Understanding and managing ecosystems affected by several anthropogenic stressors require methods that enable analyzing the joint effects of different factors in one framework. Further, as scientific knowledge about natural systems is loaded with uncertainty, it is essential that analyses are based on a probabilistic approach. We describe in this article about building a Bayesian decision model, which includes three stressors present in the Gulf of Finland. The outcome of the integrative model is a set of probability distributions for future nutrient concentrations, herring stock biomass, and achieving the water quality targets set by HELCOM Baltic Sea Action Plan. These distributions can then be used to derive the probability of reaching the management targets for each alternative combination of management actions. In 2007, the Helsinki Commission (HELCOM) launched the Baltic Sea Action Plan (BSAP) which, by focusing on eutrophication, hazardous substances, biodiversity, and maritime activities, aims at restoring the good ecological status of the Baltic marine environment by 2021. The aims of the BSAP are supported by the EU Strategy for the Baltic Sea region, which addresses the environmental challenges of the sea through intensifying cooperation in the region and implementing the Integrated Maritime Policy in the Baltic CEC . The focAchieving good environmental status calls for the incorporation of the latest scientific knowledge and innovative management approaches into strategic policy implementation. This requires an understanding on the components, dynamics, and interactions of the complex ecosystem, and how it reacts to anthropogenic pressures. In addition to understanding the past and present state of the ecosystem, information is needed for managing the future state of the system. In large scale environmental problems, the management targets are typically set for 10–20 years. Consequently, predictions are of paramount importance, but they will be uncertain because of the stochasticity of natural systems and limitation of the current knowledge. As the Baltic Sea ecosystem is altered by several stressors at the same time, integrated analyses are needed.The cause–effect relationships between the anthropogenic stressors and harmful environmental effects should be analyzed in a manner enabling decision makers to consider the risk level of the decisions made. Technically risk is defined as the product of a probability of something environmentally harmful happening and the consequence of such event. Thus, if the research community provides a single estimate, decisions will essentially be based on overconfident information. For instance, the prediction may indicate that given an action, policy target will not be met since the predicted value is below the target value. In contrast, if decision makers are provided results in the form of a probability distribution, they get more honest information  because the frequentist approach deals only with the uncertainty about potentially observable data, it does not allow assessing uncertainty about states of nature, but (2) Bayesian approach explicitly includes knowledge in the form of a probability statement about states of nature. We advocate the Bayesian approach since it enables the use of existing information that can be updated with new information. Bayesian Belief Networks (BBNs) also are flexible in combining different risk perspectives. The technical risk definition can be effortlessly combined with the economic perspective of agents aiming at utility maximization and/or sociocultural risk definition according to which social groups assign meaning to an environmental harm Renn .Bayesian belief networks are graphic models that enable linking several risk factors and their management options in one model, and the examination of their impact on variables of management interest Jensen . In studThe IBAM project  studied several anthropogenic pressures that affect the ecosystem of the Baltic Sea, using an integrative Bayesian decision model. The project focused especially on the Gulf of Finland. In this article, we describe two subcomponents of the grand model Fig.  in more First, we present the BBN approach. Second, we give a short description of the integrative decision model, after which we describe in more detail the water quality modeling and herring analysis, concentrating on the impact of eutrophication and oil spills on the herring stock dynamics. Then, we provide some example results and discuss the advantages and challenges related to the work. Finally, we conclude by discussing the relevancy of Bayesian modeling approach to research and management.The Bayesian theory allows learning as a process in which humans constantly update their understanding of the world. In practice, problems are often structured into graphic cause–effect relationships which permit examining how an information change in one variable affects that of the other ones. The Bayes’ theorem is used to update the preunderstanding (prior knowledge) of a problem by new information, to get a novel understanding (posterior knowledge) of the issue Pearl . The strdegree of belief which means a private assessment of how likely an event is, based on the available evidence : eutrophication, unsustainable fishing, and oil spills Fig. . The euta, and Secchi depth, which can be studied in nine areas within the GoF. Finnish and Estonian coastal areas were defined according to the national implementation of the WFD, and the division of the open sea areas was based on a previous similarity analysis.The main aim of water quality-modeling efforts was to offer a way to assess how successful different loading reduction scenarios could be in meeting the water quality targets of the WFD and HELCOM BSAP. The integrative model includes five water quality variables: nitrogen, phosphorus, phytoplankton biomass, chlorophyll-Six nutrient loading scenarios were included in the analysis: Business-as-usual  for Finland, Estonia, and Russia, 100 and 50 % implementation of the Baltic Sea Action Plan for all three countries, and three alternative reduction scenarios only for Finland.The influence of external loads to the water quality in GoF is currently described by the 3D EIA-SYKE ecosystem model . The model included the relevant population dynamics variables and their dependencies in a probabilistic form. The population model incorporated different harvest mortalities, the effects of oil on juveniles and adults, the influence of eutrophication on the recruitment of the herring, i.e., the risk factors included in the integrative decision model.a concentration, sea surface temperature, salinity, and abundance of sprat (Sprattus sprattus) and cod (Gadus morhua) were used as explanatory variables to account for their impact on herring recruitment, growth rate, and natural mortality rate. In this model, chl-a concentration stands for effects of eutrophication. A Gaussian Process approach was used to produce probabilistic estimates about chl-a, sea surface temperature, and salinity. Moreover, the possible additional mortality caused by the tanker Antonio Gramsci oil spill in the GoF in 1987 was included in the model by means of previously published probabilistic knowledge of the oil-induced mortality on pelagic fishes , fishing mortalities, and the effect of uncertain oil spills, after which the results were fed into the integrative decision model.The outcome of the integrative Bayesian decision model is a set of explicit distributions for the model variables, such as nutrient concentration and the herring stock biomass in the GoF. These distributions also indicate probabilities of instances, for example, meeting the water quality targets under the alternative nutrient load reduction scenarios. In the following, we present and discuss some example results that can be produced with the model.Ptot  compared with Ntot.An example of water quality-modeling results is presented in Fig. a level, impacting herring recruitment, will be minor. Maritime safety tools are not useful either, to manage herring stock abundance . It is vital to notice that the results do not indicate that the actual water quality or an oil spill would not affect herring stock size. Instead, major changes in water quality or oil spill frequency cannot to be anticipated. Additional causes to the faint response in herring abundance are stochastic fluctuations in stock dynamics and large posterior uncertainty about the variables.Regarding the GoF herring, nutrient reduction policies have a minor effect on population abundance at all alternative oil spill and fishery management scenarios. Even the most effective nutrient reduction scenario shifts the probability mass of the herring abundance just slightly toward upper classes. This is an outcome of the fact that the predicted change in the chl-In the model, fisheries management is expressed via different fishing mortalities that the commercial fleet is allowed to exercise on the herring stock. Controlling fishing mortality notably influences herring abundance, in contrast to nutrient load and oil spill management. The closure of fishing will result in larger population size, whereas doubling the fishing mortality will end in a much lower population level . It thus appears that the society’s ability to manage the herring population in the GoF is only effective in the conventional fishery management context, where the bottomline is control of mortality and survival of fishes.Modeling was carried out by applying methods that allow for uncertainty explicitly. Such an approach has many advantages but also challenges that need to be considered carefully. Vanhatalo et al.  compareda concentration, and phytoplankton biomass will not be met, while the Secchi depth target will be achieved . Although one can conclude that the Antonio Gramsci oil reduced the GoF herring abundance, uncertainty about the level of mortality is high.a concentration, which is used as an index for all eutrophication-related changes in the ecosystem, chl-a concentration should be decreased by about 50 % from the present level to facilitate the maximum reproduction of herring at any given spawning stock size.Further, the current status of eutrophication is estimated to substantially reduce reproduction of herring . In terms of chl-Bayesian models were applied in the project to provide justified uncertainty estimates and to utilize the available data complemented with the existing scientific literature to obtain an integrated risk analysis. The use of prior information in parameter estimates is important from the point of view of effective learning in science: the information content of previous publications can be used to decrease uncertainty in future analyses by including this knowledge to prior probabilities of model parameters. In particular, this is useful when examining oil accidents or other rarely occurring phenomena.An external challenge is to introduce Bayesian approach to arenas, where the classical frequentist approaches have conventionally been applied. Among natural sciences, the ideal of objective science has dominated, and this has affected managers who may prefer “exact” advice instead of subjective probability distributions in decision-making. However, it is evident that inclusion of uncertainty is an essential part of a successful decision-making process. Point estimates oblige decision makers to be risk-neutral, which may lead to poor decisions in case the decision makers are actually risk averse Burgman . CommuniThe model described in this article and other similar kinds of BBNs can assist managers in taking management decisions related to complex environmental problems. It can also be used for prioritizing future research topics through a value-of-information (VoI) analysis. This means that the posterior distributions of the model built in the IBAM project could be used to analyze whether efforts should be directed to research focusing on eutrophication, oil spills, or the fisheries management. Such a VoI analysis shows where uncertainty can be reduced with least costs (e.g., Mäntyniemi et al. Although we find BBNs to be a flexible tool to integrate different types of knowledge and submodels, there were also some issues to be solved during the project. The major challenges were related to developing the population models, and to combine several modeling techniques coherently, e.g., the use of deterministic modeling results in a probabilistic context. Regarding the population models, a large number of prior probabilities needed to be elicited from the literature and expert knowledge, and several computational problems needed to be solved.It is also important to notice that major uncertainties exist not only within natural systems but also on the human-side of the management, i.e., the behavior of people and their commitment to management decisions is difficult to predict (e.g., Nichols et al.


