Research and Evaluation

Multivariate procedures allow social workers and other human services researchers to analyze complex, multidimensional social problems and interventions in ways that minimize oversimplification. This book provides an introduction to four procedures for the analysis of multiple dependent variables: multivariate analysis of variance (MANOVA), multivariate analysis of covariance (MANCOVA), multivariate multiple regression (MMR), and structural equation modeling (SEM). Each procedure is presented in a way that allows readers to compare and contrast them in terms of appropriate research context; required statistical assumptions, including levels of measurement of variables to be modeled; analytical steps; sample size; and strengths and weaknesses. This book facilitates course extensibility in scope and depth by allowing instructors to supplement course content with rigorous statistical procedures. The book provides detailed annotated examples using Stata, SPSS (PASW), SAS, and Amos. It also gives additional resources, discussion of key terms, and a companion website.

This book focuses on the analysis of data from single case designs. The methods covered in this book range from traditional visual analysis methods to complex ARIMA statistical models. The use of graphical methods is also extensively covered. The book is most appropriate for students in doctoral programs in disciplines such as Social Work and Psychology. It should also be useful for researchers and professionals in the various helping professions that make use of single case design methodology for practice evaluation and research. The methods covered range from the very simple to the very complex.

The complexity of social problems necessitates that social work researchers utilize multivariate statistical methods in their investigations. Having a thorough understanding of basic statistics can facilitate this process as multivariate methods have as their foundation many of these basic statistical procedures. In this pocket guide, the authors introduce readers to three of the more frequently used multivariate statistical methods in social work research—multiplelinear regression analysis,analysis of variance and covariance, and path analysis—with an emphasis on the basic statistics as important features of these methods. The primary intention is to help prepare entry level doctoral students and early career social work researchers in the use of multivariate statistical methods by offering a straightforward and easy to understand explanation of these methods and the basic statistics that inform them. The pocket guide begins with a review of basic statistics, hypothesis testing with inferential statistics, and bivariate analytic methods. Subsequent sections describe bivarate and multiple linear regression analyses, one-way and two-way analysis of variance (ANOVA) and covariance (ANCOVA), and path analysis. In each chapter, the authors introduce the various basic statistical procedures by providing definitions, formulas, descriptions of the underlying logic and assumptions of each procedure, and examples of how they have been applied in the social work research literature. The authors also explain estimation procedures and how to interpret results. Each chapter provides brief step-by-step instructions for conducting these statistical tests in Statistical Package for the Social Sciences (SPSS) and AMOS (SPSS, Inc. 2011), based on data from the National Educational Longitudinal Study of 1988 (NELS: 88). Finally, the book offers a companion website that provides more detailed instructions, as well as data sets and worked examples.

McRoy, Flanzer and Zlotnik (and contributing author Lewis) in Building Research Culture and Infrastructure Tools for Social Workers provide information for social work schools and departments at various levels of research capacity, to not only examine or re-examine their research climate and culture, but to also assess their readiness to further enhance their research environment. A summary of the historical background of the development of social work research in colleges and universities is provided as well as very specific resources and tips for enhancing involvement of BSW, MSW and PhD social work faculty in research. The authors report on the current climate and status of research infrastructures and enterprise in social work education programs, weaving in information provided by faculty, deans and research administrators, obtained through a questionnaire and interview process. Faculty scenarios illustrating barriers to achieving their research funding goals are addressed along with current examples of specific steps to address these barriers at selected universities. Clear differences between PhD and non-PhD granting institutions in the types of opportunities and strategies for engaging in research, and related issues of financing and administrative support are addressed. Practical tips for grant writing, and seeking federal, state and foundation support make this book not only a guide for building research infrastructure for faculty, deans and university administrators, but it is also a good “ how to” resource for seeking research support itself.

Research has already been a significant factor in child welfare policy in recent years, but this book demonstrates that it has taken a leading role in the field to spur and guide change. The chapters in this book assess the effect of research on the full spectrum of child welfare services. The book covers every base. The opening chapters situate child welfare research in the modern context; they are followed by discussions of evidence-based practice in the field, arguably its most pressing concern now. Recent years have seen historic rises in the number of children adopted through public agencies and, accordingly, permanent placement and family ties are critical topics that occupy the book's core, along with chapters broaching the thorny questions that surround decision-making and risk assessment. The urgent need for a more effective use of research and evidence is highlighted again with looks at the future of child protection and how concrete data can influence policy and help children. Finally, in recognition of the growing importance of a global view, closing chapters address international issues in child welfare research, including an examination of policies from abroad and a multinational comparison of the economic challenges facing single mothers and their children.

