Evidence map›Paper›PMID 40116726›Full record

ArticleJMIR aging2025

A Smartphone-Based Timed Up and Go Test Self-Assessment for Older Adults: Validity and Reliability Study.

Melissa Johanna Böttinger, Sabato Mellone, Jochen Klenk, Carl-Philipp Jansen, Marios Stefanakis, Elena Litz, Anastasia Bredenbrock, Jan-Philipp Fischer, Jürgen M Bauer, Clemens Becker and 1 more

Abstract readValidation Study
In one paragraph

Article in JMIR aging, 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

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

11 authors.

Melissa Johanna BöttingerGeriatric Center, Medical Faculty Heidelberg, Heidelberg University, Bergheimer Str. 20, Heidelberg, 69115, Germany, 49 6221 548146.ORCID 0000-0002-7772-0642
Sabato MelloneDepartment of Electrical, Electronic and Information Engineering, University of Bologna, Bologna, Italy.ORCID 0000-0001-7688-0188
Jochen KlenkInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.ORCID 0000-0002-5987-447X
Carl-Philipp JansenGeriatric Center, Medical Faculty Heidelberg, Heidelberg University, Bergheimer Str. 20, Heidelberg, 69115, Germany, 49 6221 548146.ORCID 0000-0002-2779-7019
Marios StefanakisDepartment of Clinical Gerontology and Geriatric Rehabilitation, Robert Bosch Hospital, Stuttgart, Germany.ORCID 0009-0006-0612-1219
Elena LitzGeriatric Center, Medical Faculty Heidelberg, Heidelberg University, Bergheimer Str. 20, Heidelberg, 69115, Germany, 49 6221 548146.ORCID 0000-0002-1568-2679
Anastasia BredenbrockNetwork Aging Research, Heidelberg University, Heidelberg, Germany.ORCID 0009-0005-2352-539X
Jan-Philipp FischerTSG ResearchLab gGmbH, Zuzenhausen, Germany.ORCID 0009-0007-3248-0802
Jürgen M BauerGeriatric Center, Medical Faculty Heidelberg, Heidelberg University, Bergheimer Str. 20, Heidelberg, 69115, Germany, 49 6221 548146.ORCID 0000-0001-7379-0646
Clemens BeckerGeriatric Center, Medical Faculty Heidelberg, Heidelberg University, Bergheimer Str. 20, Heidelberg, 69115, Germany, 49 6221 548146.ORCID 0000-0003-1624-8353
Katharina Gordt-OesterwindGeriatric Center, Medical Faculty Heidelberg, Heidelberg University, Bergheimer Str. 20, Heidelberg, 69115, Germany, 49 6221 548146.ORCID 0000-0002-2709-1147

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The Timed Up and Go test (TUG) is recommended as an evidence-based tool for measuring physical capacity. Instrumented TUG (iTUG) approaches expand classical supervised clinical applications offering the potential of self-assessment for older adults. Objective: This study aimed to evaluate the concurrent validity and test-retest reliability of a smartphone-based TUG self-assessment "up&go app." Methods: A total of 52 community-dwelling older adults (>67 years old) were recruited. A validated and medically certified system attached with a belt at the lower back was used as a reference system to validate the "up&go app" algorithm. The participants repeated the TUG 5 times wearing, a smartphone with the "up&go app" in their front trouser pocket and an inertial sensor to test the concurrent validity. A subsample of 37 participants repeated the "up&go app" measurement 2 weeks later to examine the test-retest reliability. Results: The correlation between the "up&go app" and the reference measurement was r=0.99 for the total test duration and r=0.97 for the 5 single repetitions. Agreement between the 5 repetitions was intraclass correlation coefficient (ICC)=0.9 (0.84-0.94). Leaving out the first repetition, the agreement was ICC=0.95 (0.92-0.97). Test-retest agreement had an ICC=0.79 (0.53-0.9). Conclusions: The duration of 5 repetitions of the TUG test, measured with the pocket-worn "up&go app," was very consistent with the results of a lower-back sensor system, indicating excellent concurrent validity. Participants walked slower in the first round than in the other 4 repetitions within a test run. Test-retest reliability was also excellent. The "up&go app" provides a useful smartphone-based approach to measure 5 repetitions of the TUG. The app could be used by older adults as a self-screening and monitoring tool of physical capacity at home and thereby help to early identify functional limitations and take interventions when necessary.

Indexed as

Geriatric AssessmentMobile ApplicationsSelf-AssessmentSmartphoneAgedAged, 80 and overFemaleHumansIndependent LivingMaleReproducibility of Resultsageddiagnostic self evaluationinstrumented assessmentmobile applicationsmobilityphysical capacityself-assessmentsmartphonetechnology-based assess-menttimed up and go test

Identifiers

PMID40116726
PMCPMC11951819

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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.