Evidence map›Paper›PMID 41422846›Full record

ArticleThe journal of pain2026

Rethinking measurement of movement-evoked pain with digital technology.

Madelyn R Frumkin, Jingwen Zhang, Ziqi Xu, Salim Yakdan, Braeden Benedict, Saad Javeed, Justin Zhang, Kathleen Botterbush, Burel R Goodin, Chenyang Lu and 2 more

Abstract read
In one paragraph

Article in The journal of pain, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Madelyn R FrumkinCenter for Technology and Behavioral Health, Dartmouth College, Lebanon, NH, USA; Department of Biomedical Data Science, Dartmouth College, Lebanon, NH, USA. Electronic address: Madelyn.r.frumkin@dartmouth.edu.
Jingwen ZhangDepartment of Computer Science and Engineering, Washington University, St. Louis, MO, USA.
Ziqi XuDepartment of Computer Science and Engineering, Washington University, St. Louis, MO, USA.
Salim YakdanDepartment of Neurological Surgery, Washington University, St. Louis, MO, USA.
Braeden BenedictDepartment of Neurological Surgery, Washington University, St. Louis, MO, USA.
Saad JaveedDepartment of Neurological Surgery, Washington University, St. Louis, MO, USA.
Justin ZhangDepartment of Neurological Surgery, Washington University, St. Louis, MO, USA; Department of Neurological Surgery, University of Utah, Salt Lake, USA.
Kathleen BotterbushDepartment of Neurological Surgery, Washington University, St. Louis, MO, USA.
Burel R GoodinDepartment of Anesthesiology, Washington University, St. Louis, MO, USA.
Chenyang LuDepartment of Computer Science and Engineering, Washington University, St. Louis, MO, USA.
Wilson Z RayDepartment of Neurological Surgery, Washington University, St. Louis, MO, USA.
Jacob K GreenbergDepartment of Neurological Surgery, Washington University, St. Louis, MO, USA.

Funding

Using Mobile Health Technology and Real-Time Assessments to Address Multilevel Influences on Lumbar Spine Surgery OutcomesK23AR082986 · NIAMS · WASHINGTON UNIVERSITY · PI JACOB GREENBERG · 2024 to 2026
$515k
Personalized Models of Depression and Chronic PainF31MH124291 · NIMH · WASHINGTON UNIVERSITY · PI FRUMKIN, MADELYN · 2021 to 2022
$88k
NIAMS NIH HHS K23 AR082986NIMH NIH HHS F31 MH124291
6 · The paper itself

Abstract

Movement-evoked pain (MEP) may be a useful metric for phenotyping musculoskeletal pain conditions. However, there is significant disagreement over operationalization, and no studies have assessed stability of MEP over time. Fitbit and Ecological Momentary Assessment (EMA) data were collected from adults with moderate-to-severe chronic pain schedule to receive lumbar/thoracolumbar fusion surgery (N=114). On average, participants provided 323 h of Fitbit data and 74 EMA surveys (84% completion rate). To mimic task-based assessment of MEP using the 6-minute walk test, EMA pain ratings completed within 3 h of walking at a speed ≥70spm for at least 6 min were extracted. Of the full sample, 91 individuals (80%) had any instances of pain ratings following 6-minute activity bouts (Median=6, SD=11). Post-activity pain scores exhibited good within-person consistency (ICC=.76). However, between-person differences in average pain accounted for >70% of the variance in post-activity pain. MEP change scores defined as the difference between post-activity and pre-activity pain scores had poor reliability (ICC =.08). MEP change scores were not associated with average pain or factors related to the uncontrolled nature of digital assessment (e.g., activity amount, time from activity to pain report). However, MEP change scores tended to be lower when the preceding pain rating was elevated (β = -7.96, 95% Credible Interval: -9.28, -6.66), suggesting ceiling effects. Small effects of time of day and prior activity were also observed, which could contaminate MEP assessed in the lab or clinic. Continued development of digital methodologies for assessing MEP is recommended. PERSPECTIVE: Existing movement-evoked pain assessments have limitations. Post-activity pain ratings capture overall disability and day-to-day fluctuations in pain, rather than the relationship between movement and pain. Pre-to-post activity change scores had poor reliability when assessed naturalistically and over time. Digital methodologies capture movement-evoked pain continuously across time, contexts, and real-world environments.

Indexed as

Chronic PainEcological Momentary AssessmentMusculoskeletal PainPain MeasurementAdultAgedFemaleHumansMaleMiddle AgedMovementYoung AdultDigital assessmentDigital phenotypingEcological momentary assessmentMovement-evoked painPassive sensing

Identifiers

PMID41422846
PMCPMC13089659

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.