ArticlePain2018
Temporal dynamics of pain: an application of regime-switching models to ecological momentary assessments in patients with rheumatic diseases.
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.
What it found
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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.
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.
Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Little evidence for consistent initial elevation bias in self-reported momentary affect: A coordinated analysis of ecological momentary assessment studies.Psychological assessment · 2022Pooled it
- II. Indices of Pain Intensity Derived From Ecological Momentary Assessments and Their Relationships With Patient Functioning: An Individual Patient Data Meta-analysis.The journal of pain · 2021Pooled it
- III. Detecting Treatment Effects in Clinical Trials With Different Indices of Pain Intensity Derived From Ecological Momentary Assessment.The journal of pain · 2021Trial
- Trial
- Moving Toward Objective Diagnosis in Fibromyalgia: Emerging Biomarkers and Digital Phenotyping Tools.Biomedicines · 2026Review
- Exploring the relationship between muscle activity, jaw behaviour and pain.Scientific reports · 2025Article
- Pain when it "counts": hurdle analysis of clinical pain ratings improves data model performance.Pain reports · 2025Article
- Development and preliminary testing of a comprehensive Ecological Momentary Assessment of people with chronic pain.The journal of pain · 2025Article
- Automatic detection of pain using machine learning.Frontiers in pain research (Lausanne, Switzerland) · 2022Article
- I. Indices of Pain Intensity Derived From Ecological Momentary Assessments: Rationale and Stakeholder Preferences.The journal of pain · 2021Article
- Variability in experimental pain studies: nuisance or opportunity?British journal of anaesthesia · 2021Article
- Beyond Average: Providers' Assessments of Indices for Measuring Pain Intensity in Patients With Chronic Pain.Frontiers in pain research (Lausanne, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
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.
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