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...because epistemology evolves continually, even in medicine:
...because epistemology evolves continually, even in medicine:


'''P-value''': In medicine, for example, we rely on statistical inference to confirm experimental results, specifically the {{Tooltip|P-value|2=The p-value represents the probability that observed results are due to chance, assuming the null hypothesis <math> H_0 </math> is true. It should not be used as a binary criterion (e.g., <math> p < 0.05 </math>) for scientific decisions, as values near the threshold require additional verification, such as cross-validation. ''p-hacking'' (repeating tests to achieve significance) increases false positives. Rigorous experimental design and transparency about all tests conducted can mitigate this risk. Type I error increases with multiple tests: for <math> N </math> independent tests at threshold <math> \alpha </math>, the Family-Wise Error Rate (FWER) is <math> FWER = 1 - (1 - \alpha)^N </math>. Bonferroni correction divides the threshold by the number of tests, <math> p < \frac{\alpha}{N} </math>, but can increase false negatives. The False Discovery Rate (FDR) by Benjamini-Hochberg is less conservative, allowing more true discoveries with an acceptable proportion of false positives. The Bayesian approach uses prior knowledge to balance prior and data with a posterior distribution, offering a valid alternative to the p-value. To combine p-values from multiple studies, meta-analysis uses methods like Fisher's: <math> \chi^2 = -2 \sum \ln(p_i) </math>. In summary, the p-value remains useful when contextualized and integrated with other measures, such as confidence intervals and Bayesian approaches.}}, a "significance test" that assesses data validity. Yet, even this entrenched concept is now being challenged. A recent study highlighted a campaign in the journal "Nature" against the use of the P-value.<ref name=":1" /> Signed by over 800 scientists, this campaign marks a "silent revolution" in statistical inference, encouraging a reflective and modest approach to significance.<ref name=":2" /><ref name=":3" /><ref name=":4" /> The American Statistical Association contributed to this discussion by releasing a special issue of "The American Statistician Association" titled "Statistical Inference in the 21st Century: A World Beyond p < 0.05." It offers new ways to express research significance and embraces uncertainty.<ref name="wasser" />
'''P-value''': In medicine, for example, we rely on statistical inference to confirm experimental results, specifically the {{Tooltip|P-value|2=The p-value represents the probability that observed results are due to chance, assuming the null hypothesis <math> H_0 </math> is true. It should not be used as a binary criterion (e.g., <math> p < 0.05 </math>) for scientific decisions, as values near the threshold require additional verification, such as cross-validation. ''p-hacking'' (repeating tests to achieve significance) increases false positives. Rigorous experimental design and transparency about all tests conducted can mitigate this risk. Type I error increases with multiple tests: for <math> N </math> independent tests at threshold <math> \alpha </math>, the Family-Wise Error Rate (FWER) is <math> FWER = 1 - (1 - \alpha)^N </math>. Bonferroni correction divides the threshold by the number of tests, <math> p < \frac{\alpha}{N} </math>, but can increase false negatives. The False Discovery Rate (FDR) by Benjamini-Hochberg is less conservative, allowing more true discoveries with an acceptable proportion of false positives. The Bayesian approach uses prior knowledge to balance prior and data with a posterior distribution, offering a valid alternative to the p-value. To combine p-values from multiple studies, meta-analysis uses methods like Fisher's: <math> \chi^2 = -2 \sum \ln(p_i) </math>. In summary, the p-value remains useful when contextualized and integrated with other measures, such as confidence intervals and Bayesian approaches.}}, a "significance test" that assesses data validity. Yet, even this entrenched concept is now being challenged. A recent study highlighted a campaign in the journal "Nature" against the use of the P-value.<ref name=":1">{{cita libro  
{|
|-
|
*'''P-value''': In medicine, for example, we rely on statistical inference to confirm experimental results, specifically the {{Tooltip|P-value|2=The p-value represents the probability that observed results are due to chance, assuming the null hypothesis <math> H_0 </math> is true. It should not be used as a binary criterion (e.g., <math> p < 0.05 </math>) for scientific decisions, as values near the threshold require additional verification, such as cross-validation. ''p-hacking'' (repeating tests to achieve significance) increases false positives. Rigorous experimental design and transparency about all tests conducted can mitigate this risk. Type I error increases with multiple tests: for <math> N </math> independent tests at threshold <math> \alpha </math>, the Family-Wise Error Rate (FWER) is <math> FWER = 1 - (1 - \alpha)^N </math>. Bonferroni correction divides the threshold by the number of tests, <math> p < \frac{\alpha}{N} </math>, but can increase false negatives. The False Discovery Rate (FDR) by Benjamini-Hochberg is less conservative, allowing more true discoveries with an acceptable proportion of false positives. The Bayesian approach uses prior knowledge to balance prior and data with a posterior distribution, offering a valid alternative to the p-value. To combine p-values from multiple studies, meta-analysis uses methods like Fisher's: <math> \chi^2 = -2 \sum \ln(p_i) </math>. In summary, the p-value remains useful when contextualized and integrated with other measures, such as confidence intervals and Bayesian approaches.}}, a "significance test" that assesses data validity. Yet, even this entrenched concept is now being challenged. A recent study highlighted a campaign in the journal "Nature" against the use of the P-value.<ref name=":1">{{cita libro  
  | autore = Amrhein V
  | autore = Amrhein V
  | autore2 = Greenland S
  | autore2 = Greenland S
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  | OCLC =  
  | OCLC =  
  }} 73, 1–19.</ref>
  }} 73, 1–19.</ref>
|-
|
*'''Interdisciplinarity''': Solving science-based problems increasingly demands interdisciplinary research (IDR), as underscored by the European Union’s Horizon 2020 project.<ref>European Union, ''[https://ec.europa.eu/programmes/horizon2020/en/h2020-section/societal-challenges Horizon 2020]''</ref> Yet IDR poses cognitive challenges, partly due to the dominant "Physical Paradigm of Science" that limits its recognition. The "Engineering Paradigm of Science" has been proposed as an alternative, focusing on technological tools and collaboration. Researchers need "metacognitive scaffolds"—tools to enhance interdisciplinary communication and knowledge construction.<ref name=":0">{{cita libro
| autore = Boon M
| autore2 = Van Baalen S
| titolo = Epistemology for interdisciplinary research - shifting philosophical paradigms of science
| url = https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383598/
| volume =
| opera = Eur J Philos Sci
| anno = 2019
| editore =
| città =
| ISBN =
| LCCN =
| DOI = 10.1007/s13194-018-0242-4
| OCLC =
}} 9(1):16.</ref><ref>{{cita libro
| autore = Boon M
| titolo = An engineering paradigm in the biomedical sciences: Knowledge as epistemic tool
| url = https://www.ncbi.nlm.nih.gov/pubmed/28389261
| volume =
| opera = Prog Biophys Mol Biol
| anno = 2017
| editore =
| città =
| ISBN =
| LCCN =
| DOI = 10.1016/j.pbiomolbio.2017.04.001
| OCLC =
}} Oct;129:25-39.</ref>
|}


