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Firestein MR, Manessis A, Warmingham JM, Xu R, Hu Y, Finkel MA, Kyle M, Hussain M, Ahmed I, Lavallée A, Solis A, Chaves V, Rodriguez C, Goldman S, Muhle RA, Lee S, Austin J, Silver WG, O'Reilly KC, Bain JM, Penn AA, Veenstra-VanderWeele J, Stockwell MS, Fifer WP, Marsh R, Monk C, Shuffrey LC, Dumitriu D. Positive Autism Screening Rates in Toddlers Born During the COVID-19 Pandemic. JAMA Netw Open 2024; 7:e2435005. [PMID: 39312236 PMCID: PMC11420691 DOI: 10.1001/jamanetworkopen.2024.35005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/25/2024] Open
Abstract
Importance Stress and viral illness during pregnancy are associated with neurodevelopmental conditions in offspring. Autism screening positivity for children born during the pandemic remains unknown. Objective To examine associations between prenatal exposure to the pandemic milieu and maternal SARS-CoV-2 infection with rates of positive Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) screenings. Design, Setting, and Participants Data for this cohort study were drawn from the COVID-19 Mother Baby Outcomes (COMBO) Initiative. M-CHAT-R scores obtained from children aged 16 to 30 months during routine clinical care at Columbia University Irving Medical Center in New York City were abstracted from electronic health records (EHRs) for children born between January 2018 and September 2021 (COMBO-EHR cohort). Separately, the M-CHAT-R was administered at 18 months for children born between February 2020 and September 2021 through a prospective longitudinal study (COMBO-RSCH cohort). Prenatal pandemic exposure (birth after March 1, 2020) and maternal SARS-CoV-2 status during pregnancy was determined through EHRs. Data were analyzed from March 2022 to June 2024. Exposures Prenatal exposures to the pandemic milieu and maternal SARS-CoV-2 infection. Main Outcomes and Measures The primary outcome was rate of positive M-CHAT-R screenings. For all primary analyses, unadjusted χ2 tests and adjusted logistic regression models were performed. Results The COMBO-EHR cohort included 1664 children (442 born before the pandemic and 1222 born during the pandemic; 997 SARS-CoV-2 unexposed, 130 SARS-CoV-2 exposed, and 95 with unknown SARS-CoV-2 exposure status), of whom 266 (16.0%) were Black, 991 (59.6%) were Hispanic, 400 (24.0%) were White, 1245 (74.8%) were insured through Medicaid, 880 (52.9%) were male, and 204 (12.3%) were born prematurely. The COMBO-RSCH cohort included 385 children (74 born before the pandemic and 311 born during the pandemic; 201 SARS-CoV-2 unexposed, 101 SARS-CoV-2 exposed, and 9 with unknown SARS-CoV-2 exposure status), of whom 39 (10.1%) were Black, 168 (43.6%) were Hispanic, 157 (40.8%) were White, 161 (41.8%) were insured through Medicaid, 222 (57.7%) were male, and 38 (9.9%) were born prematurely. Prenatal pandemic exposure was not associated with a higher positive M-CHAT-R screening rate in either the COMBO-EHR or COMBO-RSCH cohort. Prenatal exposure to maternal SARS-CoV-2 infection was associated with a lower rate of M-CHAT-R positivity in the COMBO-EHR cohort (12.3% [16 children] vs 24.0% [239 children]; adjusted odds ratio, 0.40; 95% CI, 0.22-0.68; P = .001), but no association was found in the COMBO-RSCH cohort (12.9% [13 children] vs 19.9% [40 children]; adjusted odds ratio, 0.51; 95% CI, 0.24-1.04; P = .07). Conclusions and Relevance In this cohort study of 2 groups of children with prenatal pandemic exposure and/or exposure to maternal SARS-CoV-2 infection, neither exposure was associated with greater M-CHAT-R positivity.
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Affiliation(s)
- Morgan R Firestein
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
| | | | - Jennifer M Warmingham
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Ruiyang Xu
- Teachers College, Columbia University, New York, New York
| | - Yunzhe Hu
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
| | - Morgan A Finkel
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Morgan Stanley Children's Hospital, New York
| | - Margaret Kyle
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Maha Hussain
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Imaal Ahmed
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Andréane Lavallée
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Ana Solis
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Vitoria Chaves
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Cynthia Rodriguez
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Sylvie Goldman
- Department of Biostatistics, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York
| | - Rebecca A Muhle
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Morgan Stanley Children's Hospital, New York
- New York State Psychiatric Institute, New York
| | - Seonjoo Lee
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
- Department of Biostatistics, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York
- New York State Psychiatric Institute, New York
| | - Judy Austin
- Department of Population and Family Health, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York
| | - Wendy G Silver
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Morgan Stanley Children's Hospital, New York
- Department of Neurology, Division of Child Neurology, Columbia University Irving Medical Center, New York, New York
| | - Kally C O'Reilly
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
- New York State Psychiatric Institute, New York
| | - Jennifer M Bain
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Morgan Stanley Children's Hospital, New York
- Department of Neurology, Division of Child Neurology, Columbia University Irving Medical Center, New York, New York
| | - Anna A Penn
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Morgan Stanley Children's Hospital, New York
| | - Jeremy Veenstra-VanderWeele
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Morgan Stanley Children's Hospital, New York
- New York State Psychiatric Institute, New York
| | - Melissa S Stockwell
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Morgan Stanley Children's Hospital, New York
- Department of Population and Family Health, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York
| | - William P Fifer
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Rachel Marsh
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
- Department of Neurology, Division of Child Neurology, Columbia University Irving Medical Center, New York, New York
| | - Catherine Monk
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
- New York State Psychiatric Institute, New York
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center New York, New York
| | - Lauren C Shuffrey
- Department of Child and Adolescent Psychiatry, New York University Grossman School of Medicine, New York
| | - Dani Dumitriu
- Department of Psychiatry, Columbia University Irving Medical Center, New York, New York
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Morgan Stanley Children's Hospital, New York
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Seebeck J, Sznajder KK, Kjerulff KH. The association between prenatal psychosocial factors and autism spectrum disorder in offspring at 3 years: a prospective cohort study. Soc Psychiatry Psychiatr Epidemiol 2024; 59:1639-1649. [PMID: 37556019 DOI: 10.1007/s00127-023-02538-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 07/30/2023] [Indexed: 08/10/2023]
Abstract
PURPOSE Few studies of risk factors for autism spectrum disorder (ASD) have been prospective in design or investigated the role of psychosocial factors measured during pregnancy. We aimed to investigate associations between prenatal psychosocial factors and risk of ASD in offspring, as part of a multicenter prospective cohort study of more than 2000 mother-child pairs. METHODS Nulliparous women aged 18-35 years, living in Pennsylvania, USA, were interviewed during pregnancy and multiple times postpartum over the course of a 3-year period. There were 2388 mothers who completed the Screen for Social Interaction Toddler Version (SSI-T), a measure of risk of ASD, when their child was 3-years old. Multivariable logistic regression models were used to investigate the associations between prenatal psychosocial factors-including total scores on three scales (social-support, stress and depression), trouble paying for basic needs, mental illness diagnosis and use of antidepressants-and risk of ASD in offspring at the age of 3-years, controlling for relevant confounding variables. RESULTS There were 102 children (4.3%) who were scored as at-risk of ASD at 3-years. Prenatal psychosocial factors that were significantly associated with risk of ASD in the adjusted models were lower social-support (p < 0.001); stress (p = 0.003): depression (< 0.001), trouble paying for basic needs (p = 0.012), mental illness diagnosis (p = 0.016), and use of antidepressants (p < 0.001). CONCLUSION These findings suggest that maternal experience of adverse psychosocial factors during pregnancy may be important intrauterine exposures related to the pathogenesis of ASD.
