each of the subdomains of aggression was correlated with at least one other subdomain. To analyze the relationship between anxiety and aggression propensity, Pearson’s correlation coefficient was used. The area under the receiver operator characteristics (AUROC) curve was calculated for the cut-off of aggression scores. Multivariable logistic regression analysis was performed, using the backward stepwise method. The anxiety and control groups were classified according to the RCMAS . Odds ratio (OR) and adjusted OR (AOR) were calculated with 95% confidence interval (CI). The model fit of the prediction model was assessed by an analysis of the AUROC. The mean age was 15.0 ± 1.9 years and 897 (47.1%) were boys. The distribution of the students across the schools was as follows: 930 students (48.1%) in middle school, 1001 (51.8%) in high school, and 2 (0.1%) unspecified. Among them, a total of 163 (8.4%) adolescents were classified as anxiety group based on RCMAS, and 69.9% of them were girls. Adolescents under the age of 15 were more likely to be in anxiety group than those older than 15. As shown in Table As described in Table As the results of correlation analysis, aggression scores of anxiety group were higher than that of control group. Particularly, anger and hostility were more closely associated with anxiety than physical and verbal aggression in the subdomains of aggression. Pearson’s coefficients between anxiety and physical aggression, verbal aggression, anger, and hostility were 0.272, 0.246, 0.501 and 0.600, respectively . Therefore, in the model II, participants were divided into two groups using the cut-off of 69 points of aggression scores. The participants with an aggression score of 69 or higher had a nine-fold higher risk of anxiety than those under 69 (Table p = 0.920) and AUROC was 0.828 , age (under 15), medical conditions of headache, scoliosis, constipation, asthma and total aggression scales. Results revealed that the risk of anxiety significantly increased with asthma, headaches, female sex, age under 15, constipation, and total aggression score. Statistical analysis with AUROC revealed that total aggression score of 69 points had higher sensitivity (77.6%) and specificity 72.8%) to discriminate the probability of anxiety. The AUROC curve was 0.812  was more closely related with anxiety. Although many researchers have long recognized the significance of studying childhood aggression, only recently has attention been given to indirect forms of aggression. Unlike direct aggression, indirect aggression is an inconspicuous form of behavior that is difficult to detect. Therefore, teachers and parents are often unaware of who is indirectly aggressive, and therefore assessment of indirect aggression faces many complications. In this study, high level of indirect aggression was related with high level of anxiety, after adjusting confounders. As suggested in previous literature, being a victim of indirect aggression was associated with higher levels of mood disorders such as depression, loneliness, and anxiety. This was an understandable result considering that such an event could hurt standings in social groups, which is especially important in adolescence . In a coAdolescence is a period in which aggressive behavior tends to increase. Accordingly, it is essential to understand how the specific subtypes of aggression during adolescence contributes to anxiety increase, or vice versa. Previously, it was shown that aggression was a risk factor for the development of internalizing problems (depression and anxiety) in male adolescents. Although significant results were reported in that study, the relatively low internal consistencies associated with the anxiety measure likely weakened the reported results .Girls are at a higher risk for anxiety than boys, revealing a girl-to-boy prevalence ratio of 2.3. This result is coherent with previous studies reporting sex differences in anxiety disorders. Varying influences from reproductive hormones and neurotransmitter expression were suggested to account for gender difference , 26.In relation to medical conditions, students with headaches, asthma, scoliosis, and constipation were included in the high-risk group of anxiety. Numerous studies on pain comorbidity including headache have established an association between pain and psychiatric disorders ; in partOur findings support previous research indicating that children with asthma demonstrate elevation of psychological difficulties . In the This study has an inherent limitation due to its cross-sectional study design and thus cannot lead to causal conclusions. Also, the survey was conducted in a specific region in Korea, rendering generalization difficult. However, the major strength of this study is the large number of subjects, providing sufficient statistical power. Also, it is the first study to assess the relationship between aggression and anxiety in Korean adolescents. Furthermore, the discovery of an aggression cut-off value that sorts out adolescents that are highly likely to be classified as the anxiety group will also aid further medical and/or psychological research.Our results demonstrated higher risk of anxiety with increasing total aggression score. In particular, indirect aggression (i.e. anger and hostility) was more closely associated with anxiety.


Introduction: Traditionally, predictive models of in-hospital mortality in ischemic stroke have focused on individual patient variables, to the neglect of in-hospital contextual variables. In addition, frequently used scores are betters predictors of risk of sequelae than mortality, and, to date, the use of structural equations in elaborating such measures has only been anecdotal.Aims: The aim of this paper was to analyze the joint predictive weight of the following: (1) individual factors  on the mediating factors , and ultimately death (exitus); (2) contextual in-hospital factors (year and existence of a stroke unit) on the mediating factors , as determinants of death; and (3) certain factors in predicting others.Material and Methods: Retrospective cohort study through observational analysis of all hospital stays of Diagnosis Related Group (DRG) 14, non-lysed ischemic stroke, during the time period 2008–2012. The sample consisted of a total of 186,245 hospital stays, taken from the Minimum Basic Data Set (MBDS) upon discharge from Spanish hospitals. MANOVAs were carried out to establish the linear effect of certain variables on others. These formed the basis for building the Structural Equation Model (SEM), with the corresponding parameters and restrictive indicators.Results: A consistent model of causal predictive relationships between the postulated variables was obtained. One of the most interesting effects was the predictive value of contextual variables on individual variables, especially the indirect effect of the existence of stroke units on reducing number of procedures, readmission and in-hospital mortality.Conclusion: Contextual variables, and specifically the availability of stroke units, made a positive impact on individual variables that affect prognosis and mortality in ischemic stroke. Moreover, it is feasible to determine this impact through the use of structural equation methodology. We analyze the methodological and clinical implications of this type of study for hospital policies. According to the WHO, ischemic stroke (IS) is the third leading cause of death in Western countries, and the first cause of disability in adults, in addition to having a high morbimortality load . In the Europe, as of today, the age-standardized incidence of stroke falls between 95 and 290 episodes per 100,000 inhabitants, with 1-month mortality between 10 and 35%; stroke represents the second leading cause of morbidity and disability  and contextual factors, which are usually associated with availability of specific resources, shorter time to care, and the establishment of specific plans for stroke care , Diabetes Mellitus (DM), abnormal heart rhythm , hyperlipidemia and hypertriglyceridemia, liver disease, smoking, sedentary lifestyle and finally nutritional and genetic factors . More recently, their cost-effectiveness and a shortened average length of stay have also been demonstrated .A large part of the literature has focused on individual prognosis factors, while other authors have assessed isolated contextual elements, especially the availability of stroke units. To date, there is insufficient evidence that combines both types of variables and explores their interrelations using a structural, hierarchical equation methodology.objective was to establish interdependent and predictive relationships among the variables that are most often identified in association with pathogenesis and development of stroke, and the main dependent variables . Specifically, and original to this study, we evaluated the role of certain process and context variables, and how they acted as intermediate, modulating variables in the non-linear relationship between predictive variables and outcome variables.Consequently, our main hypothesis states that each individual variable defined in the linear model  and each contextual variable  would have a statistically significant effect on the intermediate variables of the previously established linear model, whether individual variables  or contextual . These in turn would have a significant effect on the two final, dependent variables, namely, readmissions, and mortality.In order to address the main objective, the initial A retrospective cohort study using analytical observation of all hospital stays of the Diagnosis Related Group (GRD) 14—non-lysed ischemic stroke—during the time period 2008–2012. All hospital stays of patients age 24 or older were included.The study was carried out within the Spanish National Healthcare System , a decentralized structure across 17 autonomous regions with their respective regional healthcare systems. Each of the Autonomous Systems has its own structure, with Basic Healthcare Zones grouped in turn into Primary Care Districts and Hospitals. This system is the same throughout the country, despite the drawback of frequent failures in inter-region communication. Healthcare within this network is free of charge; costs are borne by the different regional governments.International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9MC). The selection criteria