'''Interdisciplinarity''': Solving science-based problems increasingly demands interdisciplinary research (IDR), as underscored by the European Union’s Horizon 2020 project.<ref /> Yet IDR poses cognitive challenges, partly due to the dominant "Physical Paradigm of Science" that limits its recognition. The "Engineering Paradigm of Science" has been proposed as an alternative, focusing on technological tools and collaboration. Researchers need "metacognitive scaffolds"—tools to enhance interdisciplinary communication and knowledge construction.<ref /><ref />
==Interdisciplinarity==
==Interdisciplinarity==
A superficial view might suggest a conflict between the disciplinarity of the "Physics Paradigm of Science" (which highlights anomalies) and the interdisciplinarity of the "Engineering Paradigm of Science" (focused on metacognitive scaffolds). However, these perspectives are not in conflict; they are complementary and drive "Paradigmatic Innovation" in science.
A superficial view might suggest a conflict between the disciplinarity of the "Physics Paradigm of Science" (which highlights anomalies) and the interdisciplinarity of the "Engineering Paradigm of Science" (focused on metacognitive scaffolds). However, these perspectives are not in conflict; they are complementary and drive "Paradigmatic Innovation" in science.

Revision as of 12:02, 25 October 2024

Introduction

 

Masticationpedia
Article by  Gianni Frisardi

 

Abstract: The masticatory system, encompassing teeth, occlusion, muscles, joints, and the central nervous system, is increasingly understood as a complex system rather than a simple biomechanical mechanism. This shift in perspective aligns with Thomas Kuhn's phases of paradigm shifts, where anomalies in traditional models trigger the search for new paradigms. In the context of Masticationpedia, a new interdisciplinary approach to diagnosing and treating malocclusion emerges, focusing on "Occlusal Dysmorphisms" rather than "malocclusion."

