Evidence map›Paper›PMID 35604762›Full record

ArticleJMIR mHealth and uHealth2022

Physical Activity Behavior of Patients at a Skilled Nursing Facility: Longitudinal Cohort Study.

Ramin Ramezani, Wenhao Zhang, Pamela Roberts, John Shen, David Elashoff, Zhuoer Xie, Annette Stanton, Michelle Eslami, Neil S Wenger, Jacqueline Trent and 5 more

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2022. 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
0.5field-weighted citation impact, top 38% of its field
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, 4 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
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

15 authors at 2 institutions in 1 country.

Ramin Ramezani *Center for Smart Health, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-9276-6932
Wenhao Zhang *Center for Smart Health, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-6053-6454
Pamela RobertsDepartment of Physical Medicine and Rehabilitation, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0000-0002-1675-3782
John ShenDepartment of Hematology and Oncology, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-6455-5553
David ElashoffDepartment of Medicine Statistics Core, Biostatistics and Computational Biology, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-5865-8580
Zhuoer XieDepartment of Hematology and Oncology, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0003-1266-9804
Annette StantonDepartment of Psychology, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-9021-2549
Michelle EslamiRockport Healthcare Services, Los Angeles, CA, United States.ORCID 0000-0002-4877-3868
Neil S WengerDivision of General Internal Medicine, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-9884-3967
Jacqueline TrentDepartment of Hematology and Oncology, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-3726-4646
Antonia PetruseDepartment of Hematology and Oncology, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0003-2968-7750
Amelia WeldonDepartment of Hematology and Oncology, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-7187-574X
Andy AscencioDepartment of Hematology and Oncology, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-8197-1049
Majid SarrafzadehDepartment of Computer Science, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-8407-8689
Arash NaeimCenter for Smart Health, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-6830-5933
University of California, Los Angeles · USCedars-Sinai Medical Center · US

Funding

Sensing in At Risk Populations (SARP): Monitoring performance status, activities of daily living, and independence to promote safe outcomes for elderly patients in rehab, the home and long-term careR01HS024394 · AHRQ · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI NAEIM, ARASH · 2015 to 2017
$1.5M
AHRQ HHS R01 HS024394
6 · The paper itself

Abstract

backgroundOn-body wearable sensors have been used to predict adverse outcomes such as hospitalizations or fall, thereby enabling clinicians to develop better intervention guidelines and personalized models of care to prevent harmful outcomes. In our previous work, we introduced a generic remote patient monitoring framework (Sensing At-Risk Population) that draws on the classification of human movements using a 3-axial accelerometer and the extraction of indoor localization using Bluetooth low energy beacons, in concert. Using the same framework, this paper addresses the longitudinal analyses of a group of patients in a skilled nursing facility. We try to investigate if the metrics derived from a remote patient monitoring system comprised of physical activity and indoor localization sensors, as well as their association with therapist assessments, provide additional insight into the recovery process of patients receiving rehabilitation.

objectiveThe aim of this paper is twofold: (1) to observe longitudinal changes of sensor-based physical activity and indoor localization features of patients receiving rehabilitation at a skilled nursing facility and (2) to investigate if the sensor-based longitudinal changes can complement patients' changes captured by therapist assessments over the course of rehabilitation in the skilled nursing facility.

methodsFrom June 2016 to November 2017, patients were recruited after admission to a subacute rehabilitation center in Los Angeles, CA. Longitudinal cohort study of patients at a skilled nursing facility was followed over the course of 21 days. At the time of discharge from the skilled nursing facility, the patients were either readmitted to the hospital for continued care or discharged to a community setting. A longitudinal study of the physical therapy, occupational therapy, and sensor-based data assessments was performed. A generalized linear mixed model was used to find associations between functional measures with sensor-based features. Occupational therapy and physical therapy assessments were performed at the time of admission and once a week during the skilled nursing facility admission.

resultsOf the 110 individuals in the analytic sample with mean age of 79.4 (SD 5.9) years, 79 (72%) were female and 31 (28%) were male participants. The energy intensity of an individual while in the therapy area was positively associated with transfer activities (β=.22; SE 0.08; P=.02). Sitting energy intensity showed positive association with transfer activities (β=.16; SE 0.07; P=.02). Lying down energy intensity was negatively associated with hygiene activities (β=-.27; SE 0.14; P=.04). The interaction of sitting energy intensity with time (β=-.13; SE 0.06; P=.04) was associated with toileting activities.

conclusionsThis study demonstrates that a combination of indoor localization and physical activity tracking produces a series of features, a subset of which can provide crucial information to the story line of daily and longitudinal activity patterns of patients receiving rehabilitation at a skilled nursing facility. The findings suggest that detecting physical activity changes within locations may offer some insight into better characterizing patients' progress or decline.

Indexed as

Patient DischargeSkilled Nursing FacilitiesAgedCohort StudiesExerciseFemaleHumansLongitudinal StudiesMaleBluetooth low energy beaconsfrailtygeriatricshealth care delivery modelsindoor localizationphysical activityphysical medicine and rehabilitationremote sensing technologysmartwatcheswearable sensors

Identifiers

PMID35604762
PMCPMC9171595
OpenAlexW4282941274

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.