Abstract
The purpose of this article is to begin framing doctoral training for a science of social work. This process starts by examining two seemingly simple questions: “What is a social work scientist?” and “How do we train social work scientists?” In answering the first question, some basic assumptions and concepts about what constitutes a “social work scientist” are articulated, and how this individual is distinct from a “sharp” (a researcher with no independent vision), a scholar, and even a scientist within other disciplines. In responding to the second, these concepts are operationalized into educational principles necessary to creating new social work scientists.
In her article “Framing Education for a Science of Social Work,” Fong (2011) presents her ideas around creating a mission statement for social work incorporating a vision of science unique to the field. She discusses relevant constructs, including the promising science of translational research, the intersectionality of applied and basic science, and the grounded nature of social work science in the values of social justice and diversity. She then lays out some thoughts on the formation and training of scientists. Her article echoes themes from Brekke’s recent Rosen Lecture at the Society for Social Work and Research (2011), as well as previous work by Thyer (2001) and recent presentations by Nurius, Brekke, and Fong (2010). She distinguishes among “sharps” (who are researchers with no application), “scholars” (who have knowledge but do no research), and “scientists” (who both think and create knowledge through research). Fong concludes her article by arguing that the purpose of social work doctoral education is to create scientists, and uses discussions in other disciplines to identify key educational elements in developing these scientists. The purpose of this article is to use her discussion as the departing point in framing education for a science of social work. This process begins by examining two seemingly simple questions: “What is a social work scientist?” and “How do we train social work scientists?”
This response will consist of two sections structured around addressing these two questions. In the first section, some basic assumptions and concepts about what constitutes a “social work scientist” will be articulated, and how this individual is distinct from either a sharp, a scholar, and even a scientist within other disciplines. In the second section, these concepts will be operationalized into educational principles necessary to creating new social work scientists. This section will build not only on the work of Fong, Brekke, Thyer and others, but also on my own work in the androgogy of evidence-based practice (Bricout, Pollio, Edmond, & Moore-McBride, 2008; Howard, McMillen, & Pollio, 2003; Pollio & Macgowan, 2010), along with my own teaching of doctoral level courses in theory and methods at the University of Alabama and Washington University in St. Louis.
What is a Social Work Scientist?
To begin with, let us echo the distinction that Fong and others in related disciplines have made, that the purpose of the doctoral education process is to produce scientists (Boote & Beile, 2005; Walker, Golde, Jones, Bueschel, & Hutchings, 2008), as opposed to sharps or scholars. The skills associated with training overlap considerably. But while the overlap among the terms is substantial, the differences clearly distinguish among the three. The scientist conducts research within a broader personal context, one that incorporates a larger vision for their inquiry. A sharp is distinct from a scientist in that the sharp conducts research, but is not necessarily embracing a larger vision beyond the current set of experiments. Both the scientist and the sharp must be proficient in methodology, but only the scientist must have a larger vision of the philosophy of science.
The term scientist has a broader scope unique to the field of social work. And here is where a second and key distinction is made—between a generic scientist and a social work scientist. There are defining characteristics that separate the social work scientist from those in other disciplines and it is in this distinction that the first steps to a social work doctoral education approach emerges. Namely, that the purpose of the doctoral education process is not to train scientists, but to uniquely train social work scientists. Thus, the task for the remainder of this section is to identify distinctions between social work and generic science, and to use this to articulate some principles for creating social work scientists that can be carried over to articulate an educational approach.
To begin, a social work scientist is distinct from the generic scientist in that this person’s science is responsive to the larger social vision and the unique values of the profession. While other science in other disciplines may choose to be responsive to a larger social vision, a social work scientist always defines their work as contributing to a vision of social justice. Although this does not necessarily mean that each research project leads to social change, it does mean that all research is contextualized within this vision. A social work scientist is aware of and can articulate how their work is part of this vision. This distinction is inherent in Fong’s article, and proceeds directly from her focus on mission. The mission of the social work scientist emerges directly from the mission of the profession.
