Sean Hughes, PhD
Department of Experimental Clinical and Health Psychology, Ghent University
Imagine three scientists out to expand the limits of human understanding. The first is an astronaut busy analyzing soil samples on the cold, dark surface of the moon. The second is a marine biologist trying to find ways to get penguins more active and engaged at a large public aquarium. The third is a primatologist deeply interested in the courting behavior of silverback gorillas, who finds herself wading through a tropical forest in Central Africa. Although all three use the scientific method to understand a specific phenomenon, they approach their goals in very different ways. The fundamental questions they are interested in (e.g., What is the lunar soil composed of? How can the behavior of captive penguins be changed? How do primates behave socially in the wild?) will guide the procedures they use, the theories they generate, the types of data they collect, and the answers they ultimately find satisfactory.
In many ways, clinical psychological science faces a similar situation. Although clinicians and researchers are united by a shared goal (to understand how human suffering can be alleviated and well-being promoted), they often tackle that goal in fundamentally different ways. Some argue that this goal can be best achieved by detecting and correcting the dysfunctional beliefs, pathological cognitive schemas, or faulty information-processing styles that underpin psychological suffering (e.g., Beck, 1993; Ellis & Dryden, 2007). Others counter that the best solution requires that we contact and alter the functions of internal events rather than their particular form or frequency (e.g., Hayes, Strosahl, & Wilson, 1999; Linehan, 1993; Segal, Williams, & Teasdale, 2001). In this rich, dense jungle of clinical research and theorizing, different traditions often find themselves in fierce competition, with proponents of one perspective arguing for the logical supremacy of their own procedures, findings, theories, and therapies, while others respond with equally and strongly held convictions (see Reyna, 1995, for an example). In such an environment, you might ask yourself, Is there really a “best” solution to the problem of psychological suffering? How do clinicians and researchers define what qualifies as “best,” and is this a subjective or objective choice? How do they actually determine whether a given procedure, finding, theory, or therapy is satisfactory or even better than others?
The Ghent University Methusalem Grant BOF16/MET_V/002, presented to Jan De Houwer, supported the preparation of this chapter. Correspondence concerning this chapter should be addressed to sean.hughes@ugent.be.
Even if clinical researchers do not typically operate in the cold vacuum of outer space, the water tanks of an aquarium, or the humid interiors of tropical forests, their activities are nevertheless carried out within a larger context that guides their scientific values and goals. One of the more important aspects of this context is their philosophical worldview. Worldviews specify the nature and purpose of science, causality, data, and explanation. They define what we consider the proper subject matter of our field, what our units of analysis will be, the types of theories and therapies we build and evaluate, the methodologies we construct, and how findings should be generated and interpreted.
Questions about ontology, epistemology, and axiology can seem highly abstract and far removed from the daily trials and tribulations that make up clinical research or therapeutic practice. In what follows I aim to demonstrate how philosophical assumptions are similar to the air we breathe: typically invisible, integral to our daily functioning, and yet often taken for granted. There is no privileged place that allows you to avoid these issues: your worldview silently shapes how you think and act, influencing the theories, therapies, techniques, and data you consider convincing or valid (e.g., Babbage & Ronan, 2000; Forsyth, 2016). It dictates some of your moment-to-moment behavior when interacting with a client. By properly articulating and organizing these assumptions, you gain access to a powerful method of determining the internal consistency of your own scientific views and ensure that your efforts at knowledge development are progressive—when measured against your (clinical) scientific goals.
