Evidence map›Paper›PMID 32116854›Full record

ArticleFrontiers in psychiatry2020

Modeling Learning Patterns to Predict Placebo Analgesic Effects in Healthy and Chronic Orofacial Pain Participants.

Yang Wang, Christina Tricou, Nandini Raghuraman, Titilola Akintola, Nathaniel R Haycock, Maxie Blasini, Jane Phillips, Shijun Zhu, Luana Colloca

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Placebo and nocebo effect in pain.Handbook of clinical neurology · 2025
    Review
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Yang WangDepartment of Pain and Translational Symptom Science, School of Nursing, University of Maryland, Baltimore, MD, United States.
Christina TricouDepartment of Neural and Pain Sciences, School of Dentistry, University of Maryland, Baltimore, MD, United States.
Nandini RaghuramanDepartment of Pain and Translational Symptom Science, School of Nursing, University of Maryland, Baltimore, MD, United States.
Titilola AkintolaDepartment of Pain and Translational Symptom Science, School of Nursing, University of Maryland, Baltimore, MD, United States.
Nathaniel R HaycockDepartment of Pain and Translational Symptom Science, School of Nursing, University of Maryland, Baltimore, MD, United States.
Maxie BlasiniDepartment of Pain and Translational Symptom Science, School of Nursing, University of Maryland, Baltimore, MD, United States.
Jane PhillipsDepartment of Neural and Pain Sciences, School of Dentistry, University of Maryland, Baltimore, MD, United States.
Shijun ZhuDepartment of Organizational Systems and Adult Health, School of Nursing, University of Maryland, Baltimore, MD, United States.
Luana CollocaDepartment of Pain and Translational Symptom Science, School of Nursing, University of Maryland, Baltimore, MD, United States.
University of Maryland, Baltimore · US

Funding

Chronic orofacial pain: genetics, cognitive-emotional factors, and endogenous modulatory systemsR01DE025946 · NIDCR · UNIVERSITY OF MARYLAND BALTIMORE · PI COLLOCA, LUANA · 2016 to 2019
$2.1M
NIDCR NIH HHS R01 DE025946
6 · The paper itself

Abstract

Successfully 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.

Indexed as

conditioningexpectationlatent class analysispaintemporomandibular disorder

Identifiers

PMID32116854
PMCPMC7029355
OpenAlexW3006270633

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.