Recent advancements in electrophysiological testing, such as motor-evoked potentials and jaw reflexes, reveal functional symmetry in the masticatory system, even in patients with occlusal discrepancies. This finding challenges the traditional understanding of malocclusion, suggesting that neuromuscular dynamics play a crucial role in maintaining masticatory function. Consequently, interdisciplinary diagnostics that consider both occlusal and neuromuscular factors are necessary for accurate diagnosis and effective treatment.

This paradigm shift has implications for current rehabilitative therapies, including orthodontics and prosthetics, which have traditionally focused on achieving occlusal stability. However, considering the masticatory system as a complex system requires an integrative approach that incorporates both aesthetic and neurophysiological factors to prevent relapses and achieve long-term functional stability. The emerging field of OrthoNeuroGnathodontic treatments exemplifies this interdisciplinary approach, offering innovative strategies for addressing masticatory disorders.

By viewing the masticatory system through the lens of complexity science, the field of dentistry can expand its understanding of occlusal stability and dysfunction, ultimately leading to new treatment paradigms that enhance patient outcomes. This new model does not replace traditional treatments but seeks to enrich them with a broader interdisciplinary perspective, aligning with the evolving science of masticatory rehabilitation.

Ab ovo[1]

Before delving into the analysis of Masticationpedia, we must first introduce some preliminary considerations, particularly regarding two fundamental dimensions—social and scientific-clinical aspect—that characterize both the present era and the one immediately preceding it.

The phases of paradigm change according to Thomas Kuhn

Over the past century, technological and methodological innovations[2] have exponentially increased, especially in dentistry. These developments have significantly impacted decision-making, schools of thought, and fundamental principles, with the explicit goal of improving quality of life, as emphasized in the "Science of Exposure in the 21st Century".[3] However, this exponential growth hides conceptual ambiguities—or, practically speaking, "side effects"—that, though often underestimated, can challenge scientific certainties, making them more probabilistic.[4] These sensitive aspects of current social, scientific, and clinical reality, seemingly in conflict, will ultimately prove to be complementary by the end of this analysis. This evolution follows the concept of "Progress of Science," according to Kuhn’s interpretation of "Epistemology."

In his most famous work, Thomas Kuhn argues that science advances through distinct cycles reflecting its operational dynamics.[5][6] Kuhn posits that science is structured around paradigms and establishes a clear demarcation between science and pseudoscience based on the presence of a shared paradigm. The evolution of scientific progress is depicted as a continuous curve interrupted by discontinuities, represented by paradigm shifts.

In these periods of crisis, scientists act as problem solvers, seeking to resolve anomalies. These "scientific revolutions" occur when the existing paradigm can no longer interpret new anomalies, pushing the scientific community toward new paradigms that better align with observations.

Kuhn's phases in Dentistry

Thomas Kuhn identifies five distinct phases in the evolution of a scientific paradigm—a process crucial for Masticationpedia. However, to align with the project’s scope, we will focus on the three most significant phases, as indicated in the book’s index.

Phase 2, or Normal Science: In this phase, scientists solve problems to strengthen the correspondence between the paradigm and natural reality. This phase establishes the principles on which future research is based, and it produces most of the scientific literature. Here, "anomalies" arise—events that contradict the dominant paradigm.

Phase 4, or the Crisis of the Paradigm: During this phase, new paradigms emerge as the dominant one is rejected. Masticationpedia will address the crisis in masticatory rehabilitation by reviewing theories, axioms, and diagnostic criteria, leading to Phase 5.

Phase 5, or the Scientific Revolution: During this period, the scientific community debates which paradigm to adopt. The chosen paradigm might not be the "truest" but the one gaining the most support. In Masticationpedia, a new model in masticatory rehabilitation will be introduced, focusing on data-driven inferences rather than symptom-based models.

Kuhn’s concept gives priority to discipline-specific expertise, yet this contradicts the interdisciplinary nature of modern science. A detailed analysis of this discrepancy is therefore appropriate.


Epistemology

The black swan symbolizes one of the historical problems of epistemology: if all the swans we have seen so far are white, can we decide that all swans are white?
Black Swan (Cygnus atratus) RWD.jpg
Duck-Rabbit illusion.jpg
Kuhn used optical illusion to demonstrate how a paradigm shift can cause a person to see the same information in a completely different way.

Epistemology (from Greek ἐπιστήμη, epistēmē, meaning "certain knowledge" or "science", and λόγος, logos, "discourse") is the branch of philosophy that studies the necessary conditions for acquiring scientific knowledge and the methods through which it is achieved.[7] Specifically, it refers to the investigation of the foundations, validity, and limits of scientific knowledge. In English-speaking countries, the term "epistemology" is often synonymous with the theory of knowledge or gnoseology, which examines the study of knowledge in general.