consisted of identifying the patient stays that were discharged under DRG 14 . This diagnostic group includes exclusively those patients admitted for ischemic stroke who undergo medical treatment, but not fibrinolysis or mechanical reperfusion; consequently, this DRG defines a very specific, select group of patients. As in the relevant bibliography, the total group of hospital stays was then limited to patients over the age of 24, given the small incidence and prevalence of these events in younger persons. Additionally, outlier hospital stays were filtered out according to the classical method that defines outliers with the formula T2 = Q3+1.5(Q3-Q1), where Q identifies the third and first quartiles and T2 is the maximum value of the stay that results from applying the formula. Using this methodology, patients with stays longer than 21 days were identified and excluded.The source of information was the Spanish Minimum Basic Hospital Discharge Dataset, made available by the Ministry of Health, Consumerism and Social Policies. A total of 186,245 hospital stays were analyzed. Diagnostic and procedural coding followed the This project has been approved by the Clinical Ethics Committee of the Province of Almeria, Complejo Hospitalario Torrecardenas, Andalusian Health Service, Ministry of Health, Andalusia (Spain).context variables were identified as year, existence of a stroke unit, length of stay, total count of diagnoses and procedures at discharge, and any readmissions; the remaining variables were considered individual variables , intermediate or process variables  or initial variables  . One musIn order to make the Year variable (6 categories) more homogeneous, the derived variable “Year Gp” was obtained by establishing three bienniums.Sociodemographic information was obtained from the variables year, age, gender, and Autonomous Region. Administrative elements were assessed through the variables length of stay, readmission within 30 days for the same DRG, type of admission (emergency vs. scheduled), and type of discharge . We used the number of diagnoses at discharge (NDX) as a proxy variable for the patient's comorbidity, and the number of procedures at discharge (NPR) to estimate the procedural complexity of each episode and the main clinical comorbidities associated with ischemic processes .For each of the hospitalization episodes, the total number of diagnoses was calculated (including both new comorbidities and pre-existing comorbidities at the time of admission) and coded into 14 fields of variables assigned for that purpose. In this way, diagnosis number 1 is the one that motivates the admission and the rest of the diagnoses are recorded sequentially, some as derivatives of others, until completing the entire spectrum of pathology that existed in each event.exitus (death) and readmission were the DV.For the statistical analysis, variables were treated as follows, according to the dimension being analyzed: (1) first, the initial variables were the independent variables (IV), and the process and outcome variables were dependent (DV); (2) second, the independent process variables were the IV and the outcome variables bivariate analysis was carried out; Student's t-test was used to test the equality of means hypothesis for independent samples or analysis of variance. In cases where they could not be applied, the Mann-Whitney or Kruskall-Wallis non-parametric U was applied, as appropriate. The Chi-square test was used for comparison of qualitative variables. Relationships between quantitative variables were determined through Pearson or Spearman correlations. Second, uni- and multi-variate inferential analysis was carried out between the variables established in the rational model. Inferential statistical analyses  were carried out using SPSS (v. 23.0) for Windows.Two types of analysis were carried out in order to determine which variables to include in the structural linear model. First, Once the variables were identified, the empirical model of structural equations was finally developed. AMOS (v. 23.0) for Windows was used to construct the structural prediction model—specifically, to verify the structural linear prediction hypothesis . To interpret the confirmatory factor analysis (CFA) and the structural equation model (SEM) fit, we focused on the Comparative Fit Index (CFI) and the Root Mean Square Error of Approximation (RMSEA). CFI values equal to or greater than 0.90 and 0.95, respectively, were taken to indicate acceptable and close fit to the data . RMSEA vThe sample was composed of 186,245 hospital stays between the years 2008 and 2012. There were a total of 12,800 exitus during hospitalization. Over the study period, the death rate declined from 7.3% in 2008 to 6.5% in 2012, for an average rate of 6.9% for the whole period. Mean age of the sample was 79.92 (SD 12.54) years, with a mean hospital stay of 7.54 (SD 4.54) days, and 3.27 (SD 2.45) was the mean number of procedures applied. The mean number of diagnoses at discharge was 6.91 (SD 2.95), and 4.8% of the sample were in a readmission situation under the same DRG. First, we assessed the effects of the individual-related IVs  and context-related IVs (year and existence of a stroke unit) on the intermediate individual variables  and intermediate contextual variables .Findings showed a significant effect from each of the IVs  on the intermediate variables mentioned, except in the case of gender. No statistically significant, main interaction appeared. There were also numerous significant partial effects of each independent variable on the dependent variables; these are marked with an asterisk to the right in Year*Stroke unit), (Age*Epilepsy*Year), and finally the interaction of (Year*Gender*Obesity*StrokeUnit), the latter demonstrating great explanatory power. The most relevant variable, common to two of the interactions detected, was the existence of stroke units. Likewise, the intermediate or process variables, whether related to the individual  or to the context , had a clear effect on mortality as DV.Afterward, we analyzed the effect of the individual IVs and the contextual IVs on the main dependent, individual variable (exitus). Uni- and multi-variate analyses showed a significant main effect of all the individual and contextual factors mentioned, except gender; in addition, evidence showed that the discrete factors with the greatest effect on mortality were age and epilepsy, followed by the existence of stroke units. Moreover, certain variables produced several significant interaction effects on mortality , with thDyslipidemia*Hypertension)  variables on mortality. This effect was shown for arrhythmias, dyslipidemia, and hypertension; however, the most powerful interaction in determining exitus was the joint effect of the interaction (tension) .Length of Stay*NDX*NPR), (NDX*NPR*Readmissions), (Length of Stay*NDX*Readmissions), and (Length of Stay*NDX*NPR*Readmissions).Regarding the discrete contextual variables analyzed, those with the greatest effect were length of stay and NPR, along with readmissions. However, the variables with the greatest explanatory power were the interactions of  showed an acceptable model of relationships. The relationship parameters of both models are presented below .In the case of the personal variables, the predictive linear model establishes that the variable GENDER was predicted by AGE (0.259). OBESITY was negatively predicted by AGE (-0.111) and positively by GENDER (0.078). EPILEPSY was positively predicted by GENDER (0.008), and UNIT was positively predicted by AGE (0.013).The variable ARRHYTHMIAS was significantly predicted by AGE (0.180), GENDER (0.067), OBESITY (−0.055), the number of DIAGNOSES (0.354), and PROCEDURES (−0.029). DYSLIPIDEMIA was predicted by AGE (−0.074), OBESITY (-0.064), and by EPILEPSY (−0.013). HTN was predicted by AGE (0.230), GENDER (0.041), OBESITY (0.137), EPILEPSY (0.021), and ARRHYTHMIAS (−0.103).As for the contextual variables, the variable UNIT was significantly predicted by AGE (0.013), STAY was predicted positively by EPILEPSY (0.035) and negatively by DIAGNOSES (−0.452). The variable DIAGNOSES was predicted by AGE (0.138), EPILEPSY (0.077), YEAR (0.164), UNIT (0.107), ARRHYTHMIAS (−0.114), DYSLIPIDEMIA (0.181), HTN (0.554), and STAY (0.148). The PROCEDURES variable was predicted by AGE (−218), by STAY (0.157), and by DIAGNOSES (0.211).p < 0.001). Finally, the variable READMISSION was predicted negatively by DYSLIPIDEMIA (−0.027), HTN (−0.058) and PROCEDURES (−0.058), and positively by DIAGNOSES (0.102). The variable EXITUS (DEATH) was positively predicted by AGE (0.141), ARRHYTHMIAS (0.064), and READMISSIONS (0.052), and negatively predicted by DISLIPIDEMIA (−0.046), HTN (−0.046), and PROCEDURES (−0.065). All error variances were significant . The variable EPILEPSY was not predicted indirectly by any other variable.The variable ARRHYTHMIA was indirectly predicted, in a positive sense, by AGE (0.080), OBESITY (0.029), EPILEPSY (0.024), UNITS (0.034), DYSLIPIDEMIA (0.088), HTN (0.145), and STAY (0.044), and in a negative sense by ARRHYTHMIAS (−0.088) and DIAGNOSES (−0.092).DYSLIPIDEMIA was indirectly predicted, in a positive sense, by OBESITY (0.004), UNITS (0.005), ARRHYTHMIAS (0.008), and PROCEDURES (0.004), while negatively predicted by AGE (−0.042), GENDER (−0.004), EPILEPSY (−0.003), YEAR (-0.005), HTN (−0.020), STAY (−0.006), and DIAGNOSES (−0.036).Hypertension was indirectly and negatively predicted by AGE (−0.125), GENDER (−0.003), OBESITY (−0.016), EPILEPSY (−0.036), YEAR (−0.062), UNITS, ARRHYTHMIAS (−0.044), DYSLIPIDEMIA (−0.127), HTN (−0.210), STAY (−0.070), while predicted positively by DIAGNOSES (0.073) and PROCEDURES (0.003).In the case of contextual variables, the existence of a stroke unit (UNIT) was not indirectly predicted by any other variable in the model. Length of stay (STAY) was indirectly predicted, in a positive sense, by AGE (0.003), GENDER (0.001), DYSLIPIDEMIA (0.001), and HYPERTENSION (0.001), while negatively predicted by ARRHYTHMIAS (−0.001).The variable DIAGNOSES was positively predicted by AGE (0.009), GENDER (0.013), OBESITY (0.082) and DYSLIPIDEMIA (0.071), and negatively predicted by EPILEPSY (−0.009), ARRHYTHMIAS (−0.048), HYPERTENSION (−0.136), DIAGNOSES (−0.246), and YEAR (−0.048).PROCEDURES were positively predicted by AGE (0.003), GENDER (0.003), OBESITY (0.012), EPILEPSY (0.020), DYSLIPIDEMIA (0.053), HTN (0.088), YEAR (0.015) and UNITS (0.032); and negatively by ARRYHTHMIAS (−0.033) and DIAGNOSES (−0.052).The outcome variable READMISSION was indirectly and positively predicted by the personal variables AGE (0.003), GENDER (0.002), OBESITY (0.001), EPILEPSY (0.007), DYSLIPIDEMIA (0.048), and HTN (0.048), and positively predicted by the contextual variables YEAR (0.012) and UNIT (0.003), while predicted negatively by contextual variables DIAGNOSES (−0.015) and PROCEDURES (−0.001).The other variable, EXITUS (DEATH), was predicted positively by AGE (0.031), GENDER (0.003), HTN (0.014), DIAGNOSES (0.025), and negatively by OBESITY (−0.002), EPILEPSY (−0.002), DYSLIPIDEMIA (−0.004), UNITS (0.013), and PROCEDURES (−0.005) see .The final model is graphically represented in individual variables made a differential, statistically significant impact on the intermediate (mediating) variables, and these in turn on exitus. This is not an every-variable-to-every-variable relationship; the particular predictions are made explicit below, as well as some paradoxical relationships that deserve a detailed explanation. The inferential results presented here show effects from combined variables, similar to what has been reported with prior evidence. The clearest effects were produced by the combination of multiple variables.This investigation began with the hypothesis that each variable defined in the linear model, whether individual or contextual, would have a statistically significant effect on the intermediate variables of the established model, at the individual level and at the contextual level. These in turn would have a significant effect on the two dependent outcome variables, namely, readmissions and mortality. This hypothesis was in large measure confirmed, having verified in our SEM model that the As seen in other studies, different variables were found to be statistically significant predictors of the presence of arrhythmias as comorbidity in this group of patients. In this context, arrhythmias were significantly, positively predicted by age , 22, obeage. A possible explanation would be that stroke-affected patients suffer from vasculopathy and often arteriopathy; they are affected by different types of pathologies that are treated fundamentally with statins. Prior research has demonstrated that the use of statins increases with age. Thus, age might be negatively associated with dyslipidemia through the use of this pharmacological group in the type of patient most prevalent in this study: older people with a background of cardiovascular pathology.One paradoxical result is the negative prediction of dyslipidemia as a function of On the other hand, gender (being a woman) positively predicts arrhythmias and HTN, but not dyslipidemia. The association between the female gender and the existence of certain types of arrhythmias is well-documented , and proAnother noteworthy result is the positive predictive role of epilepsy with respect to HTN. According to the established literature, HTN is an obvious, crucial risk factor for ischemic stroke, in the same way that stroke itself is a risk factor for developing epileptic crises. We may then suppose, in full agreement with other authors , that thage positively predicts arrhythmias ; in a few cases, they seem paradoxical or difficult to explain, thus indicating a need to investigate some of the predictive effects that were found. Both dyslipidemia and NPR are significant, negative predictors of readmissions, while NDX is a significant, positive predictor. Increased procedural effort or therapeutic intensity can explain the direction of the NPR-Readmissions prediction, such that where greater effort is applied, there is less likelihood of being readmitted to hospital for the same reason in the 30 days following discharge. Similarly, when patients have a greater number of diagnoses (greater comorbidity), prediction of readmissions is positive, demonstrating that the patient's overall complexity undoubtedly influences his or her prognosis.Elsewhere, the evidence showed dyslipidemia and NPR as negative predictors of mortality, while age and the existence of arrhythmias were positive predictors. It seems logical that more elderly patients, and patients affected by arrhythmias , would have greater mortality. The negative association between dyslipidemia and mortality, to our understanding, can only be understood in that dyslipidemic patients receive greater procedural effort, and probably undergo more frequent medical checks. This assertion is supported by the direct, significant, negative prediction that occurs between the number of procedures applied, and mortality.To complete this section, we must make note of the central, core prediction between the two dependent variables. Just as each different individual variable on its own has been related through different mechanisms to each of the dependent variables, there is an obvious, significant, and very powerful prediction between readmissions and mortality. This association has been cited in many studies on a variety of pathologies, and we believe it lends even greater biological plausibility to the structural model –39.contextual variables. Year was confirmed to have a negative effect on length of stay and on in-hospital mortality. The effect on mortality was mediated by NDX and NPR, variables that in turn depend directly on the existence of stroke units and the ongoing creation of such units during the study period. The period analyzed in this study was a time of marked change, where improved stroke care, both in therapeutic terms and in organization of care, prompted a drop in average length of stay and in short-term mortality—and consequently in in-hospital mortality, which we are analyzing here , there are higher levels of 30-day readmissions, and secondarily, there are the above-mentioned increases in mortality. As for NPR, considered a proxy variable for the degree of therapeutic effort applied to the patient, we find that with greater effort, there is a decrease in readmissions and in mortality. Both variables are closely related to the existence of stroke units, such that procedural effort is objectively greater within these units than in conventional hospitalization .stroke units positively predicted length of STAY, as commented. These units admit the more complex patients in particular (greater comorbidity or NDX), and apply greater therapeutic and procedural effort (higher NPR), which would explain the decrease in both mortality and in readmissions; according to other authors, however, a paradoxical effect can occur due to the patient's own complexity (Although the moment in time (Year) predicted shorter hospital stays, within stroke units there was greater likelihood of longer stays throughout the whole study period. The most important effect found was that the existence of mplexity , 43. Themplexity .Another noteworthy result is the predictive effect of individual mediating variables on context variables. The most interesting result, from the point of view of how the healthcare system affects disease in subjects, is that the number of DIAGNOSES negatively predicts length of STAY, but positively predicts an increased number of PROCEDURES. This may be interpreted as more complex patients having shorter hospital stays because of the high levels of accumulated mortality in this group. The patient's diagnostic complexity (NDX) itself would lead to greater procedural effort (NPR), but there may also be mechanisms that limit therapeutic effort at the most advanced ages . In any illustrated algorithm, the present analysis yields an empirical model that incorporates a macro and micro view of predictive relationships between the independent, mediating, and outcome factors of the subjects' health in interaction with the contextual, organizational factors. In our view, this model has unquestionable epidemiological value for revealing probabilistic predictive relationships between personal and contextual factors, thereby enabling healthcare organizations to understand and make decisions regarding the detection of diseases that bring increased likelihood of others. It also enables large-scale assessment of the adequacy of resources deployed as a function of the pathologies analyzed, opening the way to cost-benefit analyses. Some previous analyses have contributed evidence in this line of work, using different methodologies  would unquestionably contribute to improved clinical care for the patient and to organizational efficiency itself. An understanding of how the individual and contextual elements of stroke are related to each other gives us a broad, ambitious view of this scenario, now supported by a structural model that provides empirical evidence, in contrast to the formerly fragmented or non-existent evidence in prior contributions to our understanding of this disease.The results of this study are also relevant from the point of view of large clinical-administrative databases are obvious. First, this approach goes beyond the classic, correlational methodology that establishes covariation relationships between study variables but has many limitations with respect to establishing causal relationships. In fact, certain prior studies have shown that when empirical models are based on associations between variables, and an SEM model is later developed, some of the previous association relations are not sustained in the new structural model, because of accumulated measurement errors. Second, while carrying out prior inferential analyses ensures that interdependence  relationships between variables are consistent, this type of analysis is unable to present such relationships in a combined, multidirectional manner, but only as limited to each multivariate analysis. Third, the SEM model makes it possible to establish structural multi-directionality of causation through path analysis. Consequently, this type of analysis would be appropriate to an R&D&I Department , where the role of the stroke unit is even more critical. However, given the high prevalence of this subtype of stroke (ischemic and not subject to reperfusion), we think that establishing a predictive empirical model with personal and hospital variables is of great relevance. It would be interesting to replicate the study with patients who have received treatment for acute stroke, when enough data become available. We believe that the future