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Blakey AO, Eilenberg JS, Cardona N, Kizildag D, Broder-Fingert S, Feinberg E, Long KA. Family Involvement During Comprehensive Developmental Evaluations: Perspectives of Diverse Mothers. J Dev Behav Pediatr 2024; 45:e325-e333. [PMID: 39108071 PMCID: PMC11326989 DOI: 10.1097/dbp.0000000000001288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 04/04/2024] [Indexed: 08/16/2024]
Abstract
OBJECTIVE Early diagnosis and social support postdiagnosis (i.e., family involvement) can lead to improved outcomes for children with autism spectrum disorder (ASD) and other developmental disorders. Children of minority ethnic and racial groups are typically diagnosed later in childhood compared with White children, contributing to disparities in outcomes. Research has not yet explored family involvement during comprehensive developmental evaluations nor accounted for cross-cultural differences in family roles and involvement. This qualitative study sought to characterize the nature and impact of family involvement during the developmental evaluation process among racially and ethnically marginalized mothers of children with developmental delays and possible ASD. METHODS Mothers (N = 27) of children who had a positive autism screen during their 18- or 24-month well-child visit but did not receive an ASD diagnosis after comprehensive developmental evaluation participated in individual semi-structured interviews exploring experiences with developmental screening, related services, and family involvement/social support. Qualitative data were transcribed, coded, and analyzed using applied thematic analysis. Data were stratified by partner status (i.e., partnered vs. nonpartnered) to examine differences in support and family involvement across varying family compositions. RESULTS Three qualitative themes emerged: (1) mothers sought family involvement when making decisions about pursuing developmental evaluations, (2) family involvement affected mothers' navigation of logistical challenges, and (3) mothers involved family members for emotional support. Differences by partner status emerged in themes 1 and 2. CONCLUSION Findings highlight benefits of and potential approaches to harnessing family involvement to support parents' navigation of the developmental evaluation process and ultimately improve child outcomes.
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Affiliation(s)
- Ariel O Blakey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | | | - Nicole Cardona
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Deniz Kizildag
- Department of Anthropology, Brandeis University, Waltham, MA
| | - Sarabeth Broder-Fingert
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
- Department of Pediatrics, University of Massachusetts Chan Medical School, Worcester, MA
| | - Emily Feinberg
- Department of Community Health Sciences, Boston University School of Public Health, Boston, MA
- Department of Pediatrics, Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Kristin A Long
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
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Zheng RM, Chan SP, Law EC, Chong SC, Aishworiya R. Validity and feasibility of using the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F) in primary care clinics in Singapore. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2024; 28:1758-1771. [PMID: 37882198 PMCID: PMC11191374 DOI: 10.1177/13623613231205748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
LAY ABSTRACT Systematic screening for autism in early childhood has been suggested to improve eventual outcomes by facilitating earlier diagnosis and access to intervention. However, clinical implementation of screening has to take into account effectiveness and feasibility of use within a healthcare setting for accurate diagnosis of autism. In Singapore, autism screening using a structured screening tool is not currently employed as a part of routine well-child visits for children in primary care clinics. In this study, 5336 children (aged 17-20 months) were screened for autism using the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F) during their 18-month well-child visit in seven primary care clinics. Screening and follow-up interviews were administered by nursing staff at each clinic. Children screened positive and a portion of those screened negative then underwent diagnostic assessments to determine whether they met the diagnostic criteria for autism. In total, 113 (2.1%) were screened positive, of which 54 (1.0%) met the criteria for autism. Children who screened positive and received a diagnosis accessed autism-specific intervention at an average age of 22 months. Nurses and physicians rated the acceptability and practicality of the M-CHAT-R/F highly. Therefore, the M-CHAT-R/F questionnaire was an effective and feasible tool for autism screening among 18-month-old children in this study. Future studies will be designed to determine the optimal age of screening and role of repeated screening in Singapore, as well as to better understand any potential improved outcomes nationwide compared with pre-implementation of autism screening.
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Affiliation(s)
| | - Siew Pang Chan
- National University Heart Centre, Singapore
- National University of Singapore, Singapore
| | - Evelyn C Law
- National University of Singapore, Singapore
- Agency for Science, Technology and Research (A*STAR), Singapore
- National University Hospital, Singapore
| | - Shang Chee Chong
- National University of Singapore, Singapore
- National University Hospital, Singapore
| | - Ramkumar Aishworiya
- National University of Singapore, Singapore
- National University Hospital, Singapore
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Shuffrey LC, Rennie B, Li X, Galai N, Pini N, Akbaryan A, Alshawabkeh A, Aschner J, Vargas JC, Costello L, D'Sa V, Deoni S, Dunlop A, Elliott AJ, Fifer WP, Hash J, Koinis-Mitchell D, Lai JS, Leventhal BL, Lewis J, Lucchini M, McArthur KL, Morales S, Nozadi SS, O'Connor TG, O'Shea TM, Page GP, Propper C, Sania A, Shuster C, Zimmerman E, Margolis AE. Combining developmental and sleep health measures for autism spectrum disorder screening: an ECHO study. Pediatr Res 2024:10.1038/s41390-024-03306-0. [PMID: 38867029 DOI: 10.1038/s41390-024-03306-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/01/2024] [Accepted: 05/20/2024] [Indexed: 06/14/2024]
Abstract
BACKGROUND Sleep problems are reported for up to 80% of autistic individuals. We examined whether parsimonious sets of items derived from the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) and the Brief Infant Sleep Questionnaire (BISQ) are superior to the standard M-CHAT-R in predicting subsequent autism spectrum disorder (ASD) diagnoses. METHODS Participants from 11 Environmental influences on Child Health Outcomes (ECHO) cohorts were included. We performed logistic LASSO regression models with 10-fold cross-validation to identify whether a combination of items derived from the M-CHAT-R and BISQ are superior to the standard M-CHAT-R in predicting ASD diagnoses. RESULTS The final sample comprised 1552 children. The standard M-CHAT-R had a sensitivity of 44% (95% CI: 34, 55), specificity of 92% (95% CI: 91, 94), and AUROC of 0.726 (95% CI: 0.663, 0.790). A higher proportion of children with ASD had difficulty falling asleep or resisted bedtime during infancy/toddlerhood. However, LASSO models revealed parental reports of sleep problems did not improve the accuracy of the M-CHAT-R in predicting ASD diagnosis. CONCLUSION While children with ASD had higher rates of sleep problems during infancy/toddlerhood, there was no improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. IMPACT Parental-reported sleep problems are common in autism spectrum disorder (ASD). We investigated whether the inclusion of parental-reports of infant/toddler sleep patterns enhanced the effectiveness of developmental screening for autism. We reported higher rates of difficulty falling asleep and resisting bedtime during infancy and toddlerhood among children later diagnosed with ASD; however, we did not find an improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. In our sample, the standard M-CHAT-R had a sensitivity of 39% among children of mothers with government insurance compared with a sensitivity of 53% among children of mothers with employer-based insurance.