Randomized control trials (RCTs) stopped early for benefit (truncated RCTs) are increasingly common and, on average, overestimate the relative magnitude of benefit by approximately 30%. Investigators stop trials early when they consider it is no longer ethical to enroll patients in a control group. The goal of this systematic review is to determine how investigators of ongoing or planned RCTs respond to the publication of a truncated RCT addressing a similar question.We will conduct systematic reviews to update the searches of 210 truncated RCTs to identify similar trials ongoing at the time of publication, or started subsequently, to the truncated trials ('subsequent RCTs’). Reviewers will determine in duplicate the similarity between the truncated and subsequent trials. We will analyze the epidemiology, distribution, and predictors of subsequent RCTs. We will also contact authors of subsequent trials to determine reasons for beginning, continuing, or prematurely discontinuing their own trials, and the extent to which they rely on the estimates from truncated trials.To the extent that investigators begin or continue subsequent trials they implicitly disagree with the decision to stop the truncated RCT because of an ethical mandate to administer the experimental treatment. The results of this study will help guide future decisions about when to stop RCTs early for benefit. The decision of whether to stop a randomized control trial (RCT) for apparent benefit before its planned completion is complex and requires consideration of ethical, statistical, and practical issues . The maiA systematic review ) developed by our group to evaluate the epidemiology and reporting quality of RCTs stopped early for benefit (truncated RCTs (tRCTs)) found that this type of trial was becoming more common, and often failed to adequately report relevant information about the decision to stop early . A subseThese results raise serious concerns about the potential impact of stopping trials early on the body of evidence and therefore on current health policies. First, investigators have disseminated an estimate of effect that is, on average, substantially overestimated; how stakeholders best incorporate this evidence in generating subsequent best estimates of effect is uncertain. Second, this represents a lost opportunity to generate more precise and higher quality evidence about benefits and harms. Third, the publication of a trial stopped early for benefit may stop further research addressing the same question, which may distort the effect size (overestimating the effect and making it more imprecise) of the whole body of evidence .There are a number of possible reasons investigators launch a new study with a similar research question to that of a tRCT, or continue one in progress . First, they may be unaware of the existence of the tRCTs. This seems unlikely, given that researchers are usually aware of ongoing research in their field, and that tRCTs are commonly published in high impact journals, and often receive appreciable media attention ,6. A secIf sRCTs are common, it suggests that current practice of stopping RCTs for apparent benefit might not be acceptable by many other scientists and not sufficiently conservative either by reaching different conclusions than the body of evidence or showing highly unreliable estimates. Understanding the decisions to initiate, continue, or begin sRCTs is likely to provide insights that ultimately improve the policies and procedures of clinical trial oversight and the credibility of clinical research.The present study aims to examine how often randomized trials are launched or continued after the publication of a tRCT asking the same or sufficiently similar research question. We will also analyze trials that were stopped in response to such external evidence. Our study involved two primary research questions. First, what is the proportion of tRCTs that are followed by a sRCT addressing the same or closely similar research question? Second, what factors/rationale are associated with the launching or continuation of a sRCT after the publication of a tRCT?The design and findings of STOPIT-1, 2, and 3 are depicted in Figure In STOPIT-3, we will search for and analyze RCTs (truncated or not sRCTs) published after the publication of each primary tRCTs. If we have a tRCT with sRCT that is also a tRCT, each study will be analyzed independently and two search strategies will be developed. This means that we will include this tRCT as a sRCT for the first tRCT, but it will be also analyzed as a tRCT itself.Following the same approach used in STOPIT-1, we will determine the prevalence of tRCTs reporting having stopped early for benefit. The methodology of this present study is summarized in Figure With input from study investigators  experienced in conducting systematic reviews, a reference librarian (PJE) will design and execute individual search strategies for each tRCT included in the database. These electronic search strategies will use controlled vocabulary and text words taking into account the characteristics of the population involved, the intervention, and comparison used. We will not consider the outcomes assessed in the tRCTs as a part of the search strategy to ensure high search sensitivity. For each tRCT, we will search the electronic databases  from the stated date of publication of the tRCTs through to the present time.In order to consider a trial as an eligible sRCT it has to be either: 1) launched  after the publication date of a matching tRCT; sRCT may, or may not, be terminated prematurely for benefit based on its own data; or 2) ongoing at the time of publication of the tRCT, and achieving the calculated sample size and planned study duration after the tRCT publication date. It does not matter whether the sRCT was stopped early or not.As a general approach we will consider trials as sRCTs of a tRCT if pooling them together in meta-analysis seems adequate. An example is shown in Figure We will use an online reference management system  for study selection. Reviewers will first calibrate their judgments using a small set of reports. Two reviewers will independently screen for potential eligibility the title and abstract of each citation that result from the search strategy. We will obtain the full text version of any citation that either reviewer deems potentially eligible.Two reviewers will independently evaluate each full text for eligibility. We will measure agreement using the kappa or phi statistics, as appropriate (the latter is appropriate when the distribution of agreement is extreme). This will be provided in real-time by the online system. Disagreements will be resolved by discussion or, if necessary, by third party adjudication. For all eligible sRCTs, during data extraction, reviewers will judge whether the patients, interventions, comparators, and outcomes match those of the corresponding tRCT as narrow (very closely matched), broad (closely matched), or broadest . For this purpose we will use the criteria previously established in STOPIT-2.Thus, we will classify each element of the sRCT  as very close (termed as 'fits the narrow criteria’), moderately close (termed as 'fits the broad criteria’), and less close (termed as 'fits the broadest criteria’) relative to the tRCT elements. We will also check the level of agreement (kappa or phi statistics) for this judgment. Disagreements in relation to similarity of one level or greater will require adjudication by a third reviewer .Based on these criteria we will classify each sRCT relative to its tRCT as: more or less identical; similar, but not identical; and broadly similar.This will be a subjective process done in duplicates. Disagreements will be resolved by consensus or, if necessary, third party arbitration Figure .We will collect data in pre-piloted standardized electronic forms designed using the online reference management system (DistillerSR). Two reviewers will independently extract the information from each report. We selected these variables  of tRCTs that had at least one sRCT.In multivariable regression, we will address the possible associations between the presence or absence of a sRCT (dependent variable) and the characteristics of the tRCTs (independent variables) including: risk of bias, magnitude of effect, number of events, funding, presence of DMC, explicit use of a stopping rule, and impact factor of journal of publication. The rationale for these variables is that increased risk of bias, small number of events, conflicts of interest, lack of DMC or stopping rule, and low journal impact factors are all possible reasons for sRCT investigators to be less convinced of the tRCT results. We will adjust the analysis by the year of tRCT publication .The risk of bias of most of the included tRCTs was assessed during the development of the previous studies using the items of the Cochrane risk of bias tool : allocatWe will calculate for each research question (tRCT and its sRCT) the optimal information size (relative risk reduction (RRR) 25%, weighted mean control group event rate, α = 0.05, β = 0.90) and Lan-DeMets sequential monitoring boundaries at the time of publication of the tRCT using all relevant trials published to that point. We will also calculate the necessary information size to obtain conclusive evidence of a plausible RRR of 25%, that is, the difference between the optimal information size and the actually available information size at the time of publication of the tRCT. We will check how close the boundary of the 95% CI of the summary effect at the time of the tRCT publication is to no effect . Lastly, we will determine if there is an association between the number of events and chances of the existence of sRCTs.In addition, we will estimate the prevalence of trials stopped early for benefit using the newly found sRCTs (after STOPIT-1) that were stopped early as the numerator, and all RCTs published in all MEDLINE-indexed journals or the subset of RCTs published in high impact journals as the denominator. Therefore, we will be able to compare the prevalence of stopping early before and after the publication of STOPIT-1 and 2, and determine if these publications had an impact on trial conduct.We plan to conduct two sensitivity analyses. The first one will be based on the closeness of the sRCTs to the research question of the tRCTs . Considering that there is no objective method to assess closeness of research questions it is plausible that investigators of sRCTs would continue their trial if their question were less close to the tRCT. We will test the impact of our assumptions it the results using a sensitivity analysis including only the sRCT-tRCT