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Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Early Detection of 5 Neurodevelopmental Disorders of Children and Prevention of Postnatal Depression With a Mobile
Fabrice Denis1, Florian Le Goff2, Madhu Desbois2
1Institute for Smarthealth INeS, Le Mans, France.
Insights
A mobile app effectively screened for neurodevelopmental disorders (NDDs) and reduced postnatal depression (PND) incidence by 31%. Early alerts for conditions like autism spectrum disorder (ASD) and ADHD showed high accuracy in real-world settings.
Area of Science:
- Digital health
- Pediatric screening
- Mental health technology
Background:
- Delayed diagnosis of neurodevelopmental disorders (NDDs) and postnatal depression (PND) poses significant public health challenges.
- Early intervention is critical for NDDs and PND but is often delayed in practice.
- A mobile application was developed to address these diagnostic delays.
Purpose of the Study:
- To evaluate a mobile app's effectiveness in screening for five NDDs: autism spectrum disorder (ASD), language delay, dyspraxia, dyslexia, and attention-deficit/hyperactivity disorder (ADHD).
- To determine if the app could reduce the incidence of PND.
- To assess the accuracy and usability of app-based screening tools.
Main Methods:
- An observational, cross-sectional study involving 55,618 parents using a digital health app (Malo).
- Periodic in-app questionnaires assessed child neurodevelopment and maternal PND.
- Algorithm-based alerts prompted physician consultations for potential NDDs; mothers received PND support and questionnaires.
Main Results:
- The app achieved high sensitivity (78.6%) and specificity (98.2%) in detecting potential NDDs.
- Median notification ages for NDDs ranged from 16 months (language delay) to 80 months (dyslexia).
- A 31% reduction in PND incidence was observed compared to a previous study without the app's support program; 11.4% of mothers showed probable PND.
Conclusions:
- Algorithm-based alerts from the mobile app demonstrate high accuracy for early NDD detection.
- The app facilitates efficient early identification of NDDs and PND, significantly reducing PND incidence.
- The digital health tool proved highly usable and improved parental follow-up for child development and maternal mental health.
Background:
Delay in the diagnosis of neurodevelopmental disorders (NDDs) in 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 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 in France with at least 1 child aged <10 years at the time of inclusion and regularly using Malo, an "all-in-one" multidomain digital health record electronic patient-reported outcome (PRO) app for smartphones. We included the first 50,000 users matching the criteria and agreeing to participate between May 1, 2022, and February 8, 2024. Parents received periodic questionnaires assessing skills in neurodevelopment domains via the app. Mothers accessed a support program to prevent PND and were requested to answer regular PND questionnaires. When any PROs matched predefined criteria, an in-app recommendation was sent to book an appointment with a 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 consultation as assessed by health professionals.
Results:
Among 55,618 children median age 4 months (IQR 9), 439 (0.8%) had at least 1 disorder for which consultation was critically necessary. The median ages of notification for probable ASD, language delay, dyspraxia, dyslexia, and ADHD were 32.5 (IQR 12.8), 16 (IQR 13), 36 (IQR 22.5), 80 (IQR 5), and 61 (IQR 15.5) months, respectively. The rate of probable ADHD, ASD, dyslexia, language delay, and dyspraxia in the population of children of the age included between the detection limits of each alert was 1.48%, 0.21%, 1.52%, 0.91%, and 0.37%, respectively. Sensitivity of alert notifications for suspected NDDs as assessed by the physicians was 78.6% and specificity was 98.2%. Among 8243 mothers who completed a PND questionnaire, highly probable PND was detected in 938 (11.4%), corresponding to a reduction of -31% versus our previous study without a support program. Suspected PND was detected a median 96 days (IQR 86) after childbirth. Among 130 users who filled in the satisfaction survey, 99.2% (129/130) found the app easy to use and 70% (91/130) reported that the app improved follow-up of their child. The app was rated 4.8/5 on Apple's App Store.
Conclusions:
Algorithm-based early alerts suggesting NDDs were highly specific with good sensitivity as assessed by real-life practitioners. Early detection of 5 NDDs and PNDs was efficient and led to a possible 31% reduction in PND incidence.
Trial Registration:
ClinicalTrials.gov NCT06301087; https://www.clinicaltrials.gov/study/NCT06301087.
