| Literature DB >> 35369173 |
Giacomo Rossettini1,2, Andrea Colombi1, Elisa Carlino3, Mattia Manoni1, Mattia Mirandola2, Andrea Polli4,5,6, Eleonora Maria Camerone1,7, Marco Testa1.
Abstract
This Perspective adapts the ViolEx Model, a framework validated in several clinical conditions, to better understand the role of expectations in the recovery and/or maintenance of musculoskeletal (MSK) pain. Here, particular attention is given to the condition in which dysfunctional expectations are maintained despite no longer being supported by confirmatory evidence (i.e., belief-lifting the arm leads to permanent tendon damage; evidence-after the patient lifts the arm no tendon damage occurs). While the ViolEx Model suggests that cognitive immunization strategies are responsible for the maintenance of dysfunctional expectations, we suggest that such phenomenon can also be understood from a Bayesian Brain perspective, according to which the level of precision of the priors (i.e., expectations) is the determinant factor accounting for the extent of priors' updating (i.e., we merge the two frameworks, suggesting that highly precise prior can lead to cognitive immunization responses). Importantly, this Perspective translates the theory behind these two frameworks into clinical suggestions. Precisely, it is argued that different strategies should be implemented when treating MSK pain patients, depending on the nature of their expectations (i.e., positive or negative and the level of their precision).Entities:
Keywords: contextual factors; expectation; musculoskeletal; nocebo effects; pain; physiotherapy; placebo effects; predictive brain
Year: 2022 PMID: 35369173 PMCID: PMC8966654 DOI: 10.3389/fpsyg.2022.789377
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
Figure 1The ViolEx Model and the Bayesian Brain: from theory to clinical practice in musculoskeletal (MSK) pain. The ViolEx Model (A) and the Bayesian brain (B,C). Image (A) is a schematization of the ViolEx Model showing different outcomes depending on whether the violation of expectations is followed by immunization or change, resulting in either expectations maintenance or expectations updating, respectively. Image (B) is an example in which a prior with a high level of certainty is considered reliable and therefore undergoes minimal updating, while the interpretation of the sensory data is shifted toward the prior, resulting in a biased percept. Image (C) is an example in which a prior with a low level of certainty is updated to better fit sensory data, resulting in a posterior which is a better proxy of the sensory information. Examples of clinical scenarios (D–F). Image (D) shows a typical clinical situation in which the clinician asks the patient with MSK pain to perform a basic exercise (lift the arm), while the patient is reluctant to do it due to their negative expectations (i.e., pain/injury). The patient finally agrees and lifts the arm, without facing negative consequences. Such situation may result in two different outcomes: in (E) the positive experience associated with the exercise leads to the violation of the patient’s negative expectation with an update (low prior); whereas in (F) the positive experience associated with the exercise is not sufficient to violate the patient’s negative expectation, thus maintaining the previous experience (high prior).
Figure 2A clinical framework to assess and address patients’ expectations in musculoskeletal pain. The figure depicts the three typical scenarios that can occur in clinical practice. Green block: the patient shows positive expectations toward the rehabilitation process, and the clinician can reinforce them by providing verbal suggestions and confirming such expectations with the recommended evidence-based treatments; Yellow block: if negative expectations are detected during the initial assessment, but they have low precision, the clinician can optimize them through education and reassurance and subsequently try to violate such expectations by exposing patients to experience (using manual therapy, exercise, virtual reality, or a combination of them); and Red block: if high-precision expectations are detected, we suggest starting by exposing patients to experiences that could challenge patients’ expectations, and if this outcome is achieved, it can be reinforced through verbal suggestions (education or reassurance).