pairs with clear identical research questions according to the closeness classification given to each sRCT during the study selection phase.The second sensitivity analysis will compare two definitions of sRCTs based on the timeframes of 6 and 12 months between the publication of the tRCT and the launching of the sRCT. The rationale for this analysis is that at least 6 to 12 months are needed to assure that a sRCT is truly a subsequent trial and not a parallel trial, which would make it impossible for the investigators to be aware of the tRCT.We will contact the principal investigators of the sRCTs to further explore the reasons why they launched or continued trials after the tRCT. We will use a short, standardized web-based survey instrument developed with SurveyMonkey   workgroup , and theSTOPIT-1 and 2 described the epidemiology of trials stopped early for benefit, including how often early stopping occurs, average overestimation of effect estimates, and its predictors (truncated RCTs having fewer than 500 events). In this systematic review, we will try to measure the impact of a tRCT on the body of evidence, and determine specifically the frequency of sRCTs and determinants of their occurrence. We will try to find the ideal information size for these trials.The strengths of this study include a systematic and extensive literature search for each of the included tRCTs performed by an experienced librarian and supported by methodological experts. We will also contact authors of sRCTs, and obtain their feedback and rationale. Two reviewers with experience in the development of systematic reviews will assess each study independently, thus decreasing the risk of error and strengthening confidence in the selection process. We have a priori developed this study protocol and included sensitivity analyses to determine if the assumptions we made may affect study conclusions to a certain extension.Limitations include our reliance on published and indexed publications to identify sRCTs. Considering that the previous publication of a tRCT may reduce the chances of a sRCT to be submitted and eventually published, we are facing a new potential factor for publication bias. In addition, a known limitation of STOP-IT 1, 2, and 3 is the inaccuracy of identifying tRCTs, since truncation is frequently not clearly described in the abstracts or full reports of RCTs .The results of this systematic review will impact on the development of future trials and the decision-making process of DMCs. The ultimate goal of a DMC should be to share benefits of an effective treatment as soon as there is sufficient confidence in the magnitude of its effects, both benefits and harms . SufficiFor each sRCT which their authors knew about the existence of previous tRCT on the same research question, we can infer that authors agreed that randomizing patients continues to be ethical. In such instances, we can conclude that the stopping rule used had serious limitations. If a large proportion of tRCTs are associated with sRCTs this would mandate a re-evaluation of the criteria currently used to judge the appropriateness of stopping early for benefit.The results of this review will impact on several aspects of public interest. Many different interests converge into releasing the results earlier of a study showing significant benefits. Institutional review boards and funding agencies take into account previous research made in an area before approving a new trial. Following the same approach, journals should consider previous publications before accepting a new trial. Therefore, the publication of a tRCT may slow or prevent future trials answering the same or a similar question, generating a 'freezing effect’. It is possible that our study will identify such a freezing effect if we find an old tRCT that was not followed by any sRCTs and the body of evidence remained inconclusive after the publication of the tRCT . InferentRCTs are published in higher impact journals and gain more media attention; therefore, the media and the public may be impacted more by their results, and they may have increased confidence in the findings. However, if we find a large number of sRCTs, this may suggest that the academic community did not accept the ethical judgment of trials DMCs and trialists. This would mandate a re-evaluation of the current stopping criteria and the confidence the public should have about the findings.Given the increasing frequency of tRCTs published in high impact journals and the fact that these studies may overestimate the real effect of an intervention, it is important to evaluate the impact of tRCTs on the body of evidence. Distortion of the body of evidence can subsequently lead to biased systematic reviews, and impact guideline recommendations and patient care.The systematic review is currently in full text screening phase. Completion is expected by November 2013.CI: Confidence interval; DMC: Data monitoring committee; ISPOR: International Society for Pharmacoeconomics and Outcomes Research; PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses; RCT: Randomized control trial; RRR: Relative risk reduction; sRCT: Subsequent randomized control trial; STOPIT: Study of Trial Policy of Interim Truncation; tRCT: Truncated randomized control trial.The authors declare they have no competing interests.GJP has been involved in the organization of the project since the beginning , wrote the first version of the manuscript, and was in charge of its development. JPD has been involved in the organization of the project since the beginning , collaborated with the first version of the protocol, reviewed it, and approved it before submission. PJE designed the search strategies for the project and reviewed the protocol. MB conceptualized the study, supervised all the process, and reviewed the manuscript before submission. VMM collaborated with the first version of the protocol, reviewed it, and approved it before submission. EAK, JJM, DB, SS, SDW, QZ, PAC, LM, MW, KT, PG, RK, IFG, JB, XS, AK, BK, OQA, GP, HP, and GU are reviewers and reviewed and provided feedback to the manuscript before submission. MHM participated in the design of the study, performed the statistical analysis, and reviewed and approved the manuscript before submission. GG participated in the design of the study, performed the statistical analysis, and reviewed and approved the manuscript before submission. All authors read and approved the final manuscript.Variables to be extracted.Click here for fileForm for contacting the authors of sRCTs.Click here for file


The large amount of information contained in bibliographic databases has recently boosted the use of citations, and other indicators based on citation numbers, as tools for the quantitative assessment of scientific research. Citations counts are often interpreted as proxies for the scientific influence of papers, journals, scholars, and institutions. However, a rigorous and scientifically grounded methodology for a correct use of citation counts is still missing. In particular, cross-disciplinary comparisons in terms of raw citation counts systematically favors scientific disciplines with higher citation and publication rates. Here we perform an exhaustive study of the citation patterns of millions of papers, and derive a simple transformation of citation counts able to suppress the disproportionate citation counts among scientific domains. We find that the transformation is well described by a power-law function, and that the parameter values of the transformation are typical features of each scientific discipline. Universal properties of citation patterns descend therefore from the fact that citation distributions for papers in a specific field are all part of the same family of univariate distributions. The use of bibliographic databases plays a practical, and crucial, role in modern science. Citations between scientific publications are in fact commonly used as quantitative indicators for the importance of scientific papers, as proxies for the influence of publications in the scientific community. General criticisms to the use of citation counts have been made As a matter of fact, citation practice is widespread, still basic properties of citation patterns are not completely clear. For example, we know that citations are broadly distributed, but, we do not know the exact functional form of citation distributions. In his seminal paper, de Solla Price proposed a power-law model for explaining how papers accumulate citations Annals of Mathematics, has impact factor Cell, has impact factor At the same time, it is common practice to attribute the same value to each citation, in spite of the fact that citation counts strongly depend on the field et al.et al.Although methods based on percentile ranks have been recently considered Here, we perform an exhaustive analysis of about We propose a transformation of raw citations numbers such that the distributions of transformed citation counts are the same for all subject-categories. We study the properties of this transformation and find strong regularities among scientific disciplines. The transformation is almost linear for the majority of the subject-categories. Exceptions to this rule are present, but, in general, we find that all citation distributions are part the same family of univariate distributions. In particular, the rescaling considered in For the same year of publication, the raw citation patterns of single subject-categories may be very different. Variations are a consequence of different publication and citation habits among scientific disciplines. In In order to make further progress, here we invert the approach to the problem. We know that citation patterns of single subject-categories may be different, but we do not know how to transform citation counts in order to make them similar. We implement therefore a mapping able to make all cumulative distributions coincide, and study the properties of this transformation. We use a sort of “reverse engineering” approach: instead of introducing a transformation and checking whether it works, here we impose that the transformation must work and from this assumption we derive its precise form.The idea is pretty simple and straightforward. We use as curve of reference the cumulative distribution ries see . The choique see .vs.The plot ping see . The funping see , and S7.The citation distributions of the subject-categories for which Eq. 1 holds are univariate distributions belonging to the same log-location-scale family By definition, the transformation The fact that all cumulative distributions of transformed citation counts coincide seems able to place all subject-categories on the same