- Who We Are
- What We Do
- Contact Us
- Current Events
Volume 49 Number 2
Opening the Door to Methodological Diversity and Better Matching to Community-Based Phenomena: A Valuable New Tool
Written by Maurice Elias, Rutgers University
Citation: Jason, L.A. & Glenwick, D.S. (Eds.)(2016). Handbook of Methodological Approaches to Community-Based Research: Qualitative, Quantitative, and Mixed Methods. New York: Oxford University Press
The latest edition of the Handbook of Methodological Approaches to Community-Based Research: Qualitative, Quantitative, and Mixed Methods strikes me as being three books in one, each telling a story of the growth and depth of research methodology in understanding community-based phenomena. The three stories, told by over 80 authors, correspond to the three sections of the book, and the last three terms in the title.
The book begins with qualitative methods, which are really our oldest and most enduring way of understanding the world around us. We are treated to a journey through grounded theory, giving primacy to the voices of participants and focusing on building theory inductively, through thematic analysis, which involves systematic ways of identifying patterns of recurrent meaning in textual data sets, to community narratives, which uses story-based interviewing methods to generate narratives from diverse participants and stakeholders. As you might infer from just this subset of the qualitative methods section, methodology in community psychology is phenomena-driven. As we seek to know more than individuals’ perceptions about their lives, our methodological lenses must widen to capture a wider range of ecological space.
And that space is viewed through the distinctive, strength-oriented perspective of community psychology. What if we want to build on problem-based participatory action research, rooted in the work of Kurt Lewin, to instead focus on community strengths? Use Appreciative Inquiry. What if we want to better inform decision making through understanding consensus on the part of experts? Use a Delphi method. And what if we want to be immersed in a community to better understand the forces of social justice and injustice, power and oppression, and activism and exclusion operating therein? Critical ethnography can be your guide. And what if we want our research to also begin empowering individuals, including those for whom verbal modalities are not their multiple intelligence strengths, or for those who require the courage of shared voices as a launch point for action? Photovoice and House Meetings are essential tools. And what is on the cutting edge of qualitative methodologies, both in terms of widening the methodological lens and focusing it to look into the human heart and soul? You can learn about Geographic Information Systems (GIS) and Emotional Textual Analysis.
For those of you wondering whether there is enough rigor in qualitative approaches to address directionality in observations and begin to put together stories that look at the spiral of causality, from who we are, how we think, what we do, and what we say, there is Causal Layered Analysis. Each chapter benefits from case example illustrations, and the CLA chapter presents a fascinating view of the relational sports community of women engaged in flat track roller derby in Australia. The social constructions of “women” and “athlete” are given a view that extends to cultural archetypes, values, systemic considerations, and individual perspectives to arrive at an understanding of the trivialization of the skill, strength, and power of these athletes. The authors note, “CLA can be a daunting methodology, particularly to the novice or early career researcher” (p. 109). But isn’t this the story of methodological evolution? Many researchers have been warned about the career-stifling effects of using qualitative methodologies and their “subjective” elements. This volume announces, by putting qualitative methodologies first, that we are now past that, and that soon to be routine is what was once deemed cutting edge and “daunting.”
The quantitative section has a similar narrative arc. Quantitative methods are about the power of aggregation and prediction. At some point, humans began to see the value in being able to observe trends and take action based on those tendencies. We start with what is now basic for my graduate students: latent growth curve analysis. Big computing certainly now allows calculations of equations and algorithms that used to wear out my abacus and slide rule. The chapters in this section are exemplary in that they know they are not speaking only to graduate students (though certainly and ideally to them), but also to old folks who really do want to understand these methodologies, since we read about them more and more, regardless of whether we use them. Understanding patterns and trajectories of change is ultimately essential to the action component of community-based research. That what we are studying is rarely linear is a reality with which we must grapple, particularly as it pushes us, wisely, toward more longitudinal approaches.
Subsequent chapters on latent class and profile analyses and multilevel structural equation modeling help us understand the structure of the many variables and influences on phenomena of interest, for such dependent variables as community participation, impact of community violence, or networks of collaboration. All of the latter are examples illustrated in these chapters. I, for one, felt relieved to not see the words, “imputation” or “moderated mediation analysis” in the index or in my reading of the text. Let’s see if these become chapters in the next edition of this outstanding volume. The jury is out on whether or not this would be a welcomed development.
