Being able to recognize red flags for neurodevelopmental disorders (NDD) is crucial to provide timely intervention programs. This work aims to support - within a scientific framework - the construction of an instrument capable to early detect all spectrum of NDD and explore all areas of development, detect failures in typical developmental pathways and point out atypical signs at all ages. This overview of reviews provides evidence for differences in children later diagnosed with NDD compared to typically developing peers such as delays in motor, language development and temperament in the first three years of age, repetitive/stereotyped behaviors, atypicalities/delays in play, object use, attention, visual, sensory processing and social engagement in the first and second year, and difficulties in feeding and sleeping in the first year. These behaviors must be carefully observed as potential red flags for NDD. However, data of the systematic reviews are not yet useful to develop an evidence-based clinical screening. It urges to increase efforts in producing systematic reviews on early behavioral markers for each NDD. Trial registration:CRD42019137731. (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=137731).

In recent years, there has been a great interest in utilizing technology in mental health research. The rapid technological development has encouraged researchers to apply technology as a part of a diagnostic process or treatment of Neurodevelopmental Disorders (NDDs). With the large number of studies being published comes an urgent need to inform clinicians and researchers about the latest advances in this field. Here, we methodically explore and summarize findings from studies published between August 2019 and February 2022. A search strategy led to the identification of 4108 records from PubMed and APA PsycInfo databases. 221 quantitative studies were included, covering a wide range of technologies used for diagnosis and/or treatment of NDDs, with the biggest focus on Autism Spectrum Disorder (ASD). The most popular technologies included machine learning, functional magnetic resonance imaging, electroencephalogram, magnetic resonance imaging, and neurofeedback. The results of the review indicate that technology-based diagnosis and intervention for NDD population is promising. However, given a high risk of bias of many studies, more high-quality research is needed.

Atypical motor patterns are potential early markers and predictors of later diagnosis of Autism Spectrum Disorder (ASD). This study aimed to investigate the early motor trajectories of infants at high-risk (HR) of ASD through MOVIDEA, a semi-automatic software developed to analyze 2D and 3D videos and provide objective kinematic features of their movements. MOVIDEA was developed within the Italian Network for early detection of Autism Spectrum Disorder (NIDA Network), which is currently coordinating the most extensive surveillance program for infants at risk for neurodevelopmental disorders (NDDs). MOVIDEA was applied to video recordings of 53 low-risk (LR; siblings of typically developing children) and 50 HR infants’ spontaneous movements collected at 10 days and 6, 12, 18, and 24 weeks. Participants were grouped based on their clinical outcome (18 HR received an NDD diagnosis, 32 HR and 53 LR were typically developing). Results revealed that early developmental trajectories of specific motor parameters were different in HR infants later diagnosed with NDDs from those of infants developing typically. Since MOVIDEA was useful in the association of quantitative measures with specific early motor patterns, it should be applied to the early detection of ASD/NDD markers.

Early detecting the presence of neurodevelopmental disorders plays an important role in the effectiveness of the treatment. In this paper, we present a novel tool to extract motion features using single camera video recordings of infants. The Movidea software was developed to allow the operator to track the movement of end-effectors of infants in free moving conditions and extract movement features automatically. Movidea was used by different operators to analyze a set of video recordings and its performance was evaluated. The results showed that Movidea performance did not vary with the operator, and the tracking was also stable in home-video recordings. Even if the setup allowed for a two-dimensional analysis, most of the informative content of the movement was maintained. The reliability of the measures and features extracted, as well as the easiness of use, may boost the uptake of the proposed solution in clinical settings. Movidea overcomes the current limitation in the clinical practice in early detection of neurodevelopmental disorders by providing objective measures based on reliable data, and adds a new tool for the motor analysis of infants through unobtrusive technology.

An integrated plan within a defined care pathway for the diagnosis, continuative interventions, and periodic redefinition of care of autistic people is essential for better outcomes. Challenges include delivering services across all domains or life stages and effective coordination between health/social care providers and services. Further, in the ‘real world’, service provision varies greatly, and in many settings is significantly weighted towards diagnosis and children’s services rather than treatment and support or adult care. This study aims to identify existing care pathways for Autism Spectrum Disorder (ASD) from referral to care management after diagnosis. The study reviewed the international literature in PubMed and PsycInfo databases and collected information on care for autistic individuals from the Autism Spectrum Disorders in Europe (ASDEU) project partners. The study found that published data mainly focused on specific components of care pathways rather than an integrated and coordinated plan of care and legislative indications. They should be aimed at facilitating access to the services for support and the inclusiveness of autistic individuals. Given the need for care addressing the complex and heterogeneous nature of ASD, effective coordination between different health/social care providers and services is essential. It is also suggested that research priority should be given to the identification of an integrated care pathway ‘model’ centered around case management, individualization, facilitation, support, continuous training and updating, and quality management.