footing: when raw citations are transformed according to Eq. 2, the fraction of papers with a given value of the transformed citation counts is almost the same for all subject-categories. To quantitatively assess such a qualitative result, we perform an additional test. The aim of the transformation of Eq. 2 is to suppress inevitable biases in raw citation counts among subject-categories, and thus we compare our results with the outcome expected in the absence of biases.The situation can be modeled in the following terms. We aggregate all papers of all subject-categories together, and extract the top The results of this analysis are reported in the  see . For theThe values of the transformation factor Moreover, the transformation factor The inset of . AccordiThe practical importance of citation counts in modern science is substantial, and growing. Citation numbers  are commonly used as basic units of measure for the scientific relevance not only of papers, but also of scientists Differences in citation patterns among scientific domains have been known for a long time In this paper, we consider a different notion of fairness, based on the reasonable but strong assumption that each discipline or field of research has the same importance for the development of scientific knowledge. A fair numerical indicator, based on citation numbers, must then assume values that do not depend on the particular scientific domain under consideration. Under this assumption, the probability to find a paper with a given value of the fair indicator must not depend on the discipline of the paper, or equivalently, the distribution of normalized indicators must be the same for all disciplines. It is clear that our notion of fairness strongly depends on the classification of papers into categories . Also, it is important to remark that other possible definitions of fairness could be stated, without relying on the assumption that each discipline or research field has the same importance for scientific development.We have then proposed a simple but rigorous method for the implementation of our notion of fairness. We have studied the citation patterns of papers published in more than In general, all results obtained in this paper could seem to be explained by assuming that the citations received by papers in each subject-category are continuous variables obeying log-normal distributions. However, this is only approximately true. First, citations are, by definition, non negative discrete numbers. Secondly, even assuming their discreteness, the distribution of citations received by papers within the same subject-category is not statistically consistent with a discrete log-normal distribution. We systematically tested this hypothesis for all subject-categories and publication years, and found that the log-normality of citation distributions cannot be rejected only for a very limited number of subject-categories  need to be quickly taken. The use of citations is already a common practice, and in the near future will become a necessity. As individuals directly involved in this business, we should therefore develop the best methodologies able to avoid the misuse of citation numbers.We considered papers published in six distinct years: The statistical test proposed here is very similar to the one introduced in Supporting Information S1Publication types and language of publications.(PDF)Click here for additional data file.Supporting Information S2Complete analysis for publication year .(PDF)Click here for additional data file.Supporting Information S3Complete analysis for publication year .(PDF)Click here for additional data file.Supporting Information S4Complete analysis for publication year .(PDF)Click here for additional data file.Supporting Information S5Complete analysis for publication year .(PDF)Click here for additional data file.Supporting Information S6Complete analysis for publication year .(PDF)Click here for additional data file.Supporting Information S7Complete analysis for publication year .(PDF)Click here for additional data file.Supporting Information S8Summary figures for all years of publication.(PDF)Click here for additional data file.Supporting Information S9Log-normal fit of the citation distributions.(PDF)Click here for additional data file.


AbstractFlatidae in Madagascar and indicates future prospects. While the first two species of Madagascar Flatidae were described by Hemiptera fauna of Madagascar by describing several additional species. Over the following century and a half, several investigators have turned their attention to this group of insects, with the final number of species recorded for the island reaching 79. Despite this long history of research, it is evident that much still remains to be done. Detailed taxonomic research will allow the natural history of Madagascar and changes in the biological diversity of its endemic ecosystems to be better understood. This paper should be considered as an introduction to a complex study on the systematics and phylogeny of worldwide Flatidae planthoppers.The paper provides a historical review of the research on  Flatidae constitute one of the largest families within planthoppers  with 1446 species described in 299 genera and 12 tribes distributed worldwide , a flatid species introduced into Italy from USA in 1973  gave a drawing and a short note on Flata malgacha  and Flatoides tortrix in the work Iconographie du Règne Animal . Moreover, the second half of 19th century was the realase of further papers by such eminent naturalists-hemipterologists as Carl Stål (1833–1878) and Ferdinand Karsch (1853–1936), which provided descriptions of additional representatives of Madagascan Flatidae  and Jacques Auber (1916–1995)  , 1955. Iaracters . He alsoaracters . Althoug flatids , 2001, ntoidinae .Flatidae meet these criteria and so might serve as an appropriate environmental indicator. According to Prof. Thierry Bourgoin from The Natural History Museum in Paris, this is the most abundant and easily collected group of the hemipterans in Madagascar (pers. comm.). Yet, the knowledge of the group is still very limited.The accurate and rapid measurement of patterns of species richness, species turnover, and endemism is fundamental to current conservation efforts in Madagascar . One appFlatidae as a model group of phytophagous insects could be the solution for these needs, especially in relation to rare and endangered ecosystems. One of these is tapia woodlands – a short, endemic, sclerophyllous forest formation in Madagascar, with dominant canopy tree species Uapaca bojeri Baillon, 1874 or tapia in Malagasy. It can be found in four zones located in the central and southern part of the island, covering approximately 2600 km2  will also be included. Additionally, as a novelty, we will provide analysis of Flatidae female genital structures.Summarizing, despite a long history of observation and investigation, the state of knowledge of Madagascar’s Flatidae planthoppers. It aims to clear up views on the species variability and diversity, create a modern classification system, and know in detail all the world genera and species. The goal of the long-term project is to complete the work on cladistic analysis, phylogeny and the evolutionary scenario proposal for the family.With respect to biodiversity and endemism, the basic parameters of the distribution, dispersal and zoogeographic status have yet to be understood. Furthermore, distinguishing species characteristic for particular vegetational formations is key to understanding the dynamics of endangered ecosystems. The revision will make it possible to estimate the level of endemism of Madagascan flatid fauna and its connections with the fauna of Oriental and Afrotropical regions. The project presented above is the first step in a complex study on the systematics and phylogeny of worldwide PageBreak


Brazil and Colombia have pursued extensive reforms of their health care systems in the last couple of decades. The purported goals of such reforms were to improve access, increase efficiency and reduce health inequities. Notwithstanding their common goals, each country sought a very different pathway to achieve them. While Brazil attempted to reestablish a greater level of State control through a public national health system, Colombia embraced market competition under an employer-based social insurance scheme. This work thus aims to shed some light onto why they pursued divergent strategies and what that has meant in terms of health outcomes.A critical review of the literature concerning equity frameworks, as well as the health care reforms in Brazil and Colombia was conducted. Then, the shortfall inequality values of crude mortality rate, infant mortality rate, under-five mortality rate, and life expectancy for the period 1960-2005 were calculated for both countries. Subsequently, bivariate and multivariate linear regression analyses were performed and controlled for possibly confounding factors.When controlling for the underlying historical time trend, both countries appear to have experienced a deceleration of the pace of improvements in the years following the reforms, for all the variables analyzed. In the case of Colombia, some of the previous gains in under-five mortality rate and crude mortality rate were, in fact, reversed.Neither reform seems to have had a decisive positive impact on the health outcomes analyzed for the defined time period of this research. This, in turn, may be a consequence of both internal characteristics of the respective reforms and external factors beyond the direct control of health reformers. Among the internal characteristics: underfunding, unbridled decentralization and inequitable access to care seem to have been the main constraints. Conversely, international economic adversities, high levels of rural and urban violence, along with entrenched income inequalities seem to have accounted for the highest burden among external factors. Latin America is a vast, heterogeneous land, composed of a multitude of cultures and traditions. Nevertheless, a common heritage is sadly persistent: entrenched social and health inequalities. While in 2005 a child in Cuba had a better chance of surviving to age 5 than one living in the United States, a child from Haiti had a worse chance of reaching the same age than one from Namibia . On the Colombia and Brazil, the two most populous countries of South America, face similar struggles within their own borders. Bearing the largest Gini coefficients of the region: 0.564  vs. 0.5849 , their political leaders decided in the late 1980s and early 1990s to attack some of the underlying causes of those disparities. Many social policies were