Scientific endeavors must have criteria to evaluate competing theoretical and methodological accounts if progress is to be achieved. Yet scholars often engage in debates of a different kind: ones that center on the legitimacy, primacy, and value of one intellectual tradition relative to another. Such debates have been labeled “pseudoconflicts,” given that they involve applying the philosophical assumptions (and thus scientific goals and values) of one’s own approach to the assumptions, goals, and values of others (Pepper, 1942; Hayes, Hayes, & Reese, 1988). For instance, behaviorally oriented therapists may dismiss the value of mental-mediating representations and processes, such as cognitive schemas or biases, given that such explanatory constructs are counter (or even irrelevant) to their own focus on manipulable, contextual variables that can facilitate the prediction and influence of psychological events. Similarly, cognitively oriented researchers might view any analysis that omits reference to the mental machinery of the mind as merely descriptive and nonexplanatory. As Dougher (1995) notes, these respective scholars might wonder why their counterparts “persist in taking such outdated or plainly wrong-headed positions, why they persist in misrepresenting my position, and why they can’t see that both logic and data render their position clearly inferior” (p. 215). The failure to recognize the philosophical origins of these debates often leads to “frustration, sarcasm, and even ad hominem attacks on the intellectual or academic competence of those holding alternative positions” (p. 215).
Psychological scientists who are capable of articulating their philosophical assumptions are better able to identify genuine and productive conflicts within traditions that drive theory and research forward, and they can avoid wasting time on pseudoconflicts that tend to be degenerative in nature. In other words, appreciating the philosophical underpinnings of your work also allows you to communicate without dogmatism or arrogance to those who hold different assumptions. Such flexibility is central to the theme of this book: helping different wings of evidence-based therapy learn to communicate across philosophical divides. For these reasons and others, a consortium of cognitive and behavioral organizations recently added training in philosophy of science to the training standards for empirical clinicians (Klepac et al., 2012).
Finally, the clinical literature is home to an overwhelming number of perspectives that may tempt students to adopt a vapid form of eclecticism, hoping that by mixing together all plausible theories and concepts, even better therapeutic outcomes will be likely. Disciplined combinations of approaches are possible and helpful, but confusion results if theories and therapies are mixed in ways that are inconsistent (because underlying philosophical assumptions were misunderstood or ignored).
This chapter is divided into three sections. Part 1 provides a brief introduction to the core topics of philosophy of science as they apply to those undergoing clinical training (examples of more extensive treatments are Gawronski & Bodenhausen, 2015; Morris, 1988; Guba & Lincoln, 1994; among many others). In part 2, I introduce a number of worldviews that were originally forwarded by Stephen Pepper in the 1940s, with a focus on mechanism and contextualism in particular. I will demonstrate how these latter worldviews have arguably shaped and continue to drive clinical psychology. Finally, in part 3 I consider the topics of worldview selection, evaluation, communication, and collaboration. If readers then decide to adopt a particular philosophical perspective, they will do so with awareness of the alternatives, how this decision shapes their own thinking and actions, and how they can interact with colleagues who see (or construct) the world in ways that differ from their own.
Science is broadly concerned with the development of a systematic body of knowledge that is tied to empirically derived evidence (e.g., Lakatos, 1978; Laudan, 1978). This system of knowledge is built with the intention of understanding and influencing “patterns of relations among phenomena and processes of the experienced world” (Lerner & Damon, 2006, p. 70). Philosophy of science refers to the conceptual foundation upon which this systematic body of knowledge is built. Rather than focusing on the particular theories, methods, and observations that define a scientific domain, philosophy of science is concerned with the scientific enterprise itself. The goal is to uncover the assumptions that are often implicit (or taken for granted) in scientific practice and that dictate its course (e.g., how science should proceed, what methods of inquiry should be used, how much confidence should be placed in the findings generated, and what are the limits of the knowledge obtained). In this way, philosophy of science provides a perspective from which to examine and potentially evaluate clinical psychological science.
A philosophical worldview can be defined as the coherent set of interrelated assumptions that provides the preanalytic framework that sets the stage for scientific or therapeutic activity (see Hayes et al., 1988; closely related terms are “paradigm,” Kuhn, 1962; and “research programme,” Lakatos, 1978). One’s worldview is a belief system that both describes and prescribes what data, tools, theories, therapies, participants, and findings are acceptable or unacceptable. The basic beliefs that make up a worldview typically revolve around the following set of interrelated questions, with the answers to one question constraining responses to the others.