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Affiliation(s)
- Lauren C Shuffrey
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, USA.
| | - Brandon Rennie
- Department of Pediatrics, University of New Mexico, Albuquerque, NM, USA
| | - Xiuhong Li
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Noya Galai
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Statistics, University of Haifa, Mt Carmel, Israel
| | - Nicolò Pini
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Anahid Akbaryan
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | | | - Judy Aschner
- Department of Pediatrics, Hackensack Meridian School of Medicine, Nutley, NJ, USA
| | - Julianna Collazo Vargas
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Lauren Costello
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Viren D'Sa
- Department of Pediatrics, Brown University, Providence, RI, USA
| | - Sean Deoni
- Maternal Newborn and Child Health: Discovery & Tools, The Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Anne Dunlop
- Department of Gynecology & Obstetrics, Emory University, Atlanta, Georgia
| | - Amy J Elliott
- Center for Pediatric and Community Research, Avera Research Institute, Sioux Falls, SD, USA
| | - William P Fifer
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Division of Developmental Neuroscience, New York State Psychiatric Institute, New York, NY, USA
| | - Jonica Hash
- Department of Child, Family, and Population Health Nursing, University of Washington, Seattle, WA, USA
| | - Daphne Koinis-Mitchell
- Departments of Pediatrics and Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Jin-Shei Lai
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Bennett L Leventhal
- Department of Pediatrics, University of New Mexico, Albuquerque, NM, USA
- Department of Psychiatry and Behavioral Neuroscience, The University of Chicago, Chicago, IL, USA
| | - Johnnye Lewis
- Department of Pediatrics, University of New Mexico, Albuquerque, NM, USA
| | - Maristella Lucchini
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Kristen L McArthur
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Santiago Morales
- Departments of Psychology and Pediatrics, Developmental and Brain and Cognitive Science Areas, University of Southern California, Los Angeles, CA, USA
| | - Sara S Nozadi
- Community Environmental Health Program, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Thomas G O'Connor
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, USA
| | - T Michael O'Shea
- Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Grier P Page
- Analytics Program, RTI International, Research Triangle Park, NC, USA
| | - Cathi Propper
- School of Nursing, University of North Carolina, Chapel Hill, NC, USA
| | - Ayesha Sania
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Coral Shuster
- The Brown Center for the Study of Children at Risk, Woman & Infants Hospital of Rhode Island, Providence, RI, USA
| | - Emily Zimmerman
- Department of Communication Sciences and Disorders, Northeastern University, Chicago, IL, USA
| | - Amy E Margolis
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
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Nutor C, Dunlop A, Sadler O, Brennan PA. Prenatal Cannabis Use and Offspring Autism-Related Behaviors: Examining Maternal Stress as a Moderator in a Black American Cohort. J Autism Dev Disord 2024; 54:2355-2367. [PMID: 37097527 PMCID: PMC10127191 DOI: 10.1007/s10803-023-05982-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/30/2023] [Indexed: 04/26/2023]
Abstract
Prenatal cannabis use and maternal stress have been proposed as risk factors for autism spectrum disorder (ASD). Black mothers and mothers of lower socioeconomic status (SES) may be especially likely to experience high levels of stress. This study examined the impact of prenatal cannabis use and maternal stress (i.e., prenatal distress, racial discrimination, and lower SES) on child ASD-related behaviors in a sample of 172 Black mother-child pairs. We found that prenatal stress was significantly associated with ASD-related behaviors. Prenatal cannabis use did not predict ASD-related behaviors and did not interact with maternal stress to predict ASD-related behaviors. These findings replicate previous work on prenatal stress-ASD associations and add to the limited literature on prenatal cannabis-ASD associations in Black samples.
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Affiliation(s)
- C Nutor
- Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA.
| | - A Dunlop
- Department of Gynecology and Obstetrics, Emory University, 1365 E Clifton Rd NE, Atlanta, GA, 30322, USA
| | - O Sadler
- Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - P A Brennan
- Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
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Gale-Grant O, Chew A, Falconer S, França LGS, Fenn-Moltu S, Hadaya L, Harper N, Ciarrusta J, Charman T, Murphy D, Arichi T, McAlonan G, Nosarti C, Edwards AD, Batalle D. Clinical, socio-demographic, and parental correlates of early autism traits in a community cohort of toddlers. Sci Rep 2024; 14:8393. [PMID: 38600134 PMCID: PMC11006842 DOI: 10.1038/s41598-024-58907-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 04/04/2024] [Indexed: 04/12/2024] Open
Abstract
Identifying factors linked to autism traits in the general population may improve our understanding of the mechanisms underlying divergent neurodevelopment. In this study we assess whether factors increasing the likelihood of childhood autism are related to early autistic trait emergence, or if other exposures are more important. We used data from 536 toddlers from London (UK), collected at birth (gestational age at birth, sex, maternal body mass index, age, parental education, parental language, parental history of neurodevelopmental conditions) and at 18 months (parents cohabiting, measures of socio-economic deprivation, measures of maternal parenting style, and a measure of maternal depression). Autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT) at 18 months. A multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). In order to address variable collinearity we used principal component analysis, finding that a component which was positively correlated with Q-CHAT was also correlated to measures of parenting style and socio-economic deprivation. Our results show that parenting style and socio-economic deprivation correlate with the emergence of autism traits at age 18 months as measured with the Q-CHAT in a community sample.
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Affiliation(s)
- Oliver Gale-Grant
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16, De Crespigny Park, London, SE5 8AF, UK.
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK.
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK.
| | - Andrew Chew
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - Shona Falconer
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - Lucas G S França
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16, De Crespigny Park, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
- Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, UK
| | - Sunniva Fenn-Moltu
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16, De Crespigny Park, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - Laila Hadaya
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nicholas Harper
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
| | - Judit Ciarrusta
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16, De Crespigny Park, London, SE5 8AF, UK
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Declan Murphy
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16, De Crespigny Park, London, SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- Department of Paediatric Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK
- Department of Bioengineering, Imperial College London, London, UK
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16, De Crespigny Park, London, SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16, De Crespigny Park, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King's College London, London, UK
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So WC, Wong E, Ng W, Fuego J, Lay S, So MT, Lee YY, Chan WY, Chua LY, Lam HL, Lam WT, Li HM, Leung WT, Ng YH, Wong WT. Seeing through a robot's eyes: A cross-sectional exploratory study in developing a robotic screening technology for autism. Autism Res 2024; 17:366-380. [PMID: 38183409 DOI: 10.1002/aur.3087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 12/09/2023] [Indexed: 01/08/2024]
Abstract
The present exploratory cross-sectional case-control study sought to develop a reliable and scalable screening tool for autism using a social robot. The robot HUMANE, installed with computer vision and linked with recognition technology, detected the direction of eye gaze of children. Children aged 3-8 (M = 5.52; N = 199) participated, 87 of whom had been confirmed with autism, 55 of whom were suspected to have autism, and 57 of whom were not considered to cause any concern for having autism. Before a session, a human experimenter instructed HUMANE to narrate a story to a child. HUMANE prompted the child to return his/her eye gaze to the robot if the child looked away, and praised the child when it re-established its eye gaze quickly after a prompt. The reliability of eye gaze detection was checked across all pairs of human raters and HUMANE and reached 0.90, indicating excellent interrater agreement. Using the pre-specified reference standard (Autism Spectrum Quotient), the sensitivity and specificity of the index tests (i.e., the number of robot prompts and duration of inattentiveness) reached 0.88 or above and the Diagnostic Odds Ratios were beyond 190. These results show that social robots may detect atypical eye patterns, suggesting a potential future for screening autism using social robots.
