Literature DB >> 35799406

Automated growth monitoring app (GROWIN): a mobile Health (mHealth) tool to improve the diagnosis and early management of growth and nutritional disorders in childhood.

Antonio de Arriba Muñoz1,2, María Teresa García Castellanos1,2, Mercedes Domínguez Cajal1,2, Anunciación Beisti Ortego1,2, Ignacio Martínez Ruiz3,4, José Ignacio Labarta Aizpún1,2.   

Abstract

OBJECTIVE: To assess the functionality and feasibility of the GROWIN app for promoting early detection of growth disorders in childhood, supporting early interventions, and improving children's lifestyle by analyzing data collected over 3 years (2018-2020).
METHODS: We retrospectively assessed the growth parameters (height, weight, body mass index [BMI], abdominal circumference) entered by users (caregivers/parents) in the GROWIN app. We also analyzed the potential health problems detected and the messages/recommendations the app showed. Finally, we assessed the possible impact/benefit of the app on the growth of the children.
RESULTS: A total of 21 633 users (Spanish [65%], Latin American [30%], and others [5%]) entered 10.5 ± 8.3 measurements (0-15 y old). 1200 recommendations were for low height and 550 for low weight. 1250 improved their measurements. A specialist review was recommended in 500 patients due to low height. 2567 nutrition tests were run. All children with obesity (n = 855, BMI: 27.8 kg/m2 [2.25 SD]) completed the initial test with a follow-up of ≥1 year. Initial results (score: 8.1) showed poor eating habits (fast food, commercially baked goods, candy, etc.), with >90% not having breakfast. After 3-6 months, BMI decreased ≥1 point, and test scores increased ≥2 points. This benefit was maintained beyond 1 year and was correlated with an improvement in BMI (r = -.65, P = .01). DISCUSSION/
CONCLUSIONS: The GROWIN app represents an innovative automated solution for families to monitor growth. It allows the early detection of abnormal growth indicators during childhood and adolescence, promoting early interventions. Additionally, in children with obesity, an improvement in healthy nutritional habits and a decrease in BMI were observed.
© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  digital technologies; early diagnosis; growth monitoring; mHealth application; obesity; prevention

Mesh:

Year:  2022        PMID: 35799406      PMCID: PMC9382383          DOI: 10.1093/jamia/ocac108

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   7.942


  38 in total

1.  [Spanish cross-sectional growth study 2008. Part II. Height, weight and body mass index values from birth to adulthood].

Authors:  A Carrascosa Lezcano; J M Fernández García; C Fernández Ramos; A Ferrández Longás; J P López-Siguero; E Sánchez González; B Sobradillo Ruiz; D Yeste Fernández
Journal:  An Pediatr (Barc)       Date:  2008-06       Impact factor: 1.500

2.  Towards a Rational and Efficient Diagnostic Approach in Children Referred for Growth Failure to the General Paediatrician.

Authors:  Jan M Wit; Gerdine A Kamp; Wilma Oostdijk
Journal:  Horm Res Paediatr       Date:  2019-06-13       Impact factor: 2.852

3.  Weight and height centiles of Argentinian children and adolescents: a comparison with WHO and national growth references.

Authors:  Alicia B Orden; María C Apezteguía
Journal:  Ann Hum Biol       Date:  2014-10-28       Impact factor: 1.533

4.  [Not Available].

Authors:  Antonio De Arriba Muñoz; Marta López Úbeda; Carmen Rueda Caballero; José Ignacio Labarta Aizpún; Ángel Ferrández Longás
Journal:  Nutr Hosp       Date:  2016-07-19       Impact factor: 1.057

Review 5.  Pediatric Obesity Algorithm: A Practical Approach to Obesity Diagnosis and Management.

Authors:  Suzanne E Cuda; Marisa Censani
Journal:  Front Pediatr       Date:  2019-01-23       Impact factor: 3.418

6.  The Continued Use of Mobile Health Apps: Insights From a Longitudinal Study.

Authors:  Isaac Vaghefi; Bengisu Tulu
Journal:  JMIR Mhealth Uhealth       Date:  2019-08-29       Impact factor: 4.773

7.  eHealth Intervention to Improve Health Habits in the Adolescent Population: Mixed Methods Study.

Authors:  Carmen Benavides; José Alberto Benítez-Andrades; Pilar Marqués-Sánchez; Natalia Arias
Journal:  JMIR Mhealth Uhealth       Date:  2021-02-18       Impact factor: 4.773

Review 8.  Digital technologies to improve the precision of paediatric growth disorder diagnosis and management.

Authors:  Leo Dunkel; Luis Fernandez-Luque; Sandro Loche; Martin O Savage
Journal:  Growth Horm IGF Res       Date:  2021-06-04       Impact factor: 2.372

Review 9.  Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years.

Authors:  Alex Domin; Donna Spruijt-Metz; Daniel Theisen; Yacine Ouzzahra; Claus Vögele
Journal:  JMIR Mhealth Uhealth       Date:  2021-07-21       Impact factor: 4.773

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