Positivism is a reductionistic and deterministic perspective that often involves a belief in “naïve realism,” the idea that a discoverable reality exists that is governed by a system of natural laws and mechanisms. Scientific models and theories are considered useful or valid insofar as they increase our ability to make claims that refer to entities or relations in a mind-independent reality (i.e., truth as correspondence). This type of “knowledge is conventionally summarized in the form of time- and context-free generalizations, some of which take the form of cause-effect laws” (Guba & Lincoln, 1994, p. 109). Scientific progress itself involves the development of theories in which representational nature gradually converges upon a single reality.
Postpositivism also assumes that mind-independent reality exists, but it can only be imperfectly and probabilistically understood by humans due to their biased intellectual abilities and the fundamentally intractable nature of phenomena. Postpositivists believe that there is a reality independent of perception and theories about it but also argue that humans cannot know that reality with absolute certainty (e.g., see Lincoln, Lynham, & Guba, 2011). Thus, all scientific claims about reality must be submitted to close scrutiny if we are to converge on an understanding of reality that is acceptable (if never perfect).
Constructivism, unlike positivism and postpositivism, takes a relativistic ontological stance. A mind-independent reality is substituted for a constructed one: reality does not exist independently from our perception or theories about it. Instead we interpret and construct it based on our experiences and interactions with the social, experiential, historical, and cultural environments in which we are embedded. Constructed realities are malleable, differ in their content and sophistication, and are not “true” in any absolute sense of the word. Although constructivists tend to acknowledge that phenomena exist, they challenge the extent to which we can rationally know reality outside of our personal perspectives (e.g., see Blaikie, 2007; Lincoln et al., 2011; Von Glasersfeld, 2001). In some forms of this approach, constructivists simply refuse, on pragmatic grounds, to view ontological questions as answerable, useful, or necessary (Hayes, 1997).
Positivism adopts a dualistic and objectivist position: provided that she has access to the proper methodologies, the knower (scientist) can objectively view and record events as they “really are” and as they “really work.” This process does not influence the phenomenon of interest, nor does the phenomenon influence the knower. Situations in which the knower influences the known (or vice versa) represent threats to validity, and the knower implements strategies to reduce or eliminate potential sources of contamination.
Postpositivism is qualified dualist/objectivist. Given the imperfect manner in which the world is viewed and recorded, dualism is de-emphasized: observations are accepted as being prone to error and are always open to critique. Theory is ultimately revisable and open to replacement by a different set of categories and relationships. However, objectivism is still the “regulatory ideal” to which the scientist strives (Lincoln et al., 2011). Scientific analyses are considered to be “true” or “valid” insofar as they allow us to converge on an accurate (if imperfect) understanding of reality (i.e., truth is correspondence). Such analyses are based on the idea that (a) knowledge can be best obtained through the identification of regularities and causal relationships between the component mechanisms that constitute reality; that (b) these regularities and relationships will be easier to identify when the scientist and phenomenon do not contaminate one another; and that (c) the scientific method is the best tool the scientist has to minimize such contamination. Thus, the purpose of models and theories is to provide general explanations that are logically organized and that have clearly established links with the observable world. These explanations extend beyond the observation of individual events and have a heuristic and predictive function.
Finally, constructivism is transactional and subjective. It argues that findings are obtained through the interaction of the knower and the known, and as such they are literally created as the scientific enterprise unfolds. In this way knowledge is subjective insofar as there is no objective location from which to view or obtain knowledge (and even if there was, we have no way of accessing it). Thus, the knower is an active participant rather than a passive observer in the knowledge acquisition and justification process. Truth is not correspondence with some underlying reality but rather the extent to which a particular analysis occasions “successful working” or is considered “viable.” As Von Glasersfeld puts it, “To the constructivist, concepts, models, theories…are viable if they prove adequate in the contexts in which they were created” (1995, p. 4). From the constructivist perspective, science can be viewed as “a corpus of rules for effective action, and there is a special sense in which it could be ‘true’ if it yields the most effective action possible” (Skinner, 1974, p. 235; see also Barnes-Holmes, 2000).