The cutting edge in quantitative methods is defined by cluster-randomized trials (reflective of the problems of ecological validity with traditional randomized control designs for a field that puts such emphasis on context), behavioral and time-series approaches (essential for documenting patterns of change over time, especially following intervention), data mining (an unfortunate term, in my view, as it contains the implications of panning for gold; but the authors are clear in their caveats, particularly about the quality of the data sets currently available for mining), and agent-based models. I confess that the latter term and the analyses presented were completely new to me. The authors suggest that these models “offer a single analytic tool that simultaneously integrates individual and ecological influences and that bridges the explanatory gap between microlevel processes and macrolevel outcomes” (p. 205). And there is a software program to guide you!
The final two chapters in this section, on social network analysis and dynamic social networks, were previewed for me at a presentation by the authors at the most recent SCRA Biennial conference and my team and I have already put their insights to work. My simple recommendation is to get the book to read these chapters, and follow up with these most wise, generous, and helpful authors. In my work in the schools, the essential element in virtually every change model is relational interaction. Yet, this is far too rarely measured in our studies. Social network analysis allows for examination of patterns of relationship in settings, on the part of individuals, and in multiple dyads. It allows us to answer questions related to the impact of empowerment interventions, professional development, changes in friendships and mentoring, workplace structures, personal and peer networks, and so on. We are using it to see whether and how an intervention designed to inspire youth leadership changes interaction patterns in troubled urban middle schools.
The final section, on mixed method approaches, is the future for community-based research. As this book makes abundantly clear, there are many perspectives with which to investigate community phenomena. The best of our work is deeply contextual and rooted in both time and place. So when we have the opportunity and privilege for community collaboration, we need to optimize what we can learn from the time we have. And that learning is optimized by combining qualitative and quantitative approaches to the extent possible. Otherwise, we just do not get a complete picture, and it is very difficult to “go back” into a community-based study for additional data.
Community psychology textbooks, and the introductory chapter to this section, make the point that since all methodologies have limitations, mixed methods attempt to offset weaknesses in particular approaches. But from a strengths oriented perspective, there are other, powerful reasons to employ mixed methods. The phenomena we seek to understand are ecological in nature, beginning at the level of the individual, and are shaped by context and history. We need to appreciate the meaning of the data from the participants, and we need to look at “outliers” as well as gathering broad representative samples. Community psychology is not a field focused on central tendency. We are interested in the full array of forces operating and we know that distal voices can have indirect impacts that may be obscured in nomothetic analyses.
So the reader is treated to an overview of action research and focused elaborations of community-based and youth-led participatory approaches, cross-cultural and photo-ethnographic mixed method research, functional analysis of community concerns, concept mapping, and network and stakeholder analyses. Cutting edge chapters, at least to me, focused on data visualization (which I think is different from what I am used to, praying that when I hit the SPSS execute button the data will come out as I have visualized), multilevel, multisetting inquiry (continuing to push our approaches to match the complexity of our conceptualizations and observations), dialectical pluralism (illustrated with a compelling example of how diverse perspectives can be integrated to understand the effects of a community-based intervention program for juvenile offenders), and community profiling (featuring a sophisticated approach to mapping community strengths and weaknesses into a set of profiling dimensions, including productive activities profiles, anthropological and psychological profiles, and a profile of the future, highlighted by an application to Porta Capuana, Italy, part of Naples).
This book, helpfully framed by a Foreword (Ray Lorion), Afterword (Anne Bogat), and introductory chapter by the editors (Len Jason and Dave Glenwick), should be mandatory for any graduate program in community psychology and is an essential resource for researchers and change agents working on community-based concerns. The chapters are well illustrated with examples and I actually could follow most of them—a testimony to the authors!—and my graduate students will explain the rest to me. Even if one is not actively engaged in research, the chapters in this book provide valued window into what one is reading in research reports, which, in turn, often influence practice and policy, but not always wisely or appropriately.
Jim Kelly and Ed Trickett pointed out that the ecological model is a conservative one. In a field eager to promote change toward social justice and reduced oppression, it can be frustrating to see efforts at change frequently stalled, short-lived after initial success, or difficult to replicate. As our methodologies catch up to our conceptual understanding, the products of our community-based research will better and more realistically inform our interventions and improve the effectiveness of our actions, as well as our ability to adjust our actions in light of ongoing community and systems dynamics and changes in context.
Get the book. I am heading to our Lab to start working on our social network analysis data!
You must be logged in to the website to leave a comment.