Evidence map›Paper›PMID 39932615›Full record

ReviewCurrent pain and headache reports2025

The Potential of Wearable, Modular Devices in Monitoring Functional Clinical Metrics in Patients Suffering from Chronic Pain.

Jason L Chang, Parker Nguyen, Qing Zhao Ruan, Daniel J Pak, Christopher L Robinson, Moises Dominguez, Jaspal R Singh, Amitabh Gulati

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current pain and headache reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

8 authors.

Jason L ChangDepartment of Rehabilitation and Regenerative Medicine, Columbia University, 1300 York Ave, New York City, NY, 10021, USA. jasonlinchang@gmail.com.
Parker NguyenDepartment of Rehabilitation and Regenerative Medicine, Columbia University, 1300 York Ave, New York City, NY, 10021, USA.
Qing Zhao RuanDepartment of Pain Medicine, Weill Cornell Medicine, New York City, NY, USA.
Daniel J PakDepartment of Pain Medicine, Weill Cornell Medicine, New York City, NY, USA.
Christopher L RobinsonDepartment of Anesthesiology, Critical Care, and Pain Medicine, Harvard Medical School-Beth Israel Deaconess Medical Center, Boston, MA, USA.
Moises DominguezDepartment of Neurology, Weill Cornell Medicine, New York City, NY, USA.
Jaspal R SinghDepartment of Rehabilitation Medicine, Weill Cornell Medicine, New York City, NY, USA.
Amitabh GulatiDepartment of Anesthesiology, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThis review assesses the role of wearable technologies in pain management, emphasizing their capability to transcend subjective pain evaluations with objective functional outcome tracking. We explore the types and veracity of health metrics wearable devices track, illustrating how this technological evolution can significantly enhance patient care in the context of chronic pain prevention and management. RECENT

findingsThe advancements in modular wearable technology offer new avenues to track a variety of health outcomes, including aerobic capacity, physical activity, stress, and sleep quality. This provides objective measurements that can aid in the management of chronic conditions and can offer a more comprehensive assessment of a patient's pain and function. Although the initial approach to pain management that emphasized pain as the fifth vital sign had unintended devastating consequences, leveraging wearable technology for objective outcomes tracking presents an opportunity to optimize pain management strategies. Wearable technologies capture functional metrics that provide insight into many aspects of the biopsychosocial model of pain. Utilizing function as the key performance indicator has the potential to improve treatment outcomes and, ultimately, patient care.

Indexed as

Chronic PainPain ManagementPain MeasurementWearable Electronic DevicesActigraphyHumansDataFunctional metricsOutcomes trackingPain medicineWearable technologies

Identifiers

What OpenQuestion holds

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Read underepoch 390

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.