Postpositivism takes a similar if qualified stance: all observations are assumed to be theory laden. The search for absolute truth is abandoned and the researcher accepts that analyses are guided by the cultural, social, historical, and personal expectancies she brings to the enterprise (i.e., science is value laden). Nevertheless, progress can be best achieved if the scientist does her utmost to minimize the impact of such contaminating factors on theoretical arguments and empirical findings.
Finally, constructivism is dialectical: given the variable and personal nature of the constructed world, there is no objective location from which reality can be independently observed or recorded. The scientist cannot be separated from subject matter, nor can theory be separated from practice. Thus, values are considered an integral element of the interactions between scientist and the phenomenon being studied.
Postpositivists share a similar view. However, given that all measurement is subject to error, the researcher must engage in a process of critical multiplism, in which she takes multiple observations and measurements (that are each subject to different types of error), in order to identify potential sources of error, and then creates control for them, thus better approximating reality. Through independent replication the scientist learns more about the ontological validity of her model. This in turn enables her to engage in the falsification (rather than verification) of hypotheses and theories.
Constructivism challenges the idea that knowledge exists freely in the world and that objective measurement procedures can be designed to capture such a world. All information is subject to interpretation by the researcher and, as such, the relationship between the researcher and subject matter is a central focus of methodology.
Although worldviews can and have been categorized in many different ways, Pepper’s (1942) classification scheme is useful in reflecting upon the components, assumptions, and concerns that drive theory and research in different areas of clinical and applied psychology.
The core of Pepper’s thesis is that humans are not prone to engaging in complex, abstract thought, and they tend to rely on commonsense guides or “root metaphors” to keep their intellectual bearings. He argued that the major, relatively adequate philosophical positions can be clustered into one of four core models (“world hypotheses”): formism, mechanism, organicism, and contextualism. Each uses a different root metaphor as a kind of thumbnail guide that suggests how knowledge ought to be justified or represented, how new knowledge should be obtained, and how truth can be evaluated (for more, see Berry, 1984; Hayes et al., 1988; Hayes, 1993).
These worldviews are autonomous (because their basic assumptions are incommensurable) and allow content in different domains of knowledge to be described with precision (i.e., applying a restricted set of principles to specific events) and scope (i.e., analyses that explain a comprehensive range of events across a variety of situations). Their truth criteria provide a way of evaluating the validity of scientific analyses that emerge from a particular worldview. In the following section I consider each of these worldviews and then discuss how they set the stage for particular kinds of clinical research and practice.
The root metaphor of formism is the recurrence of recognizable forms. An easy way to think of formism is that it is a form of philosophy based on the action of naming—that is, knowing how to characterize a particular event. For instance, smartphones constitute a class or category in which many particulars are said to “participate.” The truth or validity of an analysis is based on simple correspondence: an individual member possesses characteristics that correspond to the characteristics of the class. A brick is not a smartphone because it is not electronic and you cannot make calls with it; a desktop computer is electronic and you can make calls with it, but it is not a smartphone, in part, because it is not portable; and so on. The task of scientists is to create a comprehensive set of categories or names, and the truth or value of their actions can be determined from the exhaustive nature of this categorical system. “If the system has a category for all kinds of things, and things for all categories, then the categorical system is deemed to correspond with the a priori assumed world of things and events” (Wilson, Whiteman, & Bordieri, 2013, p. 29). When applied to psychology, formism suggests that phenomena can be understood by assigning them to specific classes or types, and for that reason some nosologies or personality theories provide good examples of formism.
