Vertebral compression fractures (VCFs) can impair posture, gait, and daily activities in patients undergoing total hip arthroplasty (THA). However, limited data are available regarding the incidence, risk factors, and impact of VCFs on sagittal spinal alignment following THA. Therefore, the purpose of this study was to investigate the incidence and risk factors of VCFs after THA, and to evaluate their impact on sagittal spinal alignment and clinical outcomes. This retrospective cohort study included 220 patients (243 hips) who underwent primary THA, with a mean follow-up period of 6.1years. Data collected included patient demographics, Fracture Risk Assessment Tool (FRAX) scores, lumbar bone mineral density measured before THA, sagittal spinal alignment parameters, Harris Hip Score (HHS), and the occurrence of new VCFs. We analyzed changes in spinal alignment and identified risk factors associated with incident VCFs. VCFs occurred in 20% of hips during the follow-up period. Patients who developed VCFs demonstrated a significantly increased sagittal vertical axis, reduced lumbar lordosis angle, and lower postoperative HHS compared to those without VCFs. Preexisting VCF and higher preoperative FRAX scores were significantly associated with the development of new VCFs. Multivariate logistic regression analysis identified the FRAX score as an independent predictor of incident VCFs. In this 6.1-year retrospective cohort study, 20% of hips developed new VCFs after THA, which were associated with worsened spinal alignment and hip function. The higher FRAX score, calculated prior to THA surgery, is a useful predictor of VCF risk and may help identify individuals who require closer monitoring or preventive interventions during follow-up after surgery. Video Abstract.

Chronic pain is often a primary symptom for rheumatologic conditions. With the legalization of cannabis in Canada and many other jurisdictions, the use of cannabis is increasing. A risk assessment tool can guide clinicians and patients on the potential risk associated with cannabis use for alleviating the symptoms of rheumatologic conditions. The aim of this Delphi study is to identify key elements for the development of a risk assessment tool for the safe use of cannabis for people with rheumatologic disease. International experts representing different healthcare professions in rheumatology were invited through targeted recruitment. The research team developed statements for the Delphi consensus based on literature review and focus groups. The number of rounds was dependent on when consensus was reached. The level of agreement was set at 75%. A total of 12 experts participated, independently rated 45 statements. Consensus (≥ 75% agreement) was achieved on 40 of 45 items (88.9%) after two rounds, and all 40 items were confirmed in a third validation round. Statements were categorized as patient demographics, medical history, lifestyle, or socioeconomic. Demographic factors (age and gender) and medical conditions such as substance use disorders and schizophrenia were identified as important to consider with cannabis use along with cannabis consumption patterns, including the age of first use, method, and frequency of use. This Delphi consensus identified essential elements for a comprehensive cannabis risk assessment tool for patients with rheumatologic conditions. The agreed-upon items provide a structured foundation to support clinicians in evaluating patient-specific risks and guiding safe cannabis use in rheumatology care. Further validation and clinical testing are recommended to optimize its utility in practice. Key Points • As increasing numbers of patients consider using cannabis for pain management of rheumatologic conditions, a guide would be helpful to consider a risk assessment tool for patients and healthcare providers. • The aim of this Delphi study was to gain a perspective of clinicians and experts regarding items that should be included in a cannabis safe use tool in rheumatology. • We collaborated with international experts to reach a consensus on key factors influencing cannabis use risk. • This study highlights the importance of factors such as age, gender, underlying medical conditions, and consumption patterns, including the age of first use, method, and frequency of use.

