Novice Thinker
Other types of clinical reasoning
Other types of reasoning to consider are narrative, probabilistic, and dialectical.
Narrative Reasoning
Narrative reasoning is an inductive cognitive strategy of telling and interpreting stories to inform client-centered clinical practice. It is the process of understanding clients’ experiences with illness within the biosocial context of their lives, including beliefs, values, and culture.1-4 Experts use narrative reasoning to form a multidimensional knowledge base, link assessments to function, demonstrate a caring attitude, and consider clients as individuals with unique life experiences.5-8 For example, in healthcare, some have suggested the simplification of ‘what it means to the client’ as the framework of this type of reasoning.
Probabilistic
Probabilistic reasoning calculates the probability that an event occurs based on probabilities of evidence related to the event.9 It is a form of knowledge representation in which the concept of probability indicates the degree of uncertainty in knowledge. However, in artificial intelligence, probabilistic models examine data using statistical codes.10
This form of reasoning is referred to as Bayesian reasoning. The Bayesian interpretation of probability extends propositional logic that enables reasoning with hypotheses, that is, propositions whose truth or falsity is unknown. A Bayesian probabilist specifies a prior probability and then updates it to a posterior probability in light of relevant data.11
Dialectical Reasoning
Dialectical reasoning is the process of examining an issue using cautious steps. Thus, this type of reasoning is often referred to as the utilization of a combination of the previously described types of reasoning.
References
1. Schell BA, Cervero RM. Clinical reasoning in occupational therapy: an integrative review. Am J Occup Ther. Jul 1993;47(7):605-10. doi:10.5014/ajot.47.7.605
2. Heneghan NR, Lokhaug SM, Tyros I, Longvastøl S, Rushton A. Clinical reasoning framework for thoracic spine exercise prescription in sport: a systematic review and narrative synthesis. BMJ Open Sport Exerc Med. 2020;6(1):e000713.
3. Houlihan S. Dual-process models of health-related behavior and cognition: a review of theory. Public Health. Mar 2018;156:52-59. doi:10.1016/j.puhe.2017.11.002
4. Nesbit KC, Randall, K.E., Hamilton, T.B. The development of narrative reasoning: student physical therapists’ perceptions of patient stories. Internet Journal of Allied Health Sciences and Practice. 2016;14(2)
5. Jensen GM, Gwyer J, Shepard KF. Expert practice in physical therapy. Phys Ther. Jan 2000;80(1):28-43; discussion 44-52.
6. Jensen GM, Shepard KF, Gwyer J, Hack LM. Attribute dimensions that distinguish master and novice physical therapy clinicians in orthopedic settings. Phys Ther. Oct 1992;72(10):711-22.
7. Jensen GM, Nordstrom T, Segal RL, McCallum C, Graham C, Greenfield B. Education Research in Physical Therapy: Visions of the Possible. Phys Ther. Jun 16 2016;doi:10.2522/ptj.20160159
8. Atkinson HL, Nixon-Cave K. A tool for clinical reasoning and reflection using the international classification of functioning, disability and health (ICF) framework and patient management model. Phys Ther. Mar 2011;91(3):416-30. doi:10.2522/ptj.20090226
9. Yang X. Data mining techniques. In: Yang X, ed. Introduction to Algorithms for Data Mining and Machine Learning. Elsevier; 2019.
10. Jeevanandam N. AI concepts for beginners: The importance of probabilistic reasoning in AI. Accessed December 28, 2022. https://indiaai.gov.in/article/the-importance-of-probabilistic-reasoning-in-ai
11. Howson C. The logic of Bayesian probability. In: Corfield D, Williamson, J., ed. Foundations of Bayesianism. Kluwer; 2001:137-1159.