Mechanism is a more sophisticated variant of formism and arguably the position that underpins most empirical work in contemporary psychology. Its root metaphor is the commonsense “machine.” This approach “assumes the a priori status of parts, but goes on to build models involving parts, relations, and forces animating such a system” (Wilson et al., 2013, p. 29). When applied to psychology, the purpose of science is to identify the parts and their relationships (e.g., mental constructs, neurological connections) that mediate between input (environment) and output (behavior), and to identify the operating conditions or forces that are necessary and sufficient for mechanisms to successfully function (e.g., attention, motivation, cognitive capacity, information). (Note that “mechanism” has sometimes been used within applied psychology as an epithet, meaning “robot-like” or “unfeeling.” This is not its meaning in philosophy of science, and I don’t suggest any negative connotations when I use the term.)
Within a mechanistic worldview, causation is contiguous: “one step in the mechanism (e.g., a mental state) puts in motion the next step (e.g., another mental state)” (De Houwer, Barnes-Holmes, & Barnes-Holmes, 2016; chapter 7 of this volume, p. 122). Stated more precisely, mechanism argues that mental processes operate under a restricted set of conditions, and these are separate from, but co-vary with, the environmental context under which behavior is observed. Thus, the unit of analysis for mechanisms (mental or physiological) is the component element of the machine (e.g., a process, entity, or construct). Although some of these elements are directly observable in principle (e.g., neurons), in psychology they often are inferred from changes in behavior due to organismic interactions with the environment (see Bechtel, 2008).
Note that the root metaphor of a machine applies both to the knower and what is known. “The knower relates to the world by producing an internal copy of it, through mechanical transformation. This epistemological stance preserves both the knower and the known intact and basically unchanged by their relation” (Hayes et al., 1988, p. 99). Analyses are considered “true” or “valid” when the internal copy of reality (the hypothesized model or theory) maps onto the world as it is. This is a more elaborated version of the correspondence-based truth criterion of formism. How well a particular system reflects reality is evaluated by the extent to which other independent knowers corroborate it through predictive verification or falsification.
Because mechanists view complexity as being built up from parts, they tend to be reductionistic. The goal of science is to identify the most basic units that fill the temporal gaps between one event and another (e.g., mental representations, past behaviors, neural activity, emotions). This is typically achieved by building facsimiles of reality (internal copies) in which truth or validity is determined from its objective correspondence with that reality (e.g., mental models). Description and theoretical prediction constitute satisfactory forms of scientific explanation, given that they allow one to evaluate correspondence between theory and reality. The result (at least in psychology) is a largely hypothetico-deductive and theory-driven research agenda, one that downplays distal factors (histories of learning) and emphasizes behavior as the product of internal, independent causal agents or systems.
These philosophical assumptions are inherent in many cognitive and behavioral therapies. For example, the impact of stimulus pairings or operant contingencies in early behavior therapy might be explained by the formation and revision of stimulus-response or stimulus-stimulus associations (e.g., see Foa, Steketee, & Rothbaum, 1989). Similarly, the impact of cognitive therapy (Beck, 1993; Mahoney, 1974) might be explained by the cognitive schemas, faulty information-processing styles, irrational cognitions, or automatic thoughts that are believed to mediate the relationship between environmental input and behavioral/emotional output. As a result of these explanations, the target of intervention would be a change in the occurrence of these events, through restructuring, reappraisal, the modification of core beliefs, and so on (e.g., Hofmann, 2011; see chapters 21 and 22).
The root metaphor at the core of organicism is that of the growing organism. Organicists view organic development as beginning in one form, growing and transitioning in an expected pattern, and then ultimately culminating in another form that was inherent in what came before. Consider, for example, the organic process through which a seed turns into a tree. There are rules of transition between states or phases, and stability between periods of change, but once rules are identified and explained, the states, phases, and stability are seen as part of a single coherent process. In order to explain the present and predict the future, we must understand the basic rules that govern development and how these rules operate across both time and context (Reese & Overton, 1970; Super & Harkness, 2003).
