Evidence mapPaperPMID 40357237Full record

ArticleFrontiers in digital health2025

Perspectives of key stakeholders on integrating wearable sensor technology into rehabilitation care: a mixed-methods analysis.

Allison E Miller, Carey L Holleran, Marghuretta D Bland, Ellen E Fitzsimmons-Craft, Caitlin A Newman, Thomas M Maddox, Catherine E Lang

Abstract read
In one paragraph

Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Allison E MillerProgram in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States.
Carey L HolleranProgram in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States.
Marghuretta D BlandProgram in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States.
Ellen E Fitzsimmons-CraftDepartment of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States.
Caitlin A NewmanShirley Ryan Ability Lab, Chicago, IL, United States.
Thomas M MaddoxDivision of Cardiology, Washington University School of Medicine, St. Louis, MO, United States.
Catherine E LangProgram in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States.

Funding

DOCTORAL TRAINING PROGRAM IN MOVEMENT SCIENCET32HD007434 · WASHINGTON UNIVERSITY · 1993 to 2025
$785k
Translation of In-Clinic Gains to Gains in Daily LifeR37HD068290 · WASHINGTON UNIVERSITY · 2025 to 2025
$537k
NICHD NIH HHS L30 HD116274NICHD NIH HHS R01 HD068290NICHD NIH HHS R37 HD068290NICHD NIH HHS T32 HD007434NIMH NIH HHS K08 MH120341
6 · The paper itself

Abstract

Introduction: Rehabilitation is facing a critical practice gap: Patients seek out rehabilitation services to improve their activity in daily life, yet recent work demonstrates that rehabilitation may be having a limited impact on improving this outcome due to lack of objective data on patients' activity in daily life. Remote monitoring using wearable sensor technology is a promising solution to this address this gap. The purpose of this study was to understand patient and clinician awareness of the practice gap and preferences for integrating wearable sensor technology into rehabilitation care. Methods: This study used a mixed-methods approach consisting of surveys and 1:1 interviews with clinicians (physical and occupational therapists or assistants) employed at an outpatient rehabilitation clinic within an academic medical center and patients seeking care at this clinic. Data were analyzed using descriptive statistics and thematic analysis. Results: Data saturation was reached from nineteen clinicians and ten patients. Both clinicians and patients recognized the importance of measuring activity outside the clinic and viewed wearable sensor technology as an objective measurement tool. Most clinicians (63%) preferred continuous (vs. intermittent) monitoring within a care episode and most patients (60%) were willing to sync their sensor data as often as instructed by their provider. To maximize integration into clinical workflows, clinicians voiced a preference for availability of sensor data in the electronic health record. Conclusions: Clinicians and patients value the use of wearable sensor technology to improve measurement of activity outside the clinic environment and expressed preferences for how this technology could best be integrated into routine rehabilitation care.

Indexed as

digital healthmixed-methodsoccupational therapyphysical therapyrehabilitationremote monitoringtechnologywearable sensor

Identifiers

PMID40357237
PMCPMC12066443

What Socratic holds

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LicenceCC BY
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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 Socratic graph.