inclusion of patients subjected to mechanical or chemical reperfusion would probably modify the outputs in the sense of less sequential morbidity, decreased length of stay, and lower mortality in stroke units and even in general hospitalization. We also consider that the contextual dependent variable “readmissions” would be favorably diminished by the inclusion of these new therapeutic techniques. Even in the case of non-lysed stroke, this replication in a real cohort would make it possible to simplify and further divide up the elements of the final model. We could learn more precisely which elements might be implemented in routine clinical care in order to optimize outcomes.Working with these massive clinical-administrative databases has the advantage of the great statistical power of a large sample size, but such databases are not free from significant drawbacks. On one hand, the data reflect the in-hospital situation exclusively, possibly leading to an external validity issue; in our particular case, acute stroke patients are rarely addressed on an outpatient basis, so we consider this bias to be minimal. We also must consider that the information is limited by the quality of the diagnostic and procedural codings themselves, and that this quality is rather uneven, not only geographically  but also over time (the study period), fortunately the latter tends toward improvement.In addition, we must consider the limitation that variables such as “epilepsy” imply, where we cannot identify whether it is occurring as a result of the stroke or whether the patient has suffered this pathology for some time. This obvious database limitation in not differentiating certain secondary diagnoses as complications or as comorbidity is only partially compensated by the high sample size and the diagnostic position: epilepsy encoded in the second diagnostic position is understood to be an acute complication, while in lower positions it is more likely to be a preexisting comorbidity.Finally, we must take into account the very critical patients who die shortly after admission: their chronic pathologies are often under recorded, possibly distorting the statistical results and even provoking paradoxical results. The well-known Jencks bias, a phenomenon described in Jencks et al. , has beeJdlF development of the conceptual idea. Statistical methodology Global drafting of the manuscript. JG-T general review of the manuscript. Introduction and review-writing of the discussion. MI-E general review of the manuscript and partial wording of the discussion. GS global review of the manuscript. Statistical review. AG-U review of the design evaluation process used. JF-P review of the global English level of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


An accumulation of evidence has revealed the important role of epigenetic factors in explaining the etiopathogenesis of human diseases. Several empirical studies have successfully incorporated methylation data into models for disease prediction. However, it is still a challenge to integrate different types of omics data into prediction models, and the contribution of methylation information to prediction remains to be fully clarified.A stratified drug-response prediction model was built based on an artificial neural network to predict the change in the circulating triglyceride level after fenofibrate intervention. Associated single-nucleotide polymorphisms (SNPs), methylation of selected cytosine-phosphate-guanine (CpG) sites, age, sex, and smoking status, were included as predictors. The model with selected SNPs achieved a mean 5-fold cross-validation prediction error rate of 43.65%. After adding methylation information into the model, the error rate dropped to 41.92%. The combination of significant SNPs, CpG sites, age, sex, and smoking status, achieved the lowest prediction error rate of 41.54%.Compared to using SNP data only, adding methylation data in prediction models slightly improved the error rate; further prediction error reduction is achieved by a combination of genome, methylation genome, and environmental factors. BRCA1 promoter methylation was useful in predicting the response to chemotherapy in epithelial ovarian cancer [Increasing evidence reveals the important role of epigenetic factors in explaining the etiopathogenesis of human diseases, especially in cancer . For exan cancer , and Shin cancer . Diseasen cancer , 5. Consn cancer –9. HowevIn this study, a stratified drug-response prediction model is built based on an artificial neural network (ANN) to identify the contribution of methylation information to predicting the change in the circulating triglyceride (TG) level after fenofibrate intervention. Omics data, including genetic, epigenetic, and clinical factors, are used as predictors. The analysis of GAW20 real data demonstrates that the inclusion of the methylation data improves the prediction accuracy marginally, which provides an indication for future prediction research.+ T cells harvested from stored buffy coats and the proportion of sample methylation was quantified at > 450,000 cytosine-phosphate-guanine (CpG) sites [GAW20 real data were used in this study and were provided by the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, which aimed to identify the genetic determinants of the responses of circulating lipid levels to fenofibrate treatment interventions. In total, 1053 individuals from families with at least 2 siblings were recruited. They all self-reported as being of white ethnicity [In the quality control process, 39 participant outliers were removed, and only subjects without any missing data for the key variables  were used. A total of 523 participants were included in the analysis. For the genotype data, single-nucleotide polymorphisms (SNPs) with a minor allele frequency < 0.01 were excluded. Missing variants were imputed according to the probability distribution of the genotype in all subjects. For the methylation data, cross-reactive probes and probes containing common variants were filtered. Beta-mixture quantile normalization was used to correct for the Infinium Type I/II bias , and parDrug response was used as the dependent variable which could be defined as the percentage change in the TG level.TG pre is the average of TG levels at visits 1 and 2, and TG post is the average of TG levels at visits 3 and 4. It was reported that fenofibrate, which was the intervention drug for the GAW20 real data, usually reduced the plasma TG level by approximately 30 to 60% in hyperlipoproteinemia patients at a dosage of 200–400 mg daily [Where mg daily . In thisThe features related to drug response were selected in a stratified manner , first wp value threshold of 10− 4 was applied to filter the biomarkers for GEE and LMM so that a moderate number of predictors can be used in the prediction model. SNPs were pruned to avoid the strong influence of SNP clusters, by snpgdsLDpruning, and the linkage disequilibrium threshold was set at 0.2 [The generalized estimation equation (GEE) model was used to select significant SNPs and adjust for family relatedness . CpG sitt at 0.2 , 22. ThePredictors were added into the prediction model step-by-step by data types. Afterward, chosen SNPs were inputted into the ANN first, followed by significant CpG sites. Finally, age, sex, and smoking status were included. This stratified method made it easy to identify the respective contribution of each category of information to prediction.a) for the hidden layer, which has the following form:A three-layer ANN was applied with one hidden layer. The hyperbolic tangent sigmoid transfer function was used as the activation function (purelin):A linear function was used as the activation function for the output layer , which implies that the inclusion of methylation information improves the prediction model. When clinical factors  were also included, the error rate dropped slightly to 41.54%   were included in the ANN model in a stepwise manner to compare their contributions to the prediction ability of the model. The baseline model simulates the null scenario; that is, 100 SNPs were selected from the autosomes at random and used to predict the phenotype with the ANN in 5-group cross-validation. This gave a baseline error rate of 47.15% (SD: 3.79%), representing a random-guess prediction error under the ANN. Next, including the SNP information yielded a mean test prediction error rate of 43.65% (SD: 4.79%). When methylation information was added, the prediction model achieved an error rate of 41.92%  and CTNNBL1  have both been strongly associated with obesity risk and related traits [DGAT1  plays a role in catalyzing the committed step in the biosynthesis of TGs [ALDH4A1  is known to catalyze ester hydrolysis, suggesting that it may lead to a change in the TG level [Finally, we report the biological meaning of variables identified using all data. Many of the identified SNP and CpG markers had functions that are related to the regulation of the circulating level of TG, which is a major storage molecule for metabolic energy . To listd traits , 25. Thes of TGs , and ALDTG level .Table 2Sp value = 0.3759). The combination of significant SNPs, CpG sites, age, sex, and smoking status achieved the best prediction error rate of 41.54%.Epigenetic factors are thought to be significantly associated with human diseases, making it plausible to incorporate methylation information for better disease prediction. In this study, we used an ANN to build a stratified drug-response prediction model in which SNPs, methylation, age, sex, and smoking status were considered as predictors. The GAW20 real-data analysis shows that the incorporation of methylation information could reduce the prediction error rate by approximately 4% (+ T cells harvested from stored buffy coats, and the phenotype was the TG level in blood, which has a strong correlation with T-cell functions [In previous studies, Deng et al. used fusing networks to predict schizophrenia from SNPs, methylation, and functional magnetic resonance imaging data . They acunctions . Second,Adding methylation data slightly improved the prediction accuracy for drug response using a neural network based prediction algorithm with GWAS data. The result could be constraint by the source of tissue, the outcome variable and the disorder under study. Further studies in other cohorts are necessary to validate the results.