Organicism is teleological. Just as a seed may be “meant to be” a tree, stages of development make sense only by knowing where they are headed. The truth criterion of organicism is coherence. “When a network of interrelated facts converges on a conclusion, the coherence of this network renders this conclusion ‘true.’ All contradictions of understanding originate in incomplete knowledge of the whole organic process. When the whole is known, the contradictions are removed and the ‘organic whole…is found to have been implicit in the fragments’” (Hayes et al., 1988, p. 100).
Organicists reject the idea of simple, linear cause-effect explanations, preferring a more synthetic (interactional) approach. They argue that a system cannot be understood by breaking it down into its component elements. The whole is not a combination of individual parts; rather, the whole is basic, with parts having meaning only with regard to the whole. The identification of parts or stages is to some degree an arbitrary exercise for the purpose of investigation, but the order of those stages is not. For instance, “where the line is drawn marking the difference between an infant and a toddler may be arbitrary, but that infancy precedes toddlerhood is nonarbitrary and is presumed to reflect the a priori organization of development” (Wilson et al., 2013, p. 30).
The root metaphor of contextualism is the ongoing “act in context.” Acts can be anything done in and with a current and historical context and are defined by their purpose and meaning. Contexts can “proceed outward spatially to include all of the universe…[or] backward in time infinitely to include the remotest antecedent, or forward in time to include the most delayed consequence” (Hayes & Brownstein, 1986, p. 178). The act in context is not a description of some static event that occurred in the past. Instead it is a purposeful activity that takes place here and now within physical, social, and temporal contexts. Thus, in contextualism (as in mechanism and organicism), relations and forces may be described. However, the described organization of those forces and relations is not assumed to reflect some a priori organization of the world (as is the case with formism or mechanism) nor some progression toward an “ideal form” (as is the case with organicism). Rather, speaking of the parts and relations is itself the action of scientists who operate in and with their own contexts and for their own purposes (Hayes, 1993). Consequently, scientific activity based on contextualistic thinking (within psychology) is not concerned with descriptions of the “real world” but rather “verbal analyses that permit basic and applied researchers, and practitioners, to predict and influence the behavior of individuals and groups” (De Houwer, Barnes-Holmes, & Barnes-Holmes; chapter 7 of this volume, p. 124).
Note that an act in context can vary from the most proximal behavioral instance (e.g., social anxiety as one interacts with colleagues here and now) to temporally distal and remote behavioral sequences (e.g., the impact a particular experience two years ago has on choosing whether to attend a social gathering in several days’ time). What brings order to this spread of possibility is the pragmatic goal of an analyst (see Barnes-Holmes, 2000; Morris, 1988; Wilson et al., 2013). The metric of truth is neither correspondence nor coherence with a mind-independent reality but simply anything that facilitates successful working (this is the same truth criterion previously mentioned in the section on constructivism, and indeed constructivists are often contextualists).
There are, however, varieties of scientific contextualism. In order to know what successfully works, one must know what one is working toward: there must be a clear a priori statement of the scientist’s or practitioner’s goal or intent (Hayes, 1993). Descriptive contextualists (dramaturgists, narrative psychologists, postmodernists, social constructionists) are focused on analyses that help them appreciate the participation of history and circumstance in the whole; functional contextualists are trying to predict and influence behavior with precision, scope, and depth (Hayes, 1993). Because of this, contextualism is relativistic—what is considered true differs from one scientist to another based on respective goals.
ACT can be used as a brief example to help show how contextualistic thinking takes the scientist or practitioner down a different pathway than mechanistic perspectives. Broadly speaking, ACT does not focus on the content of a thought, attempt to manipulate its form or frequency, or concern itself with the extent to which it is “real.” Instead it pays close attention to what function the thought, feeling, or behavior has for the client in a given context. Consider the example of a public speaker who encounters the thought I’m going to have a panic attack as she walks toward a podium. An ACT therapist might not assume that this thought is necessarily harmful or that it has to be eradicated or revised. Rather he might ask, “How can you relate to this thought in a way that will foster what you want?”