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Affiliation(s)
- Wing-Chee So
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Elsa Wong
- NEC Hong Kong Limited, Hung Hom, Hong Kong
| | - Wingo Ng
- NEC Hong Kong Limited, Hung Hom, Hong Kong
| | - John Fuego
- NEC Hong Kong Limited, Hung Hom, Hong Kong
| | - Sally Lay
- NEC Hong Kong Limited, Hung Hom, Hong Kong
| | - Ming-Ting So
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Yuen-Yung Lee
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Wai-Yan Chan
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Lok-Ying Chua
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Hiu-Lok Lam
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Wing-Tung Lam
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Hin-Miu Li
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Wing-To Leung
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Yu-Hei Ng
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Wing-Ting Wong
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
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9
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Pang RCC, Ho MSH, Wong PWC. A Review of the Literature on the Multiple Forms of Stigmatization of Caregivers of Children with Autism Among Ethnic Minority Groups. J Racial Ethn Health Disparities 2024; 11:545-559. [PMID: 36877377 DOI: 10.1007/s40615-023-01540-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 02/13/2023] [Accepted: 02/14/2023] [Indexed: 03/07/2023]
Abstract
Multiple forms of stigmatization are experienced by caregivers of children with autism among ethnic minority (EM) groups in various countries. Such forms of stigmatization can lead to delayed assessment and services for mental health among children and caregivers. This review identified the research literature on the types of stigmatization experienced by caregivers of children with autism with an EM background. A total of 19 studies published after 2010 (i.e., 12 from the USA, 2 from the UK, 1 from Canada, and 1 from New Zealand) of caregivers of 20 ethnicities were identified and reviewed, and their reporting qualities systematically also assessed. Four main themes: (1) self-stigma, (2) social stigma, (3) stigma towards EM parents of children on the autism spectrum, and (4) service utilization stigma, and nine sub-themes were identified. The discrimination experienced by caregivers were extracted, synthesized, and further discussed. While the reporting quality of the studies included is good, the depth of the understanding of this under-researched yet important phenomenon is very limited. The multiple forms of stigmatization experiences are complex, and it may be difficult to disentangle whether the causes of stigmatization were autism and/or EM related, and the types of stigmatization can vary enormously among different ethnic groups in different societies. More quantitative studies are needed to quantify the impacts of multiple forms of stigmatization on families of children with autism in EM groups so that more socially inclusive support for caregivers with an EM background in host countries can be developed.
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Affiliation(s)
| | - Mimi S H Ho
- Department of Special Education and Counselling, The Education University of Hong Kong, 10 Lo Ping Road, Tai Po, Hong Kong
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10
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Coulter KL, Moreno P, Barton M, Dumont-Mathieu T, Robins DL, Fein DA. Validity of the Toddler Autism Symptom Inventory in Non-Hispanic White and Black Toddlers. J Autism Dev Disord 2024; 54:339-352. [PMID: 36316523 PMCID: PMC10148924 DOI: 10.1007/s10803-022-05756-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/11/2022] [Indexed: 05/01/2023]
Abstract
Racial disparities exist in autism diagnosis, and yet, the development of most diagnostic tools has not explicitly examined measurement equity between racial and ethnic groups. We examined the validity of the Toddler Autism Symptom Inventory (TASI), a semi-structured interview developed for diagnosis of toddlers, in non-Hispanic Black/African American and non-Hispanic White children. After controlling for group differences in socio-economic status, no differences in diagnosis, age at diagnosis, mean developmental level, or autism severity were found. TASI ROC curves for both groups, in the overall sample, and in samples stratified by SES, showed high AUC values. Validity of two cutoff scores was acceptable. Lack of significant differences in TASI score or responses to individual items suggests similar symptomatology. These results provide early support for the use of the TASI in diagnostic evaluations of Black and White children.
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Affiliation(s)
- Kirsty L Coulter
- University of Connecticut, 406 Unit 1020, Babbidge Rd, 06269, Storrs, CT, USA.
| | - Paula Moreno
- University of Connecticut, 406 Unit 1020, Babbidge Rd, 06269, Storrs, CT, USA
| | - Marianne Barton
- University of Connecticut, 406 Unit 1020, Babbidge Rd, 06269, Storrs, CT, USA
| | - Thyde Dumont-Mathieu
- University of Connecticut School of Medicine, Connecticut Children's Medical Center, Farmington, CT, USA
| | | | - Deborah A Fein
- University of Connecticut, 406 Unit 1020, Babbidge Rd, 06269, Storrs, CT, USA
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11
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Mukherjee D, Bhavnani S, Lockwood Estrin G, Rao V, Dasgupta J, Irfan H, Chakrabarti B, Patel V, Belmonte MK. Digital tools for direct assessment of autism risk during early childhood: A systematic review. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2024; 28:6-31. [PMID: 36336996 PMCID: PMC10771029 DOI: 10.1177/13623613221133176] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
LAY ABSTRACT The challenge of finding autistic children, and finding them early enough to make a difference for them and their families, becomes all the greater in parts of the world where human and material resources are in short supply. Poverty of resources delays interventions, translating into a poverty of outcomes. Digital tools carry potential to lessen this delay because they can be administered by non-specialists in children's homes, schools or other everyday environments, they can measure a wide range of autistic behaviours objectively and they can automate analysis without requiring an expert in computers or statistics. This literature review aimed to identify and describe digital tools for screening children who may be at risk for autism. These tools are predominantly at the 'proof-of-concept' stage. Both portable (laptops, mobile phones, smart toys) and fixed (desktop computers, virtual-reality platforms) technologies are used to present computerised games, or to record children's behaviours or speech. Computerised analysis of children's interactions with these technologies differentiates children with and without autism, with promising results. Tasks assessing social responses and hand and body movements are the most reliable in distinguishing autistic from typically developing children. Such digital tools hold immense potential for early identification of autism spectrum disorder risk at a large scale. Next steps should be to further validate these tools and to evaluate their applicability in a variety of settings. Crucially, stakeholders from underserved communities globally must be involved in this research, lest it fail to capture the issues that these stakeholders are facing.
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Affiliation(s)
- Debarati Mukherjee
- Indian Institute of Public Health - Bengaluru, Public Health Foundation of India, India
| | | | | | - Vaisnavi Rao
- Institute for Democracy and Economic Affairs (IDEAS), Malaysia
| | | | | | | | - Vikram Patel
- Child Development Group, Sangath, India
- Harvard Medical School, USA
- Harvard T.H. Chan School of Public Health, USA
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12
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Attar SM, Bradstreet LE, Ramsey RK, Kelly K, Robins DL. Validation of the Electronic Modified Checklist for Autism in Toddlers, Revised with Follow-Up: A Nonrandomized Controlled Trial. J Pediatr 2023; 262:113343. [PMID: 36736890 PMCID: PMC10390646 DOI: 10.1016/j.jpeds.2022.11.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 10/20/2022] [Accepted: 11/30/2022] [Indexed: 02/04/2023]
Abstract
OBJECTIVE To examine the classification rates and screening properties, including sensitivity and specificity, of the web-based Modified Checklist for Autism in Toddler, Revised with Follow-Up (M-CHAT-R/F) compared with paper-phone administration, and to determine the extent to which electronic M-CHAT-R/F streamlines screening, increases screening fidelity, increases diagnostic evaluation participation, and decreases waiting time from screening to evaluation compared with paper-phone modality. STUDY DESIGN Primary-care practices in urban and suburban settings administered either the web-based or paper-phone M-CHAT-R/F using a prospective nonrandomized control design. Toddlers (n = 17 900) were screened between 2009 and 2016 at routine well-child check-ups. Toddlers who screened at risk on the M-CHAT-R/F were invited to complete diagnostic evaluations; 176 children were diagnosed with autism. The χ2, Fisher exact, and t-tests, as well as regression and screening properties, were used to compare outcome distributions, screening properties, and implementation by modality. RESULTS Classification rates of the initial M-CHAT-R into low, medium, and high risk were significantly different across modalities with very small effect sizes. Sensitivity and specificity were high across both modalities. For children in the medium-risk range, the web-based modality had a greater rate of predicting risk for autism after Follow-Up compared with the paper-phone modality, and the web eliminated delay between initial screen and Follow-Up. The web-based modality showed increased screening fidelity, no data loss, and similar rates of evaluation attendance and time to evaluation from Follow-Up administration. CONCLUSIONS The web-based M-CHAT-R/F is a valid tool for universal autism screening. Systems-level decisions should balance the increased feasibility of the electronic administration with the increase in Follow-Up accuracy provided by skilled clinician interview.