BackgroundProgrammed death-1 (PD-1) inhibitors combined with chemotherapy have become a standard treatment for human epidermal growth factor receptor 2 (HER2)-negative advanced gastric cancer (GC). However, responses vary, and effective prognostic biomarkers are needed. This study aimed to investigate the prognostic value of dynamic changes in carcinoembryonic antigen (CEA) levels in this patient population.MethodsThis retrospective cohort study included 96 patients with HER2-negative metastatic or locally advanced GC treated at our institution between June 2021 and June 2024. All patients received PD-1 inhibitors plus chemotherapy. Serial CEA measurements were used to construct a linear model (Y = ax + b) for each patient, where ‘a’ represents the slope of CEA change. Using a receiver operating characteristic (ROC) curve analysis for predicting 6-month progression-free survival (PFS), an optimal cutoff slope of a = 0.85 was determined. Patients were stratified into a Slow-riser group (a ≤ 0.85, n = 70) and a Rapid-riser group (a > 0.85, n = 26). We compared treatment efficacy, survival outcomes, and adverse events between the groups. Prognostic factors for PFS were identified using univariate and multivariate Cox proportional hazards models, in line with TRIPOD principles.ResultsDuring treatment, serial CEA levels exhibited a fluctuating pattern with an overall upward trend. Compared to the Rapid-riser group, the Slow-riser group had a significantly higher disease control rate (DCR) (71.4% vs. 46.2%, P = 0.028) and a lower incidence of progressive disease (PD) (24.3% vs. 53.8%, P = 0.012). The Slow-riser group also experienced a lower incidence of grade ≥ 3 adverse events (22.9% vs. 46.2%, P = 0.040). The median PFS (mPFS) was significantly longer in the Slow-riser group than in the Rapid-riser group (3.9 vs. 2.4 months, P = 0.022), although median overall survival (mOS) was not statistically different (16.3 vs. 12.7 months, P = 0.245). Multivariate Cox regression analysis identified CEA trend (Rapid-riser vs. Slow-riser: HR 7.15, 95% CI 2.85–12.11, P < 0.001), number of metastatic sites, peritoneal metastasis, liver metastasis, ECOG performance status, and differentiation grade as independent predictors of poor PFS.ConclusionThe dynamic trajectory of CEA levels during treatment is a significant and independent prognostic factor for patients with HER2-negative advanced GC receiving PD-1 inhibitors plus chemotherapy. Slower CEA elevation is associated with better disease control, improved safety, and longer PFS. Monitoring dynamic CEA changes could be a valuable, accessible tool for clinical risk assessment and patient stratification.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12885-025-15215-4.

Estimated pulse wave velocity (ePWV) is a non-invasive and low-cost method that uses age and blood pressure to assess cardiovascular risk. However, as it is not a true measure of arterial mechanics, its accuracy in diverse cohorts, such as Brazilian populations, is uncertain due to inherent genetic and environmental differences. to externally validate existing European ePWV equations and develop new, population-specific models for ePWV estimation in a large, admixed Brazilian cohort. We analyzed data from 2122 Brazilian adults, assessing carotid-femoral pulse wave velocity (cfPWV), age, mean arterial pressure (MAP), and sex. Linear regression models were developed, incorporating all these variables as predictors. Model performance was evaluated using root mean square error (RMSE) and coefficient of determination (R2). Bland-Altman analyses assessed agreement between estimated and measured cfPWV. The newly developed equations demonstrated superior performance compared to existing European models. Our best-performing model (Equation 2) achieved an RMSE of 0.744 in individuals without cardiovascular risk factor, demonstrating superior performance to the model derived by the Arterial Stiffness Collaboration Group (ASCG) (RMSE: 0.879). Inclusion of sex as a predictor further improved model accuracy. Bland-Altman analyses revealed narrower limits of agreement for the new models. Notably, higher prediction errors were observed in subgroups underrepresented in the sample, such as individuals with very high cfPWV, advanced age, or elevated MAP. Population-specific ePWV equations tailored to the Brazilian cohort provide more accurate estimations of arterial stiffness. This improved precision is clinically meaningful, allowing for better stratification of cardiovascular risk using a low-cost tool readily applicable in the public health system. These findings underscore the importance of developing and validating cardiovascular risk assessment tools within diverse populations to enhance predictive accuracy and clinical utility.

