Popper assesses the value of a statistical test primarily by its  as Mayo , 2018, a What, then, is the end of an explanatory hypothesis? Its end is, through subjection to the test of experiment, to lead to the avoidance of all surprise and to the establishment of a habit of positive expectation that shall not be disappointed. C.S. Peirce . Our own account highlights how the specificity of a hypothesis and its predictions boost severity by raising the expected evidential value of the experiment, and how error control can be embedded naturally into Bayesian inference. Specifically, we construe severity within the Bayesian framework as the specificity of the prediction of a hypothesis in relation to the potential data that could be observed. The value of severity is reflected in the expected evidential value of a test, quantified by the expected absolute log-Bayes factor , we believe that this negative argument is an important contribution to the debate. In other words, we show that a statistical practitioner who cares about severe testing need not be a frequentist. Severity is a concept that can be integrated equally well, or even better, into the framework of Bayesian inference.Finally, with regard to Q3, we argue that the error-statistical explication of severity faces considerable conceptual challenges. Since error statistics enjoys increasing popularity in the psychological science community  of a scientific theory lies in the combination of its universality and its precision . A theory has high empirical content when it has a vast scope in which many observations are possible in principle ; yet only a few of these possible observations are consistent with the theory . This is consistent with the common intuition that a successful risky prediction is more impressive than a successful vague prediction.Scientific theories are imperfect descriptions and explanations of reality. They allow us, with a certain degree of accuracy, to predict future observations or to uncover structure in available data. According to Popper /2002, thfalsifiablity . The higher the proportion of possible outcomes that are consistent with a theory, the less informative the theory becomes. For example, it is hard to falsify the rather uninformative theory that it will rain in Amsterdam on some days in the next year. On the opposite side, we have highly informative theories, with a limited set of parameters whose values are fixed and interrelated. An excellent example of such a theory is GTR. This theory makes specific predictions about time dilatation in GPS satellites relative to the earth’s surface, improving navigational accuracy. The more informative a theory is, the more falsifiable it is, because fewer possible observations are consistent with it. Only such informative theories can be severely tested: We may say that to make predictions with great accuracy increases the probability that they will be found wrong, but in compensation they tell us much more if they are found right. [...] The best procedure, accordingly, is to state our laws as precisely as we can, while keeping a watch for any circumstances that may make it possible to test them more strictly than has been done hitherto. . Typically, at the center of NHST there is a point null hypothesis postulating that a parameter takes a precise value —corresponding to absence of a causal effect in an experimental intervention, equality of two medical treatments, and so on. When the measured divergence from the null hypothesis exceeds a given threshold , the null hypothesis is rejected and the statistical analysis reports statistically significant results against the null. Otherwise, no conclusion is drawn.At first glance there is a striking resemblance between Popper’s emphasis on the severe testing of scientific hypotheses and not the null hypothesis . It does not commit the scientist to precise predictions; rather it states that the unknown parameter lies in a range of values. NHST does not explain how such hypotheses can be tested severely; nor does it give a general definition of severity in statistical inference.At first glance, the NHST methodology squares well with Popper’s falsificationism. First, the point null hypothesis is maximally falsifiable, because it commits to a single point value for the effect. Second, the idea of submitting the point null to a severe test and rejecting it when it fails to explain the data, has a distinct Popperian note. However, the scientific theory that we would like to submit to a severe test is usually error-statistical approach addresses this problem and explicates how parametric hypotheses can be severely tested in general. Error statistics follows Popper’s perspective on theory testing as the ability to detect and control error between data and hypothesis. The standing of a theory is primarily determined by the severity of the tests it has survived. The extent to which the theory has proved its mettle constitutes statistical evidence. Mayo (Severity Principle (strong): We have evidence for a claim C just to the extent it survives a stringent scrutiny. If C passes a test that was highly capable of findings flaws or discrepancies from C, and yet none or few are found, the passing result, x, is evidence for C.Mayo’s , 2018 erPrima facie, two important elements of severe testing are missing in the Severity Principle (in this formulation). First, Mayo’s perspective does not make explicit essential elements of severe testing that Popper stressed: the universality of the tested hypothesis H and the specificity of the predictions it makes . This contrastive aspect of severe testing is missing in Mayo’s formalization.Second, without explicit reference to alternatives to the claim, it is not clear how a claim can survive “stringent scrutiny” or when a test is “highly capable” of finding differences. For example, a stringent scrutiny of the claim C: “90% of all swans are white” requires only a single swan if the alternative claim is “all swans are black”. When the alternative is that “fewer than 80% of all swans are white”, however, the observation of a single white swan is relatively uninformative, and a large sample of swans is needed to discriminate between both hypotheses. If C encompasses all that is possible (except ¬C), no test —no matter how probative it usually is— will be capable of severely testing C. This suggests that the Severity Principle should not be interpreted in absolute, but in Severity Requirement: for data to warrant hypothesis H requires not just that (S-1) H agrees with the data (H passes the test), but also (S-2) with high probability, H would not have passed the test so well, were H false.This problem comes into sharper focus when we consider Mayo’s operationalization of the Severity Principle Mayo , p. 92: μ ≥ μ0 + δ, where δ > 0 expresses the effect size relative to the default value μ0. Mayo calls the hypothesis of interest the ‘Claim’ and indicates it with C. The application of (S-1) is then similar to the Neyman-Pearson (and NHST) approach  ≥ d(x);H0) < α), where the statistic d measures divergence of the data from H0).Suppose that the hypothesis of interest is see Mayo , p. 142:C, Mayo applies (S-2) and computes a severity function (SEV: see the corresponding https://richarddmorey.shinyapps.io/severity/). The severity function takes as arguments the statistical test, the observed data, and the target hypothesis C. The severity function outputs the probability of obtaining the observed data x or data closer to H0 and deviating more from C, if C were false. As a representative of the negation of C, we choose the point hypothesis in C that is closest to H0, which is μ = μ0 + δ. If this hypothesis is rejected with test T based on data x, the severity with which C has passed the test is defined asC, in the direction of H0 if C were false.4To assess the evidence in favor of To show how the severity function works in practice, we borrow a simple example from . She sets the Type I error rate to 2.5% (α = 0.025), thus rejects “H0 (infer there’s an indication that μ > 150) iff The question is, whether the temperature of the water high enough to constitute an ecological disaster that requires counter measures beyond mere repair of the cooling system. When the cooling system is working properly, the temperature of the water discharged into the ecosystem is around 150 degrees Fahrenheit and a temperature of 153 or higher is considered a “full-on emergency for the ecosystem” (p. 143). A series of 100 water measurements are taken at random time periods and their sample mean H0, fulfilling (S-1) of the Severity Requirement. According to the severity rationale, we are warranted in concluding that μ > 150, because “[w]ere the mean temperature no higher than 150, then over 97% of the time their method would have resulted in a lower mean temperature than observed” (p. 143). However, we are primarily concerned with the extent to which these data indicate that the water has reached devastating temperatures of 153 Fahrenheit or higher . According to the Severity Requirement (S-2), we need the probability of observing our mean temperature of 152 or lower if the actual temperature is equal the critical threshold of 153 degrees. This can be calculated with the SEV function, which is μ > 153 because it is fairly probable (84% of the time) that the test would yield an even larger mean temperature than we got, if the water samples came from a body of water whose mean temperature is 153” (p. 144). Thus, the results do not meet requirement (S-2) and the hypothesis that the temperature of the water is 153 degrees or higher does not pass a severe test ; one would again not meet (S-2) and draw the same conclusion as before  are good operationalizations of the function of severity in scientific inference and statistical testing. To recapitulate, our main criticism are (1) any theory of severe testing must be sensitive to what is considered the normal or default state of affairs, and Mayo’s theory does not; (2) more generally, Mayo’s theory neglects that the severity of a test is a function of the degree of similarity between the competing hypotheses, and the specificity of their predictions. Mayo’s explications of severity in statistical inference are decoupled from the scientific context in which the data are collected.x supports hypothesis H if and only if x raises the subjective probability of H  = p(H0) ⋅ p(x|H0)/p(x). This allows us to write the posterior odds in favor of H0 over H1 asp(H0) fixed, the posterior probability of H0 will be the larger (1) the better H0 predicts x and (2) the more surprising (worse predicted) x is under H1 , and in the experimental design. Bayesians cash out severity by ensuring that an experiment gives positive answers to the two questions below:Evidential Valueobtain strong, discriminatory evidence from this particular experiment?Is it probable to Error Controllimit the probability of finding misleading evidence? That