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13
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Segre G, Cargnelutti C, Bersani C, Njogu W, Roberti E, Campi R, De Vita MV, Morino G, Canevini MP, Bonati M. Early detection of neurodevelopmental disorders in African children living in informal settlements in Nairobi. BMJ Paediatr Open 2023; 7:e002117. [PMID: 37890890 PMCID: PMC10619007 DOI: 10.1136/bmjpo-2023-002117] [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: 06/06/2023] [Accepted: 09/28/2023] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND Children in low-income and middle-income countries (LMICs) are at a substantially increased risk of delayed physical, emotional and sociocognitive outcomes, with consequential neurodevelopmental disorders. Evidence based, cost-effective and culturally appropriate screening tools are recommended for early identification of developmental disorders. METHODS The present study aims to assess the feasibility of early screening for neurodevelopmental disorders in children living in informal settlements in Nairobi, Kenya (Korogocho). The selected tools (ie, the CDC checklist and the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R)), widely used in high-income countries, are applied in two different populations: one from Kenya (LMIC) and one from Italy, to compare the different scores. RESULTS Of 509 children screened, 8.6% were classified at-risk based on the results of the screening tools. Significant risk factors are history of low birth weight and Apgar score, presence of neurological disorders, malnutrition and/or rickets, younger age of the child and older age of the mother. Caesarean section delivery, first pregnancy and mothers' older age were common risk factors among the Kenyan and the Italian samples. The Italian sample had a significantly greater rate of missed milestones. CONCLUSIONS Our data demonstrate the feasibility of using the CDC and M-CHAT-R tools in informal settlement dwellers. Further studies are needed to explore the opportunity for early diagnosis of developmental disorders in LMICs.
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Affiliation(s)
- Giulia Segre
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Cecilia Cargnelutti
- Department of Health Sciences, Università degli Studi di Milano, Milano, Italy
| | - Carlotta Bersani
- Department of Health Sciences, Università degli Studi di Milano, Milano, Italy
| | | | - Elisa Roberti
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Rita Campi
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | | | | | | | - Maurizio Bonati
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
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14
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Classifying children with ASD by service utilization and treatment type: A cluster analysis of a nationally representative United States survey. Acta Psychol (Amst) 2023; 232:103800. [PMID: 36502602 DOI: 10.1016/j.actpsy.2022.103800] [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: 06/13/2022] [Revised: 11/15/2022] [Accepted: 12/01/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND If there are patterns of the distribution of services and treatments across the population of people with ASD, these patterns should be based along clinical characteristics or other service needs and not sociodemographic characteristics unrelated to evidence-based care. We examined how individuals in a broad, nationally representative sample "grouped together" based on service utilization and services needed but not covered by insurance. By understanding various treatment patterns, clinicians, researchers, policymakers, and self-advocates and their families can better advocate for high-quality, evidence-based services to be provided equitably. METHODS Using the 2011 Survey of Pathways to Diagnosis and Services, a cluster analysis was performed to explore patterns in this population based on medication use, private services use, school-based service use, and services not covered by insurance. Differences in clusters were then explored through multinomial logistic regression. RESULTS Six clusters emerged, showing differences in the level of service/medication usage and insurance coverage. Differences across clusters were associated with the level of functional limitation and age at ASD diagnosis. Disparities by insurance type, functional limitation, and age at diagnosis exist among patterns of ASD service provision. CONCLUSIONS Our analysis showed that intervention for children with ASD can be across several scales - high and low users of services (both private and school-based), high and low users of medications, and high and low levels of reported non-covered services. The differences were clustered in multiple ways. Further research should incorporate longitudinal and nationally representative data to explore these relationships further.
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15
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Pham C, Bacon EC, Grzybowski A, Carter-Barnes C, Arias S, Xu R, Lopez L, Courchesne E, Pierce K. Examination of the impact of the Get SET Early program on equitable access to care within the screen-evaluate-treat chain in toddlers with autism spectrum disorder. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2023:13623613221147416. [PMID: 36629055 PMCID: PMC10333446 DOI: 10.1177/13623613221147416] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
LAY ABSTRACT Delays in autism spectrum disorder identification and access to care could impact developmental outcomes. Although trends are encouraging, children from historically underrepresented minority backgrounds are often identified at later ages and have reduced engagement in services. It is unclear if disparities exist all along the screen-evaluation-treatment chain, or if early detection programs such as Get SET Early that standardize, these steps are effective at ameliorating disparities. As part of the Get SET Early model, primary care providers administered a parent-report screen at well-baby examinations, and parents designated race, ethnicity, and developmental concerns. Toddlers who scored in the range of concern, or whose primary care provider had concerns, were referred for an evaluation. Rates of screening and evaluation engagement within ethnic/racial groups were compared to US Census data. Age at screen, evaluation, and treatment engagement and quantity was compared across groups. Statistical models examined whether key factors such as parent concern were associated with ethnicity or race. No differences were found in the mean age at the first screen, evaluation, or initiation or quantity of behavioral therapy between participants. However, children from historically underrepresented minority backgrounds were more likely to fall into the range of concern on the parent-report screen, their parents expressed developmental concerns more often, and pediatricians were more likely to refer for an evaluation than their White/Not Hispanic counterparts. Overall results suggest that models that support transparent tracking of steps in the screen-evaluation-treatment chain and service referral pipelines may be an effective strategy for ensuring equitable access to care for all children.
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Affiliation(s)
| | | | | | | | | | - Ronghui Xu
- University of California, San Diego, USA
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16
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Williams LN, Wieckowski AT, Dieckhaus MFS, Dai YG, Zhang F, Dumont-Mathieu T, Barton M, Fein D, Robins DL. Primary Care Clinician and Child Characteristics Impacting Autism Surveillance. Brain Sci 2022; 13:brainsci13010018. [PMID: 36672000 PMCID: PMC9855901 DOI: 10.3390/brainsci13010018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 12/12/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022] Open
Abstract
Early detection of autism provides access to early intervention and subsequently fewer lifelong challenges. However, disparities in screening have been associated with socioeconomic status (SES) and race, and disparities in surveillance have been associated with clinician knowledge and beliefs about autism identification. The present study examines associations between demographic variables and clinician beliefs, and agreement between screening results and clinician surveillance. Surveillance included activities used by the primary care clinicians (PCCs) to assess risk for autism. PCCs reported their beliefs about autism screening and identification, their sex, race, years in practice, and racial distribution of their patient population. Children's demographic information was also collected. PCCs identified children as having, or not having, an increased likelihood of autism, and parents of children completed an autism screener. Agreement between screening and surveillance results were examined across PCC, practice, and child demographics. Higher confidence in autism knowledge and screening resources, female PCC sex, and majority White practice patient demographics all predicted agreement between screening and surveillance. Female child sex and higher maternal education also predicted agreement between screening and surveillance. These findings highlight the importance of PCC screening beliefs and child and PCC demographics on the autism identification process.