The central problem of epistemology, today as in the times of Hume,[8][9] is the issue of verifiability. According to Hempel’s paradox, every example that does not contradict a theory confirms it, which is described as:

Let’s consider the statement: “If a person has TMDs, then they experience orofacial pain.” We can represent this in logic as , where: represents "The person has TMDs." represents "The person experiences orofacial pain." In this case, "If a person has TMDs, then they experience orofacial pain" is equivalent to saying “either the person does not have TMDs (), or they experience orofacial pain ()”. The formula is true in the following cases: If the person does not have TMDs (), the statement is true, regardless of orofacial pain. If the person has TMDs () and experiences orofacial pain (), the statement is true. The statement is false only if the person has TMDs () but does not experience orofacial pain (), contradicting the implication condition.

No theory can be definitively true; while there are finite experiments to confirm it, an infinite number could refute it.[10]

But it’s not all so obvious...

...because epistemology evolves continually, even in medicine:

P-value: In medicine, for example, we rely on statistical inference to confirm experimental results, specifically the P-valueThe p-value represents the probability that observed results are due to chance, assuming the null hypothesis is true. It should not be used as a binary criterion (e.g., ) for scientific decisions, as values near the threshold require additional verification, such as cross-validation. p-hacking (repeating tests to achieve significance) increases false positives. Rigorous experimental design and transparency about all tests conducted can mitigate this risk. Type I error increases with multiple tests: for independent tests at threshold , the Family-Wise Error Rate (FWER) is . Bonferroni correction divides the threshold by the number of tests, , but can increase false negatives. The False Discovery Rate (FDR) by Benjamini-Hochberg is less conservative, allowing more true discoveries with an acceptable proportion of false positives. The Bayesian approach uses prior knowledge to balance prior and data with a posterior distribution, offering a valid alternative to the p-value. To combine p-values from multiple studies, meta-analysis uses methods like Fisher's: . In summary, the p-value remains useful when contextualized and integrated with other measures, such as confidence intervals and Bayesian approaches., a "significance test" that assesses data validity. Yet, even this entrenched concept is now being challenged. A recent study highlighted a campaign in the journal "Nature" against the use of the P-value.[11] Signed by over 800 scientists, this campaign marks a "silent revolution" in statistical inference, encouraging a reflective and modest approach to significance.[12][13][14] The American Statistical Association contributed to this discussion by releasing a special issue of "The American Statistician Association" titled "Statistical Inference in the 21st Century: A World Beyond p < 0.05." It offers new ways to express research significance and embraces uncertainty.[15]

Interdisciplinarity: Solving science-based problems increasingly demands interdisciplinary research (IDR), as underscored by the European Union’s Horizon 2020 project.Cite error: The opening <ref> tag is malformed or has a bad name Yet IDR poses cognitive challenges, partly due to the dominant "Physical Paradigm of Science" that limits its recognition. The "Engineering Paradigm of Science" has been proposed as an alternative, focusing on technological tools and collaboration. Researchers need "metacognitive scaffolds"—tools to enhance interdisciplinary communication and knowledge construction.Cite error: The opening <ref> tag is malformed or has a bad nameCite error: The opening <ref> tag is malformed or has a bad name

Interdisciplinarity

A superficial view might suggest a conflict between the disciplinarity of the "Physics Paradigm of Science" (which highlights anomalies) and the interdisciplinarity of the "Engineering Paradigm of Science" (focused on metacognitive scaffolds). However, these perspectives are not in conflict; they are complementary and drive "Paradigmatic Innovation" in science.

It could be said that "Innovations" represent "Progresses of Science," as illustrated in the article "Scientific Bases of Dentistry" by Yegane Guven, which explores the impact of biological and digital revolutions on dentistry.[16] True scientific progress is not solely achieved through "Incremental Innovations" or "Radical Innovations" but through "Paradigmatic Innovations."

"Paradigmatic Innovations" represent a change in thinking that spreads through humanity, affecting society on many levels, from the Copernican revolution to the stochastic methods applied to biological phenomena.[17]

This epistemological context, which includes initiatives like the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) and Evidence-Based Medicine, aligns with Masticationpedia’s aim to highlight anomalies that stimulate changes in scientific thought, ultimately leading to "Paradigmatic Innovation."

Dental Malocclusion

"Malocclusion" derives from the Latin "malum," meaning "bad" or "wrong," and refers to improper closure of the teeth.[18] The notion of "closure" may seem intuitive, but "bad" requires careful consideration in a medical context.