is, does it limit the probability of making an erroneous inference?Does the design of the experiment These properties also depend on the experimental design as a whole , but specifically on the choice of the tested hypotheses:SpecificityH0 and H1 make specific predictions? That is, do they rule out, or make implausible, a large proportion of possible outcomes?Do the competing hypotheses ContrastivityH0 and H1sufficiently different that the experiment can discriminate between them?Are the predictions of hypothesis In other words, the specificity and contrastivity of a hypothesis contributes to the severity of a test by increasing its evidential value and controlling error in inference. We will now discuss these concepts in detail.impose substantial restrictions on the range of potential data that are consistent with it. This is a basic ingredient of severe testing that has been retained both by philosophers such as Popper and psychological science methodologists. For example, Roberts and Pashler Theorists who use good fits as evidence seem to reason as follows: if our theory is correct, it will be able to fit the data; our theory fits the data; therefore it is more likely that our theory is correct. Figure For a test to be severe, the tested hypothesis needs to  Pashler , p. 359 H  are judged to be inconsistent with the theory.plausible outcomes. This means that possible outcomes that fall outside the X% highest density region as predicted by the hypothesis have some non-negligible probability based on, for instance, prior results  is low, and since we want to explain events in a systematic way, we infer that p(H|E) is low. A theory must always be tested against a competitor. Indeed, this aspect of severe testing is underappreciated in Vanpaemel’s account, just as it is missing in Pashler and Roberts’s and Mayo’s account.Second, Vanpaemel argues that the threshold for counting outcomes as inconsistent with a model depends on the context: in his running example of the 2020 paper, he chooses 99.99%, but he adds that in other contexts, other thresholds may be possible. Also here, we agree, but we would like to add that we (still) cannot test a hypothesis  Fisher, —either aexpected evidential value of a hypothesis test. This concept can be operationalized as the expected absolute log-Bayes factorp is the prior probability density function over the sample space that encompasses both H0 and H1.From a Bayesian perspective, specificity contributes to severity by means of increasing the diagnosticity or H0 which fixes the parameter of interest to a single number. More generally, there is a systematic connection between the degree to which a hypothesis restricts its parameters, and the degree to which it restricts the range of data consistent with it.When a hypothesis is highly specific, its predictions will in general differ notably from the alternative, and this means that we can expect strong evidential support for either one or the other hypothesis. Furthermore, the expected evidential value is higher for the more restricted hypothesis: it is easier to find evidence against it when it is false, and one obtains more easily evidence for it when it is true. Testing simple, restrictive hypotheses is thus valuable from a Bayesian perspective. Typically—but not always—the most simple, and most severely testable hypothesis is a point null hypothesis informative hypothesis testing approach . Treatment A is regular psychotherapy  and the more measurement error one can expect , the wider the interval around these expected values that are still considered consistent with the theory.𝜃A and 𝜃B. Under an encompassing model these rates can have any value between 0 and 1, He : 𝜃A = ,𝜃B = . For simplicity, we consider these values equally likely and adopt a uniform prior over 𝜃A and 𝜃B in the encompassing model. The scenario can be modelled as two independent binomial distributions. We start treating participants, randomly divided in equal number to each treatment, and count the number of successful treatments. In this case, for a treatment we would have a specific number of participants Ni, where i ∈{A,B}, and the number of successes for this treatment Si would be determined by the actual value of 𝜃i and sampling error: Specifically, assume that either treatment has a true success rate, Hv : 𝜃A = ,𝜃B = .Hv takes up 25% of the encompassing model and it predicts that the success rates for Treatment A and B will very likely be below and above 0.5, respectively  than the vague hypothesis is supported by the large data set (BFve = 3.89). As shown in Fig. These hypotheses are compared on two data sets. A small data set of four participants per treatment,  Pashler  quartet. Pashler  quartet.Hs only has a small amount wiggle room and the Bayes factor quickly drops towards zero when the number of successes deviates from the predicted range, while Hv has a large area to move in with respect to possible success rates that support it.However, the benefit of a specific hypothesis when right comes at a cost when wrong. As is visible in Fig. y:p(y) isp(y|H) isThis is also reflected in the expected evidential value of the experiment in the four situations of the example. As explained in the previous section see Eq. , the expHs and the encompassing model. Analogously for In this example, the computation of Ni = 20 per treatment, Ni = 4 per treatment, Ni = 4 per treatment, As can be gleaned from Fig. Summing up, the evidence is much more telling and discriminatory when testing specific hypotheses  . Before collecting data, the experimenter decides on a threshold for when a Bayes factor counts as evidence for a hypothesis, e.g. BF10 > 3 or BF10 < 1/3. Of course, one can set more stringent requirements as one desired . Suppose the alternative hypothesis H1 is in fact true. The BFDA then calculates H1 ;the probability of obtaining positive evidence for 10 ≤ 3); andthe probability of obtaining inconclusive evidence .the probability of obtaining misleading evidence for Identically, one can define the probability of obtaining positive evidence for H0, and misleading evidence for H1 (when H0 is true). A graphical illustration is given in Fig. t-test with a moderate group size N = 36 in both groups. The probability of finding misleading evidence for H0 when H1 is true is relatively large: 9.6%. Moreover, the most likely result is actually to obtain inconclusive evidence (55.1%). Certainly such an experiment controls error rates  poorly and cannot be counted as a severe test of the competing hypotheses.One Bayesian tool for making this assessment is a Bayes Factor Design Analysis : We have evidence for a claim C just to the extent it survives a stringent scrutiny. If C passes a test that was highly capable of findings flaws or discrepancies from C, and yet none or few are found, the passing result, x, is evidence for C.Reinterpreting Mayo from a Bayesian viewpoint, we have evidence for the claim C if and only if (a) we observe a Bayes factor in favor of C beyond a context-sensitive threshold, and (b) the probability of finding misleading evidence for C (under the assumption that C’s competitor is true) is low. The Shiny apps and the R package for a Bayes Factor Design Analysis make the implementation of this planning explicit and easy to handle for an experimenter. There is thus no reason why a Bayesian needs to give up an appreciation of severity in terms of error control. What is more, in the light of the challenges inherent to Mayo’s own operationalization of her Severity Principle, one could even draw the conclusion that Bayesian inference is suited best to implement her philosophical stance into experimental practice.This shows that error rates are no unique feature of frequentist statistics: the Bayesian has analogous tools to calculate the probability of misleading evidence and to construct his (or her) experiment in a way to control for the probability of misleading evidence. This is exactly what Mayo alludes to in her Severity Principle, which we quote again for convenience: This article presents a Bayesian proposal on how to accommodate the concept of severity when testing statistical hypotheses. It provides a translation of Popper’s (1959/2002) falsificationist philosophy and the intuitive impressiveness of risky predictions in terms of a test of specific hypotheses. The specificity of a hypothesis is defined by the degree to which predictions are spread out across the sample space, while evidence is defined by relative predictive performance, that is, how much probability mass is allocated to the data under the competing hypotheses .A complex or vague hypothesis spreads out its predictive mass across a wide range of options, and by hedging its bets will lose out against a more restrictive hypothesis that makes a more precise (and accurate) prediction. The more precise the predictions from the competing hypotheses, the higher the expected diagnosticity, and the more severe the test. This approach clearly quantifies Popper’s idea of evaluating theories on the basis of their empirical content and degree of falsifiablity Popper, /2002. Innot require any blending of Bayesian and frequentist inference; our account stays faithful to the principles of subjective Bayesianism. While error statistics postulates severe testing as a key virtue of statistical inference, our approach also explains why severity matters for conducting efficient hypothesis tests and making good decisions.Popper and Bayes can thus be reconciled: the evaluation of hypotheses in terms of Bayes factors is influenced by their specificity and Bayesian inference has the conceptual resources to reward specific predictions. Notably, obtaining this conclusion does There are several clear advantages to testing specific hypotheses in a Bayesian framework. First and foremost, it is to the researchers’ benefit to make more specific predictions. As outlined earlier, the more specific the hypothesis is, the more evidence one can expect: either more evidence is obtained from the same amount of data, or less data are needed for the same amount of evidence. This is in stark contrast with orthodox frequentist methods where “more evidence” requires more data if the discrepancy between null hypothesis and alternative hypothesis is fixed. In experimental psychology, demonstrations of the benefit of informed/specific Bayes factor hypothesis tests includes Vohs et al., (in press), Gronau et al., , Ly et aSecond, our account makes explicit why vague predictions lack diagnostic value. This is most clearly expressed in cases where  everything is consistent with the theory. In such cases where all parameter values are allowed by the theory, one can never expect to obtain strong evidence either in favor or against the theory. Only when the theory is restrictive, strong confirming or undermining evidence can plausibly be expected. Consequently, evidence is limited by the specificity of the hypothesis. Intuitively, the possible evidence in favor of a theory should be limited by its strength and how well it is tested. The specific hypothesis testing approach provides this feature, because the maximum amount of evidence in terms of the Bayes factor is one divided by the specificity of the hypothesis.Third, our approach extends the treatment of severity by Vanpaemel ; 2020, wFourth, our approach to severity can be extended to the research planning phase. Specifically, the specificity of one’s hypothesis, or the restrictiveness of one’s theory, can inform the researcher about the sample size required to be fairly certain of strongly supporting or contradicting results. Vice versa, in the case where the sample size is predetermined, the researcher can infer how specific the tested hypothesis needs to be in order to be fairly certain of obtaining high degrees of confirmation or disconfirmation. Explicitly, our approach could be integrated into the Bayes Factor Design Analysis discussed in the previous section (BFDA; Schönbrodt & Wagenmakers, Similarly, in Adaptive Design Optimization (ADO; e.g., Ahn et al., Our approach is susceptible to any objection that may be raised against Bayesian statistics as a whole (e.g., Moyé,