SummaryOsteoporosis is a growing health burden requiring early risk assessment. In Saudi adults ≥ 60 years, FRAX scores with and without BMD showed minimal reclassification, with most shifts toward higher risk in younger groups. FRAX without BMD offers reliable stratification, supporting its use as a first-line screening tool.MethodsA retrospective cross-sectional study included patients aged ≥ 60 years attending family medicine clinics at King Faisal Specialist Hospital & Research Centre, Riyadh, undergoing DXA screening between January 1, 2016, and December 31, 2022. Baseline variables were age, sex, and BMI. FRAX variables assessed were family history of hip fracture (HF), prior fracture, smoking, glucocorticoid use, rheumatoid arthritis, and alcohol intake. Fracture risk was categorized using fixed and age-specific thresholds; differences in FRAX scores and reclassification patterns were evaluated.ResultsAmong 1,429 patients (mean age 68.07 ± 6.62 years), FRAX scores for major osteoporotic fracture (MOF) and HF) differed significantly with and without BMD. Subgroup analysis revealed no significant differences within specific age ranges (70–75 years for MOF and 60–75 years for HF) or among men across all age groups. Reclassification occurred in a small subset of patients, predominantly shifting toward higher-risk categories, particularly in younger age groups.ConclusionFRAX without BMD provides robust risk stratification, with minimal impact on reclassification across age categories. These results highlight its utility as a primary screening strategy, whereas BMD assessment may be reserved for cases requiring further refinement.PurposeOsteoporosis is a skeletal disorder defined by reduced bone mineral density (BMD), commonly assessed by dual-energy X-ray absorptiometry (DXA). The Fracture Risk Assessment Tool (FRAX) estimates 10-year fracture risk. Saudi Arabia was recently included in FRAX, enabling population-specific risk estimation. Notably, FRAX can be applied with or without BMD, but limited Saudi data exist comparing both methods.

This study aimed to develop and validate a dynamic risk assessment tool for individuals serving community sentences that accounts for the effects of acute adverse events and desistance from crime. Dynamic risk prediction models that incorporate updated data on mental health relapses, incidents of victimization, and desistance from crime will produce more accurate risk stratification for reoffending than models lacking dynamic measurement of risk factors. We analyzed a national cohort of 59,676 individuals given community sentences in Sweden, of whom 23,879 (45%) had prior psychiatric diagnoses and 18,546 (31%) had substance use disorder diagnoses. Model development tested prespecified criminal history, sociodemographic, and clinical risk factors. Employing landmarking methods for time-to-event data, we modeled the effects of new health care episodes during community supervision, changes in a supervised individual's circumstances, and the impact of crime desistance. We validated the model in a geographically distinct population. During follow up, 18,307 (31%) were reconvicted, 4,416 (7%) committed a violent offense, and 5,381 (9%) were hospitalized with a psychiatric diagnosis. The model demonstrated strong calibration and discrimination performance (c-index = 0.74 for violent reoffending, c-index = 0.69 for general reoffending). It also outperformed comparison models that did not incorporate dynamic data. The final model was translated into an online risk calculator (OxMore). Implementation of dynamic models could lead to more accurate risk stratification for individuals under community supervision, including those with psychiatric and substance use disorders, potentially improving resource allocation, and linkage to interventions that reduce recidivism rates. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

