What is pragmatism?
We suggest that many healthcare workers would identify as pragmatists. The everyday use of the term pragmatism implies a focus on the practical and achievable, rather than the theoretical or ideal [41]. This idea of valuing the applied over the theoretical is mirrored in the philosophy of Pragmatism.
Pragmatism emerged in the late 1800s in the work of Charles Pierce, William James, and John Dewey. At the center of pragmatism is a rejection of the ‘impossible question’ of philosophy, that of the nature of the mind’s relationship to reality [42]. Instead, pragmatists judge the value of knowledge (and our ways of knowing) by its context-dependent, extrinsic usefulness for addressing practical questions of daily life [43]. Perfect knowledge is not possible, nor required. For pragmatism, knowledge is only meaningful when coupled with action [38].
There are many similarities between the arguments of social complexity researchers and pragmatists. Below we explore key synergies (Box 2).
Contextualized research
A key feature of pragmatism is the contextualization of knowledge [44, 45]. As contexts change, so too do the criteria of usefulness for knowledge. Similarly, social complexity theory calls for the matching of research approach to context and level of environmental complexity [4, 9]. In complexity theory, these contexts could include different nested systems, and different time points [44]. Therefore, in order to maintain a coherent research agenda in a CAS, a unifying research question is required.
In our project, the response to the challenge of working within this particular CAS manifested through the emergent formulation of two deeply pragmatic research questions: How can we (the researchers) help to improve strategic decision-making for mental health services? What can we learn of value through this process? This allowed us, as the context changed, to maintain the same focus for the project, but change and expand the evaluation focus from the experiences of the SLG to include, for instance, adaptations of the researchers to the changing stakeholder needs. The same aims were addressed, but using different methods.
Continual learning
The contextualization of knowledge does not reject the translation of knowledge between contexts. While pragmatism does hold that knowledge is not completely generalizable, it also argues that imported knowledge can play a role in shaping observation and perception and in suggesting possible solutions to the current problem [42]. For implementation science, the merging of complexity theory’s deep focus on contextual interactions and emergent outcomes, coupled with pragmatism’s perspective on knowledge translation, provides a way of fostering collective implementation learning [16, 46], without bowing to the need for research generalizability.
For our project, this led us to re-define implementation success, not as a strict adherence to the project plan or the achievement of pre-determined outcomes (i.e., the publication of four simulation models and the use of these models to inform decisions), but by the perceived usefulness of the project to the stakeholders and the lessons learned. As Byrne commented: “The point about complexity is that it is useful – it helps us to understand the things we are trying to understand” ([18], p. 7). Indeed, what we learnt was that the simulation models themselves seemed not to be the main outcome of interest to the SLG; instead, it was the personal insights that members gained from the conceptual development discussions and our presentations of amalgamated patient data.
Research as social action
Another key pillar of pragmatism is the active and social nature of inquiry. Dewey argued that the primary function of research is to solve societal problems [38]. However, he also argues for flexibility in application, proposing “that policies and proposals for social action be treated as working hypotheses, not as programs to be rigidly adhered to and executed” ([47], pp. 151–2).
These sentiments are echoed in social complexity theory:
“Complexity/chaos offers the possibility of an engaged science not founded in pride, in the assertion of an absolute knowledge as the basis for social programs, but rather in a humility about the complexity of the world coupled with a hopeful belief in the potential of human beings for doing something about it.” ([18], p. 45).
Not only does pragmatism argue for a problem-solving approach to inquiry, but also to an action-based one. All modes of experience, including research, are treated as interventions [42]. Research success within a pragmatic epistemology is measured by consequences, whether they be predicted or emergent. This aligns with the holistic system view of complexity theory, where outcomes are not pre-determined, but emergent [36]. Thus, complexity theory provides a way of operationalizing the study of emergent consequences, while pragmatism provides the impetus for change by measuring research quality with respect to its impact on social change.
Valuing of different knowledge
The usefulness of knowledge metric also creates a democratization of scientific endeavor. Scientific knowledge is treated not as a qualitatively different form of knowledge, but simply as a more formalized version of everyday human inquiry [48]. Science therefore becomes a social pursuit, within anyone’s reach. This idea of intuitive inquiry aligns with a theme, advanced by many scholars advocating for complexity theory in healthcare, that social actors already have an intuitive sense of complexity, which can be refined by the framework of complexity theory [4, 9]. Social complexity theorists also argue for a natural fit between complexity approaches and participatory research, where participant and researcher frames of reference are treated as equally important to inquiry [20], failure is tolerated and expected [49], and innovation is allowed to emerge from any part of the system [9].
In our project, this led to a fundamental shift in the implementation evaluation from a focus purely on the participant experience, to one that included the experiences of the researchers. In the initial design of the evaluation, the CAS of interest was that of the SLG. Our evaluation was focused on understanding the decision-making mental models of these individuals, and how they negotiated shared group processes and behaviors based on these individual models. However, the organizational restructure of the SLG affected not only access to participants for evaluation data collection, but also affected the researchers’ approach to the simulation modeling development and implementation. As mentioned above, one way this manifested was as a change in engagement with members of the SLG. Researchers began using one-on-one interactions with engaged SLG members to develop new scenarios directly related to the SLG members’ portfolio. Therefore, the experiences and reflections of the researchers became pivotal in understanding the project’s implementation after the organizational restructure.
Both pragmatism and complexity theory also encourage a focus on the interactions of knowledge systems, and the study of how these intersections are negotiated [4, 44, 48]. For us, this manifested as multiple themes emerging from a grounded theory approach to the implementation evaluation, including participant-researcher communication (frequency, modality, content), understanding and expectations of the modeling methodology, and different outcome priorities between the researchers and participants. The case study approach of the evaluation, supported by interviews and unstructured observation, allowed these themes to emerge, but there remains a challenge for creating more targeted research designs and methods capable of capturing, measuring, and interpreting these interactive and emergent processes.
Support for mixed methods research
A key theme in the development of social complexity research is the call for mixed methods research [8, 34]. However, there is a risk of method choice being driven by the ‘what works’ maxim [50]. As one of the key epistemologies for mixed method research, pragmatism offers a more structured approach to mixed methods research [42]. Pragmatism calls for choices of research questions and methods to be driven by the social purpose of the research, not the other way around [42, 45, 51].
Another of the risks identified by complexity theorists is the pre-emptive labelling of a system as complex [40]; a pragmatic approach does not require such a priori assumptions. Rather, it allows for the flexible use of multiple methods to capture insights in a complex environment, which may later be interpreted using a range of frameworks. Therefore, our pluralism of evaluation methods (i.e., interviews, questionnaires, document analysis, observations) provides us with multiple perspectives to be explored and structured in different ways in order to ultimately build an understanding of the process of implementation.
Pragmatism also encourages reflection and experimentation, allowing for the evolution of interventions and evaluation in a similar fashion to a CAS [7, 42, 45]. Therefore, our shift in evaluation from the quantitative analysis of participant questionnaire responses to a grounded theory case study of research adaptation is not only consistent with complexity theory, but predicted by it, as a co-evolution of the researchers in context. Thus, rather than rejecting the reductionist approach of classic complexity theory [20], pragmatism allows for the contribution of both quantitative and qualitative methods in addressing the research question. It also allows for different definitions of complexity theory. Complexity theory can be both an ontology for quantitative approaches and a metaphor for qualitative approaches.