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Subjective and Objective Probability

In this chapter, we revisit some topics previously discussed in the insightful book by Kazem Sadegh-Zadeh, which tackles the problem of the logic of medical language. We adapt their content to our clinical case of Mary Poppins, aiming to keep our understanding more relevant to dental contexts.

Events that are both random and subjectively uncertain are considered probable; therefore, causality and uncertainty are approached as qualitative, comparative, or quantitative probabilities.

To clarify this concept, let's use the example of Mary Poppins. A doctor, after hearing her symptoms, could state that:

Mary Poppins is probably suffering from TMDs (qualitative term). Mary Poppins is more likely to have TMDs than neuropathic OP (comparative term: the number of diagnosed cases of TMDs vs. neuropathic OP). The probability that Mary Poppins has TMDs is 0.15 (quantitative term, relative to the population).

Subjective Probability

In contexts of human subjective uncertainty, probabilistic, qualitative, comparative, and/or quantitative data can be interpreted by clinicians as measures of subjective uncertainty, to make 'states of conviction' numerically representable.

For instance, stating "the probability that Mary Poppins is affected by TMDs is 0.15 of the cases" is akin to saying "with a 15% degree of belief, I think that Mary Poppins is affected by TMDs"; indicating that the degree of conviction corresponds to the degree of subjective probability.

Objective Probability

Conversely, events and random processes cannot be accurately described by deterministic processes in the form 'if A then B'. Statistics are utilized to quantify the frequency of the association between A and B, representing their relationship as a degree of probability, which introduces the concept of objective probability.

Amid the increasing acknowledgment of the role of probabilization of uncertainty and randomness in medicine since the eighteenth century, the term "probability" has become an integral part of medical language, methodology, and epistemology. Unfortunately, the distinction between subjective and objective probability is not always clearly made in medicine, as is the case in other disciplines too. Nevertheless, the vital contribution of probability theory in medicine, especially in concepts of probability in etiology, epidemiology, diagnostics, and therapy, lies in its aid in understanding and representing biological causality.

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Subjective and objective probability

In this chapter, some topics already treated in the fantastic book by Kazem Sadegh-Zadeh, who tackles the problem of the logic of medical language, are taken up again and we reshape their content by referring them to our clinical case of Mary Poppins, to keep our understanding closer to dental contexts.

Random and subjectively uncertain events are said to be probable; consequently, casuality and uncertainty are treated as qualitative, comparative or quantitative probabilities.

To clarify this concept, let us go back to the example of Mary Poppins. A doctor, having heard her symptoms will be able to say that:

1. Mary Poppins is probably suffering from TMDs (qualitative term).
2. Mary Poppins is more likely to have TMDs than neuropathic OP (comparative term: number of diagnosed cases of TMDs versus _nOP.
3. The probability that Mary Poppins has TMDs is 0.15 (quantitative term, relative to the population).

Subjective probability

In a context of human subjective uncertainty, the probabilistic, qualitative, comparative and/or quantitative data can be interpreted as a measure of subjective uncertainty by the clinician, in order to make the 'states of conviction' numerically representable.

For example, saying that "the probability that Mary Poppins is affected by TMDs is 0.15 of the cases" is the same as saying "in the measure of 15%, I believe that Mary Poppins is affected by TMDs"; which means that the degree of conviction is the degree of subjective probability.

Objective probability

On the other hand, events and random processes cannot be described by deterministic processes in the form 'if A then B'. Statistics are used to quantify the frequency of association between A and B and to represent the relationships between them as a degree of probability that introduces the degree of objective probability.

In the wake of the growing probabilization of uncertainty and randomness in medicine since the eighteenth century, the term "probability" has become a respected element of medical language, methodology and epistemology. Unfortunately, the two types of probability, the subjective probability and the objective one, are not accurately differentiated in medicine, and the same happens in other disciplines too. The fundamental fact remains that the most important meaning that probability theory has generated in medicine, particularly in the concepts of probability in aetiology, epidemiology, diagnostics and therapy, is its contribution to our understanding and representation of biological casuality.