Table 1.
Concepts and definitions of an extended multi-domain approach to scientific knowledgea
| Basic concepts | Definitiona |
|---|---|
| Scientific knowledge | A fluid mix of framed evidence and expertise acquired by means of standardised methods of research following the principles of commensurability (definitions of units of analysis that can be compared like-with-like), transparency for corroboration (including replicability and falsifiability) and transferability (including generalisability to broader contexts) |
| Evidence | The part of scientific knowledge based on contextualised information from facts and data, and which is analysed using quantitative approaches alone or combined with qualitative methods to generate inferences using mainly deductive reasoning, but also non-deductive logical reasoning (induction and abduction) |
| Expertise | The part of scientific knowledge based on expert know-how, understanding, experience and insight and on the perceived experience of a phenomenon. Experiential knowledge is here considered part of this category together with professional (expert) knowledge |
| Stages of scientific knowledge | |
| Discovery | Generation of new and relevant scientific evidence mainly using experimental approaches and deductive inference. Discovery can also be generated by consilience using inductive inference |
| Corroboration | Justification of the new scientific evidence by determining the degree of confirmation given the acceptability of experimental and observational data using logical induction. It requires transparency of prior information and uses quantitative techniques for ordering available evidence (e.g., meta-analysis), and qualitative techniques for reaching expert consensus (inter-subjectivity) |
| Implementation | Factual application of corroborated scientific knowledge to real life practice and policy and to controversial cases. Under conditions of uncertainty and non-monotonicity it requires expert knowledge and incorporates abduction and means-end inferences logical reasoning in the decision-making process |
| Types of logical reasoning | |
| Inference | Process of deriving logical conclusions from premises known or assumed to be true. |
| Deductive | Inferences from general instances to a specific conclusion. Is the main necessary inference, i.e. the certainty of the explanation can be derived from the certainty of the premises |
| Inductive | Inferences from specific instances to general conclusion or explanation. General statements are made based on specific observations |
| Abductive | Inference to the best explanation. It needs a prior knowledge-base to select the best or the most plausible explanation |
| Means-end inferences | Relates fundamental norms to the means to achieve a pre-determined end. This requires experts to decide which is the best or optimal mean from a set of alternatives to achieve the final goal |
| Domains of scientific knowledge | |
| Experimental evidence | Information acquired conducting an experiment to test a formal hypothesis using deductive reasoning (e.g., Randomised control trials) |
| Observational evidence | Information acquired by the standard recording of phenomena under natural conditions and analysed mainly using inductive reasoning (e.g., cohort studies, surveys). Ecological evidence refers to observations of the phenomenon gathered in a clearly defined area and environment |
| Contextual evidence and knowledge | Context refers to the totality of circumstances that comprise the milieu of a given phenomenon. In health care it includes all sources of evidence of the local system: geography, social and demographic factors, other environmental factors, service availability, capacity, use and costs. It also includes legislation and expertise on the milieu (e.g., the historical account of the current state of the art) |
| Expert knowledge | A set of formalised know-how, understanding, experience and insight in a defined area of knowledge which is informed, contextualised, stable, consistent and connected. It is elicited using qualitative approaches alone or combined with quantitative methods to generate means-end inferences and non-inferential knowledge to complement evidence |
| Experiential knowledge | The knowledge and understanding of the health condition, intervention and context derived from exposure as a patient, consumer or carer |
| New types of scientific research relevant for guideline development | |
| Framing of scientific knowledge (FSK) | A group of studies of ‘expert knowledge’ specifically aimed at generating formal scientific frames. FSK studies contribute to the formulation of research questions, to understand and to represent complex phenomena and to guide decision making under conditions of uncertainty and insufficient evidence. FSK studies generate formal scientific frames that could be used to analyse and to interpret complexity in health sciences, particularly in public and health systems research. FSK includes scientific declarations and charts, conceptual maps, classifications and recommendations of clinical guidelines |