Evidence map›Paper›PMID 29557930›Full record

ArticlePain2018

Temporal dynamics of pain: an application of regime-switching models to ecological momentary assessments in patients with rheumatic diseases.

Stefan Schneider, Doerte U Junghaenel, Masakatsu Ono, Arthur A Stone

Abstract read
In one paragraph

Article in Pain, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Review
  6. Article
  7. Article
  8. Article
  9. Automatic detection of pain using machine learning.Frontiers in pain research (Lausanne, Switzerland) · 2022
    Article
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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

4 authors.

Stefan SchneiderDornsife Center for Self-Report Science, University of Southern California, Los Angeles, CA, USA.
Doerte U JunghaenelDornsife Center for Self-Report Science, University of Southern California, Los Angeles, CA, USA.
Masakatsu OnoDornsife Center for Self-Report Science, University of Southern California, Los Angeles, CA, USA.
Arthur A StoneDornsife Center for Self-Report Science, University of Southern California, Los Angeles, CA, USA.

Funding

UTILITY OF MOMENTARY VERSUS RECALLED SELF REPORTSR01CA085819 · NCI · STATE UNIVERSITY NEW YORK STONY BROOK · PI STONE, ARTHUR A. · 2000 to 2004
$2.2M
Innovative pain outcomes derived from patients real-time pain reportsR01AR066200 · NIAMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SCHNEIDER, STEFAN, STONE, ARTHUR A · 2015 to 2018
$1.8M
NCI NIH HHS R01 CA085819NIAMS NIH HHS R01 AR066200
6 · The paper itself

Abstract

Advances in pain measurement using ecological momentary assessments offer novel opportunities for understanding the temporal dynamics of pain. This study examined whether regime-switching models, which capture processes characterized by recurrent shifts between different states, provide clinically relevant information for characterizing individuals based on their temporal pain patterns. Patients with rheumatic diseases (N = 116) provided 7 to 8 momentary pain ratings per day for 2 weekly periods, separated by 3 months. Regime-switching models extracted measures of Average pain (mean level over time), Amplitude (magnitude of shifts in pain levels), Persistence (average duration of pain states), and Dominance (relative duration of higher vs lower pain states) for each patient and assessment period. After controlling for Average pain, the Persistence of pain states uniquely predicted emotional functioning measures, whereas the Dominance of higher pain uniquely predicted physical functioning and pain interference. Longitudinal analyses of changes over the 3 months largely replicated cross-sectional results. Furthermore, patients' retrospective judgments of their pain were uniquely predicted by Amplitude and Dominance of higher pain states, and global impressions of change over the 3 months were predicted by changes on Dominance, controlling for Average pain levels. The results suggest that regime-switching models can usefully capture temporal dynamics of pain and can contribute to an improved measurement of patients' pain intensity.

Indexed as

Activities of Daily LivingAdultAnxietyCross-Sectional StudiesDepressionEcological Momentary AssessmentFemaleHealth SurveysHumansLongitudinal StudiesMalePainPain MeasurementRheumatic Diseases

Identifiers

PMID29557930
PMCPMC6008214

What OpenQuestion holds

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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.