then instituted. Among them, two of the most profound and far reaching were the reforms of their health care systems. Remarkably, despite the fact that such reforms were initially pursued just 5 years apart from one another, each country ventured in almost opposite directions. While Brazil sought to reestablish a greater level of State control through a public national health system, Colombia embraced the philosophies of employer-based social insurance and market competition.A) How effective have these reforms been in reducing health inequities? B) How do these reforms compare to one another? C) What lessons can be learned from the respective reform processes?The present study thus aims to shed some light onto why they pursued different pathways and what that has meant in terms of health outcomes. Some of the questions addressed by this work include: Health inequities have been the subject of a thriving debate in the last few decades, drawing contributions from philosophers, economists, social scientists and physicians alike. Despite the variety of perspectives, they all seem to stem from the empirical observation that while the world is now materially richer than in any other point in known history, thousands continue to suffer and die every day due to preventable and treatable diseases. Furthermore, the widening gap in health status between developed countries and developing countries, as well as between the rich and poor segments of societies within many countries, seems to invoke a sense that something is wrong.Spurred by such troubling thoughts, several bodies of theories have emerged. Most of them can be grouped into five categories: utilitarian approaches, communitarian theories, egalitarian theories, libertarian (market-based) approaches, and deliberative democratic procedures. Ranging the gamut from consequentialist (concerned with outcomes) to proceduralistic (concerned with the process), each set of approaches has its strengths and weaknesses. In summary, utilitarian theories of health care justice require that resources be allocated in order to maximize net social utility. It is not concerned with individual inequities as long as society as a whole is better off. Communitarian theories express that there are no universal norms of social justice, but rather that those are constructed by each society through a process of social and political evolution. Under this framework, if a given society values other goals higher than health, then it has no overarching responsibility to secure it for its members. Egalitarian theories embed two different approaches: one sees that everyone is entitled to the same level of health achievement while the other believes that everyone is entitle to equal opportunities of achieving good health. While the former has a value preference for the outcomes, the latter values more the means to achieve them. Libertarian perspectives take a more blatant position: society has simply no obligation to address social or health inequalities because any measure to do so would imply redistributive policies that ultimately infringe on individual liberties . TherefoAs interesting an exercise as this would be, it is beyond the scope of the present work to further dissect the different ethical perspectives. For the motivated reader who would like to do so, the thorough review presented in the first chapter of "Health and Social Justice"  is an enavoidable, unnecessary and unfair  and a duty of the State, guaranteed by social and economic policies aimed at reducing the risk of disease and providing universal and egalitarian access to actions and services for its promotion, protection and recovery" (author's translation). Article 198 defined that health care was to be provided by a hierarchical, regionalized network of services that would constitute the Unified Health System. Its main principles would be decentralization, integral care and community participation [After more than two decades of dictatorship, the democratic Brazilian Constitutional Assembly finally defined health as a right in the National Constitution of 1988. According to Article 196: "cipation . ConversThus, a series of federal laws and ordinances were enacted in the following years to clarify those issues. Federal Law 8080 of 1990 defined as attributions of SUS: the delivery of preventive and curative services , the epidemiologic and sanitary surveillance, as well as the regulation of the entire health care system. It created the National Health Fund, from which all federal transfers to States and Municipalities would be made. It also regulated the participation of private providers within SUS and forbid foreign capital from participating in the domestic health care market. Federal Law 8142 of 1990 created the framework for social participation within SUS, by creating health councils in each sphere of government and mandating that half of its composition be assigned to patient representatives. The Basic Operational Norm of 1996 (NOB/1996) and the Operational Norm of Health Assistance of 2001 (NOAS/2001) specified the duties and responsibilities of each federative entity and how they would relate to one another. They also established the mechanisms of the intergovernmental transfer of resources and the conditions that States and Municipalities must meet in order to receive those funds.In 2000, Constitutional Amendment 29 attempted to increase the level of public health expenditures by mandating minimal budgetary floors for Federal, State and Municipal health budgets. While State governments were required to assign 12% of their income to SUS, Municipal governments were required to assign 15%. Meanwhile, the Federal government was required to yearly increase their health budget by the nominal variation of the Gross Domestic Product (GDP). Nevertheless, the Amendment had a major shortcoming. It did not define what could be considered as health expenditure. As a result, several state and local governments included in their health budgets expenses that were previously assigned elsewhere  in order to meet the new constitutional requirements, instead of incrementing Public Health activities or improving the delivery of care.Unified Health System ; the other is restricted to public employees (mainly military and high ranking civil servants), and it is financed by a traditional social insurance model based on contributions from public employees and the federal government.The health system in Brazil is mixed and segmented into two subsystems: one public and one private, with separate financing streams. The public subsystem has two segments: one provides free universal access , fully financed by public resources , called the The provision of services in SUS is usually carried out by public providers under the control of State or Municipal Health Departments, although it is possible to contract out to private providers. When doing so, laws give clear preference to other public non-governmental entities (e.g. universities) and not-for-profit Non-Governmental Organizations (NGOs). Alternatively, for-profit providers face severe restrictions to provide care under SUS. Another important aspect of current regulations is that regardless of who delivers the services, Health Departments are deemed co-responsible, and therefore liable, for any malpractice by contractors.supplementary system and encompasses several modalities of health insurance. Participation is voluntary, and it is financed either with resources from employers and employees (the rates of contribution are freely negotiated between the parties) or exclusively by individual families. The second segment offers direct access to private providers through out-of-pocket payments [The private subsystem is also comprised of two segments, both of which benefit from some form of fiscal incentive: the first is known as the payments . It is wSince 1999, individual health insurance policies are overseen by the National Agency for Supplementary Health , which has standardized three types of benefit packages that insurance companies can offer. The first covers just outpatient care, the second inpatient care and emergency services, and the third covers all of the above. Each package has a required set of diagnostic and therapeutic procedures that have to be covered. Insurance companies are free to define their providers' network and pricing policies, but are forbidden from excluding anyone on the basis of pre-existing conditions (i.e. cream-skimming). They can, however, deny care for pre-existing conditions for up to two-years. Furthermore, every year they must request an authorization from ANS for any increase in premiums. The main caveat of this legislation is that group insurance policies  are exempt from most of those requirements, resulting in much greater diversity of coverage.The old health care system in Colombia was a three-tiered system, comprised of a public sector, a social insurance sector and private insurance. The Public Sector was publicly provided within the National Health System  and financed through general taxes. It developed considerably between 1975 and 1984, when it experienced a large increase in the number of hospitals, health care centers and personnel. However, the fiscal crisis of 1982 reduced public health care expenditures from 8% of the national budget to less than 4% on subsequent years . BesidesThe social insurance sector provided coverage to 15% of the population through the Colombian Social Security Institute , for those employed by the formal private sector, and the Public Provision Funds  for the majority of civil servants. This was one of the lowest rates in Latin America and the rate of tax evasion in these segments was fairly high, as only 50% of those required to contribute to the system actually did so . In addiColombia's health care reform was as much a product of international influence by actors such as the World Bank and the Pan American Health Organization as it was part of a modernizing agenda brought by the national executive branch. Designed and implement by an external "change team"  harboredThe decentralization of the public health sector started with Decree 77 of 1987 and Law 10 of 1990. In 1993 it was further emphasized by Law 60 and culminated with the reform of the entire Social Security System of Colombia enacted by Law 100. The latter were greatly influenced by the Constitutional Reform of 1991, which strongly promoted the decentralization of public services to sub national levels and ended governmental monopoly over public services, including health care .Law 100 changed the organization, financing and delivery of Colombia's health care system, mandated the creation of a new system for