The last decade has witnessed an increased awareness of the crucial need to enhance police response and investigation of crimes related to violence against women (VAW). Although some research has been conducted on police decision-making in response to these crimes, there remains a dearth of knowledge concerning the influence of innovative police technologies on the investigative process and resulting case outcomes. This knowledge gap is particularly concerning given (1) the intricate nature and severity of VAW crimes and (2) the substantial advancements in technology that have transformed how the criminal justice system handles violent crime cases. To address this gap, the current study adopted a multi-method, quasi-experimental design to assess the impact of the Miami Police Department’s Real-Time Crime Center (MRTCC) technologies on the case processing and case clearance of sexual assault and domestic violence incidents. The results of this study illuminate the distinctive features associated with this form of violent crime and underscore the necessity of continuously advancing the strategies employed to address these incidents. Sexual assault and domestic violence are two of the most serious and pervasive forms of violent crimes. Despite numerous efforts by law enforcement agencies and other stakeholders to combat these crimes, they remain a significant challenge for criminal justice systems across the country. One of the most significant issues in addressing these forms of violence against women (VAW) is the low clearance rates, which refers to the percentage of cases in which an arrest is made, or charges are filed. Improving case clearance rates is critical for both ensuring justice for victims and deterring offenders from committing these crimes. In recent years, clearance rates for these crimes have been lower than for other types of violent offenses. According to the FBI’s Uniform Crime Report, the clearance rate for rape, which includes sexual assault, was just 30 percent in 2020, compared to a clearance rate of 50 percent for murder and 69 percent for non-negligent manslaughter. The clearance rate for aggravated assault, which includes domestic violence, was 47 percent in 2020 .The extant literature on this topic has suggested many reasons why case clearance rates for sexual assault and domestic violence are so low. Some of these noted impediments relate to cultural norms and stigma, while others relate to the limitations of investigative practice. For instance, cultural norms and societal attitudes towards women can contribute to low case clearance rates since, in some belief systems, violence against women is accepted or even condoned, making it more difficult for victims to come forward and for law enforcement to take action . This phOther reasons why case clearances for VAW are low relate to various aspects of police investigative practices. First, many cases fail to move forward due to a lack of evidence. Often, there is a lack of physical evidence that a violent encounter occurred, or there are no witnesses to the incident, which makes it difficult for law enforcement to proceed with an arrest or to bring charges for prosecution . Second,Taken together, this research suggests that there are a variety of factors that may serve to impede the successful arrest and prosecution of cases involving violence against women. Efforts to overcome these impediments may also work to improve the clearance of VAW cases. While many of these factors may be unique to this type of violence, an unmistakable need relates to the improvement of police investigative practice and methods to better identify, collect, and preserve evidence that can facilitate successful criminal justice processing. Improved collection and documentation of evidence could assist police and prosecutors in clearing cases where victim credibility may be limited, when there are no witnesses, or when the victim may be unwilling to cooperate.One approach that has been increasingly adopted by local police agencies in recent years to improve the collection of evidence and assist in the investigation of crimes is the development and use of centralized technological units housed within so-called “real-time crime centers” . RTCCs aRelatively new, emerging research has found that the use of RTCC technologies has improved the ability of police to solve violent crimes  and reduTwo pertinent areas of research are currently being explored in the realm of improving the response and outcomes of incidents of violence against women, both of which focus on the impact of police practices. The first area of investigation concerns the traditional or extralegal factors that are involved in the processing of cases, while the second area of study examines the influence of police technology on the outcomes of such investigations. A comprehensive review of each of these areas is necessary to provide a nuanced understanding of the complex factors that contribute to the effectiveness of policing interventions in this domain. Following this review, a brief overview of the Miami Real-Time Crime Center is presented, which serves to contextualize and illustrate the practical implications of the research findings.When survivors do report to the police, they are often motivated by a desire to prevent the perpetrator from victimizing others or because they have received encouragement and support from formal or informal sources to report the crime to law enforcement authorities . HoweverThe decision to arrest in sexual assault cases has been linked to the suspect’s history of assaulting the victim, their relationship with the victim, injuries sustained by the victim as a result of the assault, as well as the resistance reported by the victim, weapon use, the presence of evidence, including witnesses, a forensic exam, and suspect interview, as well as how quickly the victim reported the rape or abuse to the police ,15. ThusGiven that victim engagement is critical to the successful prosecution of these cases, some researchers have investigated the factors that encourage or discourage victims to continue with the criminal justice process. Victim continuation, for example, may be contingent upon the victim or situational characteristics—mental health, how confident they feel about the case, desire to stop the offender or relationship with the offender, presence, or absence of social support ,18. VictViolent incidents against women pose unique challenges to criminal investigations due to their sensitive and personal nature. Unlike other forms of criminal offenses, these crimes involve a complex interplay of psychological and emotional factors, which can complicate the investigation process. Moreover, the physical evidence collected is often scarce, making it more challenging to establish guilt beyond a reasonable doubt. Even in cases where such evidence is available, and despite the tremendous utility of forensics , evidence too frequently goes unused or becomes backlogged within the system ,23. ConsIn recent years, police investigations have undergone significant advancements, leading to a noteworthy impact on the ability to solve crimes. Largely facilitated by the reauthorization of the Violence Against Woman Act (VAWA), several additional measures have been implemented to enhance the effectiveness of investigations, including the establishment of specialized police units, sensitivity training for law enforcement personnel, and the formation of sexual assault response teams, among other initiatives ,25,26. TThe evidentiary significance of digital technologies has also become widely recognized. The conventional explanation for the low rate of arrests and convictions in cases of sexual assault or domestic violence is the difficulty in obtaining conclusive evidence due to conflicting testimonies ,29,30. TWhile it is commonly accepted that closed-circuit television (CCTV) systems can aid investigators in addressing key inquiries that arise during criminal investigations, the impact of such technologies on the investigative outcomes of VAW incidents has received limited scholarly attention. This lack of research is not unexpected, considering that these crimes often occur in residential settings outside the purview of CCTV cameras. Studies that do manage to include this category of crime in their analyses suggest that CCTV technology has the potential to serve as a valuable tool in the investigative process. For instance, Ashby (2017) discovered that CCTV was significantly associated with an increased likelihood of crime resolution in all categories of crimes except drug or weapon possessions and fraud . NotablyOf particular interest to this research is the role and impact of rapidly diffusing RTCC information technologies on these crimes. RTCCs are investigative units that exhibit varying structures but are generally characterized as data platforms that promptly synthesize and provide officers with comprehensive intelligence information. Staffed individuals within RTCCs possess the ability to actively monitor critical infrastructure and assets, generate post-incident investigative evidence, and facilitate cooperation across both internal units and external agencies. The quality of the information provided to officers, detectives, and external partners, as well as the turnaround time from incident to evidence, has established these units as highly valued resources for crime control and investigative purposes. At present, the evaluations of RTCCs are limited to the Chicago Police Department’s Strategic Decision Support Centers (SDSCs) and the Miami Police Department’s centralized Real-Time Crime Center (MRTCC). While the former evaluation discovered some evidence of success in decreasing