Evidence map›Paper›PMID 39291151›Full record

ArticleDigital health

Evaluation of the Garmin Vivofit 4 for assessing sleep in youth experiencing sleep disturbances.

Paul R Hibbing, Madison Pilla, Lauryn Birmingham, Aniya Byrd, Tumusifu Ndagijimana, Sara Sadeghi, Nedra Seigfreid, Danielle Farr, Baha Al-Shawwa, David G Ingram and 1 more

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Paul R HibbingDepartment of Kinesiology and Nutrition, University of Illinois Chicago, Chicago, IL, USA.ORCID https://orcid.org/0000-0002-1469-5160
Madison PillaCenter for Children's Healthy Lifestyles & Nutrition, Children's Mercy Kansas City, Kansas City, MO, USA.
Lauryn BirminghamSTAR 2.0 Program, Children's Mercy Kansas City, Kansas City, MO, USA.
Aniya ByrdSTAR 2.0 Program, Children's Mercy Kansas City, Kansas City, MO, USA.
Tumusifu NdagijimanaSTAR 2.0 Program, Children's Mercy Kansas City, Kansas City, MO, USA.
Sara SadeghiSTAR 2.0 Program, Children's Mercy Kansas City, Kansas City, MO, USA.
Nedra SeigfreidSTAR 2.0 Program, Children's Mercy Kansas City, Kansas City, MO, USA.
Danielle FarrSTAR 2.0 Program, Children's Mercy Kansas City, Kansas City, MO, USA.
Baha Al-ShawwaDepartment Pediatrics, Division of Pulmonary and Sleep Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.
David G IngramDepartment Pediatrics, Division of Pulmonary and Sleep Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.
Jordan A CarlsonCenter for Children's Healthy Lifestyles & Nutrition, Children's Mercy Kansas City, Kansas City, MO, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Wearable monitors are increasingly used to assess sleep. However, validity is unknown for certain monitors and populations. We tested the Garmin Vivofit 4 in a pediatric clinical sample. Methods: Participants (n = 25) wore the monitor on their nondominant wrist during an overnight polysomnogram. Garmin and polysomnography were compared using 95% equivalence testing, mean absolute error, and Bland-Altman analysis. Results: On average (mean ± SD), the Garmin predicted later sleep onset (by 0.84 ± 1.60 hours) and earlier sleep offset (by 0.34 ± 0.70 hours) than polysomnography. The resulting difference for total sleep time was -0.55 ± 1.21 hours. Sleep onset latency was higher for Garmin than polysomnography (77.4 ± 100.9 and 22.8 ± 20.0 minutes, respectively), while wake after sleep onset was lower (5.2 ± 9.3 and 43.2 ± 37.9 minutes, respectively). Garmin sleep efficiency averaged 3.3% ± 13.8% lower than polysomnography. Minutes in light sleep and deep sleep (the latter including rapid eye movement) were within ±3.3% of polysomnography (both SDs = 14.9%). No Garmin means were significantly equivalent with polysomnography (adjusted p > 0.99). Mean absolute errors were 0.47 to 0.95 hours for time-based variables (sleep onset, offset, and latency, plus total sleep time and wake after sleep onset), and 8.9% to 21.2% for percentage-based variables (sleep efficiency and sleep staging). Bland-Altman analysis showed systematic bias for wake after sleep onset, but not other variables. Conclusions: The Vivofit 4 showed consistently poor individual-level validity, while group-level validity was better for some variables (total sleep time and sleep efficiency) than others.

Indexed as

Actigraphymethodswearable electronic devices

Identifiers

PMID39291151
PMCPMC11406596

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.