The onset and chronification of pain often has devastating consequences on the physical and mental functioning of individuals. Medical interventions are quite efficacious in reducing pain levels. However, changes in physical and mental health status after medical interventions are not proportional. In the past decades, rational/irrational beliefs, especially catastrophizing, have contributed to a better understanding of the pain experience. This study explores whether pain reduction efforts are more beneficial for individuals scoring high in rational thinking (moderation).SD = 14.28) and 61.3% were female.The study design was longitudinal. Patients were assessed twice, 2 weeks prior to the start of medical treatment at the pain clinic and 6 months after. A total of 163 patients with heterogeneous pain (mostly low back and neck pain) participated in the study. Their mean age was 58.74 years . An improvement in physical functioning , but not mental health  was also observed. In the regression analyses, a decrease in pain intensity was moderately associated with improved physical health . This association was found to be moderated by frustration tolerance . Specifically, post hoc analyses indicated that changes in pain intensity only correlated with changes in physical health when patients reported high frustration tolerance levels , but not when patients were intolerant to frustration .Overall, there was a reduction in pain intensity (The results suggest that frustration tolerance may render adaptive by facilitating the positive effect that a reduction in pain intensity has on physical health status. The study findings are discussed in the context of personalized therapy with an emphasis on how to maximize the effectiveness of current interventions for pain. The onset and chronification of pain in previously healthy individuals often has profound and pervasive effects on the people’s ability to perform physically, as well as on their overall mental well-being . Not surMedical treatment  is the most frequent approach in the management of chronic pain , as wellConsistent with the previous idea, research in the past decades has shown psychological factors clearly contribute to a better understanding of the experience of chronic pain . For insIn relation to the latter, an increasing number of psychological factors are now gaining ground in the pain literature, including pain acceptance, coping, self-efficacy, and injustice , among oTo shed new light into the aforementioned gap in the literature, this study will investigate the moderating role of the previous forms of thinking, namely demandingness, catastrophizing, frustration intolerance, and self-downing, in the relationship between changes in pain intensity and changes in physical and mental health status in a sample of chronic pain patients following a medical intervention. We hypothesize that improvements in health status after a reduction in pain intensity will be facilitated when individuals score high in rational thinking. Conversely, we expect that irrational thinking will result in an inhibition of the positive effects of pain reduction efforts on adaptation to pain . These hypotheses come from studies showing that irrational beliefs, which are defined as a maladaptive appraisal of events in which assumptions about reality are inconsistent with that reality, act as underlying cognitive vulnerability factors for distress in front of negative situations, such as experiencing chronic pain . By contSD = 14.28) and 62.0% of them were female. Almost half of patients had not completed secondary education (49.7%), while a smaller percentage had finished technical or university studies (25.8%). At the time of assessment, 36.2% of patients were working, 11.0% were unemployed, and 52.8% were retired.A total of 163 chronic pain patients with non-cancer, musculoskeletal pain participated in this study. All patients were adults aged eighteen or over. Their mean age was 58.74 years (SD = 7.56). The main pain locations were the lower back (63.9%) and the neck (11.0%). The remaining pain locations occurred at very low frequencies and are not reported to facilitate the readability of the manuscript. Ethnic characteristics were not explored in this study due to the homogeneity of the sample, which was mostly Caucasian. The large majority of participants (93.9%) were Spanish.Duration of pain prior to intervention ranged from 6 months to 49 years, with a median of 2 years  was used to measure patients’ pain intensity at the time of assessment, with patients being asked to rate their pain intensity from 0 = e of use .The Spanish form of the Short Form-36 Health Survey SF-36;  was admistrongly disagree to 4 = strongly agree. Thus, the maximum score for each scale is 24. All scales are bipolar, with lower scores reflecting rational thinking. The GABS-SV satisfies the recommendations for the assessment of beliefs: it distinguishes processes from content, evaluates cognition rather than behavior, and it does not include affective wording , being over 18 years of age, and giving written consent to participate. From 2013 to 2015, the clinical history of patients programmed for a first consultation at the pain unit was reviewed to check the eligibility criteria of age and pain duration. Next, potential participants were approached by letter by the lead researcher, CSR, 2 weeks before patients had their first appointment at the pain unit. Patients were asked to return the completed questionnaires on the day of the first visit, so all baseline measures were completed before the onset of medical treatment. On the day of the first medical appointment, either a physician or the lead researcher, CSR, officially enrolled the participants by collecting the written informed consent and the questionnaires. Five months after this first appointment, patients were contacted again by letter, and 1 month later  they returned the new set of completed questionnaires (follow-up assessment). The protocol was the same for both assessment points and included an information sheet, an informed consent document, and the questionnaires. To explore the correlation between changes in pain intensity and changes in health status, both constructs were assessed at baseline and follow-up. By contrast, to test the study hypothesis, irrational beliefs were only measured at baseline.n = 495) were contacted again approximately 5 months after the first evaluation. Of these, 163 patients returned the completed questionnaires (32.9%). Reasons for discontinuation could be explored for some patients, but these could not be changed. These reasons mostly included hospital discharge, which resulted in decreased motivation to participate in the study or perceived difficulties in delivering the questionnaires back to us, as well as lack of time and motivation.All patients who completed the baseline assessment , we compared their characteristics against those of patients who provided data for both measurements. We used a t-test for independent samples to compare their age, pain duration, pain intensity, health status, and levels of irrational thinking. Cohen’s d effect sizes are reported. Additionally, we performed a χ2 test to explore differences in sex. These results are important to discuss the generalizability of findings. Cronbach’s alphas will also be calculated for all the study measures to ensure the internal consistency of scores.Because a large subset of patients who responded to the baseline assessment did not respond to the second administration  and patients who only provided data for the baseline evaluation (n2 = 332) by means of a Student’s t-test. No differences were revealed in any of the continuous variables, including age, pain duration, pain intensity, health status, or rational thinking . The χ2 test did not reveal sex differences between completers and non-completers either .As reported in Mmen = 7.32, SDmen = 1.80, Mwomen = 8.08, SDwomen = 1.40, t = -3.00, p = 0.003; 95% CI = -1.25, -0.26, d = 0.47) and physical functioning . Specifically, women reported having more intense pain and were less able to perform in their daily activities due to their health problems. Sex differences were not observed in age, pain duration, mental health, changes in pain intensity and health outcomes after medical treatment, and rational thinking .As reported in t = 4.25, p < 0.001; 95% CI = 0.33, 0.90) and an increase in physical functioning ratings  after the intervention. Changes in pain intensity and physical health were between small and medium . There were no significant changes in mental health at the group level .Regarding changes at the mean-level, there was a significant reduction in pain intensity  and mental health status . Irrational forms of thinking, were generally strongly intercorrelated and significantly associated