The therapist adopts this approach because he views cognitions, emotions, beliefs, and dispositions as dependent variables (actions) and not as (the ultimate) contiguous causes of other dependent variables, such as overt behavior. In order to predict and influence the relationship between, say, thoughts and overt behavior, the therapist needs to identify the independent variables that can be directly manipulated in order to alter that relationship, and—from the therapist’s perspective—only contextual variables are open to direct manipulation (Hayes & Brownstein, 1986). Mental mechanisms (e.g., associations in memory, schemas, semantic networks, or propositions) and the hypothesized forces that bind them are (at best) more dependent variables—they are not functional causes. That same truth criterion (successful working) also applies to clients who are “encouraged to abandon any interest in the literal truth of their own thoughts or evaluations…[and] instead…are encouraged to embrace a passionate and ongoing interest in how to live according to their values” (Hayes, 2004, p. 647).
Now that I’ve discussed a number of worldviews and how they inform clinical thinking and practice, you may be asking yourself a new set of questions about selection, evaluation, and communication. For instance, exactly how, when, and why did you decide to subscribe to a particular worldview, and is your belief system any better or more useful than that of your peers? Given their fundamental differences, can proponents of one worldview ever communicate and interact with those adopting another perspective? It is to these questions that I now turn.
People may find themselves adhering to a particular worldview for several reasons. First, their philosophical orientation (and thus theoretical predilections) may be partially determined by individual differences, such as temperament and personality attributes (e.g., Babbage & Ronan, 2000; Johnson, Germer, Efran, & Overton, 1988). Second, worldviews may not be consciously selected but rather implicitly thrust upon us by the prevailing scientific, cultural, historical, and social contexts in which we find ourselves embedded. In other words, scientists may assimilate or inherit the philosophical framework that underpins the dominant zeitgeist of their field during their training. Thus worldview selection may be to some extent irrational (Pepper, 1942; Feyerabend, 2010; Kuhn, 1962; although see Lakatos, 1978, for arguments centered on rational research-program selection). For instance, once prediction is implicitly adopted as a scientific aim, then (mental) mechanistic explanations may be simpler and “commonsense.” If your goal is to predict and influence behavior, a contextual position may seem more valuable. Third, people can evaluate the different types of scientific outcomes that are produced when different worldviews are adopted and effectively “vote with their feet” (Hayes, 1993, p. 18). The popularity of worldviews seems to shift across time, both within and between scientific communities (Kuhn, 1962). Psychological science is no exception, with a variety of metatheoretical paradigms, theories, and empirical issues gaining prominence at one time or another.
Although popular convention, personality disposition, or matters of taste may guide the selection of any particular worldview, the standards of evaluation applied to that worldview are specified. When we evaluate a particular product of scientific activity (e.g., a finding, theory, or therapy) as being either good or satisfactory, we are basically asking whether that activity is consistent or coherent with the internal requirements of a worldview and with the consumers of new knowledge.
Theory testing looks quite different if one takes a contextualistic or constructivist stance. In these worldviews, theories are merely tools with which to achieve some end. Consider how a commonsense tool, say a hammer, could be evaluated: “A hammer is a good ‘hammer’ if it allows the carpenter to drive a nail. It would not make sense to say that the hammer does so because it accurately refers to the nail or reflects the nail” (Wilson et al., 2013, p. 30). Similarly, a theory is considered a good theory if it allows the scientist to achieve some desired outcome. In this case, theory evaluation involves determining the consistency with which models or theories can be shown to lead to useful interventions across a range of situations (e.g., see Hayes, Barnes-Holmes, & Wilson, 2012; Long, 2013).
