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

Artificial intelligence in paediatric endocrinology: conflict or cooperation

Artificial intelligence (AI) in medicine is transforming healthcare by automating system tasks, assisting in diagnostics, predicting patient outcomes and personalising patient care, founded on the ability to analyse vast datasets. In paediatric endocrinology, AI has been developed for diabetes, for insulin dose adjustment, detection of hypoglycaemia and retinopathy screening; bone age assessment and thyroid nodule screening; the identification of growth disorders; the diagnosis of precocious puberty; and the use of facial recognition algorithms in conditions such as Cushing syndrome, acromegaly, congenital adrenal hyperplasia and Turner syndrome. AI can also predict those most at risk from childhood obesity by stratifying future interventions to modify lifestyle. AI will facilitate personalised healthcare by integrating data from 'omics' analysis, lifestyle tracking, medical history, laboratory and imaging, therapy response and treatment adherence from multiple sources. As data acquisition and processing becomes fundamental, data privacy and protecting children's health data is crucial. Minimising algorithmic bias generated by AI analysis for rare conditions seen in paediatric endocrinology is an important determinant of AI validity in clinical practice. AI cannot create the patient-doctor relationship or assess the wider holistic determinants of care. Children have individual needs and vulnerabilities and are considered in the context of family relationships and dynamics. Importantly, whilst AI provides value through augmenting efficiency and accuracy, it must not be used to replace clinical skills.

V-care: An application to support lifestyle improvement in children with obesity

BACKGROUND

Obesity is increasing in the pediatric population, and it represents an important risk factor for the life-long development of several diseases. Although health promotion represents the mainstay of obesity prevention and treatment, lifestyle modification programs are often unsuccessful.

OBJECTIVES

The purpose of this article is to introduce the V-care app, a mobile health platform specifically developed to offer effective interaction and support young people in a long-term obesity treatment, combining different strategies to maximize the results of the lifestyle modification program and minimize the possibility of dropouts.

METHODS

The V-care app is based on a conventional client-server architecture, but novelties of our approach are the involvement of families in the lifestyle modification program, and the design inspired to psychological/behavioral change theories, with the aim of raising the chance of patients' compliance to the program. V-care implements a goal-based behavioral intervention, providing specific feedbacks according to the patient's performance. A pilot usability and acceptability study was performed on a sample of thirteen children aged 6-12 years, using a questionnaire with a 5-points Likert scale to evaluate eight system features, identified as essential requirements based on the analysis of strengths and weaknesses of similar systems in literature.

RESULTS

The pilot study highlighted very high rate of overall friendliness and perceived utility evaluation, while some critical issues emerged especially for the chatbot section, which may be due to the novelty of the technology. The positive evaluation of the design choices is confirmed by the average score greater than 3 for all the questions.

CONCLUSIONS

The V-care app represents a digital innovation in the pediatric healthcare, and it could be introduced in children's primary healthcare nationwide, with the aim to offer an intervention program for controlling and preventing childhood obesity.

A novel wide scale well-baby clinic mobile application: an Egyptian pilot study

BACKGROUND

Utilization of under 5-year-old child healthcare services in Egypt is considered low, the highest proportion of well-baby visits is mainly for immunization in the first 2 years of age. Mobile health (mHealth) interventions have the potential to be a useful and low-cost way to disseminate information about proper nutrition, can be used to monitor children's growth using the official charts of World Health Organization, can also help in accessing vaccine-related information and schedules.

OBJECTIVES

To assess needs and requirements for a new comprehensive well-baby clinic mobile application (app) covering well-baby clinic service components. Thereafter, to develop the app prototype and validate it.

METHODS

This study was conducted in four phases: User requirements, development, validation and usage. In user requirement phase, the need for the new app was assessed by performing literature review, market app research and an online survey. In development phase, we developed the novel well-baby clinic app that constituted all well-baby clinic services for children's health monitoring relying on evidence-based information and honoring data safety. In validation phase, after a series of testing, the app was validated using Mobile app rating scale (MARS) by public health and pediatrics consultants to assess its quality. Finally, the app was launched and made available to the public on Android platform.

RESULTS

Sehhat Tefly app was developed based on the demands and requirements of mothers of under 5-year-old children. The app constituted caregiver, child information and seven service elements: physical growth, developmental milestones, immunizations, nutrition, teething, safety & emergency measures and report. The app quality mean was rated 3.7 out of 5 by the panel of experts. The app was downloaded 1445 times in a 4 month period.

CONCLUSIONS

Sehhat Tefly app can meet the need for a free, easy and accessible tool for caregivers to track the progress of children's development and wellbeing. It can also provide advice for referral to physician consultation in case of deviation from normal measures.

Effectiveness of a mobile app, KhunLook versus the maternal and child health handbook on Thai parent’s health literacy, accuracy of health assessments and convenience of use: A randomized controlled trial (Preprint)

BACKGROUND

Children of parents who have higher health literacy (HL) benefit more from preventive child health care. Digital interventions have been used to improve parents' HL with high satisfaction. KhunLook is a Thai mobile app conceived using strategies to improve HL. It was developed to assist parents in assessing and keeping track of their child's health in complement to the standard Maternal and Child Health Handbook (MCHH).

OBJECTIVE

This trial focuses on the effectiveness of using the KhunLook app with the MCHH and standard care (intervention) compared with the conventional MCHH and standard care (control) on parents' HL. Data on accuracy of parents' assessment of their child's health and growth as well as convenience of use of the tool (app or MCHH) in the well-child clinic were collected at 2 visits (immediate=visit 1, and intermediate=visit 2).

METHODS

Parents of children under 3 years of age who (1) had a smartphone or tablet and the MCHH and (2) could participate in 2 visits, 2-6 months apart at Srinagarind Hospital, Khon Kaen, Thailand, were enrolled in this 2-arm parallel randomized controlled trial between April 2020 and May 2021. Parents were randomized 1:1 to 2 groups. At visit 1, data on demographics and baseline HL (Thailand Health Literacy Scales) were collected. Parents in the app group used the KhunLook app and the control group used their child's handbook to assess their child's growth, development, nutrition and feeding, immunization status and rated the convenience of the tool they used. At visit 2, they repeated the assessments and completed the HL questionnaire.

RESULTS

A total of 358 parents completed the study (358/408, 87.7%). After the intervention, the number of parents with high total HL significantly increased from 94/182 (51.6%) to 109/182 (59.9%; 15/182; Δ 8.2%; P=.04), specifically in the health management (30/182; Δ 16.4%; P<.001) and child health management (18/182; Δ 9.9%; P=.01) domains in the app group, but not in the control group. Parents in the app group could correctly assess their child's head circumference (172/182, 94.5% vs 124/176, 70.5%; P<.001) and development (173/182, 95.1% vs 139/176, 79.0%; P<.001) better than those in the control group at both visits. A higher proportion of parents in the app group rated their tool as very easy or easy to use (174-181/182, 95.6%-99.5% vs 141-166/176, 80.1%-94.3%; P<.001) on every item since the first visit.

CONCLUSIONS

Our results suggest the potential of a smartphone app (KhunLook) to improve parents' HL as well as to promote superior accuracy of parents' assessment of their child's head circumference and development, with a similar effect on weight, height, nutrition and feeding, and immunization as in traditional interventions. Using the KhunLook app is useful and more convenient for parents in promoting a healthy child preventive care during early childhood.

TRIAL REGISTRATION

Thai Clinical Trials Registry TCTR20200312003; https://www.thaiclinicaltrials.org/show/TCTR20200312003.