sexual assaults in districts that implemented SDSCs , the latThe MRTCC was established in April 2019 as a fundamental component of the Criminal Investigations Division’s Investigative Support Section. The main objective was to provide real-time, actionable investigative intelligence, enhance situational awareness, and generate a virtual environment for law enforcement personnel responding to priority calls and unfolding events. To accomplish this goal, the MRTCC was designed to manage and coordinate the operations of various technological systems, such as CCTV cameras, gunshot detection software, license plate readers, facial recognition, and social media software. Over the course of the study period, the MRTCC gradually expanded its capabilities to operate approximately 582 cameras and access a wide range of information technology resources. The unit was staffed with nine full-time personnel, providing coverage for 86% of weekly hours, equivalent to near 24/7 operations.Miami is an urban area with a high population density, covering approximately 36 square miles and inhabited by a diverse population of roughly 450,000 people. The city’s demographic makeup comprises 70% Hispanic, 16% African American/Black, and 14% White Non-Hispanic individuals. Over time, Miami has undergone significant growth as a metropolitan hub and has become a popular tourist destination with a tourist-to-local ratio of nearly 1600 visitors per 100 residents. However, despite its growth and prosperity, poverty levels in the area remain higher than the national average. Like many other large cities, crime tends to be concentrated in specific neighborhoods, which has led to the predominant deployment of MRTCC technologies in these areas.The primary objective of this study was to examine the impact of police information technologies on the outcomes of cases that involve VAW incidents and to assess their role within the investigative process. Specifically, the study aimed to assess whether the use of MRTCC technologies was associated with higher rates of case clearance and to what extent these technologies were integrated into the processing of sexual assault and domestic violence cases, as compared to other forms of violent crimes and traditional evidence sources. The research questions guiding this investigation were twofold: (1) what is the influence of MRTCC technologies on the clearance of VAW incidents? and (2) to what extent have MRTCC technologies been integrated into the case processing of VAW incidents?The decreasing incidence of sexual assault and domestic violence incidents in “offline” settings, coupled with the increasing importance of digital evidence in linking victims and alleged perpetrators, suggest that the police agencies’ technological resources could enhance the investigation of these crimes . This hyIn the current study, three different analytical techniques were utilized to determine the extent to which RTCC technologies impact the investigation of violent crimes against women and their outcomes. First, a set of nested multivariate logistic regression models were employed to determine the likelihood of case clearance for sexual assaults and domestic violence incidents compared to all violent crime incidents and controlling for RTCC support. The multivariate model was adjusted for various case characteristics and solvability factors that could potentially impact the clearance probability of incidents outside the scope of the technologies employed within the unit.Second, module network analysis was used to empirically examine the extent to which RTCC technologies influence the investigative process of these unique crime types. This type of network analysis involves a set of integrated techniques that aim to depict the relational properties of individual elements and analyze the structures that emerge from the recurrence of these relations . The netFinally, a post hoc analysis utilizing non-nested logistic regression was undertaken to discern the impact of conventional extralegal predictors on case clearance rates for instances of sexual assault and domestic violence. These extralegal factors encompass the relationship between the victim and the suspect, the incident’s location, and the severity of the crime. It is worth noting that not all instances of violent crime provided data pertaining to these factors. For a comprehensive understanding of the data collection methodology, please consult the “Post Hoc Analysis” section outlined below.The dataset utilized for this study stemmed from a collaborative Smart Policing Initiative with the City of Miami Police Department, which concluded in October of 2022. . The analyses relied on data from an expanded MRTCC incident log analytical database, which contained measures of violent crime incident characteristics and sources of evidence used by responding officers and detectives within the unit. An initial MRTCC incident log established within the unit recorded basic information on every incident to which the unit assisted. This section will detail the process involved in gathering this information, with emphasis on the measures included for analyses that follow.The MPD RTCC maintained an internal log to document their daily activities and work associated with requested incident support. The incidents recorded within the log provided a framework for the development of the extended log used in the eventual outcome evaluation of the unit. The log-recorded incidents brought to the attention of MRTCC personnel through dispatch or officers in the field incidents identified through active monitoring, and cases in which the MRTCC was asked to assist in the post-incident investigative process. The assembly of the internal log began in January 2020 and at the time of the evaluation period, it consisted of 3636 entries, of which 2228 involved an incident resulting in an assigned case number.The purpose of the expanded database was to capture additional measures for all violent and property crime incidents that received support from the MRTCC. The incidents recorded within the expanded MRTCC database had all received real-time or post-hoc deployment of information from the MRTCC to responding officers or detectives. The extended database allowed for more in-depth analysis of the assessment of selected outcomes for incidents treated by the RTCC compared to non-MRTCC incidents. The data collection for the extended MRTCC analytical database occurred simultaneously with the internal MRTCC incident log. Data collection was concluded on 30 April 2022, to allow for the assembly of the non-MRTCC treated control sample. The violent crime incidents recorded within the extended MRTCC database are comprehensive. That is, all homicides, aggravated assaults, robberies, sexual assaults, and domestic violence incidents that were included and validated within the internal MRTCC log were also captured within the extended database. Selected property crimes  were likewise included within the extended database. The extended analytical database consisted of a total number of 886 incidents, of which 648 were violent crimes. The time period of cases within the expanded MRTCC database was naturally the same as that in the MRTCC incident log.The selected measures included victim characteristics , human-based evidence sources , crime scene evidence  team was deployed, and whether ballistics tracing via NIBIN was undertaken), and warrant evidence and manpower used .All but two of these measures were coded dichotomously with 1, indicating it was present within the investigation of the case, and 0 indicating its absence. Two measures, victim age and the number of officers responding, were coded as continuous measures. There were two dependent measures in the outcome analysis, whether the case was cleared by arrest (coded as 1 indicating an arrest was made and 0 one was not) and the number of days from the time the incident occurred to the time the arrest was made. Days to arrest was coded as a continuous measure. Each of these variables had precedent in the literature as representing factors that were relevant predictors of crime solvability ,38,39.A randomly drawn control sample was also used to compare differences in these outcomes across the two samples while adjusting for violent crime incident characteristics. The control sample was stratified by neighborhood operational area and violent crime type proportionate to that represented in the MRTCC “treated” expanded analytical database. This random selection within the stratifications resulted in equivalency between the two samples based on those two stratifications. There were no significant differences between the two in terms of the number of incidents occurring in the respective neighborhood operational areas or the number of violent crime incident types. Having proportionate numbers of incidents occurring within specific neighborhood areas and incident types ensured that neighborhood effects  were equivalent between the two samples. The control sample included the same dependent measures and incident characteristic measures that were recorded in the MRTCC expanded analytical database and were coded in the exact same manner.For the outcome measure, a larger proportion of cases from the MRTCC-assisted sample  were cleared compared to the control sample, where only 202 cases (33%) were cleared. Among human evidence characteristics, four out of five measures were significantly different between the two samples. The MRTCC-assisted cases had a statistically significant greater proportion of witness interviews (n = 221 vs. n = 190), conducted more suspect lineups (n = 141 vs. n = 102), and disseminated more public information flyers (n = 191 vs. n = 54). The presence of external or private CCTV footage was also significantly higher in the MRTCC-assisted cases (n = 286 vs. n = 71). Concerning crime scene-based evidence, five out of six measures were significantly different between the samples. The MRTCC-assisted cases had significantly more guns present (n = 292 vs. n = 185) and vehicles used (n = 353 vs. n = 189) in the commission of a crime, leading to more processing of gunshot residue (n = 72 vs. n = 22), greater use of the CSI unit (n = 327 vs. n = 228), and more utilization of NIBIN ballistics tracing (n = 171 vs. n = 42). Finally, regarding warrant evidence and manpower, there were significantly greater numbers of search warrants (n = 47 vs. n = 12) and cell warrants (n = 38 vs. n = 9) used, as well as more officers assigned to incidents (mean = 4.02 vs. mean = 3.74) in the MRTCC-assisted cases than in the control sample.Once observed independently, there were no significant difference in the case clearance outcome measure between the MRTCC-assisted cases and the control sample for both sexual assault incidents  and domestic violence incidents . For sexual assault incidents, only three evidence sources exhibited a significant difference between the MRTCC-assisted