In‐Field Ecological Momentary Assessment From Wearable Motion Sensors and Self‐Report in a Chronic Low Back Pain Cohort

Despite having cLBP with self-reported moderate pain levels, participants generally reported periods of relatively low levels of pain intensity and interference in their EMA. In addition, their EMA-reported activity levels differed from the sensor data. Participants self-reported higher levels of activity compared to the activity levels calculated by the wearable sensors. This suggests that participants overestimated their activity levels on EMA, or that the activity level cut-points may need to be re-evaluated for the cLBP population. Additionally, sensors placed on different body locations showed varying activity and step counts. The activity counts calculated from the waist ActiGraph and the back sensor from this cohort were lower than the average activity counts in the US adult population. Further research is needed to better quantify these differences for people with cLBP to develop a more comprehensive understanding of the pain experience.

Authors

Institutions

Publication Details

Journal
JOR Spine
Published
2026-02-01
DOI
https://doi.org/10.1002/jsp2.70156
Primary Topic
Musculoskeletal pain and rehabilitation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In‐Field Ecological Momentary Assessment From Wearable Motion Sensors and Self‐Report in a Chronic Low Back Pain Cohort

Harold A. Cook, Meenakshi Sundaram, John M. Jakicic, Rachel E. Roos et al.
JOR Spine
Musculoskeletal pain and rehabilitation
article

In‐Field Ecological Momentary Assessment From Wearable Motion Sensors and Self‐Report in a Chronic Low Back Pain Cohort

Harold A. Cook, Meenakshi Sundaram, John M. Jakicic, Rachel E. Roos, Jordan Hoydick, Zakiy Alfikri, Carol M. Greco, Charity G. Patterson, Nam V. Vo, Brad E. Dicianno, Gina P. McKernan, Michael J. Schneider, Gwendolyn A. Sowa, William Anderst, William W. Clark, Jessa Darwin, Kevin M. Bell, Sara R. Piva, Leming Zhou, Bambang Parmanto
article en

Abstract

Despite having cLBP with self-reported moderate pain levels, participants generally reported periods of relatively low levels of pain intensity and interference in their EMA. In addition, their EMA-reported activity levels differed from the sensor data. Participants self-reported higher levels of activity compared to the activity levels calculated by the wearable sensors. This suggests that participants overestimated their activity levels on EMA, or that the activity level cut-points may need to be re-evaluated for the cLBP population. Additionally, sensors placed on different body locations showed varying activity and step counts. The activity counts calculated from the waist ActiGraph and the back sensor from this cohort were lower than the average activity counts in the US adult population. Further research is needed to better quantify these differences for people with cLBP to develop a more comprehensive understanding of the pain experience.

JOR SpineVol. 9(1)
University of Pittsburgh (US), Health Information Management (BE), University of Kansas Medical Center (US), Greater Pittsburgh Orthopaedic Associates (US), McGowan Institute for Regenerative Medicine (US)
National Institutes of Health
Openalex Percentile: Top 69%
Musculoskeletal pain and rehabilitation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

In‐Field Ecological Momentary Assessment From Wearable Motion Sensors and Self‐Report in a Chronic Low Back Pain Cohort — Harold A. Cook, Meenakshi Sundaram, et al. · JOR Spine (2026) | TGRS Research Map | TGRS