with poorer mental health . Irrational beliefs did not correlate with pain intensity and physical functioning.The Pearson correlations indicated that pain intensity was significantly associated with poorer physical functioning  and modestly correlated with changes in mental health .Additionally, the bivariate analyses revealed that changes in pain intensity were moderately associated with changes in physical health status . The negative beta coefficient in the interaction between LFT and changes in pain intensity indicates that LFT reduced the contribution of changes in pain intensity on changes in physical health status. A probing post hoc analysis and a graphical representation were performed to help interpret this finding (SD from the mean of LFT and changes in pain intensity. At high levels of LFT (M = 17), changes in pain intensity were not related to changes in physical health . Conversely, at low levels of LFT (M = 7) the relationship between changes in pain intensity and changes in physical health was moderate and significant . Similarly, as reflected in We explored whether irrational forms of thinking moderated the relationship between changes in pain intensity and changes in health status, with an emphasis on physical functioning as this was the measure of health status that revealed changes after the treatment. As reported in  finding . Simple t = 0.29, p = 0.775; 95% CI = -0.20, 0.27) and mental health , the moderation of catastrophizing in the relationship between pain intensity and both physical functioning  and mental health , the moderation of LFT in the relationship between pain intensity and mental health , and the moderation of self-downing in the relationship between pain intensity and both physical functioning  and mental health .The remaining moderation effects were not significant, that is, the moderation of demandingness in the relationship between pain intensity and both physical functioning . For instance, while pain catastrophizing has been reliably associated with numerous pain-related variables, its moderating role in predicting treatment efficacy  has little support , thus inWhile acknowledging the previous limitation in the conclusions that can be drawn for the present study findings, past research has also shown that the belief that discomforting events cannot be tolerated boosts the negative impact of stressful situations on functioning . By contThe moderation of pain-to-health associations after medical treatment is a key finding in the present investigation. The idea that psychological factors can act as moderators of treatment efficacy is not new. In fact, there is an increasing body of research supporting the role of psychological factors as moderators of the effectiveness of psychological interventions . HoweverSD range) to those of other pain clinics  exceed medical costs for chronic pain patients by a factor of five . ConsequIn sum, our results lead us to recommend the assessment of frustration tolerance beliefs before starting pain reduction interventions in pain settings. By doing so, we could personalize treatments by offering psychological treatment  to patients scoring low in this form of thinking in conjunction or prior to their usual medical treatment. Further studies are needed to replicate the present study findings, as well as to test whether an early psychological intervention targeting maladaptive beliefs can indeed maximize the secondary gains of pain-reduction efforts .The Ethics Review Committee of the Vall d’Hebron Hospital in Barcelona approved the present study and all its procedures. The protocol was the same for both assessment points and included an information sheet, an informed consent document, and the questionnaires.All authors made substantial contributions to this work–helped in data interpretation, reviewed and discussed the manuscript, and approved the final version of the manuscript after a number of revisions. CS-R, SS-V, and DG-P designed the study. CS-R and LC-G collaborated in data acquisition. CS-R, JO, and DG-P worked in data analysis. CS-R elaborated the first draft of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Primary dysmenorrhea (PDM) is one of the most prevalent gynecological diseases in women of childbearing age. The major medications treating PDM usually make sense and side effects, while moxibustion is known as a safe and effective treatment for PDM. This review aims to systematically evaluate the effect and safety of moxibustion for treating PDM.We will search all randomized controlled trials for moxibustion therapy on PDM, electronically and manually, regardless of publication status, till October 31, 2019. Online databases include the Cochrane Central Register of Controlled Trials; PubMed; EMBASE; China National Knowledge Infrastructure; Chinese Biomedical Literature Database; Chinese Scientific Journal Database (VIP database); and Wan-Fang Database. Two reviewers will search these databases, select data and measure the quality of studies independently. The methodological quality will be assessed by the Cochrane Reviewer's Handbook 6.0. The primary outcomes include clinical efficacy and visual analog scale, and the secondary outcomes include adverse events and quality of life. Four reviewers will independently extract the data and assess the qualities of the studies. Statistical analysis will be conducted with R package for each outcome. Study selection, data extraction, and assessment of risk of bias will be performed independently by 2 reviewers.This study will provide a comprehensive review of the available evidence for the treatment of moxibustion with PDM.The conclusion of our study will provide updated evidence to judge whether moxibustion is an effective and safe intervention for patients with PDM.CRD42019129993 PDM is not associated with obvious pelvic organic disease and has high socioeconomic impact.–10Primary dysmenorrhea (PDM) is one of the most prevalent gynecological diseases in women of childbearing age. It refers to menstrual pain, often spasmodic, concentrated in the lower abdomen. issued by the Society of Obstetricians and Gynaecologists of Canada, the drugs currently used to treat PDM are acetaminophen, nonsteroidal anti-inflammatory drugs or oral contraceptives and complementary replacement therapies. However, nonsteroidal anti-inflammatory drugs or oral contraceptives may cause adverse effects on the liver, digestive tract, and other metabolic organs.,13 Due to these shortcomings, moxibustion is a viable supplemental replacement therapy in China, Japan, the United States, and other regions. Years of application experience and widely used, especially in China, ongoing clinical trials have made moxibustion more and more accepted.So far, the cause of PDM has not yet been elucidated. Among the guideline analyzed herb-partitioned moxibustion could regulate the endocrine hormone to upregulated pregnenolone, prostaglandin E2, and γ-aminobutyric acid and downregulated the content of estrone and prostaglandin H2. Chen et al found after moxibustion treatment, uterine Prostaglandin F2α (PGF2α) content were obviously down and increase Natural Killer (NK) cell activity by regulating neuroendocrine-immune network. In the past, there are only 2 meta-analyses about moxibustion in the treatment of PDM, but their research had been 3 years and 5 years, respectively, and their focus is on the time of moxibustion intervention and all acupoint therapies including moxibustion. However, there is still no critically designed systematic review to assess the effectiveness and safety of moxibustion for PDM. Therefore, we will perform a systematic review of moxibustion for PDM to collect some reliable evidence for clinical guidance and to assistant PDM patients to seek more reasonable treatments. In this review, we aim to conduct a systematic review to evaluate all the clinical studies on the effects and safety of moxibustion for treating PDM in adults.Many researchers have conducted experiments on the mechanisms of moxibustion in the treatment of PDM. Ma et al22.1http://www.crd.york.ac.uk/PROSPERO). This protocol is reported in compliance with the preferred reporting items for systematic reviews and meta-analysis protocols (PRISMA-P) statement guidelines. The review will be conducted in accordance with the PRISMA guidelines and follows the recommendations of the Cochrane Handbook for Systematic Reviews of Interventions.,21 If we refine the procedures described in this protocol, we will update the record in the PROSPERO and disclose them in future publications related to this study.This study has been registered at PROSPERO  which explore the specific efficacy and safety of moxibustion in the treatment of PDM. Cross-trials, quasi-RCT, animal experiments, and other studies that were repeatedly published or did not have access