Evidence map›Paper›PMID 29079549›Full record

ArticleJMIR mHealth and uHealth2017

iPhone Sensors in Tracking Outcome Variables of the 30-Second Chair Stand Test and Stair Climb Test to Evaluate Disability: Cross-Sectional Pilot Study.

Gautam Adusumilli, Solomon Eben Joseph, Michael A Samaan, Brooke Schultz, Tijana Popovic, Richard B Souza, Sharmila Majumdar

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Telemental health in emergency care settings: A qualitative analysis of considerations for sustainability and spread.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2023
    Article
  6. Review
  7. Telehealth in emergency medicine: A consensus conference to map the intersection of telehealth and emergency medicine.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2021
    Article
  8. Article
  9. Article
  10. Article
  11. Article
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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

7 authors.

Gautam Adusumilli *Musculoskeletal Quantitative Imaging Research Group, Department of Radiology and Imaging, University of California San Francisco, San Francisco, CA, United States.ORCID http://orcid.org/0000-0003-1707-6370
Solomon Eben Joseph *Musculoskeletal Quantitative Imaging Research Group, Department of Radiology and Imaging, University of California San Francisco, San Francisco, CA, United States.ORCID http://orcid.org/0000-0003-0779-7705
Michael A SamaanMusculoskeletal Quantitative Imaging Research Group, Department of Radiology and Imaging, University of California San Francisco, San Francisco, CA, United States.ORCID http://orcid.org/0000-0003-0597-1159
Brooke SchultzHuman Performance Center, Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, CA, United States.ORCID http://orcid.org/0000-0003-4407-395X
Tijana PopovicMusculoskeletal Quantitative Imaging Research Group, Department of Radiology and Imaging, University of California San Francisco, San Francisco, CA, United States.ORCID http://orcid.org/0000-0001-9592-1651
Richard B SouzaMusculoskeletal Quantitative Imaging Research Group, Department of Radiology and Imaging, University of California San Francisco, San Francisco, CA, United States.ORCID http://orcid.org/0000-0001-7556-4132
Sharmila MajumdarMusculoskeletal Quantitative Imaging Research Group, Department of Radiology and Imaging, University of California San Francisco, San Francisco, CA, United States.ORCID http://orcid.org/0000-0002-0201-871X

Funding

Structural, Biochemical and Functional Connectivity in Osteoarthritis using Quantitative Magnetic Resonance Imaging and Skeletal BiomechanicsR01AR069006 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MAJUMDAR, SHARMILA, SOUZA, RICHARD BRIAN · 2016 to 2025
$7.2M
MRI TO STUDY CARTILAGE/BONE INTERACTIONSR01AR046905 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MAJUMDAR, SHARMILA · 1999 to 2015
$6.3M
Longitudinal Assessment of the Effects of Hip Arthroscopy on Articular Cartilage Biochemistry through a Novel Quantitative MRI-Based ApproachF32AR069458 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SAMAAN, MICHAEL A · 2016 to 2017
$124k
NIAMS NIH HHS F32 AR069458NIAMS NIH HHS R01 AR046905NIAMS NIH HHS R01 AR069006
6 · The paper itself

Abstract

backgroundPerformance tests are important to characterize patient disabilities and functional changes. The Osteoarthritis Research Society International and others recommend the 30-second Chair Stand Test and Stair Climb Test, among others, as core tests that capture two distinct types of disability during activities of daily living. However, these two tests are limited by current protocols of testing in clinics. There is a need for an alternative that allows remote testing of functional capabilities during these tests in the osteoarthritis patient population.

objectiveObjectives are to (1) develop an app for testing the functionality of an iPhone's accelerometer and gravity sensor and (2) conduct a pilot study objectively evaluating the criterion validity and test-retest reliability of outcome variables obtained from these sensors during the 30-second Chair Stand Test and Stair Climb Test.

methodsAn iOS app was developed with data collection capabilities from the built-in iPhone accelerometer and gravity sensor tools and linked to Google Firebase. A total of 24 subjects performed the 30-second Chair Stand Test with an iPhone accelerometer collecting data and an external rater manually counting sit-to-stand repetitions. A total of 21 subjects performed the Stair Climb Test with an iPhone gravity sensor turned on and an external rater timing the duration of the test on a stopwatch. App data from Firebase were converted into graphical data and exported into MATLAB for data filtering. Multiple iterations of a data processing algorithm were used to increase robustness and accuracy. MATLAB-generated outcome variables were compared to the manually determined outcome variables of each test. Pearson's correlation coefficients (PCCs), Bland-Altman plots, intraclass correlation coefficients (ICCs), standard errors of measurement, and repeatability coefficients were generated to evaluate criterion validity, agreement, and test-retest reliability of iPhone sensor data against gold-standard manual measurements.

resultsApp accelerometer data during the 30-second Chair Stand Test (PCC=.890) and gravity sensor data during the Stair Climb Test (PCC=.865) were highly correlated to gold-standard manual measurements. Greater than 95% of values on Bland-Altman plots comparing the manual data to the app data fell within the 95% limits of agreement. Strong intraclass correlation was found for trials of the 30-second Chair Stand Test (ICC=.968) and Stair Climb Test (ICC=.902). Standard errors of measurement for both tests were found to be within acceptable thresholds for MATLAB. Repeatability coefficients for the 30-second Chair Stand Test and Stair Climb Test were 0.629 and 1.20, respectively.

conclusionsApp-based performance testing of the 30-second Chair Stand Test and Stair Climb Test is valid and reliable, suggesting its applicability to future, larger-scale studies in the osteoarthritis patient population.

Indexed as

algorithmsmedical informaticsmobile appsmobile phoneosteoarthritistelemedicine

Identifiers

PMID29079549
PMCPMC5681723

What OpenQuestion 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 OpenQuestion graph.