cases and control cases. These evidence sources comprised the use of a suspect lineup (n = 7 vs. n = 17), the presence of external CCTV evidence (n = 10 vs. n = 2), and whether a vehicle was used in the commission of a crime (n = 10 vs. n = 1). For domestic violence incidents, two evidence sources exhibited significant differences, that being the age of the victim, with the control sample being slightly older (mean = 37 vs. mean = 32), and whether a vehicle was used in the commission of the crime, with a higher frequency of vehicle usage depicted in the MRTCC-assisted cases (57% vs. 17%).p = ≤0.001). Conversely, domestic violence incidents were ten times more likely to be cleared (p = ≤0.001). Among the array of variables considered, the utilization of MRTCC technology, witness interviews, lineups, suspect flyers, and search warrants emerged as significant contributors to enhancing the odds of case clearance. Notably, the most influential predictor among them was the execution of a suspect lineup, which amplified the odds of case clearance by a factor of five. Conversely, the presence of external CCTV surveillance and the involvement of firearms exhibited a substantial decrease in the likelihood of case clearance, taking into account all other factors pertaining to solvability.In Model Six, all variables, including those related to warrant evidence and manpower, were included in the final analysis. The results showed that sexual assault incidents had an 80% lower probability of being cleared when compared to other violent crime types and case characteristics  with no multicollinearity revealed. All VIF factors ranged from a low of 1.098 to a highest of 2.091 (these scores are far below the area of concern for VIF where convention dictates that scores of 5 or greater suggest the presence of multi-collinearity among independent measures).Module network analysis helped to determine the influence of MRTCC technologies on the case processing of sexual assault and domestic violence incidents. The analyzed data were drawn from the expanded data set derived from the MRTCC log and the stratified randomly drawn control sample as discussed in the previous “Data” section, with a total sample size of 1222 included within the analysis. The data were coded to represent whether various evidential sources were used in the investigation of the violent crime incident, regardless of whether usable evidence was obtained from the evidence sources. These evidence sources were grouped into four types and included MRTCC evidence , crime scene evidence , human-based evidence  and warrant-based evidence . Two additional crime type variables were intentionally coded to represent the investigation of VAW incidents with the aim of examining the role of police technology in the processing of these crimes. These nodes are maintained within the violent crimes against women category. Victim characteristics and other investigative solvability factors were not included as they were outside of the scope of the analysis.Notably, and as expected based on the existing body of literature, the sexual assault incident node is primarily linked to the presence of suspect lineups latent/DNA testing, and victim interviews, with weaker connections established with external CCTV and NIBIN. The sole relationship observed between MRTCC technologies, and the sexual assault node is linked to social media searches and identifications. It is plausible that these searches on social media platforms are conducted by MRTCC personnel to gather supplementary information regarding the individuals under investigation. For instance, such searches may aid in tracking suspect movements or identifying specific items of clothing worn during the commission of the crime. In contrast, investigations related to domestic violence cases heavily rely on nodes representing external or private CCTV systems, followed by suspect lineups, latent/DNA testing, and crime scene investigation processing. Of all the MRTCC technologies examined, the LPR system exhibited the greatest influence on the domestic violence node. This can be observed in Furthermore, understanding the centrality of nodes within the network holds significance, as nodes with high centrality function as pivotal hubs connecting other nodes, while those with low centrality possess weaker peripheral connections. Four commonly employed indices, namely betweenness, closeness, degree, and expected influence, are employed to gauge node centrality. Collectively, these indices offer a quantitative assessment of a node’s significance within the network. As depicted in A post hoc analysis was conducted to determine the influence of traditional extralegal predictors of case clearance for both sexual assault (n = 42) and domestic violence incidents (n = 84). To perform this analysis, additional variables were collected at a later stage using the same methodology as outlined in the “Data” section. The information retrieved was obtained from the case file of each incident itself, in which the initial report was completed at the time of an officer’s arrival at the scene and updated by an investigator assigned to the sexual assault or domestic violence unit. Thus, the difference in data collection periods should not impact the results of the analysis, as these are extralegal variables that remain stable in the investigation over time.These variables were grouped into the following four distinct categories: victim characteristics , victim race (Black), victim–offender relationship , location , and crime severity . These variables can be found in precedent literature as important factors impacting the case outcomes of VAW incidents ,40,41. ADespite including the victim characteristics, victim–offender relationship, location, and crime severity variables, the analysis consistently showed significantly lower odds of case clearance for sexual assaults compared to domestic violence incidents. The likelihood of arrest for sexual assaults remained between 93% and 95% lower than for domestic violence incidents. Additionally, none of the covariates included in the analysis, beyond the sexual assault variable, reached statistical significance. Although all six models were statistically significant according to the chi-square and −2 log-likelihood coefficients, Model Six predicted the model variance best, with a Nagelkerke pseudo-R-square value of forty-three percent.The current study adopted a multi-method, quasi-experimental design to assess the impact of the Miami Police Department’s RTCC technologies on the case processing and case clearance of sexual assault and domestic violence incidents. The present study builds upon prior evaluations of RTCCs conducted in the districts of the Chicago Police Department , as wellThe study yielded three primary findings. First, despite the broad array of information technologies housed within the unit, their impact on the case clearance of sexual assault incidents is limited. Irrespective of the models assessed, sexual assault cases were less likely to be cleared than other forms of violent crime. This may be due to the complexity of investigating sexual assaults, which presents unique challenges for law enforcement, including the private nature of the crime, lack of eyewitnesses, and difficulties in obtaining physical evidence and credible testimonies. Without some form of digital evidence, the processing of a case through the real-time crime center seldom occurs. Inconsistencies in victim and witness statements and the difficulty in collecting and processing physical evidence, especially if the assault happened outside of a specific time frame, may also contribute to this outcome. Consequently, due to underlying factors that may further complicate a sexual assault case, the adoption of centralized police technologies alone may not have a significant impact on the case clearance rates of sexual assault incidents.Secondly, the findings of the study indicate that domestic violence incidents have higher case clearance rates than all other violent crimes included in the analyses. Beyond some influence of MRTCC information technologies, this improvement in clearance rates may be attributed to the following two elements: the relationship between the victim and offender and mandatory arrest policies. In all domestic violence incidents included within the analyses, a relationship existed between the victim and offender , facilitating the identification and apprehension of the perpetrator by law enforcement personnel. The prompt arrest of the offender may further encourage victims to cooperate with law enforcement and the prosecution, leading to a higher likelihood of successful case clearance or resolution. Moreover, improvement in clearance rates may be credited to the mandatory arrest policy implemented across Florida agencies. This policy requires officers to make an arrest when responding to a domestic violence call if they have probable cause to believe a crime has been committed, thus eliminating officer discretion.Thirdly, despite the integration of MRTCC technologies with conventional evidentiary sources in processing other violent crimes, traditional means of evidence collection and crime scene analysis are found to be more prevalent in the investigation of sexual assault and domestic violence incidents. This discovery emphasizes the complexity of these crimes and the necessity for a multi-faceted investigative approach, where technological advancements supplement, rather than replace traditional investigative techniques. This finding underscores the importance of continually evaluating and improving investigative methods to ensure that the highest possible clearance rates for sexual assault and domestic violence cases are achieved.The limitations of the study were its focus on only one city-level jurisdiction and a subset of criminal activity . Accordingly, we do not know if these findings would hold up if replicated in other jurisdictions across the country, nor do we know how the use of these technologies for sexual assault by domestic violence investigations would compare to other non-violent crime types . However, this does not diminish the significance of its findings. By elucidating the mechanisms by which RTCC platforms can successfully combat underreported criminal acts such as sexual assault and domestic violence, law enforcement agencies in other jurisdictions can potentially apply these approaches to bolster their efforts toward crime reduction and enhanced public safety.Furthermore, in the context of case processing and outcomes, a significant limitation arose regarding the ability to determine the admissibility of evidence obtained by MRTCC detectives and external unit investigators. Specifically, the coding of variables was based solely on whether these personnel utilized sources of evidence or technologies, without considering whether such evidence ultimately proved to be valuable in the investigation process. For instance, although the dataset included CCTV footage, the actual evidentiary value of the footage was not taken into account. Additionally, the limited sample sizes prevented the independent analysis of domestic violence and sexual assault incidents.The critical role of law enforcement in the development of a comprehensive strategy to combat sexual assault and domestic violence cannot be overstated. The enactment of the Violence Against Women Act in 1994 marked a significant milestone in the history of combating gender-based violence in the United States, with law enforcement at the forefront of its implementation . This le


