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Praise for Meta-Analysis for Public Management and Policy \"In his usual rigorous but readable style, Evan Ringquist and co-author Mary Anderson have produced a tour-de-force on the topic of meta-analysis in public policy and management research. Meta-analysis is badly needed in the all-too-common situation when researchers have low confidence in summarizing the overall results of dozens of studies on the effectiveness of some policy. This book has a nice combination of conceptual overview, methodological details, and applications that will make it possible for researchers to conduct their own meta-analysis. It is tempting to require all graduate students to write a meta-analysis as a chapter in their dissertation, or include meta-analysis as a standard offering in the research methods curriculum of social science graduate programs. The more people that adopt Ringquist and Anderson's approach, the less resources will be wasted on conducting studies that do not contribute to cumulative scientific knowledge. \" -Mark Lubell Department of Environmental Science and Policy Director, Center for Environmental Policy and Behavior University of California-Davis \"Ringquist and his colleagues deliver value and add to canon of public management methods by delivering an analytical framework that makes the case for systematic research using the tools of meta-analysis. This book will be a must read for all committed to strengthening evidence-based research that improves public policy and management decision making.\" -David M. Van Slyke The Maxwell School of Citizenship and Public Affairs Syracuse University \"In Meta-Analysis for Public Management and Policy Evan Ringquist and his colleagues provide a lucid and practical roadmap for policy and public management scholars who use meta-analysis in their research. But this is more than a \"how to\" volume; it provides background on why meta-analysis is a potent means for accumulating and synthesizing empirical research findings, and shows how its use has evolved in recent decades. Specific applications of meta-analysis to long-standing policy and management debates are given, essentially providing an array of developed \"templates\" through which scholars and practitioners can assess how to approach different kinds of analytical problems using meta-analysis. Particularly valuable to me is the careful development and presentation of the necessary stages of meta-analysis, from conceptualization through data coding and bias assessment to advanced modeling. All of the statistical analyses can be conducted in Stata, utilizing readily available \".ado\" modules. I will use this book, both in research and in the classroom. Overall it is one of the most useful methodological contributions I've seen in some time.\" -Hank Jenkins-Smith Department of Political Science Director, Center for Applied Social Research University of Oklahoma \"Meta-Analysis for Public Management and Policy conveys the considerable untapped potential of meta-analysis to strengthen and advance bodies of knowledge and evidence in public management and policy. This book takes students and researchers deep into the methods of meta-analysis and details of their empirical application, without losing sight of the important policy questions and the implications of choices that researchers make in their empirical work for the production of evidence for public managers and policymakers. This book will serve as an excellent practical guide for those conducting their first meta-analysis, while at the same time supporting critically-focused consumption of existing meta-analyses and discussion of where the field can gainfully take this approach to enhance our research and knowledge bas.

A Practical Guide to Analytics for Governments provides demonstrations of real-world analytics applications for legislators, policy-makers, and support staff at the federal, state, and local levels. Big data and analytics are transforming industries across the board, and government can reap many of those same benefits by applying analytics to processes and programs already in place. From healthcare delivery and child well-being, to crime and program fraud, analytics can-in fact, already does-transform the way government works. This book shows you how analytics can be implemented in your own milieu: What is the downstream impact of new legislation? How can we make programs more efficient? Is it possible to predict policy outcomes without analytics? How do I get started building analytics into my government organization? The answers are all here, with accessible explanations and useful advice from an expert in the field.

Background:Rigorous measurement of organizational performance requires large, unbiased samples to allow inferences to the population. Studies of organizations, including hospitals, often rely on voluntary surveys subject to nonresponse bias. For example, hospital administrators with concerns about performance are more likely to opt-out of surveys about organizational quality and safety, which is problematic for generating inferences.Objective:The objective of this study was to describe a novel approach to obtaining a representative sample of organizations using individuals nested within organizations, and demonstrate how resurveying nonrespondents can allay concerns about bias from low response rates at the individual-level.Methods:We review and analyze common ways of surveying hospitals. We describe the approach and results of a double-sampling technique of surveying nurses as informants about hospital quality and performance. Finally, we provide recommendations for sampling and survey methods to increase response rates and evaluate whether and to what extent bias exists.Results:The survey of nurses yielded data on over 95% of hospitals in the sampling frame. Although the nurse response rate was 26%, comparisons of nurses' responses in the main survey and those of resurveyed nonrespondents, which yielded nearly a 90% response rate, revealed no statistically significant differences at the nurse-level, suggesting no evidence of nonresponse bias.Conclusions:Surveying organizations via random sampling of front-line providers can avoid the self-selection issues caused by directly sampling organizations. Response rates are commonly misinterpreted as a measure of representativeness; however, findings from the double-sampling approach show how low response rates merely increase the potential for nonresponse bias but do not confirm it.

