Evidence map›Paper›PMID 42226084›Full record

ArticleJournal of neurologic physical therapy : JNPT2026

Using Compositional Data Analysis to Explore Movement Behaviors in People Who Have Experienced a Stroke.

George D Fulk, Karen J Klingman, Sandra A Billinger, Bria L Bartsch, Amanda J Britton-Carpenter, Keenan Batts, Mary Forgea, Pamela W Duncan, Emily Peterson

Abstract read
In one paragraph

Article in Journal of neurologic physical therapy : JNPT, 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
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

George D FulkDivision of Physical Therapy, Department of Rehabilitation Medicine, School of Medicine, Emory University, Atlanta, Georgia (G.D.F., K.B.); College of Nursing, State University of New York, Upstate Medical University, Syracuse, New York (K.J.H., M.F.); Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas (S.A.B., B.L.B., A.J.B.-C.); Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina (P.W.D.); and Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia (E.P.).
Karen J Klingman
Sandra A Billinger
Bria L Bartsch
Amanda J Britton-Carpenter
Keenan Batts
Mary Forgea
Pamela W Duncan
Emily Peterson

Funding

The SLEEPR study: SLEep Effects on Post-stroke RehabilitationR01NR018979 · NINR · UPSTATE MEDICAL UNIVERSITY · PI KLINGMAN, KAREN J · 2020 to 2024
$3.1M
Building a data science workforce to improve the reproducibility of rehabilitation researchR25HD105583 · NICHD · UNIVERSITY OF SOUTHERN CALIFORNIA · PI David Nelson Kennedy, Sook-Lei Liew · 2022 to 2026
$812k
NICHD NIH HHS R25 HD105583NINR NIH HHS R01 NR018979
6 · The paper itself

Abstract

background and purposePeople with stroke have low levels of activity, are sedentary, and have poor sleep, which have a negative impact on outcomes. Compositional data analysis (CoDA) provides a method to analyze movement behaviors that preserves the relative nature of the different movement behaviors within a day. The purpose of this study was to use CoDA analysis to explore the association between the composition of movement behaviors and physical function and to compare it to traditional analyses that consider movement behaviors as independent variables.

methodsParticipants (n = 68) wore activity monitors that measured time in active, sedentary, and sleep behaviors at 60 days post stroke. CoDA using the isometric log-ratios of the composition of the movement behaviors in a linear regression was used to explore the association between movement behaviors and the Stroke Impact Scale 16. Traditional analysis considered individual movement behaviors separately.

resultsThe compositional mean of the movement behaviors found that participants spent 7.3% of the day in active, 58.1% in sedentary, and 34.6% in sleep behaviors. The composition of the movement behaviors was significantly associated with Stroke Impact Scale 16 (adjusted R2 = 0.5007, P < 0.05). This was greater than when the individual movement behaviors were considered separately (adjusted R2 = 0.3926, P < 0.05). DISCUSSION AND

conclusionsThe composition of movement behaviors (active, sedentary, and sleep) was associated with physical function. Using CoDA with movement behavior data in people with stroke may improve the interpretability of the data by accounting for the dependency between compositional components. Clinicians may want to consider a comprehensive intervention to support behavioral change that seeks to increase physical activity, enhance sleep, and reduce sedentary time.

Indexed as

ExerciseSedentary BehaviorSleepStrokeAgedFemaleHumansMaleMiddle AgedMovementactivity trackerphysical activitysedentary behaviorsleepstroke

Identifiers

PMID42226084
PMCPMC13573727

What OpenQuestion holds

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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.