To evaluate quality use of medicines (QUM) in patients admitted to the Psychiatric Alcohol and Non-Prescription Drug Assessment (PANDA) Unit through analysis of polypharmacy risk, prescribing safety indicators and national QUM indicators. Retrospective review of electronic medical records for 787 patients (1245 episodes) admitted to PANDA Unit, St Vincent's Hospital Sydney, November 2020-December 2021. We assessed polypharmacy risk using NSW Therapeutic Advisory Group's Inappropriate Polypharmacy Risk Assessment Tool, evaluated nine prescribing safety indicators (PSIs) and assessed four national quality use of medicines indicators (NQUMIs) in a randomly selected subset of 103 patients. Mean age was 40.2years; 67.2% were male. Alcohol-related diagnoses comprised 32.1% of presentations. Medium-risk (43.5%) and high-risk (37.2%) polypharmacy were prevalent, largely reflecting protocol-driven prescribing for acute presentations. Co-prescription of QT-prolonging drugs with antipsychotics affected 17.2% of patients, with 64.7% associated with rapid sedation protocols; only one case of potential QT prolongation was documented. Major gaps were identified in medication reconciliation (40.8% had documented medication history) and discharge documentation (13.1% of discharge summaries contained complete medication information). Patients experiencing homelessness demonstrated poorer outcomes across all QUM indicators, with no discharge summaries meeting quality standards. While PANDA demonstrated appropriate protocol-driven prescribing for acute psychiatric presentations, substantial gaps in medication reconciliation and discharge communication highlight challenges in care transitions for priority populations. Standard polypharmacy and prescribing safety indicators may require adaptation for acute psychiatric settings to distinguish appropriate acute prescribing from potentially inappropriate practices.

Purpose AI-driven marketing is transforming how food brands connect with younger audiences, especially Generation Z (Gen Z). Artificial intelligence has evolved from a trend into a structural norm that influences personalization and persuasion in food marketing. This paper examines how Gen Z engages with AI versus traditional food ads, mapping psychological pathways and their relevance to the EU AI Act. Design/methodology/approach An online survey of 982 participants (ages 18–27) from Hungary, Germany and Spain compared responses to a traditional Lidl ad and an AI-generated Heinz ad. Engagement was measured using a shortened Multimedia Ad Exposure Scale (MMAES) alongside established psychological scales for social media addiction, compulsive buying, flourishing and eating style. Analyses included t-tests, correlations and clustering. Two new measures, the Impulse Susceptibility Score (ISS) and the Flourishing Engagement Delta (FED), were introduced as scalable risk assessment tools. Findings The AI-generated ad elicited significantly higher engagement than the traditional ad. Impulsivity-related traits correlated with elevated engagement, indicating susceptibility to persuasive content. Unexpectedly, participants with high well-being (flourishers) also showed stronger engagement, revealing a “flourishing paradox”. Clustering identified two pathways aligning with EU AI Risk categories. The ISS and FED detected that about 28% of participants fall into a high-risk group. Originality/value The study shows how AI-generated ads activate dual psychological pathways: impulsive and reflective. By introducing ISS and FED, it offers scalable tools for assessing digital risk profiles and supports responsible innovation in AI food marketing by exposing its algorithmic influence on consumer behaviour and engagement.

Recovery-oriented models are rarely taught to care providers, and knowledge is insufficient on the practical challenges of implementing recovery-oriented care in secure settings with consistency and fidelity. This study identifies the knowledge, skills, and education needs of forensic care staff related to the practice and implementation of secure recovery. Our mixed-methods approach using a needs assessment survey and focus groups found that most (73.2-77.8%) staff surveyed (n = 108) reported "excellent" or "good" knowledge and understanding of recovery-oriented care. Fewer (43.5%) staff felt confident in their ability to administer risk and recovery-oriented assessment tools in forensic settings. The conceptual domains of knowledge, skills, and education needs were clear in focus group data. Data reflected a varied understanding among staff regarding secure recovery principles and variation as to what recovery "looks like" in practice. Participants perceived a lack of available training and support when commencing employment in forensic mental health, and specific gaps in knowledge and training were noted in relation to the structured risk and recovery tools used in our program. Results from this study will be used to improve forensic patient care through implementation of a tailored educational curriculum in secure recovery for forensic staff.

