Evidence map›Paper›PMID 30913159›Full record

ReviewMedicine and science in sports and exercise2019

Standardizing Analytic Methods and Reporting in Activity Monitor Validation Studies.

Gregory J Welk, Yang Bai, Jung-Min Lee, Job Godino, Pedro F Saint-Maurice, Lucas Carr

Open access · greenAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Medicine and science in sports and exercise, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 9 pooled it
8.7field-weighted citation impact, top 2% 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

60 citing papers in PubMed, 9 syntheses or guidelines pooled it, 145 citations in OpenAlex.

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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

6 authors at 6 institutions in 2 countries.

Gregory J WelkDepartment of Kinesiology, Iowa State University, Ames, IA.
Yang BaiDepartment of Rehabilitation and Movement Science, University of Vermont, Burlington, VT.
Jung-Min LeeCollege of Physical Education, Kyung Hee University, Yong-in, KOREA.
Job GodinoDepartment of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA.
Pedro F Saint-MauriceMetabolic Epidemiology Branch, National Cancer Institute, NIH, HHS, Rockville, MD.
Lucas CarrDepartment of Health and Human Physiology, University of Iowa, Iowa City, IA.
Iowa State University · USKyung Hee University · KRNational Cancer Institute · USUniversity of California, San Diego · USUniversity of Iowa · USUniversity of Vermont · US

Funding

Training CoreU54EB020405 · NIBIB · STANFORD UNIVERSITY · PI DELP, SCOTT L · 2014 to 2018
$11.6M
NIBIB NIH HHS U54 EB020405
6 · The paper itself

Abstract

introductionA lack of standardization with accelerometry-based monitors has made it hard to advance applications for both research and practice. Resolving these challenges is essential for developing methods for consistent, agnostic reporting of physical activity outcomes from wearable monitors in clinical applications.

methodsThis article reviewed the literature on the methods used to evaluate the validity of contemporary consumer activity monitors. A rationale for focusing on energy expenditure as a key outcome measure in validation studies was provided followed by a summary of the strengths and limitations of different analytical methods. The primary review included 23 recent validation studies that collectively reported energy expenditure estimates from 58 monitors relative to values from appropriate criterion measures.

resultsThe majority of studies reported weak indicators such as correlation coefficients (87%), but only half (52%) reported the recommended summary statistic of mean absolute percent error needed to evaluate actual individual error. Fewer used appropriate tests of agreement such as equivalence testing (22%).

conclusionsThe use of inappropriate analytic methods and incomplete reporting of outcomes is a major limitation for systematically advancing research with both research grade and consumer-grade activity monitors. Guidelines are provided to standardize analytic methods and reporting in these types of studies to enhance the utility of the devices for clinical mHealth applications.

Indexed as

AccelerometryCalibrationData Interpretation, StatisticalEnergy MetabolismExerciseFitness TrackersHealth BehaviorHumansResearch DesignValidation Studies as Topic

Identifiers

PMID30913159
PMCPMC6693923
OpenAlexW2933385900

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.