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Affiliation(s)
- Lashae N. Williams
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, PA 19104, USA
- Correspondence:
| | | | - Mary F. S. Dieckhaus
- Department of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA
| | - Yael G. Dai
- Department of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA
| | - Fengqing Zhang
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA 19104, USA
| | - Thyde Dumont-Mathieu
- Department of Pediatrics, University of Connecticut School of Medicine, Farmington, CT 06032, USA
| | - Marianne Barton
- Department of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA
| | - Deborah Fein
- Department of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA
| | - Diana L. Robins
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, PA 19104, USA
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17
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Wieckowski AT, Zuckerman KE, Broder-Fingert S, Robins DL. Addressing current barriers to autism diagnoses through a tiered diagnostic approach involving pediatric primary care providers. Autism Res 2022; 15:2216-2222. [PMID: 36254366 DOI: 10.1002/aur.2832] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 10/03/2022] [Indexed: 12/15/2022]
Abstract
Formal autism diagnosis from a specialist trained in autism assessment is customary prior to a child accessing early, intensive autism-specific services. However, long wait lists for diagnostic evaluations and limited specialty workforce have created substantial delays. Additionally, lengthy multidisciplinary evaluations are costly to insurers, inconvenient to families, and disproportionally impact under-resourced families. Diagnostic delays can impede access to intervention services. These barriers, combined with evidence regarding the importance of receiving early, autism-specific treatment, demand new approaches enabling access to autism specific services before comprehensive evaluation. Pediatric primary care providers (PCPs) are often the only health care professionals with whom a family interacts during early childhood and can play a crucial role in helping children with autism symptoms access services. Many strategies for autism diagnosis in primary care are being developed and tested; however, they have yet to be broadly adopted by PCPs, primarily due to critical implementation barriers in primary care settings. There is also not enough evidence on the accuracy of PCPs' diagnostic impressions without extensive specialty support, resulting in PCP hesitancy in diagnosing ASD, as well as family and service provider hesitancy in accepting a PCP autism diagnosis. In this commentary, we explore the acute need for shortening waitlists for autism evaluations through a tiered diagnostic approach, in which PCPs can rule in or rule out autism in children, for whom diagnosis is clear, and refer more complex cases for specialist evaluations, and explore implementation challenges to this approach.
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Affiliation(s)
| | | | - Sarabeth Broder-Fingert
- Department of Pediatrics and Eunice Kennedy Shriver Center, UMASS Chan Medical School, Worcester, Massachusetts, USA
| | - Diana L Robins
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania, USA
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18
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Cao M, Li L, Raat H, Van Grieken A, Wang X, Lin L, Chen Q, Jing J. Socioeconomic factors and autism among 16- to 30-month-old children: Evidence from a national survey of China. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2022:13623613221132743. [DOI: 10.1177/13623613221132743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
We examined the association of socioeconomic status with the diagnosis of autism during 16–30 months of age. Using data from a national survey in China, we included 6049 children (55.6% male) in the final analysis, among which 71 of them were clinically diagnosed with autism. Adjusted for covariates, the odds ratios for having the diagnosis of autism (2.46, 95% confidence interval: [1.32, 4.59]) among children whose mother’s level is “junior middle school or below” were significantly higher than children whose mother’s level is “college or above.” Among children of lower educated mothers, there is a higher risk of being diagnosed with autism at a young age. We recommend more support for families with a low socioeconomic status to early detect, diagnose, and manage autism. Lay abstract Does being born in a family of high socioeconomic status mean a higher risk of being diagnosed with autism? The evidence from the Asian area is lacking. This research was conducted among 6049 toddlers who went through an evaluation–diagnose procedure of autism and whose parents were surveyed during the national survey of China, 2016–2017. Parents reported their education levels, occupations, family income, and ethnic background. We recruited the toddlers and parents from kindergartens, communities, and hospitals in five geographically representative areas of China. On average, these toddlers were 23 months of age. We found toddlers whose mothers had less than 9 years of education (junior middle school or below) had 2.46 times the chance to get a diagnosis of autism, compared with toddlers whose mothers had more than 15 years of education (college or above). We also found that 1.17 toddlers could be diagnosed with autism in each 100 Chinese toddlers. These findings have important implications for providing support to families that have low socioeconomic status, especially families with a mother who did not complete 9 years of education. Early detection programs focused on children from low socioeconomic backgrounds should be promoted.
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Affiliation(s)
| | - Li Li
- Maternity and Children Health Care Hospital of Luohu District, China
| | - Hein Raat
- Erasmus University Medical Centre, The Netherlands
| | | | | | | | - Qiang Chen
- Zhuhai Women and Children’s Hospital, China
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19
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Wallis KE, Nekrasova E, Bennett AE, Fiks AG, Gerdes M, Jenssen BP, Miller JS, Shu D, Guthrie W. Autism Spectrum Disorder Screening During the COVID-19 Pandemic in a Large Primary Care Network. Acad Pediatr 2022; 22:1384-1389. [PMID: 35460894 PMCID: PMC9020644 DOI: 10.1016/j.acap.2022.04.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 04/12/2022] [Accepted: 04/13/2022] [Indexed: 01/18/2023]
Abstract
OBJECTIVE To assess the impact of the COVID-19 pandemic on screening for autism spectrum disorder (ASD) and screening equity among eligible children presenting for well-child care in a large primary care pediatric network, we compared rates of ASD screening completion and positivity during the pandemic to the year prior, stratified by sociodemographic factors. METHODS Patients who presented for in-person well-child care at 16 to 26 months between March 1, 2020 and February 28, 2021 (COVID-19 cohort, n = 24,549) were compared to those who presented between March 1, 2019 and February 29, 2020 (pre-COVID-19 cohort, n = 26,779). Demographics and rates of completion and positivity of the Modified Checklist for Autism in Toddlers with Follow-up (M-CHAT/F) were calculated from the electronic health record and compared by cohort using logistic regression models. RESULTS Total eligible visits decreased by 8.3% between cohorts, with a greater decline in Black and publicly insured children. In the pre-COVID-19 cohort, 89.0% of eligible children were screened at least once, compared to 86.4% during the pandemic (P < 0.001). Significant declines in screening completion were observed across all sociodemographic groups except among Asian children, with the sharpest declines among non-Hispanic White children. Sociodemographic differences were not observed in screen-positive rates by cohort. CONCLUSIONS Well-child visits and ASD screenings declined across groups, but with different patterns by race and ethnicity during the COVID-19 pandemic. Findings regarding screen-completion rates should not be interpreted as a decline in screening disparities, given differences in who presented for care. Strategies for catch-up screening for all children should be considered.
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Affiliation(s)
- Kate E Wallis
- Division of Developmental and Behavioral Pediatrics (KE Wallis, AE Bennett, JS Miller, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Pediatrics (KE Wallis, AE Bennett, AG Fiks, M Gerdes, BP Jenssen, JS Miller, D Shu, and W Guthrie), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa; Center for Autism Research (KE Wallis, AE Bennett, JS Miller, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Center for Pediatric Clinical Effectiveness (KE Wallis, E Nekrasova, AG Fiks, M Gerdes, BP Jenssen, D Shu, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa.