Evaluate benefits and harms of needling therapies (NT) for chronic primary low back pain (CPLBP) in adults to inform a World Health Organization (WHO) standard clinical guideline.Electronic databases were searched for randomized controlled trials (RCTs) assessing NT compared with placebo/sham, usual care, or no intervention (comparing interventions where the attributable effect could be isolated). We conducted meta-analyses where indicated and graded the certainty of evidence.We screened 1831 citations and 109 full text RCTs, yeilding 37 RCTs. The certainty of evidence was low or very low across all included outcomes. There was little or no difference between NT and comparisons across most outcomes; there may be some benefits for certain outcomes. Compared with sham, NT improved health-related quality of life (HRQoL)   at 6 months. Compared with no intervention, NT reduced pain at 2 weeks  and 3 months ; and reduced functional limitations at 2 weeks  and 3 months . In older adults, NT reduced functional limitations at 2 weeks  and 3 months . Compared with usual care, NT reduced pain  and functional limitations  at 3 months.Based on low to very low certainty evidence, adults with CPLBP experienced some benefits in pain, functioning, or HRQoL with NT; however, evidence showed little to no differences for other outcomes.The online version contains supplementary material available at 10.1007/s10926-023-10125-3. These ieridians . A seconeridians . It is ueridians . Variouseridians ; the releridians ; or locaeridians , 9.Mu and colleagues published a Cochrane systematic review (2020) to assess the effects of needling therapies compared to sham intervention, no treatment, or usual care for chronic non-specific LBP ; 8270 participants; search end date of August 2019) . They foThe objectives of this systematic review of RCTs were to determine: (1) the benefits and harms (as reported in RCTs) of needling therapies compared with placebo/sham, usual care, or no intervention for the management of CPLBP in adults, including older adults (aged ≥ 60 years); and (2) whether the benefits and harms of needling therapies vary by age, gender/sex, presence of leg pain, race/ethnicity, or national economic development of the countries where the RCTs were conducted.This systematic review was conducted as part of a series of reviews to inform the WHO guideline on the management of CPLBP in adults. CPLBP is defined as pain of more than three months duration between the lower costal margin and the gluteal fold with no specific underlying cause. Guideline development was ongoing at the time of submission of this manuscript. The methods are detailed in the methodology article of this series .Briefly, we updated and expanded the scope of the previously published high-quality Cochrane systematic review by Mu et al. . We regiWe included RCTs that compared needling therapies to placebo/sham , usual care, no intervention  in adults (aged ≥ 20 years) with CPLBP. Eligible needling therapies included those conducted according to TCM theory or myofascial acupuncture methods . Specifically, we included interventions where needles were inserted into classical meridian points, tender points, or trigger points through the skin. Manual stimulation, heating by moxa, heat lamps, cupping or electrical current stimulation could be further administered to maximize the treatment effect . We exclWe assessed between-group differences to determine the magnitude of the effect of an intervention and to assess its effectiveness , 13  using the Cochrane ROB 1 tool , modifieIn addition to the main sub-group analyses conducted for all reviews in this series , we conducted the following pre-specified sub-group analyses: needling therapy type , and stimulation used with needling therapies . We conducted sensitivity analyses by excluding RCTs judged to have high risk of bias.We performed random-effects meta-analyses and narrative synthesis where meta-analysis was not appropriate , and graWe screened 1831 records and 109 full-text reports ; while 6 of 37 RCTs (16%) assessed mysofascial acupuncture , 48, 62./37, 84%;The outcomes were assessed in the immediate term 31 RCTs) [ RCTs 31, 31–34, The certainty of the evidence for all outcomes was low or very low, downgraded due to risk of bias, inconsistency, indirectness, and imprecision of the effect estimates .no pain) in the immediate term    [With low certainty evidence, needling therapies may reduce pain  , 62, 66.t 1.1.1) –28, 32, t 1.1.1) , 27. Duet 1.1.1) , 41, 57.functional limitations in the immediate  (plot 1.2.1) [Due to very low certainty evidence, it is uncertain whether needling therapies make little or no difference to t 1.2.1) , 57, 62,t 1.2.1) –28, 32. t 1.2.1) , 57.HRQoL in the immediate term  (plot 1.3.1) [Due to very low certainty evidence, it is uncertain whether needling therapies make little or no difference to t 1.3.1) . In the t 1.3.1) , or maket 1.3.1) , 32. In t 1.3.1) , or to Ht 1.3.1) , 32. Duet 1.3.1) , 32; andt 1.3.1) , 32.depression in the immediate  ( plot 1.4.1) [Due to very low certainty evidence, it is uncertain whether needling therapies make little or no difference to t 1.4.1) , short (t 1.4.1) , 28, or t 1.4.1) , 28.adverse events/harms  = 1.62, 95% CI 0.67 to 3.90) (plot 1.5) [Due to very low certainty evidence, it is uncertain whether needling therapies make little or no difference to lot 1.5) , 57, 62.Based on one RCT  and repopain in the immediate , short , or intermediate term ; function in the immediate , short , or intermediate term ; or HRQoL in the immediate term (effect estimates not provided). Authors reported no serious harms/adverse events occurred during the 4-week RCT; 2 of 46 participants total (4.3%) had subcutaneous hematoma after needling (both from the needling therapy group) [It is uncertain whether needling therapy makes little or no difference to: y group) .pain in the immediate   in the immediate   in the immediate term  (plot 2.3.1) [HRQoL with respect to the PCS   (plot 2.3.2.1) [Due to very low certainty evidence, it is uncertain whether needling therapy makes little or no difference to t 2.3.1) . In the 2.3.2.1) . It is u2.3.2.1) .depression in the short term  (plot 2.4.1) [Due to very low certainty evidence, it is uncertain whether needling therapy makes little or no difference to t 2.4.1) .adverse events/harms  (plot 2.5) [Due to very low certainty evidence, it is uncertain whether needling therapies make little or no difference to lot 2.5) , 49, 57.pain in the immediate   (plot.2.6.1.1), or short term  (plot2.6.2.1); or functional limitations in the immediate  (plot 2.7.1.1), or short term  (plot 2.7.2.1). No RCTs assessed harms/adverse events.One RCT assessed older adults . Due to pain in the short  (plot 3.1.1), or intermediate term   (plot 3.2.1); or whether needling therapy makes little or no difference to pain in the long term  (plot 3.1.3). It is uncertain whether needling therapy reduces functional limitations in the short  (plot 3.2.1), intermediate  (plot 3.2.2), or long term   (plot 3.2.3). No RCTs assessed harms/adverse events.One trial assessed benefits . Due to The subgroups were small (consisting of 1 to 3 RCTs per group), yielding small, imprecise pooled effects (see Online Resource 7). In addition, there was inadequate reporting of some factors, such as gender/sex or presence of leg pain in participants, which further limited the usefulness of the pooled results. Despite limitations, subgroup effects were overall in line with those of the main analysis.We examined publication bias using funnel plots when the number of RCTs per comparison was 10 or more. Two funnel plots (needling therapy versus no treatment for pain and function in the immediate term) showed no substantial publication bias .Recent evidence regarding the benefits and harms of needling therapies for CPLBP in adults is based on 37 RCTs . Most of the RCTs  were rated as having a high overall ROB and the certainty of the evidence for all outcomes ranged from low to very low. For most outcomes, there was little or no difference between needling therapies and comparison interventions. Evidence suggested the following clinically important benefits for certain outcomes (with low to very low certainty): (1) compared to sham, evidence suggested a small improvement in HRQoL  in the intermediate term; (2) compared to no intervention (including comparison interventions where the attributable effect of needling therapies could be isolated), evidence suggested small reductions in pain in the immediate and short terms, and large and moderate reductions in functional limitations in the immediate and short term, respectively. In older adults, evidence suggested a larger reduction in functional limitations in the immediate and short terms; (3) compared to usual care, evidence suggested a small reduction in pain and functional limitations in the short term. Of nine RCTs reporting on harms/adverse events, 4.3% (2/46) older adults reported mild subcutaneous hematoma after needling compared with sham needling (1 RCT).Our findings align with those by Mu et al. , as discOur systematic review has several strengths. First, we had an expert review team that included international clinical and methodological experts in the fields of LBP, systematic reviews and evidence syntheses, and answering important policy questions from the WHO. Second, our review employed comprehensive and peer-reviewed literature search strategies that did not have any language restrictions. Third, we ensured that at least half of the screening and ROB pairs were formed by a member of the core team, who was the most trained and reliable in screening and ROB judgements. Fourth, unlike other systematic reviews that relied on the number of items at risk of bias or summary scores for ROB assessments, we developed and used adjunct guidance forms based on the ROB1 criteria, which allowed reviewers to consider important critical flaws . ConsequThere are potential limitations to our systematic review. First, despite our rigorous literature search strategies, we may have missed some potentially relevant RCTs, especially as we were unable to retrieve and assess the eligibility of 54 full-text RCTs identified from our database search . This may have increased or decreased our effect estimates. Second, our