United Kingdom blood shortages necessitate better prediction of surgical blood requirement. We sought to assess the predictive accuracy of tools designed to identify those patients requiring blood transfusion within the perioperative period. We searched the Cochrane library, EMBASE, MEDLINE, ClinicalTrials.gov and WHO trials portal, 2000-July 2023. We included studies that developed and/or validated prediction tools for blood requirement during the early perioperative period (48 hours). Risk of bias was evaluated using the Prediction model Risk Of Bias Assessment Tool. We pooled area under receiver operating curve and calibration data via random effects meta-analysis. We evaluated certainty of evidence of any estimates using the Grading of Recommendations Assessment, Development and Evaluation framework. We used meta-regression to describe associations between included variables/tool characteristics with tool accuracy. We included 50 papers, describing 67 unique prediction tools. Most tools were at high risk of bias, with limited external validation. Discrimination (area under receiver operating curve) of prognostic models ranged from 0.49 to 0.96. Only two surgery-specific tools, the McClusky Index (liver transplant surgery) and Papworth Bleeding Risk Score (cardiothoracic surgery), had sufficient data to enable pooling of discrimination measures. The McClusky Index's pooled area under receiver operating curve: 0.74 (95% CI 0.61 to 0.84) and Bleeding Risk Score's area under receiver operating curve: 0.68 (95% CI 0.49 to 0.82) were both rated 'very low' certainty by Grading of Recommendations Assessment, Development and Evaluation. Pooling calibration data was not possible for any prediction tools. Meta-regression suggested that fewer included variables, longer time from surgery and independent validation studies were all associated with lower accuracy. There were insufficient studies to assess overall tool performance via meta-analysis in other surgical subgroups beyond cardiothoracic surgery and liver transplant. Our study population is also predominantly made up of elective surgeries which may make our results less generalisable to emergency settings. Implementation and cost-effectiveness studies are needed to evaluate how promising tools could be applied to clinical practice and the economic impact such tools could have upon the service. Despite the availability of multiple potential tools, available data suggest none are currently suitable for predicting blood transfusion in surgical practice. Our summary of the data comes with caveats around the quality of the included papers and the limited number of tools with more than one reported external validation. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number NIHR159933.

Objective To identify the risk factors for intestinal failure occurring beyond 42 days postoperatively or death in neonates with necrotizing enterocolitis (NEC), and to develop a nomogram for predicting the likelihood of these outcomes. Methods A retrospective cohort study was conducted on neonates who underwent surgical intervention for NEC at Shanxi Children's Hospital between January 1, 2018 and December 31, 2023. According to clinical outcomes, the patients were classified into two groups: those who either developed intestinal failure occurring beyond 42 days postoperatively or died, and a control group without intestinal failure. Univariate analysis and LASSO regression were employed to identify the optimal predictive variables. These variables were then incorporated into multivariate Logistic regression analysis to determine the risk factors for intestinal failure occurring beyond 42 days postoperatively or death. A predictive nomogram was developed based on the results. Internal validation was performed using the bootstrap resampling method. For external validation, clinical data were collected from neonates with NEC treated during two separate periods: January 2016 to December 2017 and January 2024 to January 2025, which bracketed the primary training period. The performance of the nomogram was assessed using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results A total of 110 neonates with NEC were enrolled in this retrospective study. Among them, 21 developed the composite outcome of intestinal failure occurring beyond 42 days postoperatively or death. This group consisted of 5 cases of postoperative intestinal failure and 16 postoperative deaths. Among the deaths, 14 directly attributable to the progression of NEC and intestinal failure (such as enterogenic sepsis, refractory septic shock, progressive hepatic failure, etc.), one neonate died of severe respiratory infection, and one died due to the parental withdrawal of treatment. Multivariate logistic regression identified five independent risk factors significantly associated with the composite outcome: gestational age, history of asphyxia, multiple birth (twins), preoperative sepsis, and postoperative short bowel syndrome ( P = 0.033, P = 0.016, P = 0.037, P = 0.015, P = 0.005). These variables were incorporated into a predictive nomogram, which demonstrated good discrimination with an area under the ROC curve (AUC) of 0.878 (95% CI: 0.804–0.952), a sensitivity of 90.5%, and a specificity of 80.9%. The external validation showed an AUC of 0.789 (95% CI: 0.632–0.947), with a sensitivity of 90% and a specificity of 66.7%, indicating good discrimination. Furthermore, both internal and external validation calibration curves showed moderate agreement between the predicted and actual outcomes, and DCA supported the model's clinical applicability. Conclusion Gestational age, history of asphyxia, multiple birth, preoperative sepsis, and postoperative short bowel syndrome (SBS) were identified as key risk factors for intestinal failure occurring beyond 42 days postoperatively or death. The nomogram developed using these factors provided a quantitative, simple, and intuitive tool for clinical risk assessment of postoperative outcomes in patients with NEC.