What should be clear, however, is that these arguments are pseudoconflicts—an attempt by proponents of one worldview to position their own philosophical assumptions (and thus scientific goals and values) as ultimately right and the worldview of others as wrong. Yet philosophical assumptions cannot be proven to be right or wrong because they are not the result of evidence—they define what is to be considered “evidence.” The standards developed within a given worldview can be applied only to the products that emerge from that approach (in much the same way that the rules that make sense within one sport (soccer) cannot be used to govern the activity of another (say, basketball). Furthermore, no worldview is strengthened by showing the weaknesses of other positions.
There are four legitimate forms of evaluation. One is to improve your own scientific products as measured against the criteria appropriate to your approach. A second is less obvious but professionally helpful and collegial: enter into the assumptions of colleagues that differ from your own and then help them improve the scientific products as measured against the criteria that are appropriate to those assumptions. A third is to clearly articulate the assumptions and purposes that underpin your scientific activity and note (nonevaluatively) how they differ from others. For instance, you can describe the root metaphor and truth criterion that you’ve adopted, and how your analyses are carried out from this perspective, without insisting that others with different assumptions do the same. A fourth approach is to note the goals and uses of science by consumers (e.g., government funders, clients) and to objectively assess whether research programs serve those ends.
In light of the above, you might wonder if it’s possible for adherents of one worldview to communicate and collaborate with those from another without sacrificing their respective goals and values in the process. The received wisdom in psychology is that communication across worldviews is not possible. A concrete example is the way researchers use the same words to refer to different concepts (e.g., “cognition” means very different things for mental-mechanistic and functional-contextual researchers; see chapter 7) or use different words to refer to a similar idea (e.g., “attentional allocation” or “stimulus discrimination”). The most common result of these difficulties appears to be either fights over perceived scientific legitimacy or an ignoring of the fruits of colleagues’ labors.
There is a radically different way to think of this situation, however, and it helps explain why training in philosophy of science is now expected of practitioners. If scientific goals of different worldviews are orthogonal, it also means they cannot be in direct conflict with one another. Thus, there is no reason why developments within one tradition cannot be used to further the scientific agenda of the other. This book is organized around that core idea. Process-based therapy can be linked to evidence from different traditions. By appreciating legitimate differences, the different wings or waves of evidence-based therapy can complement each other.
One way that individuals from different traditions can achieve scientific cooperation is by adopting a metatheoretical perspective known as the functional-cognitive (FC) framework (see chapter 7 for a detailed treatment). According to this perspective, psychological science can be conducted at two different but supportive levels of analysis: a functional level that aims to explain behavior in terms of elements in the environment, and a cognitive level that aims to understand the mental mechanisms by which elements in the environment influence behavior. The FC framework does not interfere with the individual researcher’s goals, nor does it pass judgment on those goals or the reasons behind them. Instead, it seeks a mutually supportive interaction. Research at the functional (contextual) level, for example, can provide knowledge about the environmental determinants of behavior, which can also be used to drive mental research and/or to constrain mental theorizing. So long as each approach remains committed to its form of explanation, knowledge gained at one level can be used to advance progress at the other (De Houwer, 2011). This metatheoretical framework has yielded benefits in several areas of research (for a recent review see Hughes, De Houwer, & Perugini, 2016), and there appears to be no reason not to extend it to clinical psychology and such issues as the differences among wings of behavioral and cognitive therapy (De Houwer, Barnes-Holmes, & Barnes-Holmes, 2016; see also chapter 7 of this volume).
The main goal of this chapter was to introduce the topic of philosophy of science as it applies to clinical and applied psychology. Philosophical assumptions silently shape and guide our scientific activity and therapeutic practice. “Assumptions or ‘world-views’ are like the place one stands. What one sees and does is greatly determined by the place from which one views. In this way, assumptions are neither true nor false, but rather provide different views of different landscapes” (Ciarrochi, Robb, & Godsell, 2005, p. 81). Appreciating the role of philosophical assumptions tempers and guides collegial interaction within the field and is an important context for research evaluation, communication, and collaboration. Philosophical assumptions make a difference, whether in the laboratory or the therapy room.
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