1
|
Horiuchi S, Nomura O, Curry L, Kushima M, Arnold L, Yamagata Z. 'Caregivers' awareness matters': Call for a child-centred approach to early detection of autism spectrum disorder through well-child visits in Japan. Child Care Health Dev 2023; 49:985-994. [PMID: 36807909 DOI: 10.1111/cch.13107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 02/08/2023] [Accepted: 02/13/2023] [Indexed: 02/22/2023]
Abstract
BACKGROUND Early detection of autism spectrum disorder (ASD) is essential to provide children with timely treatment and support. Evidence-based screening measures make it possible to identify children with suspected ASD at an early stage. Although Japan has a universal healthcare system that covers well-child visits, detection rates of developmental disorders, including ASD, at 18 months vary widely between municipalities (0.2%-48.0%). The reasons for this high level of variation are poorly understood. The present study aims to describe the barriers and facilitators of incorporating ASD identification during well-child visits in Japan. METHODS This is a qualitative study that conducts semi-structured in-depth interviews in two municipalities of Yamanashi Prefecture. We recruited all public health nurses (n = 17) and paediatricians (n = 11) involved in the well-child visit in each municipality and caregivers of children who also participated in the visits during the study period (n = 21). RESULTS We identified four themes characterizing the process of ASD identification in the target municipalities: (1) Identification of children with ASD is driven by caregivers' sense of concern, acceptance and awareness. (2) Multidisciplinary cooperation and shared decision-making is limited. (3) Skills and training for developmental disabilities screening are underdeveloped. (4) Caregivers' expectations shape the interaction in important ways. CONCLUSIONS Non-standardization of screening methods, limited knowledge and skills on screening and child development among healthcare providers and poor coordination among healthcare providers and caregivers are the main barriers to effective early detection of ASD through well-child visits. The findings suggest the importance of promoting a child-centred care approach through the application of evidence-based screening measures and effective information sharing.
Collapse
Affiliation(s)
- Sayaka Horiuchi
- Department of Health Sciences, Division of Medicine, Graduate School Department of Interdisciplinary Research, University of Yamanashi, Yamanashi, Japan
| | - Osamu Nomura
- Department of Health Sciences Education, Hirosaki University, Aomori, Japan
- Centre for Community-based Health Professions Education, Hirosaki University, Aomori, Japan
| | - Leslie Curry
- Global Health Leadership Initiative, Yale School of Public Health, New Haven, Connecticut, USA
| | - Megumi Kushima
- Center for Birth Cohort Studies, University of Yamanashi, Yamanashi, Japan
| | - Linda Arnold
- Global Health Leadership Initiative, Yale School of Public Health, New Haven, Connecticut, USA
- International Pediatric Association (IPA), IPA-LEAD program, Marengo, Illinois, USA
| | - Zentaro Yamagata
- Department of Health Sciences, Division of Medicine, Graduate School Department of Interdisciplinary Research, University of Yamanashi, Yamanashi, Japan
- Center for Birth Cohort Studies, University of Yamanashi, Yamanashi, Japan
| |
Collapse
|
2
|
Tilwani D, Bradshaw J, Sheth A, O'Reilly C. ECG Recordings as Predictors of Very Early Autism Likelihood: A Machine Learning Approach. Bioengineering (Basel) 2023; 10:827. [PMID: 37508854 PMCID: PMC10376813 DOI: 10.3390/bioengineering10070827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 06/22/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023] Open
Abstract
In recent years, there has been a rise in the prevalence of autism spectrum disorder (ASD). The diagnosis of ASD requires behavioral observation and standardized testing completed by highly trained experts. Early intervention for ASD can begin as early as 1-2 years of age, but ASD diagnoses are not typically made until ages 2-5 years, thus delaying the start of intervention. There is an urgent need for non-invasive biomarkers to detect ASD in infancy. While previous research using physiological recordings has focused on brain-based biomarkers of ASD, this study investigated the potential of electrocardiogram (ECG) recordings as an ASD biomarker in 3-6-month-old infants. We recorded the heart activity of infants at typical and elevated familial likelihood for ASD during naturalistic interactions with objects and caregivers. After obtaining the ECG signals, features such as heart rate variability (HRV) and sympathetic and parasympathetic activities were extracted. Then we evaluated the effectiveness of multiple machine learning classifiers for classifying ASD likelihood. Our findings support our hypothesis that infant ECG signals contain important information about ASD familial likelihood. Amongthe various machine learning algorithms tested, KNN performed best according to sensitivity (0.70 ± 0.117), F1-score (0.689 ± 0.124), precision (0.717 ± 0.128), accuracy (0.70 ± 0.117, p-value = 0.02), and ROC (0.686 ± 0.122, p-value = 0.06). These results suggest that ECG signals contain relevant information about the likelihood of an infant developing ASD. Future studies should consider the potential of information contained in ECG, and other indices of autonomic control, for the development of biomarkers of ASD in infancy.
