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Article

Julia H. Littell

Systematic reviews summarize a body of empirical evidence to address important questions for practice and social policy. Widely used to compile evidence about intervention effects in the helping professions, systematic reviews can also be used to assess rates, trends, associations, and variations on many topics. Credible reviews are based on the science of research synthesis, which provides the theoretical and empirical foundations that undergird efforts to minimize bias and error at each step in the review process to ensure that systematic reviews are comprehensive and their conclusions are accurate. Methods for the synthesis of quantitative studies are well developed. Meta-analysis, a set of statistical procedures, is often used in quantitative reviews, but meta-analysis is only one part of the systematic review process; other steps are needed to limit bias and error. Methods for systematic reviews of qualitative research are under development, as are strategies to combine quantitative and qualitative data in reviews.

Article

Meta-analysis and structural equation modeling (SEM) are two popular statistical models in the social, behavioral, and management sciences. Meta-analysis summarizes research findings to provide an estimate of the average effect and its heterogeneity. When there is moderate to high heterogeneity, moderators such as study characteristics may be used to explain the heterogeneity in the data. On the other hand, SEM includes several special cases, including the general linear model, path model, and confirmatory factor analytic model. SEM allows researchers to test hypothetical models with empirical data. Meta-analytic structural equation modeling (MASEM) is a statistical approach combining the advantages of both meta-analysis and SEM for fitting structural equation models on a pool of correlation matrices. There are usually two stages in the analyses. In the first stage of analysis, a pool of correlation matrices is combined to form an average correlation matrix. In the second stage of analysis, proposed structural equation models are tested against the average correlation matrix. MASEM enables researchers to synthesize researching findings using SEM as the research tool in primary studies. There are several popular approaches to conduct MASEM, including the univariate-r, generalized least squares, two-stage SEM (TSSEM), and one-stage MASEM (OSMASEM). MASEM helps to answer the following key research questions: (a) Are the correlation matrices homogeneous? (b) Do the proposed models fit the data? (c) Are there moderators that can be used to explain the heterogeneity of the correlation matrices? The MASEM framework has also been expanded to analyze large datasets or big data with or without the raw data.

Article

Quincy J. J. Wong, Alison L. Calear, and Helen Christensen

Internet-based cognitive behavioral therapy (ICBT) is the provision of cognitive behavioral therapy (CBT) using the Internet as a platform for delivery. The advantage of ICBT is its ability to overcome barriers to treatment associated with traditional face-to-face CBT, such as poor access, remote locations, stigmas around help-seeking, the wish to handle the problem alone, the preference for anonymity, and costs (time and financial). A large number of randomized controlled trials (RCTs) have tested the acceptability, efficacy, and cost-effectiveness of ICBT for anxiety disorders, mood disorders, and associated suicidality. A meta-review was conducted by searching PsycINFO and PubMed for previous systematic reviews and meta-analyses of ICBT programs for anxiety, depression, and suicidality in children, adolescents, and adults. The results of the meta-review indicated that ICBT is effective in the treatment and prevention of mental health problems in adults and the treatment of these problems in youth. Issues of adherence and privacy have been raised. However, the major challenge for ICBT is implementation and uptake in the “real world.” The challenge is to find the best methods to embed, deliver, and implement ICBT routinely in complex health and education environments.