| | - Ekaterina Nekrasova
- Center for Pediatric Clinical Effectiveness (KE Wallis, E Nekrasova, AG Fiks, M Gerdes, BP Jenssen, D Shu, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; The Possibilities Project (E Nekrasova, AG Fiks, BP Jenssen), Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Amanda E Bennett
- Division of Developmental and Behavioral Pediatrics (KE Wallis, AE Bennett, JS Miller, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Pediatrics (KE Wallis, AE Bennett, AG Fiks, M Gerdes, BP Jenssen, JS Miller, D Shu, and W Guthrie), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa; Center for Autism Research (KE Wallis, AE Bennett, JS Miller, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Alexander G Fiks
- Department of Pediatrics (KE Wallis, AE Bennett, AG Fiks, M Gerdes, BP Jenssen, JS Miller, D Shu, and W Guthrie), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa; Center for Pediatric Clinical Effectiveness (KE Wallis, E Nekrasova, AG Fiks, M Gerdes, BP Jenssen, D Shu, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; The Possibilities Project (E Nekrasova, AG Fiks, BP Jenssen), Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Marsha Gerdes
- Department of Pediatrics (KE Wallis, AE Bennett, AG Fiks, M Gerdes, BP Jenssen, JS Miller, D Shu, and W Guthrie), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa; Center for Pediatric Clinical Effectiveness (KE Wallis, E Nekrasova, AG Fiks, M Gerdes, BP Jenssen, D Shu, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Brian P Jenssen
- Department of Pediatrics (KE Wallis, AE Bennett, AG Fiks, M Gerdes, BP Jenssen, JS Miller, D Shu, and W Guthrie), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa; Center for Pediatric Clinical Effectiveness (KE Wallis, E Nekrasova, AG Fiks, M Gerdes, BP Jenssen, D Shu, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; The Possibilities Project (E Nekrasova, AG Fiks, BP Jenssen), Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Judith S Miller
- Division of Developmental and Behavioral Pediatrics (KE Wallis, AE Bennett, JS Miller, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Pediatrics (KE Wallis, AE Bennett, AG Fiks, M Gerdes, BP Jenssen, JS Miller, D Shu, and W Guthrie), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa; Center for Autism Research (KE Wallis, AE Bennett, JS Miller, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Child and Adolescent Psychiatry and Behavioral Sciences (JS Miller and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Psychiatry, Perelman School of Medicine (JS Miller and W Guthrie), University of Pennsylvania, Philadelphia, Pa
| | - Di Shu
- Department of Pediatrics (KE Wallis, AE Bennett, AG Fiks, M Gerdes, BP Jenssen, JS Miller, D Shu, and W Guthrie), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa; Center for Pediatric Clinical Effectiveness (KE Wallis, E Nekrasova, AG Fiks, M Gerdes, BP Jenssen, D Shu, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Biostatistics, Epidemiology and Informatics (D Shu), University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa
| | - Whitney Guthrie
- Division of Developmental and Behavioral Pediatrics (KE Wallis, AE Bennett, JS Miller, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Pediatrics (KE Wallis, AE Bennett, AG Fiks, M Gerdes, BP Jenssen, JS Miller, D Shu, and W Guthrie), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa; Center for Autism Research (KE Wallis, AE Bennett, JS Miller, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Center for Pediatric Clinical Effectiveness (KE Wallis, E Nekrasova, AG Fiks, M Gerdes, BP Jenssen, D Shu, and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Child and Adolescent Psychiatry and Behavioral Sciences (JS Miller and W Guthrie), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Psychiatry, Perelman School of Medicine (JS Miller and W Guthrie), University of Pennsylvania, Philadelphia, Pa
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20
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Wallace-Watkin C, Sigafoos J, Waddington H. Barriers and facilitators for obtaining support services among underserved families with an autistic child: A systematic qualitative review. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2022; 27:588-601. [PMID: 36081366 DOI: 10.1177/13623613221123712] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
LAY ABSTRACT Families from underrepresented ethnic or racial groups and those with limited financial resources could experience more difficulty in accessing support services for their autistic child due to certain types of barriers. We searched academic journals, websites, and other sources for studies which looked at what barriers might be present for such families and what might help families access support services for their autistic child. The search found 18 studies. Results from each study were examined and coded into themes. Parents reported that accessibility, diversity of support services, and stigma influenced their experiences with support services. We discuss what these findings might mean for future research and for service delivery.
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21
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Deveau N, Washington P, Leblanc E, Husic A, Dunlap K, Penev Y, Kline A, Mutlu OC, Wall DP. Machine learning models using mobile game play accurately classify children with autism. INTELLIGENCE-BASED MEDICINE 2022; 6:100057. [PMID: 36035501 PMCID: PMC9398788 DOI: 10.1016/j.ibmed.2022.100057] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 01/10/2022] [Accepted: 03/29/2022] [Indexed: 11/23/2022]
Abstract
Digitally-delivered healthcare is well suited to address current inequities in the delivery of care due to barriers of access to healthcare facilities. As the COVID-19 pandemic phases out, we have a unique opportunity to capitalize on the current familiarity with telemedicine approaches and continue to advocate for mainstream adoption of remote care delivery. In this paper, we specifically focus on the ability of GuessWhat? a smartphone-based charades-style gamified therapeutic intervention for autism spectrum disorder (ASD) to generate a signal that distinguishes children with ASD from neurotypical (NT) children. We demonstrate the feasibility of using "in-the-wild", naturalistic gameplay data to distinguish between ASD and NT by children by training a random forest classifier to discern the two classes (AU-ROC = 0.745, recall = 0.769). This performance demonstrates the potential for GuessWhat? to facilitate screening for ASD in historically difficult-to-reach communities. To further examine this potential, future work should expand the size of the training sample and interrogate differences in predictive ability by demographic.
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Affiliation(s)
- Nicholas Deveau
- Biomedical Data Science, Stanford University, Stanford, 94305, California, United States
| | - Peter Washington
- Bioengineering, Stanford University, Stanford, 94305, California, United States
| | - Emilie Leblanc
- Pediatrics, Stanford University, Stanford, 94305, California, United States
| | - Arman Husic
- Pediatrics, Stanford University, Stanford, 94305, California, United States
| | - Kaitlyn Dunlap
- Pediatrics, Stanford University, Stanford, 94305, California, United States
| | - Yordan Penev
- Pediatrics, Stanford University, Stanford, 94305, California, United States
| | - Aaron Kline
- Pediatrics, Stanford University, Stanford, 94305, California, United States
| | - Onur Cezmi Mutlu
- Electrical Engineering, Stanford University, Stanford, 94305, California, United States
| | - Dennis P Wall
- Biomedical Data Science, Stanford University, Stanford, 94305, California, United States
- Pediatrics, Stanford University, Stanford, 94305, California, United States
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22
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Diemer MC, Gerstein ED, Regester A. Autism presentation in female and Black populations: Examining the roles of identity, theory, and systemic inequalities. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2022; 26:1931-1946. [PMID: 35899909 DOI: 10.1177/13623613221113501] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
LAY ABSTRACT Although the prevalence of autism has been rising in recent years, disparities in diagnosis still remain. Female and Black populations in the United States are diagnosed later, are more likely to have an intellectual disability, and are excluded from research as well as services designed for autistic individuals. Autistic Black girls are effectively invisible in the current scientific literature. Intersectional theory, which looks at a person as a whole, examines models that are inclusive toward diverse gender, ability, and racial/ethnic backgrounds. This theory may be a useful approach to clinical and research work with autism so that practitioners may be most effective for the whole population of autistic people. The authors recommend research focusing on inclusion of autistic populations with intellectual disability and research studies that include evaluations as part of the procedure. Clinically, the authors recommend a focus on screening all young children for autism and improving provider knowledge in working with diverse autistic populations.