pre-specified eligibility criteria was restricted to published trials and did not search the grey literature. However, we do not have strong evidence to suggest our review was impacted by publication bias, based on our publication bias assessment. We searched for unpublished RCTs in the WHO ICTRP registry and contacted authors of unpublished RCTs. However, only two authors responded, and the reason given for non-publication was ongoing RCTs. While we are uncertain how publication bias may have impacted our findings, unpublished studies have been shown to represent a small proportion of studies and rarely impact the results and conclusions , 69. FinWe identified evidence gaps across all comparisons. First, there were some outcomes for which there were no RCTs, mainly psychological outcomes , social participation including work; or change in medication use or falls in older adults. Further research is needed to explore these outcomes comprehensively.For the comparison of needling therapies to sham, we found no RCTs to inform the long-term benefits on function, or depression. For the comparison of needling therapies to no intervention or interventions where the attributable effect of needling therapies could be isolated, we found no RCTs to inform the intermediate- to long-term benefits on pain, HRQoL and depression and no RCTs to inform the long-term benefits on function. Finally, we identified a scarcity of pragmatic RCTs comparing needling therapies with usual care, which may limit our understanding of their comparative effectiveness in real-world settings.In terms of assessing benefits and harms, subgroup analyses posed challenges, particularly when considering mode of delivery and spine-related leg pain. This limitation may prevent guideline developers from providing specific case mix recommendations for clinical practice. Moreover, the reporting of harms/adverse events across studies was inadequate and inconsistent. This is particularly concerning for older adults and individuals taking anti-coagulants, as it hampers our ability to assess potential risks accurately.Based on low or very low certainty evidence, adults with CPLBP experienced small improvements with respect to pain and HRQoL , and both adults and older adults experienced larger reductions in functional limitations. Needling therapy was associated with a small increased risk of subcutaneous hematoma in older adults, compared to sham needling. The remaining evidence showed little to no difference in benefits between needling therapies and comparisons for other outcomes, such as depression. Patient care plans should be developed through a collaborative decision-making process, that carefully considers scientific evidence, cost-effectiveness, and relevant contextual factors, such as values and preferences of users of needling therapies. Adverse events should be investigated systematically.Supplementary file1 (DOCX 6077 kb)Below is the link to the electronic supplementary material.


Evidence-based sentencing (EBS) is a new name for an aspiration that has deep roots in criminal law: to apply the sentence most appropriate to each offender's risk of reoffending, in order to reduce that risk as far as possible. This modern version of the traditional sentencing goals of rehabilitation and incapacitation fits into the broader approach of so-called “evidence-based public policy.” It takes the view that the best existing evidence for reducing reoffending are modern structured risk assessment tools and claims to be able to achieve several goals at once: reducing reoffending, maintaining high levels of public safety, making more efficient use of public resources, and moving criminal policy away from ideological battles by basing it on the objective knowledge provided by the best available scientific evidence. However, despite the success of this approach in recent years, it is not clear to what extent it succeeds in correctly assessing the risk of individual offenders, nor whether it achieves its intended effect of reducing recidivism. This paper aims to critically examine these two issues: the quality of the scientific evidence on which EBS is based, and the available data on the extent to which it achieves (or does not achieve) its intended goals. The evidence provided by social science on the effects of punishment has been systematically ignored by US criminal justice policy for at least 40 years.None of these initiatives had evidence that they were effective in reducing crime , the pre-trial phase and the adoption of precautionary measures, the sentencing phase, and the enforcement of the penalties (evidence-based corrections).In the evidence-based sentencing approach (hereinafter EBS) there is a very close link between the moment when the sentence is imposed and its subsequent enforcement, since the aim is to impose sentences that, due to their characteristics, allow the implementation of the programmes that are considered most appropriate to reduce the risk of reoffending , whereas in the social sciences there are many other types of analysis that can provide relevant knowledge about the complexity of the relationships and tensions inherent in social reality.As a result of all these problems, other approaches have also emerged that broaden the type of scientific evidence considered relevant for evaluating public policies in relation to complex social problems, moving away from an exclusive focus on randomized control trials and meta-analysis, and combining qualitative and quantitative methods in a flexible way. One example is realist evaluation, developed by Pawson and Tilley , which rIn short, the (laudable) goal of designing and implementing policies that are more transparent and effective because they are based on solid knowledge of their effects and consequences is by no means easy to achieve, as it is threatened by at least two risks: on the one hand, the risk of passing off as “evidence-based policy” what in reality is nothing more than “policy-based evidence,” i.e., the selective use of data to legitimize pre-established policy objectives with this supposed scientific evidence , false negative (considered not dangerous but did reoffend), true positive (considered dangerous and did reoffend) and false positive (considered dangerous but did not reoffend).Since the 1990s, however, a distinction has been made between the occurrence or non-occurrence of the event, and the different degrees of confidence one can have that the event will occur , but the false positive and false negative rates can vary dramatically depending on which discrimination threshold is used to make a particular decision. For example, suppose we were to use a risk assessment tool that classifies people into five risk levels  and has an area under the ROC curve of 0.75, to decide whether to grant parole. If we decide to parole only those who are classified as very low risk, we will have many false positives and very few false negatives; if we parole all but those in the very high risk group, we will have many more false negatives and fewer false positives. None of these error rates need to coincide with the area under the curve (75%), and both false positives and false negatives can be well above or well below 75% for each of our decisions, depending on the threshold we have set in each case.For these reasons, several authors have warned that the value of the area under the ROC curve alone is very uninformative when assessing the usefulness of a risk assessment tool for legal decision-making , explicitly stating that these achieve acceptable or satisfactory values, but not providing information on absolute risk, i.e., the probability of reoffending or violent reoffending associated with each level of risk, nor do they usually provide the positive and negative predictive values associated with each discrimination threshold.Because of all these problems, and some others that risk assessment also presents,In short, notwithstanding the fact that risk estimates work much better for other things , the empirical evidence accumulated over the last 40 years shows time and again that we are still wrong more than half the time when we make estimates of high risk of violent crime. And although it is sometimes criminologists themselves who explicitly warn of this problem and of the consequences of using these estimates as the basis for measures that severely restrict rights,It is relatively common for evidence of the success of EBS to be cited, for example, that judges and other actors in the criminal justice system find the information provided by risk assessments useful, or that as a result of the introduction of EBS the number of prison sentences has been reduced and the number of alternative sentences increased.However, whereas there are many studies on the predictive validity of risk assessment tools, far fewer have studied their usefulness in reducing recidivism or crime rates .As for the fact that recidivism remained constant after the introduction of risk assessment, the authors of the study rule out as a possible explanation that the tool used in Virginia is flawed or poorly designed, and simply point to the fact that recidivism is a very difficult phenomenon to predict under any circumstances. In their view, risk estimates explain only a tiny percentage of recidivism, so that adopting one policy or another on the basis of these estimates can have only a very limited effect on the variation in reoffending rates , but at the same time there are good reasons for not doing so, which must be respected and which make it impossible, then it would seem that the proponents of the practice themselves are acknowledging the impossibility of its success.On the other hand, it is highly doubtful that even if sentencing were to be based solely and exclusively on risk level, the desired objectives could be achieved. This is partly because, as we have already seen, the scientific evidence on which evidence-based sentencing is based is much less robust than it might appear at first sight. The high rates of false positives raise serious questions about the efficiency of a system that would systematically devote excessive resources to intensive criminal control of people who do not need it. And the concern for reoffending that underpins the whole approach reflects an intolerance of false negatives that would probably also favor a penal response to low-risk groups that is disproportionate to the real risk they pose. Moreover, if it is not easy to estimate the risk of reoffending with a high degree of accuracy, it is even more difficult to reduce that risk. There are, of course, effective treatment programmes for reducing reoffending,What is more, risk assessments are not the only knowledge about crime that criminology has produced in its long history: on the contrary, there is scientific evidence that would support penal policies quite different from those advocated by EBS. Take age, for example: being young