Finally, a practical guide to mixed methods research has been written with health and human services professionals in mind. Watkins and Gioia review the fundamentals of mixed methods research designs and the general suppositions of mixed methods procedures, look critically at mixed method studies and models that have already been employed in social work, and reflect on the contributions of this work to the field. But what is most important is that they lead the reader through considerations for the application of the mixed methods research in social work settings. The chapters of this book are structured so that readers can (figuratively) walk through the mixed methods research process using nine steps. Chapters one, five, and six provide supplemental material meant to serve as grounding for chapters two, three, and four, which outline nine steps in the mixed methods research process, and specific to social work research. This is a short and practical guide not just for learning about mixed methods research, but also doing it.

A comprehensive overview of the variation within content analysis and detailed descriptions of three approaches found in the contemporary literature: basic content analysis, interpretive content analysis and qualitative content analysis.

This text features discussions on emerging technologies in the field of needs assessment as well as abundant social work case examples. It covers one of the most essential kinds of research for social work management.

This slim volume is one of a number of excellent guides published as part of Oxford's "Pocket Guide to Social Work Research Methods" series. Compact but comprehensive, it provides a thorough introduction to one of the fastest-growing genres of research in the social work field today: secondary data analysis. After an all-too-brief summary of what constitutes this genre and a balanced analysis of its advantages and disadvantages, Vartanian (Bryn Mawr) provides guidelines for those considering the feasibility and appropriateness of using secondary data in their work. He then offers extensive summaries of 29 of the most commonly used secondary data sets. For all of the data sets, he provides a full and complete description, including key characteristics and where and how to access them. He also provides, most valuably, citations to examples of how researchers have recently used them in their empirical work. Rather redundantly, a similar package of information appears in appendixes at the end of the book. This is an admirable contribution whose only detractions are the rather random and poorly identified screenshots and other "pictures" interspersed throughout the text. Those seriously considering using secondary data analysis in their research should find this book immensely beneficial. Summing Up: Highly recommended. Graduate students and faculty/researchers. Graduate Students; Researchers/Faculty. Reviewed by J. C. Altman.

This book assists scholars in conducting studies about substance use. Organized around a translational science framework, this practical guide takes readers step-by-step through issues specific to substance use research in study design, participant recruitment and retention, measurement and analysis, and the processes involved in the implementation of evidence-informed innovations.

Applied Cross-Cultural Data Analysis for Social Work is a research guide for examining and interpreting data for the purpose of cultural group comparisons. This book aims to provide practical applications in statistical approaches of data analyses that are commonly used in cross-cultural research and evaluation. Readers are presented with step-by-step illustrations in the use of descriptive, bivariate, and multivariate statistics to compare cross-cultural population using large-scale, population-based survey data. These techniques have important applications in health, mental health, and social science research relevant to social work and other helping professions, especially in providing a framework of evidence to examine health disparities using population-health data. For each statistical approach discussed in this book, Thanh V. Tran and Keith T. Chan explain the underlying purpose, basic assumptions, types of variables, application of the Stata statistical package, the presentation of statistical findings, and the interpretation of results. Unlike previous guides on statistical approaches and data analysis in social work, this book explains and demonstrates the strategies of cross-cultural data analysis using descriptive and bivariate analysis, multiple regression, additive and multiplicative interaction, mediation, SEM and HLM for subgroup analysis and cross-cultural comparisons. This book also includes sample syntax from Stata for social work researchers to conduct cross-cultural analysis with their own research.

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 factory analysis (CFA) is one way to do so, and in this clearly written pocket guide Donna Harrington provides social work researchers with an essential roadmap to the highlights of CFA's powers and how to harness them.CFA has four primary functions-- psychometric evaluation of measures, construct validation, testing method effects, and testing measurement invariance-- all of which Harrington makes exceedingly accessible. She includes an easy-to-follow overview of the method, step-by-step guides to creating a CFA model and assessing its fit, and clear explanations of the requirements for using CFA, as well as underscoring the issues that are necessary to consider in alternative situations, such as when multiple groups are involved. Real-world examples, screenshots from the Amos software program that can be used to conduct CFA, and reading suggestions for each chapter make the material accessible for even the greenest novice.This pocket guide is ideally suited for readers who plan to conduct CFA analyses and need a brief, non-technical introduction to the topic to get them started before getting into the more detailed and technical literature, as well as readers who do not plan to conduct CFA analyses, but want to be knowledgeable consumers of research literature that uses CFA.

This pocket guide presents a reader-friendly introduction to narrative inquiry. It addresses major aspects of the design and implementation of a narrative research project, emphasizing established and emerging approaches to the analysis of narrative data.

Developing Cross-Cultural Measurement in Social Work Research and Evaluation, Second Edition is an applied practice-to-research text, with a focus on developing, assessing, and validating meaningful measurements across cultures and populations. This book deeply examines cultural differences that may present problems with measurements for target populations relevant to social work researchers, and features practical hands-on solutions to managing these problems using advanced quantitative methods. The authors present a step-by step approach, beginning with the conceptualization of measurements for different cultures, the processes involved in identifying item questions, and the quantitative techniques that can be used to validate new or pre-existing measures. This Second Edition also includes sample syntax from publicly available data for social work researchers to learn to conduct these types of analyses with their own research. New to the Second Edition: - Emphasis on Item Response Theory, and a new chapter devoted to the concept. - Increased focus on the process of instrument development, based on real-world examples - in particular, a detailed examination of the development of a new cross-cultural instrument, the Empathy Scale, created and validated by a group of multinational and culturally diverse students from the US, China, Mexico, and Turkey under the supervision of Dr. Tran. - Significant updates of all content to reflect new developments in cross-cultural research across social sciences and psychological disciplines.

When used in tandem, systematic reviews and meta-analysis-- two distinct but highly compatible approaches to research synthesis-- form a powerful, scientific approach to analyzing previous studies. But to see their full potential, a social work researcher must be versed in the foundational processes underlying them. This pocket guide to Systematic Reviews and Meta-Analysis illuminates precisely that practical groundwork. In clear, step-by-step terms, the authors explain how to format topics, locate and screen studies, extract and assess data, pool effect sizes, determine bias, and interpret the results, showing readers how to combine reviewing and meta-analysis correctly and effectively. Each chapter contains vivid social work examples and concludes with a concise summary and notes on further reading, while the book's glossary and handy checklists and sample search and data extraction forms maximize the boo'ks usefulness. Highlighting the concepts necessary to understand, critique, and conduct research synthesis, this brief and highly readable introduction is a terrific resource for students and researchers alike.