In a similar vein, the social work scientist must conduct their work with attention to the larger context within which the research takes place. We can call it person-in-environment, or systems perspective, or whatever term we prefer to capture this, but the bottom line remains the same—the social work scientist attends to this broader context in which their research takes place and incorporates it into their scholarly vision. Thus, again building on Fong, the social work scientist is able to articulate how their science fits within the realm of micro/mezzo/macro practice. This represents only a minimal condition. I would, in fact, prefer a stronger statement of this principle—that a social work scientist incorporates a broader systems agenda to their research vision. This may mean conducting a scientific agenda that includes research at multiple levels or conducting more complex multilevel research.
A corollary of these first two characteristics proceeds from the ethics of the social work profession. A social work scientist focuses on oppressed populations and principles of social justice. This extends beyond the public health position in that it incorporates not just a focus on issues of social relevance, but an injunction to focus on science that seeks to alleviate the conditions leading to oppression. Social work thus is not only a profession that focuses on specific problems but endeavors to provide knowledge that leads to solutions. This principle proceeds from Fong’s discussion of intersectionality, but takes it forward. The implication here is that implementation of this approach incorporates an applied perspective, but also an understanding that appropriate application requires basic knowledge to guide it.
A social work scientist is unique in that the product of science must have implications in the real world. This does not preclude theory development, but insists that it be grounded in a complex understanding of how this theory describes the world in which our social vision is conducted. On one level, this clearly fits with Fong’s focus on translational research. However, it moves beyond that in that, it insists on the presence of some attempt to understand the theory that leads to translation. It also suggests that the level of theory be less focused on grand theories (or paradigms) and on microtheory, but more on theories of the midrange. This further distinguishes our social work scientist-in-training from the “sharp” described in Fong’s article.
The combination of these distinctions leads to a further conclusion that is inherent in all of the above distinctions, but I think it is worth stating separately. A social work scientist always incorporates a value of, and attention to, diversity. This is distinct from a standard human science approach that generally incorporates diversity as a descriptive variable to be collected and used in analyses. Rather, the social work scientist endeavors to understand diversity as a complex construct and incorporates attention to it in all aspects of research. A caveat is appropriate here. This does not mean that all research should incorporate a focus on all diversity populations. Rather, it means that the decisions around how and when to incorporate diversity must be ongoing and thoughtful. It may be the case that the scientist may decide to include a focus on diversity in a later project or may choose a simpler descriptive approach to help decide how (or even whether) to include a focus on a particular population. This principle also carries a distinct message for social work science in that it challenges the scientist to recognize their own limitations in understanding diversity and include this self-awareness into development of research methodologies.
A final distinction between a social work scientist and a more generic one lies once again within the vision of the profession of social work. Because a social worker is dedicated to facilitating change, a social work scientist must be engaged in using the science to make actual change. Thus, a social work scientist is also an advocate, engaged in change efforts that build on the knowledge gained in their science. Now, it is important to two more distinctions here, namely, to distinguish a social work scientist from a social work practitioner. Both are equally members of the profession, but advocacy for a social work scientist additionally must be indelibly intertwined with their substantive work. It is not enough for the scientist to be engaged in advocacy, the results of their science should be used to inform and shape their advocacy.
Competencies and Educational Processes
In considering the initial question of what constitutes a social work scientist, a number of principles emerge for training. The following constitutes requirements for development of scientists, primarily through doctoral education. After presenting training principles emerging from the vision of a social work scientist, how this translates into the classroom and dissertation process is presented. These principles are not meant to be final or exhaustive, but rather to present thinking on how social work scientists might be developed, and to further the dialog by asserting initial principles for creating training programs.