Failure Mode and Effects Analysis (FMEA) is a systematic risk assessment tool that effectively evaluates the safety and reliability of products prior to their deployment. However, traditional FMEA fails to consider and leverage inherent system-specific information during risk assessment, while also neglecting the weights of risk factors (RFs) when processing data related to the Risk Priority Number (RPN). This leads to significant subjectivity in the final risk ranking of failure modes. To overcome these drawbacks, this study proposes an improved FMEA risk assessment method based on load sharing, aiming to develop an improved FMEA method that addresses the critical limitations of traditional approaches by integrating load sharing principles and systematic weight determination, thereby enhancing risk assessment objectivity and accuracy in complex multi-component systems. First, probabilistic linguistic terms are adopted to quantify experts’ risk assessment information, and the geometric mean method is then used to aggregate assessments from multiple experts. Second, the Fuzzy Best–Worst Method (FBWM) is employed to determine the relative weights of the three RPN factors (Occurrence, Severity, and Detection). Additionally, partial system structural data are obtained through load sharing, and these data—combined with the calculated factor weights—are integrated into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to generate the final risk ranking of failure modes. Finally, a case study of a magnetic crane is conducted to verify the feasibility and effectiveness of the proposed method, supplemented by comparative experiments to demonstrate its superiority.

A significant challenge in improving outcomes for hepatocellular carcinoma (HCC) patients is the scarcity of reliable prognostic markers and predictive tools. Chondroitin Sulfate Proteoglycan 4 (CSPG4) has shown potential as an oncogenic driver in various cancers, but its role in HCC is largely unexplored. CSPG4 expression was analyzed using The Cancer Genome Atlas data and two independent cohorts of HCC patients who underwent curative-intent hepatectomy (n = 153 and n = 112). Immunohistochemistry was used to assess CSPG4 expression. The optimal cutoff value for CSPG4 H-score was determined by receiver operating characteristic (ROC) curve analysis combined with the Youden index. Survival curves were plotted via the Kaplan-Meier method, and differences in survival rates were compared using the log-rank test. Multivariate analyses were utilized to determine the prognostic significance of CSPG4, both independently and in conjunction with established clinical parameters. In vitro studies using CSPG4 knockdown or recombinant CSPG4 protein treatment in HCC cell lines were conducted, with cell proliferation, migration and invasion assessed by CCK-8, wound healing and transwell assays. The expression of CSPG4 was significantly upregulated in HCC tissues compared to adjacent normal liver tissues. Elevated levels of CSPG4 were associated with more severe clinical and pathological characteristics, as well as reduced overall survival (OS) and shorter progression-free survival (PFS) across both study groups. In vitro experiments demonstrated that CSPG4 knockdown suppressed proliferation, migration and invasion of HCC cells, while recombinant CSPG4 protein treatment promoted cell proliferation in a dose-dependent manner. High CSPG4 expression was an independent risk factor for OS in HCC patients after resection (hazard ratio 2.577, 95% confidence interval [CI]: 1.564-4.246, P < 0.001). The combined predictive model incorporating CSPG4 expression with clinical parameters, especially tumor size and microvascular invasion achieved a C-index of 0.811 (95% CI: 0.742-0.881) for OS prediction, which was significantly superior to traditional staging systems. CSPG4 overexpression serves as an oncogenic driver and independent predictor of poor survival in HCC. Combining CSPG4 expression with established clinical variables presents a more precise risk assessment tool for individuals with HCC after hepatectomy, offering new insights for personalized treatment strategies and outcome prediction in HCC.