Purpose To evaluate the effect of postoperative interferon-alpha 2b (IFN-α2b) ophthalmic drops versus intraoperative mitomycin-c (MMC) on preventing pterygium recurrence. Methods This prospective randomized clinical trial was conducted on patients who were candidates for pterygium surgery. A total of 75 patients were included in the study from December 2021 to December 2022, of which 64 patients (one eye each) were examined and analyzed based on the inclusion criteria. Then the patients were randomly assigned to control groups, intra-operative MMC (32 patients) and the intervention group, IFN-α2b drops after the operation (32 patients). All patients underwent pterygium surgery using the rotational conjunctival flap method. Results In terms of pterygium grading, 8 (12.5%), 25 (39.06%), and 31 (48.44%) eyes were in grades 1, 2, and 3, respectively. The average size of the pterygium was 3.6 ± 0.7 mm. The grade and size of pterygium had the same distribution in the two groups. There was no statistically significant difference between the two groups in the level of post-operative clinical inflammation. The present study showed no significant difference in complications between the two groups ( p  = 0.999). The recurrence rate in the control group was 9.4% (3 eyes), and 0% (no recurrence) in the intervention group ( p  = 0.119). Conclusions interferon-alpha 2b group did not show a statistically significant difference in preventing pterygium recurrence compared to the mitomycin C group. The post-surgery administration of IFN-α 2b drops can effectively prevent pterygium recurrence with a comparable and even more compelling effect than MMC during surgery. Key message What is known: • Mitomycin-C is applied intra-operatively to reduce the recurrence risk of pterygium. What is new: • Interferon alpha-2b drops after pterygium surgery can prevent pterygium recurrence with a comparable effect and maybe even more effective than MMC during surgery. • There was no statistically significant difference between the intraoperative MMC and postoperative IF alpha-2b groups in the level of post-operative clinical inflammation and complications.

To evaluate the effects of canagliflozin, a sodium-glucose cotransporter 2 inhibitor, in type 2 diabetes mellitus inadequately controlled with metformin monotherapy. This was a double-blind, placebo-controlled, parallel-group, multicenter, dose-ranging study in 451 subjects randomized to canagliflozin 50, 100, 200, or 300 mg once daily (QD) or 300 mg twice daily (BID), sitagliptin 100 mg QD, or placebo. Primary end point was change in A1C from baseline through week 12. Secondary end points included change in fasting plasma glucose (FPG), body weight, and overnight urinary glucose-to-creatinine ratio. Safety and tolerability were also assessed. Canagliflozin was associated with significant reductions in A1C from baseline (7.6-8.0%) to week 12: -0.79, -0.76, -0.70, -0.92, and -0.95% for canagliflozin 50, 100, 200, 300 mg QD and 300 mg BID, respectively, versus -0.22% for placebo (all P < 0.001) and -0.74% for sitagliptin. FPG was reduced by -16 to -27 mg/dL, and body weight was reduced by -2.3 to -3.4%, with significant increases in urinary glucose-to-creatinine ratio. Adverse events were transient, mild to moderate, and balanced across arms except for a non-dose-dependent increase in symptomatic genital infections with canagliflozin (3-8%) versus placebo and sitagliptin (2%). Urinary tract infections were reported without dose dependency in 3-9% of canagliflozin, 6% of placebo, and 2% of sitagliptin arms. Overall incidence of hypoglycemia was low. Canagliflozin added onto metformin significantly improved glycemic control in type 2 diabetes and was associated with low incidence of hypoglycemia and significant weight loss. The safety/tolerability profile of canagliflozin was favorable except for increased frequency of genital infections in females.

Common statistical modeling methods do not necessarily produce the most relevant or interpretable effect estimates to communicate risk. Overreliance on the odds ratio and relative effect measures limit the potential impact of epidemiologic and public health research. We created a straightforward R package, called riskCommunicator, to facilitate the presentation of a variety of effect measures, including risk differences and ratios, number needed to treat, incidence rate differences and ratios, and mean differences. The riskCommunicator package uses g-computation with parametric regression models and bootstrapping for confidence intervals to estimate effect measures in time-fixed data. We demonstrate the utility of the package using data from the Framingham Heart Study to estimate the effect of prevalent diabetes on the 24-year risk of cardiovascular disease or death. The package promotes the communication of public-health relevant effects and is accessible to a broad range of epidemiologists and health researchers with little to no expertise in causal inference methods or advanced coding.

