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dc.contributor.authorWang, Y.
dc.contributor.authorTricou, C.
dc.contributor.authorRaghuraman, N.
dc.contributor.authorAkintola, T.
dc.contributor.authorHaycock, N.R.
dc.contributor.authorBlasini, M.
dc.contributor.authorPhillips, J.
dc.contributor.authorZhu, S.
dc.contributor.authorColloca, L.
dc.date.accessioned2020-03-23T15:54:14Z
dc.date.available2020-03-23T15:54:14Z
dc.date.issued2020
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85081098962&doi=10.3389%2ffpsyt.2020.00039&partnerID=40&md5=cecc60bd8c48a1a30700bab6fb0112bb
dc.identifier.urihttp://hdl.handle.net/10713/12316
dc.description.abstractSuccessfully predicting the susceptibility of individuals to placebo analgesics will aid in developing more effective pain medication and therapies, as well as aiding potential future clinical use of placebos. In pursuit of this goal, we analyzed healthy and chronic pain patients' patterns of responsiveness during conditioning rounds and their links to conditioned placebo analgesia and the mediating effect of expectation on those responses. We recruited 579 participants (380 healthy, 199 with temporomandibular disorder [TMD]) to participate in a laboratory placebo experiment. Individual pain sensitivity dictated the temperatures used for high- and low-pain stimuli, paired with red or green screens, respectively, and participants were told there would be an analgesic intervention paired with the green screens. Over two conditioning sessions and one testing session, participants rated the painfulness of each stimulus on a visual analogue scale from 0 to 100. During the testing phase, the same temperature was used for both red and green screens to assess responses to the placebo effect, which was defined as the difference between the average of the high-pain-cue stimuli and low-pain-cue stimuli. Delta scores, defined as each low-pain rating subtracted from its corresponding high-pain rating, served as a means of modeling patterns of conditioning strength and placebo responsiveness. Latent class analysis (LCA) was then conducted to classify the participants based on the trajectories of the delta values during the conditioning rounds. Classes characterized by persistently greater or increasing delta scores during conditioning displayed greater placebo analgesia during testing than those with persistently lower or decreasing delta scores. Furthermore, the identified groups' expectation of pain relief acted as a mediator for individual placebo analgesic effects. This study is the first to use LCA to discern the relationship between patterns of learning and the resultant placebo analgesia in chronic pain patients. In clinical settings, this knowledge can be used to enhance clinical pain outcomes, as chronic pain patients with greater prior experiences of pain reduction may benefit more from placebo analgesia. Copyright The Authors.en_US
dc.description.sponsorshipNational Institute of Dental and Craniofacial Research, NIDCR; NIH NIDCRen_US
dc.description.urihttps://doi.org/10.3389/fpsyt.2020.00039en_US
dc.language.isoen_USen_US
dc.publisherFrontiers Media S.A.en_US
dc.relation.ispartofFrontiers in Psychiatry
dc.subjectconditioningen_US
dc.subjectexpectationen_US
dc.subjectlatent class analysisen_US
dc.subjectpainen_US
dc.subjecttemporomandibular disorderen_US
dc.titleModeling Learning Patterns to Predict Placebo Analgesic Effects in Healthy and Chronic Orofacial Pain Participantsen_US
dc.typeArticleen_US
dc.identifier.doi10.3389/fpsyt.2020.00039


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