Collapse
Affiliation(s)
- Deepa Tilwani
- Artificial Intelligence Institute, University of South Carolina, Columbia, SC 29208, USA
- Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA
- Carolina Autism and Neurodevelopment Research Center, University of South Carolina, Columbia, SC 29208, USA
- Institute for Mind and Brain, University of South Carolina, Columbia, SC 29208, USA
| | - Jessica Bradshaw
- Carolina Autism and Neurodevelopment Research Center, University of South Carolina, Columbia, SC 29208, USA
- Institute for Mind and Brain, University of South Carolina, Columbia, SC 29208, USA
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | - Amit Sheth
- Artificial Intelligence Institute, University of South Carolina, Columbia, SC 29208, USA
- Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA
| | - Christian O'Reilly
- Artificial Intelligence Institute, University of South Carolina, Columbia, SC 29208, USA
- Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA
- Carolina Autism and Neurodevelopment Research Center, University of South Carolina, Columbia, SC 29208, USA
- Institute for Mind and Brain, University of South Carolina, Columbia, SC 29208, USA
| |
Collapse
|
3
|
Hadders‐Algra M. Emerging signs of autism spectrum disorder in infancy: Putative neural substrate. Dev Med Child Neurol 2022; 64:1344-1350. [PMID: 35801808 PMCID: PMC9796067 DOI: 10.1111/dmcn.15333] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/06/2022] [Accepted: 06/07/2022] [Indexed: 12/30/2022]
Abstract
Autism spectrum disorder (ASD) is characterized by altered development of the social brain with prominent atypical features in the fronto-temporo-parietal cortex and cerebellum. Early signs of ASD emerge between 6 and 12 months: reduced social communication, slightly less advanced motor development, and repetitive behaviour. The fronto-temporo-parietal cortex and cerebellum play a prominent role in the development of social communication, whereas fronto-parietal-cerebellar networks are involved in the planning of movements, that is, movement selection. Atypical sensory responsivity, a core feature of ASD, may result in impaired development of social communication and motor skills and/or selection of atypical repetitive behaviour. In the first postnatal year, the brain areas involved are characterized by gradual dissolution of temporary structures: the fronto-temporo-parietal cortical subplate and cerebellar external granular layer. It is hypothesized that altered dissolution of the transient structures opens the window for the expression of early signs of ASD arising in the impaired developing permanent networks. WHAT THIS PAPER ADDS: The early social and motor signs of autism spectrum disorder emerge between the ages of 6 and 12 months. Altered dissolution of transient brain structures in the fronto-temporo-parietal cortex and cerebellum may underlie the emergence of these early signs.
Collapse
Affiliation(s)
- Mijna Hadders‐Algra
- University of Groningen, University Medical Center GroningenDepartment of Paediatrics, Section of Developmental NeurologyGroningenthe Netherlands,University of Groningen, Faculty of Theology and Religious StudiesGroningenthe Netherlands
| |
Collapse
|
4
|
Van Goidsenhoven L. Early interventions for children with an increased likelihood of autism: opportunities and challenges. Dev Med Child Neurol 2021; 63:1366. [PMID: 34247398 DOI: 10.1111/dmcn.14986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/02/2021] [Indexed: 11/28/2022]
Affiliation(s)
- Leni Van Goidsenhoven
- Department of Philosophy, Antwerp University, Antwerp, Belgium.,Department of Cultural Studies, KU Leuven, Leuven, Belgium
| |
Collapse
|