the financing and delivery of health care, allocating public funds directly to individuals instead of institutions , therebyLaw 100 models individual health care services differently from traditional Public Health functions. Whereas the latter are seen as public goods and as such to be funded by public funds, the former are seen as goods with intrinsic individual value, for which consumers would be willing to pay. As such, individual health care services were reorganized as to become part of a National Health Insurance (NHI) scheme under a market-driven framework, which incorporated principles of managed competition .The most important mechanisms of managed competition introduced in Colombia health care model were: 1) the mandate that all workers in the formal sector participate of NHI; 2) the existence of one single collecting fund to each all resources flow to, called the National Fund of Security and Guarantees ; 3) the establishment of a new payment mechanism to insurers, through a risk-adjusted capitation system; and 4) the definition of a standardized package of benefits to be offered to all insurance beneficiaries, called the Mandatory Health Plan  .Alleging resource constraints, the NHI was in effect designed as a two-tiered system, composed of the Contributory Regime (CR) and the Subsidized Regime (SR). The CR included all formal sector employees or independent workers with ability to pay who were already enrolled in some form of either private or public insurance, extending coverage to their families. Formal workers were set to contribute an equivalent to 12% of their salary, of which 4% was to be paid by the employee and 8% by the employer. Independent workers would pay the full 12% starting from a floor of 2 minimum wages. The SR targeted the poor and indigent population by providing subsidies to the insurance premium from specific public resources and contributions from the CR. For instance, a percentage point from payroll taxes was to be channeled to the SR. Tax revenues from several sources and social investment transfers to municipalities were also to be earmarked for health. Among these were new resources from oil revenues and matching funds by the national government to FOSYGA, the solidarity fund .As resources became available, expansion in insurance coverage for the population eligible for subsidies would be accompanied by gradual additions to the benefits package. It was expected that both regimes would have identical coverage of benefits by 2000, so that a single universal health insurance system could be implemented throughout the nation . Howeverde facto privatized.The delivery of services was to be carried out by both public and private providers, which would compete among themselves under the watchful eyes of regulatory authorities. Nevertheless, due to funding constraints and cumbersome administrative structures, public hospitals have lost the upper hand to private providers. Consequently, 14 years later, most of the provision of health care services in Colombia has been Although several different methods have been suggested to evaluate the performance of health systems -26, and The data for outcome variables was drawn from BADEINSO, a cross-national database of social indicators produced by the Economic Commission for Latin America and the Caribbean (ECLAC) . It contThe four primary outcome measures (dependent variables) in this study were crude mortality rate , infant mortality rate , under-five mortality rate , and life expectancy at birth (LEXP - the expected average life-span measured in years). The main control variables were gross domestic product (GDP) per capita, converted to constant 2000 U.S. dollars), fertility rate (number of births per woman), population growth  and rural population . The first step in this analysis was to decide what would be time interval used to evaluate the time series. Considering several gaps in the data, a 5-year interval was chosen, covering the period 1960-2005. Subsequently, when data for any specific time point was missing, the respective value was estimated from a five-year average of adjacent years. As a result, a total of 10 observations for each country were obtained for each variable.x = | Xoptimal - Xactual | SI, where X represents the value of the indicator being analyzed in each given year of the time series.The second set of outcome variables  was calculated by comparing the actual value of the original indicators for each of the two countries against the optimal average value for Latin America and the Caribbean in order to obtain the absolute shortfall inequality for each country in each given time period, using the following equation: Finally, in order to evaluate the reform, two dummy variables were created. The first one was created to represent whether any given time point was either before or after (pre/post) the health care reforms. The second one was created to represent how many years had elapsed since the reforms. The years in which the major legislative changes were enacted  were defined as the break points for each country time series.For each outcome variable, the time-series values for Brazil and Colombia were plotted against the optimal average value for the region (Latin America and the Caribbean).Overall characteristics of each variable were assessed by univariate analysis. Subsequently, control variables were tested for correlation. High values (greater than 95%) were found among them. As a result, GDP per capita was chosen as the sole control (independent) variable in the multivariate models in order to avoid multicollinearity. Bivariate analysis examined unadjusted relationships between the outcome variables and the overall time trend as well as the reform. Bivariate correlations were analyzed with the t-test. The null hypothesis in all the tests was that the health care reforms had no impact in the reduction of health inequities, whether analyzed separately for each country or when compared to the optimal regional average value .Multivariate analyses were performed using ordinary least square regression. Separate sets of models were used for each country (Brazil and Colombia), for each outcome (dependent) variable. To test for a change point difference (i.e. to see the impact of the reforms in each outcome variable), two approaches were used. The first approach was to fit models which included the year span and the second reform dummy, in order to assess the impact of the reform while controlling for the overall time trend. Subsequently, this initial model served as the basis for another model, which included the variable GDP per capita to also control for economic development. The second approach was to perform predictive Chow tests in all of the above models, in order to test for structural change by evaluating whether the coefficients in the regression model were the same in the separate subsamples (pre/post reform).2 and partial-F tests. Two-tailed p-values are reported for all analyses. All statistical analyses were performed using SAS® and Microsoft Excel®.As expected by the nature of time-series analysis, two of the dependent variables (IMR and U5MR) presented second-order lag influence in the linear regressions of the Brazilian data using the first set of models (time trend + reform). Accordingly, new estimates were obtained by correcting for the autoregressive parameters. No other adjustments were made. Multivariate linear regressions were validated using adjusted-RThe graphic analysis of the time-series trend data for crude mortality rate shown in Figure 0.16893 per year) and Colombia (-0.16183 per year). The predictive Chow test also confirmed that a break in the time-series seemed in fact to have happened at the time each one of the reforms was enacted. Indeed, the average crude mortality rates for the post-reform periods were 4.01080 units smaller for Brazil and 3.20810 units smaller for Colombia.The bivariate analyses of the baseline values of crude mortality rate showed a persistent, and similar, trend of reduction in this rate for both Brazil  and Colombia (-1.42364 per year). The predictive Chow test suggested that a break in the time-series seemed to have happened at the time the reform was enacted in Brazil but not so in Colombia. Nevertheless, the average infant mortality rates for the post-reform periods were both substantially smaller: -61.66667 in Brazil and -30.88095 in Colombia.The bivariate analyses of the baseline values of infant mortality rate showed a much steeper trend of reduction in this rate than in the crude mortality rate, both for both Brazil (-1.19610 vs. 1.54147). Both results were statistically significant at p < 0.0001 and p = 0.0164, respectively. As shown in Table The multivariate analyses of the baseline values pointed out that such gain might not have been due to the reforms. Instead, the original time trend seems to have remained the main driver, even after the reforms were enacted. In fact, when that effect was controlled for, each subsequent year after the reforms saw the slowdown of the reduction of the infant mortality rate in both countries. Nonetheless, the downturn in Brazil seems to have been less pronounced than in Colombia  and Colombia (-2.46303 per year). Results from the predictive Chow test once again implied the presence of a significant break in the Brazilian time-series but not the Colombian. Nonetheless, the average under-five mortality rates for the post-reform periods were substantially reduced in both countries: -84.50000 in Brazil and -52.09524 in Colombia.The bivariate analyses of the baseline values of under-five mortality rate exhibited a slightly greater trend of reduction in this rate than in the infant mortality rate, both for both Brazil (-3.10686 /reform years: 3.18061). Both results were statistically significant at p < 0.0001 and p = 0.0095, respectively. As shown in Table The multivariate analyses of the baseline values pointed out that such improvement was slowed down in the years after the reform, to the point of nearly reversing the trend in Colombia , although not statistically significant. More startling was the impact in Colombia, where reform years increased the shortfall inequality by 1.66040 a year (p = 0.0134), all but erasing the progress represented by the underlying trend of -1.76641 (p < .0001). The introduction of GDP per capita into the model produced no significant changes in the analysis.When shortfall inequalities were evaluated Table , the bivThe graphic analysis of the time-series trend data for life expectancy shown in Figure 0.38764 year gained per calendar year vs. 0.36424), which justifies their near tie in 2005. Accordingly, the predictive Chow test for the time