Untreated wastewater enters the ocean at an outfall in Mexico and spreads to the San Diego‐Tijuana (USA‐Mexico) border region, posing significant risks to human health. Here, we developed a risk assessment tool for coastal communities, leveraging hindcast oceanographic simulations (2017–2019), to link changes in temperature and salinity at the coastline to high wastewater concentrations. We first calculated the modeled timescales (i.e., duration and return time) of wastewater exposure for popular beaches in the region. Most high wastewater exposure events occurred about once a month and lasted less than a week at the southern locations (e.g., Imperial Beach), and occurred less frequently and for shorter periods of time further north (e.g., Coronado). Using the same hindcast simulations, we then identified relationships between anomalous environmental conditions and wastewater concentration along the coastline. High wastewater concentrations were typically associated with lower salinity and temperature, reflecting the low salinity of wastewater and the colder temperatures of water originating south of the USA‐Mexico border. Statistical models with only parameters of salinity and temperature anomalies captured a large proportion of the variation in wastewater‐associated risk of illness (R2 = 0.63–0.78). We tested the risk assessment approach with several months of recent observations (January–December 2024) to show how this tool may be practically applied. This study provides an efficient method for developing risk models that utilize commonly measured environmental data, with applications to other pollution‐impacted coastal locations.

Risk assessment tools for women with breast atypia: A systematic review.