A search for "Malocclusion" on PubMed yielded 33,309 articles,[19] reflecting a lack of consensus on the term. Smaglyuk and colleagues’ study underscores the importance of an interdisciplinary approach to diagnosing malocclusions.[20]

«Diagnosis, treatment strategies, and prevention of anomalies and dento-facial deformities should be approached by considering the organism as a whole. This is especially important in children, whose physical structure is still forming. The interconnectedness of various organs and systems is crucial for effective treatment planning.»

Another notable observation from PubMed queries on interdisciplinary malocclusion diagnostics is the drastic drop to only four articles.[21]

These findings suggest the emergence of phase 4 in Kuhn’s model, indicating a potential paradigmatic shift. Some prefer incremental innovations, while others favor a new path of "Paradigmatic Innovation."

What does "Malocclusion" mean?

In this clinical case of malocclusion, characterized by a unilateral posterior crossbite and anterior open bite, orthodontic appliances and possibly orthognathic surgery are recommended.[22] The crossbite requires concurrent treatment due to its functional relationship with the open bite.[23]

In this case, the patient refused treatment, insisting that their chewing function was fine. The dentist responded by explaining the long-term risks of leaving the malocclusion untreated, but respected the patient's decision to decline treatment.

The case illustrates the complexity of diagnosing malocclusion, which involves more than occlusal discrepancies. Specific electrophysiological tests, such as the motor-evoked potential and jaw reflex tests, can reveal functional symmetry in the masticatory system despite occlusal issues.

These electrophysiological results challenge conventional interpretations of malocclusion, highlighting the importance of interdisciplinary diagnostics that consider neuromuscular function as well as occlusal discrepancies.

Occlusal Dismorphisms and Not Malocclusion ......which, as we will see shortly, is an entirely different matter.

Conclusion

Before concluding, we must clarify that the masticatory system is a "Complex System"[24], not a simple biomechanical mechanism focused solely on dental occlusion. Occlusion is just one subset within a broader context that includes periodontal receptors, neuromuscular spindles, motor units, the central nervous system, and the temporomandibular joint. This interaction creates " Emergent BehaviorThe **masseter silent period** (MSP) is a relevant example of emergent behavior in masticatory neurophysiology. This reflex is triggered by sudden chin taps, leading to a brief cessation of electrical activity in the masseter muscle, and is closely related to the recruitment of motor units. During the MSP, there is a specific modulation of motor unit recruitment, regulated by the central nervous system, to respond to external stimuli. In the context of emergent behavior, this reflex is not limited to a single muscle but represents a coordinated response involving synergies among various neuronal centers and antagonist muscles. This integration stabilizes the mandible, adapting in real time to the force of the stimulus and producing an adaptive response. Mathematically, we can describe the probability of an emergent response as a function of the input variables that influence motor unit activation: where represents the non-linear interaction among incoming stimuli (such as the type and intensity of the chin tap) and the central integration processes of the trigeminal system. This model helps to understand how the MSP reflects an integrated and adaptive response that emerges from complex neurophysiological circuits rather than a single neural pathway.," or masticatory behavior.

Emergent behavior cannot be fully explained by analyzing a single subset; instead, the integrity of the entire system must be assessed. A notable intellectual movement addressing this challenge is Kazem Sadegh-Zadeh’s work, "Handbook of Analytic Philosophy of Medicine."[25]

The masticatory system's various subsets, such as teeth, occlusion, joints, and muscles, exhibit "Coherence" with the Central Trigeminal Nervous System, as shown in the electrophysiological tests. Therefore, "malocclusion" may not be the appropriate term; "Occlusal Dysmorphisms" would be more accurate.

«Viewing the masticatory system as a "Complex System" doesn’t deny existing rehabilitative therapies like prosthetics or orthodontics but instead aims to enrich them by considering a broader interdisciplinary perspective.»

This approach, exemplified in OrthoNeuroGnathodontic treatments, integrates aesthetic and neurophysiological aspects to achieve "Occlusal Stability" and prevent "Relapses."[26][27] While not replacing traditional treatments, this model seeks to expand medical knowledge and interdisciplinary practices in dentistry.

In the meantime, let us pause with a question from Linus Sapiens, our curious yellow figure on the left. He reminds us of the importance of remaining open to new perspectives in masticatory science.

Question 2.jpg

What do we mean by “Complex Systems” when we are talking about masticatory functions?


Bibliography & references
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