Article

Anthony Petrosino, Claire Morgan, and Trevor Fronius

Systematic reviews and meta-analyses have become a focal point of evidence-based policy in criminology. Systematic reviews use explicit and transparent processes to identify, retrieve, code, analyze, and report on existing research studies bearing on a question of policy or practice. Meta-analysis can combine the results from the most rigorous evaluations identified in a systematic review to provide policymakers with the best evidence on what works for a variety of interventions relevant to reducing crime and making the justice system fairer and more effective. The steps of a systematic review using meta-analysis include specifying the topic area, developing management procedures, specifying the search strategy, developing eligibility criteria, extracting data from the studies, computing effect sizes, developing an analysis strategy, and interpreting and reporting the results. In a systematic review using meta-analysis, after identifying and coding eligible studies, the researchers create a measure of effect size for each experimental versus control contrast of interest in the study. Most commonly, reviewers do this by standardizing the difference between scores of the experimental and control groups, placing outcomes that are conceptually similar but measured differently (e.g., such as re-arrest or reconviction) on the same common scale or metric. Though these are different indices, they do measure a program’s effect on some construct (e.g., criminality). These effect sizes are usually averaged across all similar studies to provide a summary of program impact. The effect sizes also represent the dependent variable in the meta-analysis, and more advanced syntheses explore the role of potential moderating variables, such as sample size or other characteristics related to effect size. When done well and with full integrity, a systematic review using meta-analysis can provide the most comprehensive assessment of the available evaluative literature addressing the research question, as well as the most reliable statement about what works. Drawing from a larger body of research increases statistical power by reducing standard error; individual studies often use small sample sizes, which can result in large margins of error. In addition, conducting meta-analysis can be faster and less resource-intensive than replicating experimental studies. Using meta-analysis instead of relying on an individual program evaluation can help ensure that policy is guided by the totality of evidence, drawing upon a solid basis for generalizing outcomes.

Article

Alexandra Dehnhardt, Kati Häfner, Anna-Marie Blankenbach, and Jürgen Meyerhoff

All types of wetlands around the world are heavily threatened. According to the Ramsar Convention on Wetlands, they comprise “areas of marsh, fen, peatland or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish, or salt.” While they are estimated still to cover 1,280 million hectares worldwide, large shares of wetlands were destroyed during the 20th century, mainly as a result of land use changes. According to the Millennium Ecosystem Assessment (MEA), this applies above all to North America, Europe, Australia, and New Zealand, but wetlands were also heavily degraded in other parts of the world. Moreover, degradation is expected to accelerate in the future due to global environmental change. These developments are alarming because wetlands deliver a broad range of ecosystem services to societies, contributing significantly to human well-being. Among those services are water supply and purification, flood regulation, climate regulation, and opportunities for recreation, to name only a few. The benefits humans derive from those services, however, often are not reflected in markets as they are public goods in nature. Thus, arguing in favor of the preservation of wetlands requires, inter alia, to make the non-marketed economic benefits more visible and comparable to those from alternative—generally private—uses of converted wetlands, which are often much smaller. The significance of the non-market value of wetland services has been demonstrated in the literature: the benefits derived from wetlands have been one of the most frequently investigated topics in environmental economics and are integrated in meta-analyses devoted to synthesizing the present knowledge about the value of wetlands. The meta-analyses that cover both different types of wetlands in different landscapes as well as different geographical regions are supplemented by recent primary studies on topics of increasing importance such as floodplains and peatlands, as they bear, for example, a large flood regulation and climate change mitigation potential, respectively. The results underpin that the conversion of wetlands is accompanied by significant losses in benefits. Moreover, wetland preservation is economically beneficial given the large number of ecosystem services provided by wetland ecosystems. Thus, decision-making that might affect the status and amount of wetlands directly or indirectly should consider the full range of benefits of wetland ecosystems.

Article

Kevin J. Boyle and Christopher F. Parmeter

Benefit transfer is the projection of benefits from one place and time to another time at the same place or to a new place. Thus, benefit transfer includes the adaptation of an original study to a new policy application at the same location or the adaptation to a different location. The appeal of a benefit transfer is that it can be cost effective, both monetarily and in time. Using previous studies, analysts can select existing results to construct a transferred value for the desired amenity influenced by the policy change. Benefit transfer practices are not unique to valuing ecosystem service and are generally applicable to a variety of changes in ecosystem services. An ideal benefit transfer will scale value estimates to both the ecosystem services and the preferences of those who hold values. The article outlines the steps in a benefit transfer, types of transfers, accuracy of transferred values, and challenges when conducting ecosystem transfers and ends with recommendations for the implementation of benefit transfers to support decision-making.

Article

Simon Zebregs and Gert-Jan de Bruijn

Meta-analyses are becoming increasingly popular in the field of health and risk communication—meta-analyses allow for more precise estimations of the magnitude of effects and the robustness of those effects across empirical studies in a particular domain. Despite its popularity, most scholars are not trained in the basic methods involved with meta-analyses. There are advantages to meta-analysis in comparison to other forms of research synthesis. An overview of the methods involved in conducting and reporting meta-analytical research is helpful. However, the methods involved with meta-analyses are not as clear-cut as they may first appear. Numerous issues must be considered and various arbitrary decisions are required during the process. These issues and decisions relate to various topics such as inclusion criteria, the selection of sources, quality assessments for eligible studies, and publication bias. Basic knowledge of these issues and decisions is important for interpreting the outcomes of a meta-analysis correctly.