ABSTRACT Assessment of the risk of engaging in a violent radicalization/extremism trajectory has evolved quickly in the last 10 years. Guided by what has been achieved in psychology and criminology, scholars from the field of preventing violent extremism (PVE) have tried to import key lessons from violence risk assessment and management, while bearing in mind the idiosyncrasies of their particular field. However, risk tools that have been developed in the PVE space are relatively recent, and questions remain as to their level of psychometric validation. Namely, do these tools consistently and accurately assess risk of violent extremist acting out? To answer this question, we systematically reviewed evidence on the reliability and validity of violent extremism risk tools. The main objective of this review was to gather, critically appraise, and synthesize evidence regarding the appropriateness and utility of such tools, as validated with specific populations and contexts. Searches covered studies published up to December 31, 2021. They were performed in English and German across 17 databases, 45 repositories, Google, other literature reviews on violent extremism risk assessment, and references of included studies. Studies in all languages were eligible for inclusion in the review. We included studies with primary data resulting from the quantitative examination of the reliability and validity of tools used to assess the risk of violent extremism. Only tools usable by practitioners and intended to assess an individual's risk were eligible. We did not impose any restrictions on study design, type, method, or population. We followed standard methodological procedures outlined by the Campbell Collaboration for data extraction and analysis. Risk of bias was assessed using a modified version of the COSMIN checklist, and data were synthesized through meta‐analysis when possible. Otherwise, narrative synthesis was used to aggregate the results. Among the 10,859 records found, 19 manuscripts comprising 20 eligible studies were included in the review. These studies focused on the Terrorist Radicalization Assessment Protocol (TRAP‐18), the Extremism Risk Guidance Factors (ERG22+), the Multi‐Level Guidelines (MLG‐V2), the Identifying Vulnerable People guidance (IVP guidance), and the Violent Extremism Risk Assessment (VERA)—all structured professional judgment tools—as well as Der Screener—Islamismus , an actuarial scale. Studies mostly involved adult male participants susceptible to violent extremism ( N = 1106; M = 58.21; SD = 55.14). The types of extremist ideologies endorsed by participants varied, and the same was true for ethnicity and country/continent of provenance. Encouraging results were found concerning the inter‐rater agreement of scales in research contexts (kappas between 0.76 and 0.93), but one of the two studies that examined it in a field setting obtained disappointing results (kappas ranging between of 0.47 and 0.80). Content validity studies indicated that PVE risk tools adequately cover the risk factors and offending processes of individuals who go on to commit extremist violence. Construct validity analyses were few and far between, with results indicating that empirical divisions of scales did not match their conceptual divisions. The internal consistency of subscales was lackluster (Cronbach's alphas between 0.19 and 0.85), whereas full scales demonstrated acceptable internal consistency when assessed (0.80 for the ERG22+ and 0.64 for the IVP guidance). Only one study examined convergent validity, and it revealed a lack of convergence, primarily due to particularities of the scale under study (the MLG‐V2). Discriminant validity analyses were exploratory in nature, but suggested that PVE risk tools might not be ideology‐specific and may apply to both group and lone actors. Finally, although the TRAP‐18 showed a relatively strong postdictive effect size (pooled r = 0.62 [0.35–0.77], p = 0.000), the results were highly heterogeneous ( I 2 = 86%), and all studies used retrospective designs, meaning the outcome was already known at the time of assessment. As such, no included study evaluated true predictive validity (i.e., the ability to forecast future violent extremist outcomes based on prospective risk assessment). This represents a significant evidence gap. Threats to validity were substantial: (a) Many studies were case studies or had very small samples, (b) nearly all samples were constituted through the triangulation of publicly available data, and (c) convenience outcome measures were often used. Although having imperfect data is better than having no data, the current state of empirical validation precludes the recommendation of one tool over another for specific populations and contexts, and calls for higher‐quality validation studies for PVE risk assessment tools. Nevertheless, these tools constitute useful checklists of relevant risk and protective factors that could be taken into account by evaluators who wish to assess the risk of violent extremism and identify intervention targets.

Diagnostic Accuracy of Fall Risk Screening Tools in Older Individuals: A Systematic Review With Bivariate Random-Effects Meta-Analysis.

Validation and Comparison of 4 Fall Risk Assessment Tools for Older Adults in Chinese Nursing Homes: A Prospective Cohort Study.

Development and calibration of the cross-laminated timber Roof Assembly Moisture and mould (CRAMM) risk assessment tool

To describe a quality improvement project based on the 'Standards for Quality Improvement Reporting Excellence' (SQUIRE) guidelines, to implement care bundles for pressure ulcer (PU) prevention and management. The study was conduct in the medical, surgical and intensive care departments of six hospitals in northern Italy, between 2002 and 2020. The data collection was carried out by the unit's nurses and nurse managers. Implementation strategies included the dissemination of the PUs standard of care, the engagement of the unit nurses' mangers, the definition and the adoption of a clinical tool for PU risk assessment, the decision algorithm for the Braden score range and the class of air surface, the definition of PUs being monitored and the auditing system. The development of a quality improvement programme allowed the authors to invest in a structured plan of organisational interventions, which impacted different areas such as leadership, staffing, information technology, performance and improvement. There was no significant change in the prevalence of PUs, which remained at around 11%, but the improvement program allowed for standardisation of PU risk assessment and the supply of air mattresses in the company. Therefore, an evidence-based PU prevention and management bundle, drafter by a multidisciplinary team, was implemented at the six hospitals. Despite PU quality improvement programmes promoting healthcare professionals' adherence to evidence-based practice, demonstrating a measurable reduction in PU rates can be challenging in real-world settings. However, standardising clinical practice can generate reliable data to support targeted investments in nursing care and help establish an audit framework for evaluating clinical and organisational outcomes. The authors have no conflict of interest to declare.