to complete data will be excluded.Trials will be excluded as follows:(1)studies that involved a combination of moxibustion with other treatments, such as acupuncture, massage, cupping, and drugs or Chinese herbs;(2)comparing moxibustion with other forms of acupuncture or other treatment;(3)quasi-randomized trials and case reports.2.2.2The included studies must be RCTs with patients diagnosed with PDM. PDM is defined as a lower abdomen pain that occurs during menses. Patients that were diagnosed with pelvic pathology or secondary dysmenorrhea will be excluded.2.2.3Any type of moxibustion therapy such as direct moxibustion, indirect moxibustion, heat-sensitive moxibustion, natural moxibustion, moxa-burner moxibustion, crude drug moxibustion as the sole treatment or a part of combination therapy with other intervention will be included. Studies in which moxibustion is not used as a major intervention will be excluded.2.2.4The primary endpoint evaluated will be the level of pain, with measurements made in the individual studies using the visual analog scale, numerical visual scale, or any other scale used for pain assessment. All response rates will be calculated from the total number of patients randomized. When the studies report response rates at various points of time, we decided a priori to compare the results obtained at the baseline with the endpoint of the treatment.The secondary outcomes are adverse events and quality of life of women complaining of dysmenorrhea, who underwent moxibustion treatments. Symptoms often co-occurring with PDM include diarrhea, skin rash, and nausea. Diarrhea refers to abnormal bowel movements. Skin rash refers to some changes in the skin traits. Nausea refers to an urge to vomit. Quality of life was measured using questionnaires before and after treatment. When the studies report response rates at various points of time, we decided a priori to compare the results obtained at the baseline with the endpoint of the treatment.2.3Our systematic review will search all RCTs for moxibustion therapy on PDM, electronically and manually, regardless of publication status, till October 31, 2019. Online databases include the Cochrane Central Register of Controlled Trials; PubMed; EMBASE; China National Knowledge Infrastructure; Chinese Biomedical Literature Database; Chinese Scientific Journal Database (VIP database); and Wan-Fang Database. Ongoing trials with unpublished data will be retrieved from the 4 following clinical trial registries: International Clinical Trials Registry Platform, NIH clinical registry Clinical Trials.gov, the Chinese clinical registry, and the Australian New Zealand Clinical Trials Registry. The reference lists of the selected studies and published systematic reviews will be screened for additional studies. Manually search for the grey literature, including conference proceedings.2.4 and will be applied to all the electronic databases .A search strategy will be created according to the Cochrane handbook guidelines,The key search terms are  AND (“moxibustion” OR “moxa” OR “mox∗” OR “mugwort”) AND (“randomized”). The search strategy will be adapted to different databases demands. Search strategy in PubMed is shown in Table 2.52.5.1In the literature screening process, search results will be imported from the databases to EndNote V.X9, and this software will be used to remove duplicates and manage the trials that have been searched. Two reviewers (HW and XH) will independently review and screen the titles and abstracts of all retrieved studies to confirm eligible trials. The full text will be scanned if the studies cannot be identified after the screening of titles and abstracts. Excluded studies will be recorded with the reasons of their exclusion. In this process, disagreements will be discussed by the 2 authors (HW and XH) and be arbitrated by the third author (QY) when the 2 authors cannot reach consensus. The authors of the original studies will also be contacted for clarification when necessary. The process of the selection is shown in Figure 2.5.2Before beginning extraction, a consistency assessment will be performed through a pilot test, in which each of them will evaluate 2 trials, respectively. After making a common consensus, 2 reviewers (QY and HW) will independently extract the data and assess the qualities of the studies. Data of the included studies will be collected, including first author, language used, study design, sample sizes, diagnostic criteria, patients’ ages, duration of disease, interventions used in the experimental group and control group, treatment duration, outcomes, adverse events, and type of moxibustion. Any discrepancy noticed in the process of data extraction will be resolved through discussion and the suggestion of a third reviewer (LH). For publications with insufficient or ambiguous data, we will attempt to obtain information from the corresponding authors by e-mail or telephone.2.5.3,21 will be used to evaluate the quality of the included studies.The Cochrane risk of bias tool, which is recommended by the Cochrane Reviewer's Handbook 6.0,HW and XH will independently evaluate the quality of selected articles from the following 5 aspects: selection bias , performance bias and detection bias (blinding), attrition bias (incomplete outcome data), reporting bias (selective outcome reporting), and other biases. If necessary, we will contact the corresponding author to clarify issues. The result of the consistency evaluation will be presented with Kappa statistics, Kappa value <0.75 will be considered the consistency have reached. Any disagreements will be resolved through discussion or consultation with BXZ.2.5.4I2 test is less than 50%, the fixed-effects model will be used for data synthesis. If the I2 test is between 50% and 75%, the random-effects model will be conducted for data synthesis. If the I2 test is higher than 75%, we will investigate possible reasons from both clinical and methodological perspectives, and provide a descriptive analysis or conduct subgroup analysis.Statistical analysis will be conducted with R package for each outcome. Relative risk, including 95% confidence intervals, will be used for the analysis of dichotomous data on clinical efficacy. If the If the moxibustion has many different forms, such as direct-moxibustion, herb-partitioned moxibustion, moxa burner moxibustion, or natural moxibustion, they will be classified as 1 group in the meta-analysis. Data will be extracted for all time points if sufficient data are available, and outcomes in different time points will be analyzed. The consistency will be assessed by node-splitting method, which estimates the direct and indirect treatment effect separately. If inconsistency is identified, potential sources of the inconsistency need to be detected.2.5.5To test the robustness of the primary decisions of the review process, sensitivity analysis will be conducted. The principal decision nodes conclude methodological quality, sample size, and the effect of missing data. The meta-analysis will be repeated and studies of lower quality will be excluded. The result will be compared and discussed according to the results.2.5.6 In this approach, direct evidence from RCTs starts at high quality and can be downgraded based on the risk of bias, indirectness, imprecision, inconsistency (or heterogeneity), and/or publication bias to levels of moderate, low, and very low quality.The quality of evidence for all outcomes will be judged using the grading of recommendations assessment, development, and evaluation working group methodology.3PDM is a major public health problem in the world, which seriously affects the quality of life and work efficiency of women, causing great economic losses. Studies have signified that moxibustion is effective for relieving the symptoms of PDM. Nevertheless, currently, no systematic review related to moxibustion for PDM has been published in English. The evaluation of this systematic review will be divided into 4 sections: identification, study inclusion, data extraction, and data synthesis. We hope that this review will give more convincing proof to assist clinicians during the decision-making process when dealing with PDM. This review has some potential limitations. Different types of moxibustion therapies and the efficacy evaluation criteria of urticaria in included trials may cause significant heterogeneity.Conceptualization: Hao Wang, Xin Hui.Data curation: Hao Wang, Xin Hui.Funding acquisition: Baixiao Zhao.Investigation: Lue Ha, Baixiao Zhao, Qin Yao.Methodology: Hao Wang, Xin Hui.Resources: Baixiao Zhao.Software: Hao Wang, Xin Hui.Supervision: Lue Ha, Baixiao Zhao, Qin Yao.Validation: Lue Ha, Baixiao Zhao, Qin Yao.Writing – original draft: Hao Wang, Xin Hui.Writing – review and editing: Hao Wang, Xin Hui.Hao Wang orcid: 0000-0002-4637-6527.