Article

Scott O. Lilienfeld and Candice Basterfield

Evidence-based therapies stemmed from the movement toward evidence-based medicine, and later, evidence-based practice (EBP) in psychology and allied fields. EBP reflects a progressive historical shift from naïve empiricism, which is based on raw and untutored observations of patient change, to systematic empiricism, which refines and hones such observations with the aid of systematic research techniques. EBP traces its roots in part to the development of methods of randomization in the early 20th century. In American psychology, EBP has traditionally been conceptualized as a three-legged stool comprising high-quality treatment outcome evidence, clinical expertise, and patient preferences and values. The research leg of the stool is typically operationalized in terms of a hierarchy of evidentiary certainty, with randomized controlled trials and meta-analyses of such trials toward the apex. The most influential operationalization of the EBP research leg is the effort to identify empirically supported treatments, which are psychotherapies that have been demonstrated to work for specific psychological conditions. Still, EBP remains scientifically controversial in many quarters, and some critics have maintained that the research base underpinning it is less compelling than claimed by its proponents.

Article

Persuasive messages use statistical evidence in order to convince an audience to accept a conclusion. Statistical evidence represents a compilation of experiences structured and collected in a manner that permits expression in mathematical form. Research demonstrates that the use of statistical evidence increases the persuasiveness of a message, and a message that uses both statistical and narrative evidence generates the greatest persuasiveness. Statistical evidence can take the form of summarizing the collective opinion of experts on a topic or an expression of the collective set of experiences. The challenge becomes gaining acceptance of statistical expressions of experience versus what is perceived as the narrative or lived experience of the single person. Statistical evidence is often presented using a mathematical expression to indicate the size or force of the evidence. The accumulation of statistical evidence often involves the use of meta-analysis to reduce Type I (false positive) and Type II (false negative) error. The use of evidence is strategic and can target specific elements of belief by understanding the structure of beliefs and the connectivity among elements. The use of the Subjective Probability Model provides a means to capitalize on the use of evidence by changing probabilities in beliefs to increase the effectiveness of a message campaign. Statistical evidence, however, may be ineffective under circumstances referred to as the “base-rate fallacy.” The base-rate fallacy occurs when the presentation of statistical information is accepted, but examples are used that contradict the base-rate. The impact of the use of the example is to create a shift in the belief in the typicality of the example, despite knowledge of the base-rate. Fear appeals provide a particularly useful and important application of statistical evidence in the pursuit of public health campaigns. The tenets of the Extended Parallel Processing Model indicate that message effectiveness relies on a combination of: (a) perceived severity of the threat, (b) perceived vulnerability to the threat, (c) perceived efficacy of the solution, and (d) perceived personal efficacy of the solution. Each element is largely impacted by the application and use of statistical information to make claims. The use of statistics generally outlines the argument and supports the conclusion offered in support of a conclusion offered to the message recipient. Statistical evidence when used in a message often offers data or information that becomes the justification for a conclusion. A large part of a message becomes gaining acceptance of information by an audience, then explaining (reasoning) to the audience how those facts support a conclusion, often involving some type of recommendation for behavior. Understanding statistical evidence requires understanding how the material functions within the context of the belief system of the individual.

Article

Investigative practices, including research methodologies, approaches, processes, as well as knowledge dissemination efforts continue to evolve within inclusive or special education. So too do such practices evolve within related fields such as nursing, psychology, community-based care, health promotion, etc. There are several research approaches that promote the tools required to effect inclusive education, such as: evidence-based practice (EBP), EBP in practice, creative secondary uses of (anonymous) data, collective impact, qualitative evidence synthesis (QES), and lines of action (LOA). Other approaches that promote a more inclusive education research agenda more generally, include action research and participatory action research, inclusive research, appreciative inquiry, and arts-based educational research.