Background Implementation outcome measures are essential for monitoring and evaluating the success of implementation efforts. Yet, currently available measures lack conceptual clarity and have largely unknown reliability and validity. This study developed and psychometrically assessed three new measures: the Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of Intervention Measure (FIM). Methods Thirty-six implementation scientists and 27 mental health professionals assigned 31 items to the constructs and rated their confidence in their assignments. The Wilcoxon one-sample signed rank test was used to assess substantive and discriminant content validity. Exploratory and confirmatory factor analysis (EFA and CFA) and Cronbach alphas were used to assess the validity of the conceptual model. Three hundred twenty-six mental health counselors read one of six randomly assigned vignettes depicting a therapist contemplating adopting an evidence-based practice (EBP). Participants used 15 items to rate the therapist’s perceptions of the acceptability, appropriateness, and feasibility of adopting the EBP. CFA and Cronbach alphas were used to refine the scales, assess structural validity, and assess reliability. Analysis of variance (ANOVA) was used to assess known-groups validity. Finally, half of the counselors were randomly assigned to receive the same vignette and the other half the opposite vignette; and all were asked to re-rate acceptability, appropriateness, and feasibility. Pearson correlation coefficients were used to assess test-retest reliability and linear regression to assess sensitivity to change. Results All but five items exhibited substantive and discriminant content validity. A trimmed CFA with five items per construct exhibited acceptable model fit (CFI = 0.98, RMSEA = 0.08) and high factor loadings (0.79 to 0.94). The alphas for 5-item scales were between 0.87 and 0.89. Scale refinement based on measure-specific CFAs and Cronbach alphas using vignette data produced 4-item scales (α’s from 0.85 to 0.91). A three-factor CFA exhibited acceptable fit (CFI = 0.96, RMSEA = 0.08) and high factor loadings (0.75 to 0.89), indicating structural validity. ANOVA showed significant main effects, indicating known-groups validity. Test-retest reliability coefficients ranged from 0.73 to 0.88. Regression analysis indicated each measure was sensitive to change in both directions. Conclusions The AIM, IAM, and FIM demonstrate promising psychometric properties. Predictive validity assessment is planned.

Background and objective Most troubling of painless gastrointestinal endoscopy is hypoxia and hypotension. Esketamine has sympathomimetic and respiratory protection, which combined with midazolam and propofol may reduce these troubles. So, this study aims to explore the efficacy and safety of this regimen. Methods In total, 318 patients who received painless gastrointestinal endoscopy from November 2022 to April 2023 were included and randomly divided into two groups at 1:1: 0.1 µg/kg sufentanil (Suf) or 0.15 mg/kg esketamine (Esk) group. Except for analgesics, all patients were given midazolam and propofol. The incidence of hypotension and hypoxia (SPO 2  < 93%) during the examination was observed. Results Compared with the Suf, the Esk group reduced the incidence of hypotension (12.8% vs 36.2%, 95% confidence interval (CI) 13.20—33.09, P  < 0.001), respiratory depression (apnea > 30 s) (2.1% vs 15.4%, 6.47—20.52, P  < 0.001), and hypoxia (7.1% vs 16.1%, 1.07—16.92, P  = 0.018), but may increase the incidence of coughing ( P  < 0.001) and increased secretions ( P  = 0.032). There was no significant difference in the examination and recovery time ( P  > 0.05). Conclusion Esketamine, midazolam, and propofol for painless gastrointestinal endoscopy can achieve opioid-free sedation and reduce the occurrence of hypotension and hypoxia. However, the dosages of this regimen need to be further explored to avoid coughing and increased secretions. Trial registration This study has been registered in the Chinese Clinical Trial Center ( https://www.chictr.org.cn/index.html , Date: November 3, 2022, No: ChiCTR2200065379). Key point Esketamine, midazolam and propofol for gastrointestinal endoscopy can achieve opioid-free sedation. Esketamine (vs. Sufentanil) for gastrointestinal endoscopy can reduce the incidence of hypotension and hypoxia. Esketamine (vs. Sufentanil) for gastrointestinal endoscopy may increase the incidence of coughing and increased secretions.

Objectives. We sought to outline the framework and methods used by the World Health Organization (WHO) STEPwise approach to noncommunicable disease (NCD) surveillance (STEPS), describe the development and current status, and discuss strengths, limitations, and future directions of STEPS surveillance. Methods. STEPS is a WHO-developed, standardized but flexible framework for countries to monitor the main NCD risk factors through questionnaire assessment and physical and biochemical measurements. It is coordinated by national authorities of the implementing country. The STEPS surveys are generally household-based and interviewer-administered, with scientifically selected samples of around 5000 participants. Results. To date, 122 countries across all 6 WHO regions have completed data collection for STEPS or STEPS-aligned surveys. Conclusions. STEPS data are being used to inform NCD policies and track risk-factor trends. Future priorities include strengthening these linkages from data to action on NCDs at the country level, and continuing to develop STEPS’ capacities to enable a regular and continuous cycle of risk-factor surveillance worldwide.