To investigate the clinical significance of color visual acuity (CVA) in preperimetric glaucoma (PPG) and open-angle glaucoma (OAG).A total of 123 eyes of 73 subjects  were enrolled. CVA was tested for red, green-yellow, blue-green and blue-purple with a newly developed test.P = 0.008 and P = 0.015, respectively), although green-yellow VA and blue-purple VA were not significantly worse. Furthermore, red VA and blue-green VA were significantly correlated with MD in a group of eyes with either PPG or OAG , but green-yellow VA and blue-purple VA were not.There was no statistical difference in clinical background factors, including age, sex, intraocular pressure, or spherical equivalent between the three groups. Red VA and blue-green VA were significantly worse in the OAG eyes than in the normal eyes (Red VA and blue-green VA were detectably worse in eyes with OAG, in close association with the degree of functional loss. This suggests that measuring CVA with the new color test described here may be a promising supplement to existing methods of detecting glaucoma and evaluating its severity. Glaucoma affects over 70 million people worldwide and is the second most common cause of blindness., 2 It isFoveal function, including visual acuity (VA) and retinal sensitivity, is very important for quality of life. Even though glaucoma primarily affects the peripheral visual field, it can also affect foveal function. Previously, we found that cpRNFLT in the mid-temporal area was significantly correlated to VA in patients with glaucoma, and could accurately predict decreased VA. However,The human visual system is capable of processing chromatic  information, not only the achromatic information evaluated by conventional clinical test parameters, such as VA and contrast sensitivity. Furthermore, both the L- and M-cones are believed to be preferentially affected in experimental models of glaucoma, leading to acquired color vision loss. This suggests that the ability of the eye to sharply resolve objects of different colors, known as color visual acuity (CVA), might change with the progression of glaucoma, and that this impairment might differ with different colors. Recent research has established a method to measure CVA for the first time., 19 ThisThis was a single-center, cross-sectional study. This research followed the tenets of the Declaration of Helsinki and was approved by the Institutional Review Board of the Tohoku University Graduate School of Medicine. Written informed consent was obtained from all subjects.Normal subjects, patients with PPG, and patients with glaucoma were recruited from Tohoku University Hospital. All subjects were at least 20 years old and had refractive error within the range of +3.00 to -6.00 diopters (including some patients with emmetropia), reliable performance in visual field testing , and no cataract progression. The inclusion criteria for the normal eyes were: best-corrected visual acuity (VA) ≥ 20/20; intraocular pressure (IOP) < 22 mmHg; normal findings in slit lamp and funduscopic examinations; and a visual field within the normal limits of the Anderson-Patella classification.[The exclusion criteria for all subjects were: best-corrected VA < 20/20; central visual field defects; clinical evidence or history of ocular disorders such as corneal, retinal and neural disease; presence of blood flow-affecting systemic disease requiring medical treatment; and IOP ≥ 21 mmHg.Subjects underwent an ophthalmological and general examination, which comprised the following: slit lamp and funduscopic examination, gonioscopy, IOP measurement with Goldmann applanation tonometry, spherical equivalent (SE) measurement with auto refractometry and mean deviation (MD) measurement with SAP using the Swedish Interactive Threshold Algorithm (Standard 24–2) of the Humphrey Field Analyzer . Visual field measurements with fixation losses of more than 20%, or with more than 33% false positives or false negatives, were excluded from the analysis. MD was used for the evaluation of visual field function.In order to easily evaluate color vision performance with CVA in a clinical setting, we developed a paper-based chart. This chart showed a colored Landolt’s ring against an achromatic  background, which we carefully checked and calibrated for color accuracy. The luminance of the colored Landolt’s rings and the uncolored background were similar under various clinical lighting conditions during the initial design of the paper-based charts, as confirmed with a contact colorimeter. The chart was shown to the subjects at 3 meters after complete correction for refractive errors. We tested CVA for black-white (BW), red (R), green-yellow (GY), blue-green (BG) and blue-purple (BP). These four colors are all used in the New Color Test, a color arrangement test. The sizeP < 0.05 in the Spearman’s rank correlation test.The data are presented as the mean ± standard deviation or as percentages. The statistical analyses were performed with JMP software . The Wilcoxon/Kruskal-Wallis test (rank sums) with Bonferroni correction was used to determine the significance of differences between groups in age, IOP, SE, MD and CVA for different colors. Fisher’s test with Bonferroni correction was used to determine the significance of differences between groups in sex distribution. The Mann-Whitney U test with Bonferroni correction was used to determine the significance of differences between groups in CVA for different colors. The significance level was set at P < 0.017 in the Wilcoxon/Kruskal-Wallis test, Fisher’s test and Mann-Whitney U test. Finally, Spearman’s rank correlation test was used to evaluate single correlations between MD and CVA for each color, i.e., BW VA, R VA, GY VA, BG VA, and BP VA. The significance level was set at A total of 123 eyes of 73 subjects  were enrolled.P = 0.008 and P = 0.015, respectively), although BW VA , GY VA and BP VA were not significantly worse  was similar in the normal and PPG eyes, as well as in the PPG and glaucoma eyes . R VA anP = 0.45, P = 0.02, P = 0.01 P = 0.37, P = 0.87, Furthermore, BW VA was not correlated with MD in the PPG or glaucoma eyes , temporal perception , and color perception. The use of Landolt rings as a stimulus allows color spatial perception to be measured for each color as a logarithmic value (logMAR). Recent improvements in LCD display technology have enabled the development of a testing system to evaluate color visual performance, i.e., CVA., 19 ThisThe current study is the first to show that CVA for some colors, such as R VA and BG VA, was detectably lower in eyes with glaucoma than healthy eyes. This finding points to the role of glaucoma as a cause of acquired color vision defects. The main cause of glaucoma is elevated IOP, which can also affect the cone cells.–24 Cone Interestingly, the current study is the first to show that R VA and BG VA were associated with MD in patients with glaucoma. This result was due to our inclusion of patients with PPG in the analysis. This inclusion reflects the current view that there is a “glaucoma continuum,, 33 withThe development of simple, easy-to-use methods of detecting glaucoma and monitoring its progression is an important goal of glaucoma research. Approaches to achieve this goal include structural, functional, and blood flow analyses. Blue-on-yellow perimetry has been reported to be an early indicator of glaucoma,, 31 and Our study had several limitations. First, it was a cross-sectional study enrolling only Japanese subjects, including the healthy controls, PPG patients, and glaucoma patients. To avoid IOP-related biases, the glaucoma subjects included only patients with IOP-controlled OAG, and the PPG subjects excluded patients with ocular hypertension. This decision was made because the effect of high IOP on CVA remains unclear. The glaucoma patients were carefully selected by an experienced glaucoma specialist (T.N.). In fact, the PPG group included 7 out of 14 eyes with MD greater than 1.0 dB, while the normal group included only 2 such eyes out of 22. This, combined with the small number of PPG eyes, may explain the inverse difference between normal and PPG subjects in MD. Second, though all patients had best-corrected VA ≥ 20/20 and no patients had central visual field defects, we included patients with all stages of OAG. Thus, the OAG patients overall had relatively severe glaucoma, with a mean MD of about -8 dB. Despite this, a significant number of the OAG patients had relatively normal CVA, suggesting that future investigation of the precise relationship between MD and CVA might be valuable. Furthermore, some of the older individuals in the study are likely to have had cataract. Even if this did not significantly affect their BCVA  this may have been a confounding factor in the CVA results. Third, though we produced a paper-based color chart that minimized differences between the chromatic intensity of the stimulus and the background , there might have been some difference in intensity between the stimulus and background for the GY rings, perhaps caused by limitations of current printers. This might explain our finding that GY VA was better in all subject groups than BP VA. In principal, GY and BP VA both reflect the condition of the S-cones, and these two types of CVA should therefore be equivalent. Fourth, M- to L-quantum catches may support spatial discrimination, possibly leading to red-green color discrimination being correlated with BCVA to some degree. However, we did not obtain any results to support such an association. This might be explained by the fact that the sampling unit for color acuity is by necessity larger than for achromatic contrast, and that the color acuity test in effect assays more peripheral cells. Fifth, it is difficult to balance the color of the chart (D60) under all possible clinical light conditions, even with advanced devices, such as the Minolta CS 2000. However, we have included information on the theoretical chromaticity of the chart, and the results of Konica-Minolta FD7 measurements, to In conclusion, this study investigated changes in CVA in PPG and glaucoma patients using a paper-based chart with Landolt’s rings. We found that R VA and BG VA were detectably impaired in eyes with glaucoma, in close association with the degree of functional loss. Contrarily, CVA for GY VA and BP VA was not impaired in eyes with glaucoma, and there was no association with glaucoma severity. Our findings suggest that measuring various types of CVA with the new color vision test described here may be a promising supplement to existing methods of detecting glaucoma and evaluating its severity.S1 Table(PPTX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.