trend was statistically significant only for Colombia, meaning that the break point represented by the reforms was not observed in Brazil. Unfortunately, that was not necessarily a positive outcome, quite the opposite.The bivariate analyses of the baseline values of life expectancy confirm the expectations geared from Figure -0.23368 per year; p = 0.0090) in the years after the reform in Colombia. Conversely, such period in Brazil produce only a non-statistically-significant (p = 0.0678) reduction of -0.03861 per year. No significant additional effect was observed when GDP per capita was included in the model.As the multivariate analyses showed in Table 0.21585 per year, overriding the underlying reductionist time trend of -0.19078 per year. In the case of Brazil, no statistically significant change was observed in the multivariate analysis, except for the time trend, which was significant in both multivariate models (p < .0001). The introduction of GDP per capita into the model only produced significant changes in the analysis of the Colombian time-series, where it also acted against the reduction of the shortfall inequalities in life expectancy.When shortfall inequalities were evaluated Table , the bivMany countries in Latin America have undergone substantial reforms of their health care systems in the last twenty years. Measuring their impact on health outcomes is crucial to understand how effective they have been in achieving their stated goals -31 of prhealth capability paradigm [crude mortality rate, infant mortality rate, under-five mortality rate and life expectancy), but also assessed their success in reducing the shortfall inequalities in those variables when measured against the corresponding optimal values in Latin America and the Caribbean.The present work thus attempted to redress those issues by utilizing internationally standardized time series data for Brazil and Colombia, covering the period from 1960 to 2005. Another innovation introduced by this study was that it is the first to compare the achievements in health functioning for Brazil and Colombia within the context of the paradigm . As a rethe years after the reform often saw the deceleration of the pace of improvements in both countries for all the variables analyzed. This effect was even more pronounced in Colombia, where some of the previous gains in the under-five mortality rate and the crude mortality rate were reversed.The results of the analyses of the baseline values of each country showed that while both of them succeeded in improving those indicators throughout the time period of the analysis, the impact of their health care reforms was much less tangible. In fact, in most cases they were not able to alter the underlying time trend already in place when the reforms were enacted. However, when they did influence the outcomes, the outline was inevitably negative. In other words, p = 0.0242) and shortfall inequality of life expectancy in Colombia (p = 0.0262). When it did so, its influence was to increase the inequities.The subsequent analyses of the shortfall inequalities further aggravated the perception that the health care reforms of Brazil and Colombia did not contribute to the reduction of heath inequities. When controlling for the underlying time trend, neither reform produced a statistically significant positive contribution to any of the variables studied. On the contrary, their respective impacts were often counterproductive. Consistent with the above results, Colombia fared once again worse than Brazil. In fact, both in life expectancy and crude mortality rate the average measured effect of the reform years overturned the historical time trend and effectively increased shortfall inequalities among those variables. Also worth noticing is the fact that GDP per capita, used as a control in the second model of the multivariate linear regressions, only had a statistically significant impact in two of them, namely: shortfall inequality of crude mortality rate in Brazil  and 0.563 for Colombia (2003).This study has found that the health care reforms of the late 1980s in Brazil and early 1990s in Colombia do not seem to have had a positive impact in improving the crude mortality rate, the infant mortality rate, the under-five mortality rate or life expectancy when controlled for the underlying historical time trend. On the contrary, for all studied variables, the progress that otherwise would have been expected appeared to have been deterred in the years after the reforms were enacted. In the case of Colombia, such deterrence all but overturned previous achievements. The reasons for such failures are likely to be related both to the specific design of the reforms themselves, as well as external factors. Underfunding, unbridled decentralization, and inequitable access to care seem to be the main drivers among the former. Concerning the latter, the major impediments might have come from economic adversities, high levels of rural and urban violence, along with entrenched income inequalities.Fortunately, governments in both countries seem to have awakened from those problems and have recently proposed measures to correct the flaws in the design and implementation of their respective health care reforms ,38. NeveLikewise, in order to be able to inform, policymakers need evidence of what type of policy works best in each circumstance and what to expect from them. The aim of the present work was precisely to help fill this gap. I believe the results of this study can shed some light into the shady corners of health care reforms and further advance the quest for equity in Latin America.I declare no competing interests.Although I am presently a government official at the Ministry of Health of Brazil, the research presented in this article was conducted before my governmental appointment, during my Master of Public Health at Yale University. The views and standpoints presented here are solely mine, and do not necessarily represent those of, or are sanctioned by, either the Ministry of Health of Brazil or Yale University.


JAMA, across a 20-year period, with a focus on implications for medical education.Statistical training across the continuum of medical education may not have advanced at the pace of statistical reporting in the medical literature, yet a comprehensive understanding of statistical concepts most commonly presented in current research is critical to the effective practice of Evidence Based Medicine. The objective of this content analysis was to describe statistical techniques used in a leading medical journal, JAMA published each month in 1990, 2000, and 2010 were randomly selected; from these, 361 articles were reviewed. Primary focus, study design, and statistical components were abstracted and examined by year of publication. The number of published RCTs and cohort studies differed significantly across years of interest, with an increasing trend of publication. The most commonly reported statistics over the 20-year period of interest included measures of morbidity and mortality, descriptive statistics, and epidemiologic outcomes. However, between 1990 and 2010, there was an increase in reporting of more advanced methods, such as multivariable regression, multilevel modeling, survival analysis, and sensitivity analysis. While this study is limited by a focus on one specific journal, a strength is that the journal examined is widely read by a range of clinical specialties and is considered a leading journal in the medical field, setting standards for published research.Two issues of The increases in frequency and complexity of statistical reporting in the literature over the past two decades may suggest that moving beyond basic statistical concepts to a more comprehensive understanding of statistical methods is an important component of clinicians' ability to effectively read and use the medical research. These findings provide information to consider as medical schools and graduate medical education training programs review and revise their statistical training components. Teaching and using statistics across the spectrum of medical training is a key issue in medical education today. Much of the recent attention relates to the impending addition of statistics questions to the Medical College Admissions Test (MCAT) 2015, required for admission by most U.S. medical schools, signaling a shift in focus in medical school preparation from the traditional premedical sciences to other aspects of population health New England Journal of Medicine found that approximately half of articles published in 1978–1979 were accessible with knowledge of only basic descriptive statistics  While increasing attention has been given to teaching and using statistics in medical education across the continuum of lifelong learning Traditionally, statistics courses have not been part of the required pre-medical curriculum, which focuses largely on the basic biological and physical sciences. Even through the mid-1990s, not every medical school included statistics as part of its medical student curriculum. In 1993, a survey of 100 medical schools found that only 83% offered a statistics course as part of the undergraduate medical curriculum, and none of the schools surveyed required statistics for admission what should be taught and reinforced throughout medical training. Rather than asking if future physicians should be required to learn and use statistics, the question becomes “What type and depth of statistics do future physicians need to know?” A critical element needed to address these issues is evidence from the medical literature regarding common statistical measures and approaches published today and how this relates to that published in previous decades. Thus, and as a starting point, the current study was a content analysis that reviewed the statistical measures and techniques reported in the Journal of the American Medical Association (JAMA) and examined how the nature and use of statistics in the literature has changed over the last 20 years. JAMA was specifically chosen due to its reputation for being read by a diverse clinical audience in a range of specialties and for publishing high-quality research that contributes to EBM.With the renewed interest in statistics as part of medical training comes the question of Journal of the American Medical Association (JAMA) published in the years 1990, 2000, and 2010. A random number generator in Excel was used to select two weekly issues of JAMA from each month within each year of interest. In situations where a special theme edition was among the weekly issues randomly selected, that issue was excluded , and the subsequent issue was selected for