Training of scientists requires grounding within the field of social work. Minimally, this includes a familiarity with the profession and history of social work. But, as a way to create the discussion around this point, I am going to go further. I believe that social work scientists should have a degree in social work prior to admission to a doctoral program. While there may be exceptions that might be addressed by required additional coursework, the average social work scientist-to-be should begin by being credentialed specifically within the discipline. I further believe that an intervention or prevention or services researcher is so strongly advantaged by having a practice background, it may be worthwhile to assure that practice researchers have practice experience.
Training requires attention to developing multiple complementary skills, including an understanding of the philosophy of science, integration of theory, and sophistication in multiple methodologies. This point emerges directly from the discussion of the need for social work scientists to understand the context in which their research occurs. Rather than focusing only on training excellent research technicians (sharps), we need to train scientists who understand philosophy of science, and the means through which assumptions about the nature of complex concepts such as “truth” or “reality” lead directly to the methods used to answer research questions. We also need to train our scientists on how to use theory to conceptualize and integrate context and complexity into their models. This is not to argue that all research necessarily tests theory, but rather that research is couched within theories or conceptual models. Finally, and I think this represents easily the least contentious of my principles, we need to train our scientists to be sophisticated in multiple methodologies and to be exposed to many other methodological options. In this way, social work scientists have the ability to answer a variety of questions using various approaches and methodologies that increases their ability to deeply understand a specific content area.
Training requires a focus on problem solving and an ability to apply critical thinking to this process. A focus on problem solving is a long-standing tradition in social work, dating back to Helen Harris Perlman (1957). Although there has been a more recent emphasis on strengths and solutions, from a science perspective, I believe that the process inevitably comes down to identifying a problem and understanding what is necessary to develop solutions. In identifying this training requirement, I had initially thought to describe it solely through the lens of critical thinking. But I would argue that critical thinking represents only a facet of science used in solving social or individual problems. Problem solving involves more than thinking, it includes action—in the case of the training of the scientist-to-be through conducting research. It is here that the distinction between the terms scholar and scientist is perhaps most clear. The scholar has the ability to think critically, the scientist to apply the thinking to problem solving.
Training requires social work scientists to be able to design robust, real-world research and also to be able to develop sophisticated, complex designs. This particular aspect of training represents a duality in methodological approaches specific to social work research, and hence to social work science. Designing interventions (at all levels) means attention to outcomes that have real-world significance. It is generally agreed in applied and translational research that statistical significance does not necessarily equate with meaningful changes to individual lives. Translation and implementation research also proceeds from a premise that interventions must result in significant clinical gains outside of laboratory settings—that they must demonstrate gains in the messy world of practice. This leads to an important point for training—the goal of training in social work science is not in the ability to produce perfect experiments, but to understand methods in a sophisticated manner in order to create meaningful evaluation and research models that can result in information that is useful, as opposed to sophisticated. In this approach to research, we are training social work scientists to develop research that results in important effect (or effect sizes) by developing simple models that capture the overall impact of conducting a project in the real-world setting. The resulting research can be simple and conducted with relatively small samples because the thing studied is robust enough to show main effects with little or no additional control. I maintain that it is necessary to have a complex understanding of methods to successfully design simple studies. This applies equally to intervention and policy research. To me, this level of sophistication is equally applicable to designing complex research projects. In creating robust models aimed at examining “real-world” effects of translation or implementation models, we need to train our scientists on what to “leave out” of their procedures. On the other side of the coin, to understand behaviors and problems within the context in which they occur, training should also to focus on developing the ability to design and successfully conduct complex research designs. Conceptually, this includes training in issues such as longitudinal research, multilevel modeling, as well as statistical knowledge on how to analyze more complex research designs. But training on experimental and quantitative designs only is not sufficient. Just as I have argued for the ability to be trained in solving complex problems, a social work scientist requires exposure and training to qualitative and mixed methods. Although I will not presume to identify or prioritize which specific methods, in my classrooms I consistently include exposure to grounded theory and participatory action methods. These latter methods are particularly important in our training process if we expect our social work scientists to be able to include theory development as part of their agendas, and if we expect them to be able to understand the real-world settings and how to advocate for change.