Research in children's mental health lags behind research for adults, in part because it is intrinsically context-bound. Children are embedded in families, in schools, and in communities who have responsibility for their care. Making research findings useful and ensuring that they are applied to improve the lives of children and families require attention to these contexts. This entails a process of collaboration with many partners: teachers, nurses, healthcare providers, church leaders, neighborhood group directors, and other community leaders. The process of collaboration in children's mental health is complicated, but the products that it yields have the potential to benefit both children and families. This volume, with the toolkit and casebook that it contains, distills the process of collaboration into manageable steps, and provides concrete examples of how researchers have addressed specific challenges. The premise of this book is that collaborative research, in contrast to traditional research paradigms, will yield findings that are more ethical, valid, and useful. Highlighting the transformation of science from ivory tower theories to action-oriented practices, this book offers practical advice for researchers and practitioners interested in using data to inform and transform children's mental health. Concrete examples of projects that have involved community leaders and researchers provide an insider's guide to conducting successful collaborations that can yield better results than traditional top-down research paradigms.

Clinical data-mining (CDM) involves the conceptualization, extraction, analysis, and interpretation of available clinical data for practice knowledge-building, clinical decision-making, and practitioner reflection. Depending upon the type of data mined, CDM can be qualitative or quantitative; it is generally retrospective, but may be meaningfully combined with original data collection. Any research method that relies on the contents of case records or information systems data inevitably has limitations, but with proper safeguards these can be minimized. Among CDM's strengths however, are that it is unobtrusive, inexpensive, presents little risk to research subjects, and is ethically compatible with practitioner value commitments. When conducted by practitioners, CDM yields conceptual as well as data-driven insight into their own practice- and program-generated questions. This book covers all the basics of conducting practitioner-initiated CDM studies or CDM doctoral dissertations, drawing extensively on published CDM studies and completed CDM dissertations from multiple social work settings in the United States, Australia, Israel, Hong Kong, and the United Kingdom. In addition, it describes consulting principles to help with forging collaborative university-agency CDM partnerships.

The growth of the criminal justice system poses a number of significant problems that require ongoing research efforts by scholars across multiple disciplines. Despite the impact that the criminal justice system has on client populations served by social workers and related professions, there are few practical sources available to guide research in these settings. Conducting Research in Juvenile and Criminal Justice Settings: Strategies and Issues fills this gap and represents a cutting-edge yet user friendly book that will be of interest not only to researchers but also to graduate students and agency administrators. This book covers major issues in conducting field research with adults and juveniles and using extant and administrative data sources on criminal justice populations. In particular, the chapters explore the many challenges that often arise in criminal justice settings and offer practical strategies to issues such as how to gain and maintain IRB approval, how to manage a project across multiple agencies, courts, and institutions, and how to maintain relationships with key stakeholders. Furthermore, discussion of issues related to planning a research project in adult and juvenile justice settings, including research designs, recruitment, and retention, are delineated. An extensive bibliographic description of data sources, case studies, and research forms and letters is included.

Measures that are reliable, valid, and can be used across diverse populations are vital to social work research, but the development of new measures is an expensive and time-consuming process. An array of existing measures can provide a cost-effective alternative, but in order to take this expedient step with confidence, researchers must ensure that the existing measure is appropriate for the new study. Confirmatory factor analysis (CFA) is one of the ways to do so. CFA has four primary functions—psychometric evaluation of measures, construct validation, testing method effects, and testing measurement invariance. This book provides an overview of the method, step-by-step guides to creating a CFA model and assessing its fit, and explanations of the requirements for using CFA, as well the book underscores the issues that are necessary to consider when using multiple groups or equivalent and multilevel models. Real-world examples, screenshots from the Amos software program that can be used to conduct CFA, and reading suggestions for each chapter form part of the book.

The purpose of the book is to provide researchers with a framework to conduct research in a culturally sensitive manner with individuals, families, and communities in diverse cultural settings in the United States, as well as in a global context within the context of three aims: (1) To understand and describe the nature and extent to which a particular problem occurs; (2) To understand the etiology or potential factors associated with the occurrence of a particular problem; (3) To evaluate programs or interventions designed to ameliorate or eliminate a problem. For each of these three aims, applications of different research methods with various population groups are discussed with considerable detail. The work presented falls into different sides of the emic–etic continuum, with some studies taking a more emic perspective (i.e., Chapter 2, a mixed methods study with American Indian populations), others presenting more of an etic approach (i.e., Chapter 3, a multicountry study of drug use in Central America), and yet others presenting an emic–etic distinction that is less salient (i.e., Chapters 4–6, a longitudinal studies of ecological factors and drug use in Santiago, Chile; a longitudinal study of ecological factors and PTSD in the City of Detroit; and a randomized clinical trial and community-based participatory research project both also conducted in Detroit). Two central themes that guided this work are that culture is not static, rather it is fluid and changing, and that cross-cultural researchers should avoid making sweeping generalizations that risk taking on essentialist characteristics. The book concludes with a call for anyone conducting cross-cultural research to include an intersectionality lens, one that encompasses a broader range of multiple identities, into their work.