review. All articles within those issues selected were then evaluated for eligibility; eligible articles were those in which authors implemented a study and analyzed primary or secondary data. Specifically, the following categories of articles were eligible for inclusion: original contribution, clinical investigation, brief report, preliminary communication, clinical review, caring for the critical ill patient, concepts in emergency and critical care, toward optimal laboratory use, review, and rational clinical examination. As commentary, editorial, clinical crossroads, clinical crossroads update, special communication, and consensus statement articles did not involve primary or secondary data analysis, they were excluded from the study.To conduct this content analysis, a stratified random sample of Journal issues was identified, and articles published within these issues examined for statistical content . The samA reading schedule was created using the Microsoft Excel random number generator to determine month order for reading. Year order within each month was also randomly determined. For example, January articles might have been read in the order of 1990/2010/2000, while March could be read in the order of 2010/2000/1990. Two readers with masters-level training in public health were assigned data abstraction schedules, in which months were read in the same order, but the year and issue orders within each month were rotated for the purposes of minimizing fatigue bias.The readers independently abstracted data pertaining to the type of article (as determined by Table of Contents), primary focus, study location, design, data source (s), collection or analysis of biospecimens, laboratory value measurements, power, statistical software, and statistical content. When data did not clearly fall into one of the pre-determined categories (e.g. study design was not clearly specified), coding was discussed and consensus reached.If no sources of data were mentioned in the article but demographic or background information was collected or presented, data abstracters operated under the assumption that the source of data was self-reported. Power was recorded when an article's authors reported the power for their study; if power was calculated based on the study's anticipated – but not actual – sample size, and thus did not reflect the actual power of the study, then it was not recorded on the data abstraction form. If statistics other than descriptive measures  were calculated, large sample sizes  were analyzed, or computer-generated graphs were presented in the article but no software package was mentioned, it was recorded as software not otherwise specified. When computer-generated graphs of large sample sizes  were presented in the article but no software package was mentioned, it was assumed that the authors used Excel. If the authors calculated hazard ratios but did not specify the type of survival analysis, the hazard ratios were coded as Cox proportional survival analysis.The readers entered data into independent files and then merged entries into one file for data reconciliation. Instances of discordant information were flagged, and the readers reconciled the data case-by-case, referencing the article when discrepancies arose. The majority of discrepancies were due to errors in data entry or failure of one reader to abstract the information from the article. When discrepancies could not be solved by referencing the article, the readers discussed the issue and reached agreement; a third investigator was consulted if necessary.Descriptive statistics were generated for each data category , overall and by year of publication. Significant differences for variables over the three study years  were examined using Chi-Square, with p<0.05. IBM SPSS Statistics v.19  was used for all analyses.A total of 361 articles were reviewed: 133 (36.8%) from 1990, 122 (33.8%) from 2000, and 106 (29.4%) from 2010. The majority of articles were categorized by the Journal as “Original Contribution” . As demonstrated in Reflecting the frequencies of RCT publication, the majority of studies reviewed focused on new therapeutic uses  . This waOverall, the most commonly reported statistics in the Journal among the articles reviewed included measures of morbidity and mortality , descriptive statistics (e.g. means and percentages), and “low-level” epidemiologic statistics  . Power wBecause medical education and standards for publication are continuously evolving, it is necessary to revisit the issue of statistical reporting to see if findings from the 1980s and 1990s are still supported today. In this way, our study adds to the literature as it supports the continuing use of more advanced statistical measures and techniques in the medical literature. In turn, this suggests higher levels of statistical understanding may be needed in order for clinicians to effectively use some – but not necessarily all – of the literature in the practice of Evidence Based Medicine today, relative to a decade or two ago. In this way, this study provides additional evidence to support re-visiting of what is taught to medical students, residents, and fellows throughout their training to, familiarize them with emerging statistical methods.JAMA in 2010. Furthermore the proportion of papers reporting multilevel modeling results, multivariable regression, survival analysis, and sensitivity analysis, all increased with significant differences over the study period of 1990 to 2010. These higher level statistical methods require a solid statistical understanding to interpret their application and the results reported. Traditional epidemiologic study design (case-control and cohort), meta-analysis, and randomized controlled trials account for 60% of study designs by 2010, with a corresponding decline in the proportion of studies that were descriptive or cross sectional. It is possible that some of these trends and techniques, such as intention-to-treat analysis were performed in earlier studies but were less likely to be included in studies published before implementation of CONSORT guidelines in 1996. Nonetheless, the trends observed imply that understanding the strengths and limitations and applicability of results from varied research designs and research synthesis is required to interpret and apply results of studies reported in JAMA as of 2010.More specifically, we observed that nearly all studies published in 1990, 2000, and 2010 included some form of statistical reporting and that more complex multivariable regression methods , and contingency tables were present in up to 50% of papers published in These findings provide information to consider as medical schools and post-graduate training programs review and revise statistical training components. Moreover, for clinicians and medical investigators interested in continuing their own education in statistics, the frequencies in JAMA articles was extended to include articles from other comparable journals , such as New England Journal of Medicine, or if additional articles from JAMA were included in the sample, then it is anticipated that individual findings would vary but that overall trends of increasing statistical complexity over the decades would be similar.The focus on one journal for this content analysis is a limitation as it restricts generalizability of findings and does not account for variation by specialty. For example, preferred choice of study design (s) and data analysis expectations in surgical fields may differ from those in psychiatry or pediatrics. Thus, trends in study design and analytic techniques presented here may differ from journals with more directed target audiences and areas of focus. If this content analysis of One journal alone does not serve as a “gold standard” by which to judge medical education needs. However, the choice of Journal for this study does serves as a strength in that the study focused on a leading medical journal with extremely broad readership. The Journal is widely read by clinicians in a variety of specialties and publishes across a range of clinically related issues. In these ways, understanding the statistical measures and techniques most commonly reported in JAMA may serve as a once source of evidence for generating discussion about and guiding areas on which to focus the statistical aspects of medical education.New England Journal of Medicine suggest that by 2004 nearly 88% of articles required some statistical analysis beyond descriptive statistics American Journal of Radiology and RadiologyClinical Radiology and British Journal of RadiologyPediatrics demonstrated that statistical complexity increased from 1982 to 2005. The number of statistical procedures per article increased (to 3.9 in 2005 from 2.5 in 1982), as well as the range of inferential statistical procedures used during that time Although others have reported on use of statistics in specific disciplines, many of these studies are older in nature or have used smaller samples of articles. Results from the Over the time frame of this study of use of statistics, 1990 to 2010, we note that there has been little change in content of medical education JAMA is considered a leading Journal in the field, and the studies published are read by a broad range of clinicians. While our findings do not directly suggest that medical education necessarily needs to be modified, the statistical reporting trends described may have implications for medical education. Similarly, while this study does not provide data to suggest that improved statistical knowledge could translate to more effective use of the literature, we do propose that physicians' familiarity with certain (advanced) statistical approaches may assist them in critically evaluating and weighing the literature. The evolution of statistical software programs over the past years has expanded analytic capabilities – or at least broadened the spectrum of appropriate statistical options. To this end, medical educators may wish to be aware of the benefits and limitations of different and more complex statistical strategies as they try to teach certain topical content or critical evaluation skills. Moreover, as future and current clinicians engage in a life-long learning process, findings from this study may be used as part of the discussion about statistical training across the continuum of medical education.Findings from this content analysis of JAMA articles over a three-decade period support and extend trends in previous studies that point to continued use of complex statistical approaches, such as multivariate modeling and regression, in the medical literature. While this is not generalizable to all the medical literature,