Evidence map›Paper›PMID 31518367›Full record

ArticlePloS one2019

Validity of six consumer-level activity monitors for measuring steps in patients with chronic heart failure.

Tomas Vetrovsky, Michal Siranec, Jitka Marencakova, James J Tufano, Vaclav Capek, Vaclav Bunc, Jan Belohlavek

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
5.8field-weighted citation impact, top 4% 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 55 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Observational
  5. Article
  6. Article
  7. Comparing Step-Counting Algorithms for High-Resolution Wrist Accelerometry Data in Older Adults in the ARIC Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
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  13. Article
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  15. Article
  16. Article
  17. Article
  18. Systematic Review of Fitbit Charge 2 Validation Studies for Exercise Tracking.Translational journal of the American College of Sports Medicine · 2022
    Article
  19. Article
  20. Review
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 at 1 institution in 1 country.

Tomas VetrovskyFaculty of Physical Education and Sport, Charles University, Prague, Czech Republic.ORCID 0000-0003-2529-7069
Michal Siranec2nd Department of Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.
Jitka MarencakovaFaculty of Physical Education and Sport, Charles University, Prague, Czech Republic.
James J TufanoFaculty of Physical Education and Sport, Charles University, Prague, Czech Republic.
Vaclav CapekSecond Faculty of Medicine, Charles University, Prague, Czech Republic.
Vaclav BuncFaculty of Physical Education and Sport, Charles University, Prague, Czech Republic.
Jan Belohlavek2nd Department of Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.
Charles University · CZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAlthough numerous activity trackers have been validated in healthy populations, validation is lacking in chronic heart failure patients who normally walk at a slower pace, making it difficult for researchers and clinicians to implement activity monitors during physical activity interventions.

methodsSix consumer-level activity monitors were validated in a 3-day field study in patients with chronic heart failure and healthy individuals under free living conditions. Furthermore, the same devices were evaluated in a lab-based study during treadmill walking at speeds of 2.4, 3.0, 3.6, and 4.2 km·h-1. Concordance correlation coefficients (CCC) were used to evaluate the agreement between the activity monitors and the criterion, and mean absolute percentage errors (MAPE) were calculated to assess differences between each device and the criterion (MAPE <10% was considered as a threshold for validity).

resultsIn the field study of healthy individuals, all but one of the activity monitors showed a substantial correlation (CCC ≥0.95) with the criterion device and MAPE <10%. In patients with heart failure, the correlation of only two activity monitors (Garmin vívofit 3 and Withings Go) was classified as at least moderate (CCC ≥0.90) and none of the devices had MAPE <10%. In the lab-based study at speeds 4.2 and 3.6 km·h-1, all activity monitors showed substantial to almost perfect correlations (CCC ≥0.95) with the criterion and MAPE in the range 1%-3%. However, at slower speeds of 3.0 and 2.4 km·h-1, the accuracy of all devices substantially deteriorated: their correlation with the criterion decreased below 90% and their MAPE increased to 4-8% and 10-45%, respectively.

conclusionsEven though none of the tested activity monitors fall within arbitrary thresholds for validity, most of them perform reasonably well enough to be useful tools that clinicians can use to simply motivate chronic heart failure patients to walk more.

Indexed as

AccelerometryAdultAgedChronic DiseaseExerciseExercise TestFemaleFitness TrackersHeart FailureHumansMaleMonitoring, AmbulatoryReproducibility of ResultsWalking

Identifiers

PMID31518367
PMCPMC6743766
OpenAlexW2972777558

What OpenQuestion holds

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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.