is one of the factors most directly correlated with a higher risk of reoffending and violent recidivism, and is therefore included in virtually all assessment tools. Age can explain almost 50% of the risk score in structured instruments, and its weight in the total score is often equal to or greater than that of criminal history.There is yet another consideration to be made in relation to age as a risk factor and scientific evidence. We have already mentioned, there is a well-established tradition in criminal law of valuing youth as a mitigating factor. Most countries have specific juvenile justice systems that operate based on re-education criteria and provide for comparatively lighter penalties than those imposed on adults who commit the same offense. This is justified by the fact that social sciences, and psychology in particular, show that minors, even if they know the rules from a certain age onwards, are generally still immature, highly impressionable, impulsive, and with a lower capacity to tolerate frustration. These psychological characteristics merit the application of milder punishments from a retributive perspective. More recently, neuroscience has confirmed that there are not only psychological differences between adolescents and adults, but that the degree of brain development differs between them, and that this difference persists not only until the legal age that marks the borderline for treatment as an adult in many countries (around 18 years), but also until the early twenties.There is, therefore, empirical evidence to justify imposing more intensive penal regimes on young adults because of the greater risk of reoffending they represent, if we consider that incapacitation is the central aim of the penal system. And there is also empirical evidence to justify a more lenient penal response for the same group of people if we consider that punishment proportionate to the degree of responsibility should be the central criterion for sentencing. Much the same can be said for other factors, such as certain mental illnesses.In the design of criminal policy, scientific evidence is sometimes important and sometimes not. There are areas that have proved to be impervious to the social science evidence accumulated over the years on the zero or very limited effectiveness and the enormous side effects of certain practices , and others where scientific evidence has been more or less successful in penetrating . The main reasons why criminological evidence is or is not taken into account are not primarily related to its scientific quality, but to other factors: whether or not it fits in with the political objectives pursued by governments at a given time, whether it coincides with a window of opportunity to be well received by public opinion, whether or not there is pressure from certain interest groups for or against the inclusion of this evidence, and so on Tonry, . The samConsequently, the term “evidence-based”  is not justified in my view, and it would be preferable to refer to this approach by one of the other terms that, as we saw at the beginning of this paper, describe its content well: predictive sentencing or risk-based sentencing, for example.What is more, evidence-based sentencing suffers from some of the problems that plague “evidence-based policy” described in section 2.3 of this paper. It presents itself as based on “the best available evidence” but fails to make explicit the many shortcomings (as well as the undoubted virtues) of structured risk assessment for reoffending, and thus offers at best an incomplete (and at worst a biased) picture of the true state of scientific knowledge about the predictive capacity of risk assessment and its actual impact (or lack of impact) on crime rates. On the other hand, it encourages (either deliberately or inadvertently) a depoliticisation of the criminal justice debate by presenting risk-based sentencing as a practice that “works,” and should therefore be accepted, when the crucial question is: it works for what? Evidence-based sentencing assumes that the “what for” must be the reduction of reoffending, but it has not yet been shown to do so, nor is it at all clear that this should be the primary aim of the criminal justice system. There are many other possible and legitimate objectives, such as ensuring the non-discriminatory application of sentences, promoting the rehabilitation of as many offenders as possible, avoiding the imposition of disproportionate sentences, or, of course, reducing crime rates, which is not the same as reducing reoffending rates. The debate about which of these goals should be preferable or a priority necessarily involves value-based arguments , and although it can  also deal with arguments related to what criminology knows about the effects of punishment, it cannot be replaced by them.This is why I believe that evidence-based sentencing, at least in the form that it has taken in recent years in the US, is not a truly evidence-based practice, but rather an example of the selection of certain scientific evidence to justify certain public policies (policy-based evidence), hiding behind supposedly technical reasons options that can only be the subject of political debate.Finally, I would like to stress that the criticism leveled at EBS in no way detracts from the fact that various rehabilitation programmes have shown good results in reducing reoffending. I also believe that risk assessment tools do a reasonably good job of discriminating between groups at higher and lower relative risk, and that they identify the lower-risk groups with a remarkable degree of accuracy, which can help with allocation to treatment programmes and provide a strong argument for widening the range of alternatives to prison. Effective rehabilitation can (and in my view should) have an important place in the enforcement of sanctions. But this does not mean that there is a sufficient scientific basis—nor, in my view, better reasons—to make so-called “evidence-based” sentencing the cornerstone of the criminal justice system.LM-G: Writing—original draft, Writing—review & editing.


Spleen stiffness did not correlate with spleen fat content and liver stiffness but a statistically significant correlation with spleen volume was found. Conclusions: The findings of this study provide normative values for 2D MRE-based measurement of spleen stiffness in young adults, a basis for assessing the value of this biomarker in young patients with portal system pathologies.Purpose: Magnetic resonance elastography (MRE) has been established as the most accurate noninvasive technique for diagnosing liver fibrosis. Recent publications have suggested that the measurement of splenic stiffness is useful in setting where portal hypertension may be present. The goal of the current study was to compile normative data for MRE-assessed stiffness measurements of the spleen in young adults. Materials and Methods: A total of 100 healthy young Caucasian volunteers  in the age range of 20 to 32 years were enrolled in this study. The participants reported no history of chronic spleen and liver disease, normal alcohol consumption, and a normal diet. The MRE data were acquired by using a 1.5 T whole-body scanner and a 2D GRE pulse sequence with 60 Hz excitation. Spleen stiffness was calculated as a weighted mean of stiffness values in the regions of interest manually drawn by the radiologist on three to five spleen slices. Results: Mean spleen stiffness was 5.09 ± 0.65 kPa for the whole group. Male volunteers had slightly higher splenic stiffness compared to females: 5.28 ± 0.78 vs. 4.98 ± 0.51 kPa, however, this difference was not statistically significant ( Magnetic resonance elastography (MRE) is an innovative diagnostic technique used to assess the stiffness of soft tissues in a non-invasive manner. MRE was developed by researchers at the Mayo Clinic in Rochester, USA, during the 1990s . InitialFrom a physical perspective, MRE involves three steps. The first step is to induce shear waves in the targeted area. This is achieved by applying vibrations generated by an active acoustic driver located outside the diagnostic room. Typically, the vibration frequency ranges from 20 to 100 Hz  spleen stiffness value in the cohort was 5.09 [0.65] kPa , ranging from 3.89 to 7.24 kPa.2 with a mean [SD] of 21.33 [2.16] kg/m2. The spleen volume ranged from 123.94 to 422.43 cm3 while the mean [SD] value was 231.13 [58.44] cm3.The BMI was in the range of 16.85–25.76 kg/mp = 0.12)  and male volunteers  was not significant statistically ( = 0.12) . p = 0.20) (p = 0.74), BMI  (p = 0.95) (p < 0.001)  . Spleen  = 0.36) , and liv = 0.95) . However< 0.001) . The resThe spleen stiffness obtained in the group of healthy volunteers ranged from 3.89 to 7.24 kPa with a mean value of 5.09 kPa. These results show that the normal spleen is stiffer than the normal liver, pancreas, prostate, and uterus ,43,44,45The spleen stiffness value from our study was higher than in a group of 12 volunteers recruited by Talwalkar et al.: 3.6 ± 0.3 kPa . Other rThe splenic stiffness was higher in men than in women but this difference did not show statistical significance. Prior reports have been mixed in this regard ,47.In contrast to the results of Talwalkar et al. , the splThe estimated fat content in the spleen and spleen R2* also did not impact its stiffness in healthy volunteers. On the other hand, we observed a statistically significant correlation between spleen stiffness and spleen volume in healthy volunteers. Alternative shear wave-based methods for elasticity assessment of the spleen are ultrasound-based transient elastography (TE), point shear wave elastography (pSWE), and 2D and 3D shear wave elastography (SWE) ,49. The It is worth emphasizing that ultrasound-based elastography techniques differ from each other and MRE in terms of technological and physical details as well as methods of data acquisition . Hence, The presented study has several limitations. In this project, we focused on assessing the spleen stiffness of healthy young adults, therefore, the age range of the subjects was relatively narrow. Future studies including individuals within a wider age range should be conducted to verify the results. The study included exclusively Caucasian volunteers, which might be also perceived as a limitation. Finally, the study was conducted with a 2D MRE technique, which has known limitations compared with 3D MRE for splenic stiffness measurement but the latter technique is not yet widely available.The current research is the largest prospective study compared with all other reports on this topic. Another strength of the presented study is the meticulous selection of participants, which increases the credibility of the obtained findings.The findings of this study provide normative values for 2D MRE-based measurement of spleen stiffness, a basis for assessing the value of this biomarker in young patients with portal system pathologies.