Evidence map›Paper›PMID 38169882›Full record

ArticleMayo Clinic proceedings. Digital health2023

A Digital Health Solution for Child Growth Monitoring at Home: Testing the Accuracy of a Novel "GrowthMonitor" Smartphone Application to Detect Abnormal Height and Body Mass Indices.

Thilipan Thaventhiran, Joanna Orr, Joan K Morris, Anne Hsu, Lee Martin, Kate M Davies, Vincent Harding, Paul Chapple, Leo Dunkel, Helen L Storr

Open access · diamondAbstract read
In one paragraph

Article in Mayo Clinic proceedings. Digital health, 2023. 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
0.9field-weighted citation impact, top 24% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  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

10 authors at 4 institutions in 1 country.

Thilipan ThaventhiranCentre for Endocrinology, William Harvey Research Institute, Queen Mary University of London, United Kingdom.
Joanna OrrCentre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, United Kingdom.
Joan K MorrisPopulation Health Research Institute, St George's University of London, United Kingdom.
Anne HsuCentre for Endocrinology, William Harvey Research Institute, Queen Mary University of London, United Kingdom.
Lee MartinDepartment of Paediatric Endocrinology, The Children's Hospital at The Royal London, United Kingdom.
Kate M DaviesDepartment of Health and Social Care, London South Bank University, United Kingdom.
Vincent HardingUCL Digital Experience, Information Services Division, University College London, United Kingdom.
Paul ChappleCentre for Endocrinology, William Harvey Research Institute, Queen Mary University of London, United Kingdom.
Leo DunkelCentre for Endocrinology, William Harvey Research Institute, Queen Mary University of London, United Kingdom.
Helen L StorrCentre for Endocrinology, William Harvey Research Institute, Queen Mary University of London, United Kingdom.
Queen Mary University of London · GBDepartment of Health and Social Care · GBSt George's, University of London · GBUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop and evaluate a smartphone application that accurately measures height and provides notifications when abnormalities are detected. Patients and Methods: A total of 145 (75 boys) participants with a mean age ± SD of 8.7±4.5 years (range, 1.0-17.0 years), from the Children's Hospital at Barts Health Trust, London, United Kingdom, were enrolled in the study. "GrowthMonitor" (UCL Creatives) iPhone application (GMA) measures height using augmented reality. Using population-based (UK-WHO) references, algorithms calculated height SD score (HSDS), distance from target height (THSDS Results: Bland-Altman plots revealed no appreciable bias in differences between paired study team GMA and stadiometer height measurements, with a mean of the differences of 0.11 cm with 95% limits of agreement of -2.21 to 2.42 cm. There was no evidence of greater bias occurring for either shorter/younger children or taller/older children. The 2 methods of measurements were highly correlated ( Conclusion: GrowthMonitor iPhone application provides the potential for parents/carers and health care professionals to capture serial height measurements at home and without specialized equipment. Reliable interpretation and flagging of abnormal measurements indicate the potential of this technology to transform childhood growth monitoring.

Identifiers

PMID38169882
PMCPMC10759636
OpenAlexW4387204724

What OpenQuestion holds

Textmetadata
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.