Evidence map›Paper›PMID 29371113›Full record

SynthesisThe journal of pain2018

Ecological Momentary Assessment Methodology in Chronic Pain Research: A Systematic Review.

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

2 registry-linked trialsAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in The journal of pain, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 124 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
124citing papers in PubMed, 8 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.

NCT05025787 phase2completednot on this mapstarted 2021, after this paper: background citation

EN20-01: A 24 Week Study to Evaluate the Safety and Efficacy of CNTX-6970 in Subjects With Moderate to Severe Knee Osteoarthritis Pain.

TypeinterventionalSponsorMaurizio Fava, MDRan2021 to 2024Enrolled55ConditionsKnee OsteoarthritisArmsCNTX-6970, Placebo
NCT06044584 recruitingnot on this mapstarted 2023, after this paper: background citation

Unveiling Physiological and Psychosocial Pain Components with an Artificial Intelligence Based Telemonitoring Tool (pAIn-sense)

TypeobservationalSponsorETH ZurichRan2023 to 2028Enrolled150ConditionsNociceptive Pain, Neuropathic PainArmsNo intervention
3 · Its place in the literature

Who cites it

124 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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  16. Emerging Clinical Technology: Application of Machine Learning to Chronic Pain Assessments Based on Emotional Body Maps.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2020
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  19. Beyond one-time PROMs: high-frequency single-item mobile ePROM tracking of postoperative recovery in spine surgery-a prospective feasibility study.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
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64 more citing papers are in PubMed but not listed here.

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

5 authors.

Marcella MayCenter for Self-Report Science, Center for Economic and Social Research, University of Southern California, Los Angeles, California. Electronic address: mmay@miami.edu.
Doerte U JunghaenelCenter for Self-Report Science, Center for Economic and Social Research, University of Southern California, Los Angeles, California.
Masakatsu OnoCenter for Self-Report Science, Center for Economic and Social Research, University of Southern California, Los Angeles, California.
Arthur A StoneCenter for Self-Report Science, Center for Economic and Social Research, University of Southern California, Los Angeles, California.
Stefan SchneiderCenter for Self-Report Science, Center for Economic and Social Research, University of Southern California, Los Angeles, California.

Funding

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
NIAMS NIH HHS R01 AR066200
6 · The paper itself

Abstract

Self-reported pain intensity assessments are central to chronic pain research. Ecological momentary assessment (EMA) methodologies are uniquely positioned to collect these data, and are indeed being used in the field. However, EMA protocols are complex, and many decisions are necessary in the design of EMA research studies. A systematic literature review identified 105 articles drawing from 62 quantitative EMA research projects examining pain intensity in adult chronic pain patients. Study characteristics were tabulated to summarize and describe the use of EMA, with an emphasis placed on various dimensions of decision-making involved in executing EMA methodologies. Most identified studies considered within-person relationships between pain and other variables, and a few examined interventions on chronic pain. There was a trend toward the use of smartphones as EMA data collection devices more recently, and completion rates were not reported in nearly one third of studies. Pain intensity items varied widely with respect to number of scale points, anchor labels, and length of reporting period; most used numeric rating scales. Recommendations are provided for reporting to improve reproducibility, comparability, and interpretation of results, and for opportunities to clarify the importance of design decisions. PERSPECTIVE: Studies that use EMA methodologies to assess pain intensity are heterogeneous. Aspects of protocol design, including data input modality and pain item construction, have the potential to influence the data collected. Thorough reporting on design features and completion rates therefore facilitates reproducibility, comparability, and interpretation of study results.

Indexed as

Chronic PainData CollectionEcological Momentary AssessmentHumansPain MeasurementSelf Reportchronic painEcological momentary assessmentelectronic diariesexperience samplingself-report

Identifiers

PMID29371113
PMCPMC6026050

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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.