Evidence map›Paper›PMID 30093371›Full record

ReviewJMIR mHealth and uHealth2018

Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data.

Lynne M Feehan, Jasmina Geldman, Eric C Sayre, Chance Park, Allison M Ezzat, Ju Young Yoo, Clayon B Hamilton, Linda C Li

2 registry-linked trialsOpen access · goldAbstract readReview
In one paragraph

Review in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 283 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
283citing papers in PubMed, 13 pooled it
37.6field-weighted citation impact, top 1% 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.

NCT04956393 nacompletednot on this mapstarted 2021, after this paper: background citation

Proof-of-Concept of the SOAR (Stop OsteoARthritis) Program: A Randomized Delayed-Control Trial

TypeinterventionalSponsorUniversity of British ColumbiaRan2021 to 2023Enrolled58ConditionsArthritis, Osteoarthritis, Arthritis Knee, Osteo Arthritis KneeArmsImmediate 8-Week SOAR Program, Delayed 8-Week SOAR Program
NCT07119658 nacompletednot on this mapstarted 2025, after this paper: background citation

Targeting Metabolic Syndrome From the Emergency Department Through Mixed-Methods: Pilot Trial

TypeinterventionalSponsorIndiana UniversityRan2025 to 2026Enrolled20ConditionsHypertension, Hyperglycemia, Dyslipidemia, Metabolic SyndromeArmsComposite intervention to address MetS
3 · Its place in the literature

Who cites it

283 citing papers in PubMed, 13 syntheses or guidelines pooled it, 637 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pooled it
  12. Pooled it
  13. Pooled it
  14. Trial
  15. Trial
  16. Trial
  17. Comparing sleep measures in cancer survivors: self-reported sleep diary versus objective wearable sleep tracker.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Trial
  18. Trial
  19. Article
  20. Article

223 more citing papers are in PubMed but not listed here.

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

8 authors at 2 institutions in 1 country.

Lynne M FeehanDepartment of Physical Therapy, University of British Columbia, Vancouver, BC, Canada.ORCID http://orcid.org/0000-0002-5758-4241
Jasmina GeldmanArthritis Research Canada, Richmond, BC, Canada.ORCID http://orcid.org/0000-0002-2292-4891
Eric C SayreArthritis Research Canada, Richmond, BC, Canada.ORCID http://orcid.org/0000-0002-4526-278X
Chance ParkArthritis Research Canada, Richmond, BC, Canada.ORCID http://orcid.org/0000-0002-3248-448X
Allison M EzzatSchool of Population and Public Health, University of British Columbia, Vancouver, BC, Canada.ORCID http://orcid.org/0000-0003-2576-0412
Ju Young YooArthritis Research Canada, Richmond, BC, Canada.ORCID http://orcid.org/0000-0002-1165-6019
Clayon B HamiltonDepartment of Physical Therapy, University of British Columbia, Vancouver, BC, Canada.ORCID http://orcid.org/0000-0002-6852-3436
Linda C LiDepartment of Physical Therapy, University of British Columbia, Vancouver, BC, Canada.ORCID http://orcid.org/0000-0001-6280-0511
Research Canada · CAUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough designed as a consumer product to help motivate individuals to be physically active, Fitbit activity trackers are becoming increasingly popular as measurement tools in physical activity and health promotion research and are also commonly used to inform health care decisions.

objectiveThe objective of this review was to systematically evaluate and report measurement accuracy for Fitbit activity trackers in controlled and free-living settings.

methodsWe conducted electronic searches using PubMed, EMBASE, CINAHL, and SPORTDiscus databases with a supplementary Google Scholar search. We considered original research published in English comparing Fitbit versus a reference- or research-standard criterion in healthy adults and those living with any health condition or disability. We assessed risk of bias using a modification of the Consensus-Based Standards for the Selection of Health Status Measurement Instruments. We explored measurement accuracy for steps, energy expenditure, sleep, time in activity, and distance using group percentage differences as the common rubric for error comparisons. We conducted descriptive analyses for frequency of accuracy comparisons within a ±3% error in controlled and ±10% error in free-living settings and assessed for potential bias of over- or underestimation. We secondarily explored how variations in body placement, ambulation speed, or type of activity influenced accuracy.

resultsWe included 67 studies. Consistent evidence indicated that Fitbit devices were likely to meet acceptable accuracy for step count approximately half the time, with a tendency to underestimate steps in controlled testing and overestimate steps in free-living settings. Findings also suggested a greater tendency to provide accurate measures for steps during normal or self-paced walking with torso placement, during jogging with wrist placement, and during slow or very slow walking with ankle placement in adults with no mobility limitations. Consistent evidence indicated that Fitbit devices were unlikely to provide accurate measures for energy expenditure in any testing condition. Evidence from a few studies also suggested that, compared with research-grade accelerometers, Fitbit devices may provide similar measures for time in bed and time sleeping, while likely markedly overestimating time spent in higher-intensity activities and underestimating distance during faster-paced ambulation. However, further accuracy studies are warranted. Our point estimations for mean or median percentage error gave equal weighting to all accuracy comparisons, possibly misrepresenting the true point estimate for measurement bias for some of the testing conditions we examined.

conclusionsOther than for measures of steps in adults with no limitations in mobility, discretion should be used when considering the use of Fitbit devices as an outcome measurement tool in research or to inform health care decisions, as there are seemingly a limited number of situations where the device is likely to provide accurate measurement.

Indexed as

accuracydata accuracydistanceenergy expenditureenergy metabolismFitbitfitness trackersreviewsleepstepssystematic reviewtime in activitywearable activity tracker

Identifiers

PMID30093371
PMCPMC6107736
OpenAlexW2883411829

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.