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Justin Thomas, EBHC DPhil Candidate

I am currently studying my DPhil in Evidence Based Healthcare (EBHC) through Oxford’s Centre for Evidence Based Medicine. My research focuses on understanding how formal rules interact with informal rules to affect how a complex system (an airport healthcare service) is organised and performs over time. [1] My project is a mixed-methods study; it requires that the collected qualitative and quantitative data be integrated to provide a more comprehensive answer to the research question. Whilst learning about “mixing” the data, I was introduced to the concept of data characteristics or the nature of data. I began to explore philosophy and specifically how philosophy affects the research process. This led me to exploring the relationship between reality, knowledge and how research is used to produce knowledge.

In this blog, I share what I have learnt about the philosophical implications that reality theories (ontologies) and knowledge theories (epistemologies) have for the research process, and it’s consequences for the quality of knowledge being produced. I will argue for the inclusion of knowledge justification as an element in critically appraising the quality of research. I begin with an overview of the differences between information and knowledge and how this is relevant to the research context, both generally and within EBHC. I then discuss knowledge justification within the context of answering research questions and closing knowledge gaps within health sciences research.

Information or Knowledge, that is the question?

A core purpose of research is to produce new knowledge that provides a new understanding of the world. This knowledge can be integrated, using an EBHC approach, with wider expertise, values and judgement to improve healthcare delivery and decision making (1-5). Indeed, evidence, values, and judgement all represent different forms of knowledge. Petty (6), et al, highlight that decision making within healthcare delivery can use at least 28 different types of knowledge. Shaw (5), et al, have argued for expansion of the evidence base to provide a more complete knowledge base to inform healthcare delivery.

Information can be described as “processed data or raw facts that have been packaged into a usable form” (7). Within research, information is generated after data have been collected and analysed into results; e.g., statistics, graphs, or thematic codes summarising the raw data. Knowledge can be understood as “actionable information that has been learnt through application, observation or experience” (7-12). Within research, knowledge is the product of interpreting the results; e.g., what was learned from the results or how do the results improve our understanding of the research topic and, by extension, reality.

The study of reality is ontology. Research paradigms each have their own criteria for what qualifies as knowledge which is based on how that paradigm assumes reality works. Each ontology has a corresponding epistemology that provides a theory of knowledge describing beliefs about the nature and extent of that reality (9, 11, 12). Epistemology is concerned with describing the nature and extent of what is knowledge and how should knowledge be justified (8, 9, 11, 12). [2]

A research project’s methodology provides the ontological and epistemological basis from which the researcher will build the criteria for what is the project’s contextual knowledge. This in turn justifies the methods that will produce the data/results. The results of a research project form the foundation from which the knowledge is developed (6, 8, 13). The data being collected should be internally consistent with the type of information required to build the type of knowledge that answers the research question.

In research, raw data is collected using methods which have been justified by the methodology. The raw data is analysed and transformed into information using techniques which have been justified by the methodology. The information is interpreted by the researcher and transformed into knowledge through applying the criteria from the project’s epistemology. The epistemology justifies what type of knowledge is required to answer the research question.

 

Carter and Little (8) describe the relationship between epistemology, methodology, methods and knowledge creation in Figure 1.

 Epistemology.jpg

 

Figure 1: The Relationship between epistemology, methodology, methods and knowledge creation. (8)

Justifying Knowledge to close the Research Gap

I’ve learnt that the first step in developing a research project is to identify a research gap. Then a researchable question can be developed that, when answered, will close that gap. The research gap is a knowledge gap.

There should then be internal consistency between the assumptions held by the project’s ontology and epistemology and how the research question is framed. The methodology is then the vehicle that applies those assumptions to the research process and informs the selection of methods.

Within EBHC, critical appraisal can disproportionately emphasise justifying methods over justifying knowledge in the evaluation of quality. [3] It is commonly assumed that knowledge production is a forgone conclusion of the research process. Methods are evaluated and if biases are determined to have been kept low, results are deemed to be good quality. This process assumes that the results qualify as knowledge. However, this assumption may be incorrect as the results, characteristically, represent information and not knowledge.

Knowledge justification through applying epistemology adds a deeper, more fundamental dimension to critical appraisal and quality analysis. It functions comparably to justifying methods, but answers the questions: 

  1. Does the information produced by the end of the research process qualify as knowledge?
  2. Does that knowledge have the correct internal characteristics to qualify as the type of knowledge that is required to answer the research question?

