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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Mar 19, 2024
Date Accepted: May 16, 2024

The final, peer-reviewed published version of this preprint can be found here:

Early Detection of 5 Neurodevelopmental Disorders of Children and Prevention of Postnatal Depression With a Mobile Health App: Observational Cross-Sectional Study

Denis F

Early Detection of 5 Neurodevelopmental Disorders of Children and Prevention of Postnatal Depression With a Mobile Health App: Observational Cross-Sectional Study

JMIR Public Health Surveill 2024;10:e58565

DOI: 10.2196/58565

PMID: 38888952

PMCID: 11220427

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

An Observational Cross-Sectional Study of Early Detection of 5 Neurodevelopmental Disorders of Children and prevention of Postnatal Depression by Mobile Health App

  • Fabrice Denis

ABSTRACT

Background:

Delay in the diagnosis of neurodevelopmental disorders (NDDs) of toddlers and postnatal depression (PND) is a major public health issue. In both cases, early intervention is crucial but too rarely implemented in practice.

Objective:

Our goal was to determine if a dedicated the mobile app can improve screening of 5 NDDs (autism spectrum disorder (ASD), language delay, dyspraxia, dyslexia and attention deficit hyperactivity disorder (ADHD)), and reduce PND incidence.

Methods:

We performed an observational, cross-sectional, data-based study in a population of young parents with a minimum of 1 child under 10 years of age at the time of inclusion and using Malo on a regular basis. We included between May 1, 2022, and February 8, 2024. the first 50,000 users matching the criteria and agreeing to participate. Parents received via the app, periodic questionnaires assessing skills on neurodevelopment domains. Mothers accessed a support program to prevent PND and were requested to answer regular questionnaires regarding PND. When any patient-reported outcomes matched predefined criteria, an in-app notification was sent to the user, recommending the booking of an appointment with their family physician or pediatrician. The main outcomes were the median age of the infant at the time of notification for possible NDD and the incidence of PND detection after childbirth. One secondary outcome was the relevance of the NDD notification by a consultation as assessed by health professionals.

Results:

Among 55,618 children with median age of 11-months, 439 (0,8%) had at least 1 disorder for which a consultation was critically necessary. The median age of notification for probable ASD, language delay, dyspraxia, dyslexia and ADHD was 32.5, 16, 36, 80 and 61 months, respectively. The sensitivity of the alert notifications of suspected NDDs as assessed by the physicians was 78.6%, and the specificity was 98.2%. Among 8,243 mothers who completed a PND questionnaire, highly probable PND was detected in 938 (11.4%) mothers corresponding to a reduction of -31% versus our previous study without support program).

Conclusions:

The algorithm-based alert suggesting NDD was highly specific with good sensitivity as assessed by real-life practitioners. The app was efficient in the early detection 5 NDD and PND and in possible reduction of PND incidence. Clinical Trial: NCT04958174


 Citation

Please cite as:

Denis F

Early Detection of 5 Neurodevelopmental Disorders of Children and Prevention of Postnatal Depression With a Mobile Health App: Observational Cross-Sectional Study

JMIR Public Health Surveill 2024;10:e58565

DOI: 10.2196/58565

PMID: 38888952

PMCID: 11220427

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