Training requires attention to advocacy and change efforts. This training requirement follows directly from the previous ones. The ability to understand how the social work scientist’s research efforts can be used, directly or indirectly, to provide information to facilitate advocacy or even to study (or participate) in advocacy efforts. This requires an ability to understand a phenomenon in such a way as to be able to support change efforts. This requires an ability to understand a problem in such a way that it can be implemented in advocacy efforts, but also studied in rigorous research. It implies that the social work scientist needs to not only be able to discuss the work using precise scientific language but also be able to explain the results clearly and simply to a nonscientific target audience. If any of my students read this, I am sure they will smile when they recognize my frequent requests to explain their ideas “in English, not research.”
Thoughts From the Classroom
I thought it would be appropriate to conclude this response using my own doctoral teaching experience to present some initial thoughts about both teaching and content aspects of a science of social work. I am going to focus on the foundational skills that I believe all social work scientists must acquire as part of the training. This section is meant to represent a starting place for thinking through this issue and not as a finished statement toward designing a program. I need to give credit here to multiple discussions that I have had with friends and colleagues.
Let me start with what I view as the easiest area, content. I believe that all social work doctoral programs require a significant grounding in the philosophy of science (Thyer, 2001). I have seen multiple lists of who should be on that list, and will not take time to name names here, but I believe that training our scientists requires original reading of major figures, as well as critiques and historical perspectives on how their ideas emerged. I would further argue (without, I believe, much opposition) that all doctoral students require a solid grounding in multiple research methods. A partial list would include experimental methods, instrument development, policy and organizational research, qualitative methods (grounded theory, focus groups, and others), mixed methods, and advanced statistics. I also believe that doctoral students should be exposed to theory and theory development. I would also like to see students exposed to emerging methodologies, such as Geospatial Information Science (GIS).
I also think the discussion around pedagogy (or, as I prefer andragogy) is also straightforward. Since we are training individuals to carry out independent and meaningful research, as I have argued several times before, we are definitely looking toward adult learner models (Bricout et al., 2010). Our job as educators is to promote sustained inquiry around specific problems chosen by the individual doctoral student and use that to facilitate their ability to independently pose sophisticated and rigorous models. The end product of the educational process is to use this knowledge to conduct a dissertation that demonstrates competence as a social work scientist sufficient to grant the degree.
I want to make a brief detour to discuss dissertations. I have long been a participant in the debate around collecting data or conducting secondary analyses of existing data sets. My purpose is not to state one preference or another but to argue that either choice must be held up to scrutiny, based on our concept of social work scientist, not in terms of research competence. To me, an elegant statistical analysis is not demonstration of scientific competence of a social work scientist. Nor is collection of poor primary data. Rather, the goal of the social work dissertation is to complete a study that demonstrate research competence, and also answers a meaningful “real-world” question that has implications for advancing knowledge in the student’s focal problem or population area. Thus, the social work dissertation becomes distinct from those conducted in other areas, as they have additional standards unique to the profession.
In closing this response, I am reminded of Specht and Courtney’s book, Unfaithful Angels (1994). In it, they argue that social work has abandoned its social justice mission. I think it is extremely cogent in that I believe that educating social work scientists requires us to rededicate ourselves to envisioning our research and science as something coming from social work, not a version of other social sciences, but rather a unique blend of a social vision, real-world applicability, and employing rigorous methods to contribute to solving important social problems.
Footnotes
Author’s Note
This paper was presented at the conference on “Shaping a Science of Social Work”, held at the university of Southern California School of Social Work on May 23-24, 2011. This article was invited and accepted by the Editor.
Declaration of Conflicting Interests
The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author received no financial support for the research, authorship, and/or publication of this article.