Closing a knowledge gap implies that a specific type of knowledge is required to do so. Methodologies which are explicitly informed through applying epistemology provides a systematic approach to evaluating not only methods but also the actual knowledge being produced. It provides a framework that helps to remove bias during the interpretation phase where results are being converted from information into knowledge.

The practice of EBHC can be improved through developing skills in justifying both methods and, crucially, knowledge. As the evidence base expands to include different research designs, evaluating different types of knowledge may become a crucial skillset for both conducting and appraising research. A piece of research may fail to produce knowledge if it only produced information or produced knowledge that was not the type required to answer the question.

A failure to interpret the results to describe what was learnt is a failure to convert information into knowledge, thus, the research would have failed in its primary task of “producing new knowledge”. The research process has then either produced an incorrect answer or an incomplete one. This will have implications for the quality of decision making being informed by that research.

Further research, engagement and discussion on the topic is needed to better understand the role of knowledge justification in EBHC and health sciences research. Comments and engagement from readers are welcomed.

Justin is a Health Manager and Paramedic with additional expertise in international public health, port health and travel medicine. He holds a Bachelors in Emergency Medical Care from the University of Johannesburg; two Masters degrees from the University of New South Wales (Australia), a Masters in Health Management and a Masters in International Public Health, and is currently a DPhil student on the University of Oxford EBHC programme.

Bibliography:

 

1.       Djulbegovic B, Guyatt GH. Progress in evidence-based medicine: a quarter century on. The Lancet. 2017;390(10092):415-23.

2.       Heneghan C, Mahtani KR, Goldacre B, Godlee F, Macdonald H, Jarvies D. Evidence Based Medicine Manifesto For Better Healthcare: A Response To Systematic Bias, Wastage, Error And Fraud In Research Underpinning Patient Care. Evidence Based Medicine. 2017;22(4):120 - 2.

3.       Greenhalgh T, Howick J, Maskrey N. Evidence Based Medicine: A Movement In Crisis? BMJ. 2014;348:g3725.

4.       Sackett DL, Rosenberg WM, Gray JM, Haynes RB. Evidence Based Medicine: What It Is And What It Isn't - It's About Integrating Individual Clinical Expertise And The Best External Evidence. BMJ. 1996;312:71 - 2.

5.       Shaw RL, Larkin M, Flowers P. Expanding The Evidence Within Evidence-Based Healthcare: Thinking About The Context, Acceptability And Feasibility Of Interventions. Evidence Based Medicine. 2014;19(6):201 - 3.

6.       Petty NJ, Thomson OP, Stew G. Ready For A Paradigm Shift? Part 1: Introducing The Philosophy Of Qualitative Research. Manual Therapy. 2012;17:267 - 74.

7.       Liew A. Understanding Data, Information, Knowledge And Their Inter-Relationships. Journal of Knowledge Management Practice. 2007;8(2):10.

8.       Carter SM, Little M. Justifying Knowledge, Justifying Method, Taking Action: Epistemologies, Methodologies, And Methods In Qualitative Research. Qualitative Health Research. 2007;17(10):1316 - 28.

9.       Truncellito DA. Epistemology. Internet Enyclopedia of Philosophy. USA2020. p. 18.

10.      Zins C. Conceptual Approaches for Defining Data, Information, and Knowledge. Journal of the American Society for Information Sciences & Technology. 2007;58(4):479 - 93.

11.      Moser PK. The Oxford Handbook of Epistemology. Oxford, England: Oxford University Press; 2002.

12.      Steup M, Ram N. Epistemology. In: Zalta EN, editor. Standford Encylopedia of Phillosophy. Fall 2020 Edition ed. USA: Metaphysics Research Lab, Stanford University; 2020. p. 45.

13.      Gilson L, editor. Health Policy and Systems Research: A Methodology Reader. Geneva, Switzerland: Alliance for Health Policy and Systems Research, World Health Organisation; 2012.

 



[1] A more detailed and context-specific description can be found here

[2] For more indepth reading, reference 7-12 provide a broader more in depth discussion.

[3] Example, none of the six critical appraisal tools, including the qualitative research appraisal tool, available on the CEBM website explicitly asks the reviewer to consider ontology or epistemology as part of the appraisal process. All six focus exclusively on the methods of the research to identify systematic bias introduced through research methods. This is helpful to evaluate bias in the raw data and results, but does not identify bias in the knowledge generated after interpretation. None of the six account for bias introduced through epistemic or ontologic criterion that is needed to evaluate for bias during the intepretation of the results to produce knowledge. However, the Joanna Briggs Institutes qualitative research appraisal tool does specifically account for philosophical assumptions.