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23
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Hoekstra RA. Serving the underserved: How can we reach autism families who systemically miss out on support? AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2022; 26:1315-1319. [PMID: 35757982 DOI: 10.1177/13623613221105389] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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24
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Sassu KA, Volkmar FR. Autism and intersectionality: Considerations for school‐based practitioners. PSYCHOLOGY IN THE SCHOOLS 2022. [DOI: 10.1002/pits.22757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Kari A. Sassu
- Department of Counseling and School Psychology Southern Connecticut State University New Haven Connecticut USA
| | - Fred R. Volkmar
- Center of Excellence on Autism Spectrum Disorders Yale University School of Medicine & Southern Connecticut State University New Haven Connecticut USA
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25
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Autism Screening Practices in Preschools and Early Childcare Centers: A Systematic Review. REVIEW JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS 2022. [DOI: 10.1007/s40489-022-00323-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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26
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Samadi SA, Biçak CA, Noori H, Abdalla B, Abdullah A, Ahmed L. Autism Spectrum Disorder Diagnostic Criteria Changes and Impacts on the Diagnostic Scales-Utility of the 2nd and 3rd Versions of the Gilliam Autism Rating Scale (GARS). Brain Sci 2022; 12:brainsci12050537. [PMID: 35624925 PMCID: PMC9138584 DOI: 10.3390/brainsci12050537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 04/20/2022] [Accepted: 04/21/2022] [Indexed: 11/16/2022] Open
Abstract
There is joint agreement among professionals internationally on the importance of diagnosing autism spectrum disorders (ASD) in the early stages of the emergence of symptoms. Criteria changes for the diagnosis of ASD need updated versions of the scale to make the diagnosis feasible. This study aimed to evaluate the level of overlap between two different versions of the Gilliam Autism Rating Scale (GARS-2 and GARS-3), which have been updated based on changes in DSM-IV and DSM-5 on a Kurdish sample of individuals at risk of having ASD and Intellectual Disability, referred to the Bahoz center in the Kurdistan Region of Iraq. A group of 148 cases with ASD and developmental disabilities (DD) was evaluated using the 2nd and 3rd versions of the GARS scale to understand the level of cases that confirm an ASD diagnosis in both scales. Ninety-six individuals (65%) scored about the cut-off score for being diagnosed with ASD based on the GARS-2, and 137 individuals (93%) scored above the cut-off score based on the GARS-3. Moreover, keeping updated and meeting the changing demand of standardization and cultural suitability of the updating scales is a challenge. This challenge is due to the shortage of infrastructure sources and lack of established professionals in low- and middle-income countries (LMICs). Findings indicated that GARS-3, updated based on the DSM-5, tends to diagnose children with accompanying diagnoses and different levels of symptoms severity of ASD at different age levels. Further studies are needed to help professionals and policymakers in low- and middle-income countries understand the updated versions of the available scales and depend on the older version, which must be considered cautiously.
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Affiliation(s)
- Sayyed Ali Samadi
- Institute of Nursing and Health Research, Ulster University, Newtownabbey BT37 0QB, Northern Ireland, UK
- Bahoz Centre for Children with Developmental Disabilities, Erbil 44002, The Kurdistan Region of Iraq, Iraq; (C.A.B.); (H.N.); (B.A.); (A.A.); (L.A.)
- Correspondence: ; Tel.: +964-7502040080
| | - Cemal A. Biçak
- Bahoz Centre for Children with Developmental Disabilities, Erbil 44002, The Kurdistan Region of Iraq, Iraq; (C.A.B.); (H.N.); (B.A.); (A.A.); (L.A.)
| | - Hana Noori
- Bahoz Centre for Children with Developmental Disabilities, Erbil 44002, The Kurdistan Region of Iraq, Iraq; (C.A.B.); (H.N.); (B.A.); (A.A.); (L.A.)
| | - Barez Abdalla
- Bahoz Centre for Children with Developmental Disabilities, Erbil 44002, The Kurdistan Region of Iraq, Iraq; (C.A.B.); (H.N.); (B.A.); (A.A.); (L.A.)
| | - Amir Abdullah
- Bahoz Centre for Children with Developmental Disabilities, Erbil 44002, The Kurdistan Region of Iraq, Iraq; (C.A.B.); (H.N.); (B.A.); (A.A.); (L.A.)
| | - Lizan Ahmed
- Bahoz Centre for Children with Developmental Disabilities, Erbil 44002, The Kurdistan Region of Iraq, Iraq; (C.A.B.); (H.N.); (B.A.); (A.A.); (L.A.)
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27
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Integrating a New Online Platform in Primary Care for Early Detection, Referral, and Intervention in Autism Spectrum Disorder: The First Italian Pivotal Clinical Study. Brain Sci 2022; 12:brainsci12020256. [PMID: 35204020 PMCID: PMC8869863 DOI: 10.3390/brainsci12020256] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/08/2022] [Accepted: 02/11/2022] [Indexed: 11/23/2022] Open
Abstract
Autism spectrum disorder (ASD) is a heterogeneous condition characterized by deficits in social communication and a repetitive pattern of behavior, with recent Italian prevalence estimates of 1 in 77. Although the core behavioral features of ASD appear to emerge within the first two years of life, clinical diagnosis is often not received before the third birthday. The American Academy of Pediatrics (AAP) has recommended that primary care physicians routinely screen for ASD at the 18- and 24-month visits. In Italy, the Guidelines of the Italian National Institute for Health (ISS) recommend the Checklist for Autism in Toddlers (CHAT) as a screening tool for ASD, which compares parent responses with a semistructured observation by a healthcare provider. In the Italian National Health System, pediatricians have regular visits with all children; however, there is wide variability in following screening guidelines, and some barriers have been detected. For these reasons, other studies have highlighted the advantages of using telemedicine with the potential for enhancing ASD screening practices. The current study is an examination of the implementation of the first Italian online web-based screening tool (Web Italian Network for Autism Spectrum DisorderWIN4ASD), an innovative web app for pediatricians. We present the data obtained from the screening activity through the platform by a small group of pediatricians. The results of this study show that the implemented web-based platform appears to be an effective, efficient, and sustainable way to integrate screening services into primary care.
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28
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Chen S, Zhao J, Hu X, Tang L, Li J, Wu D, Yan T, Xu L, Chen M, Huang S, Hao Y. Children neuropsychological and behavioral scale-revision 2016 in the early detection of autism spectrum disorder. Front Psychiatry 2022; 13:893226. [PMID: 35935438 PMCID: PMC9354041 DOI: 10.3389/fpsyt.2022.893226] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 06/27/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND The Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) is a widely used developmental assessment tool for children aged 0-6 years in China. The communication warning behavior subscale of CNBS-R2016 is used to assess the symptoms of autism spectrum disorder (ASD), and its value of >30 points indicates ASD based on CNBS-R2016. However, we observed that children with relatively lower values were also diagnosed with ASD later on in clinical practice. Thus, this study aimed to identify the suitable cutoff value for ASD screening recommended by the communication warning behavior of CNBS-R2016. MATERIALS AND METHODS A total of 90 typically developing (TD) children and 316 children with developmental disorders such as ASD, developmental language disorder (DLD), and global developmental delay (GDD; 130 in the ASD group, 100 in the DLD group, and 86 in the GDD group) were enrolled in this study. All subjects were evaluated based on the CNBS-R2016. The newly recommended cutoff value of communication warning behavior for screening ASD was analyzed with receiver operating curves. RESULTS Children in the ASD group presented with lower developmental levels than TD, DLD, and GDD groups in overall developmental quotient assessed by CNBS-R2016. We compared the consistency between the scores of communication warning behavior subscale and Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), Autism Diagnostic Observation Schedule, second edition (ADOS-2), and clinical diagnosis for the classification of ASD at a value of 30 based on the previously and newly recommended cutoff value of 12 by the CNBS-R2016. The Kappa values between the communication warning behavior and ABC, CARS, ADOS-2, and clinical diagnosis were 0.494, 0.476, 0.137, and 0.529, respectively, with an agreement rate of 76.90%, 76.26%, 52.03%, and 82.27%, respectively, when the cutoff point was 30. The corresponding Kappa values were 0.891, 0.816, 0.613, and 0.844, respectively, and the corresponding agreement rate was 94.62%, 90.82%, 90.54%, and 93.10%, respectively, when the cutoff point was 12. CONCLUSION The communication warning behavior subscale of CNBS-R2016 is important for screening ASD. When the communication warning behavior score is 12 points or greater, considerable attention and further comprehensive diagnostic evaluation for ASD are required to achieve the early detection and diagnosis of ASD in children.
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Affiliation(s)
- Shuling Chen
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Department of Child Health Care, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinzhu Zhao
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaolin Hu
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lina Tang
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinhui Li
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dandan Wu
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tian Yan
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lu Xu
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Min Chen
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shan Huang
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Hao
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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29
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Rosen NE, Lord C, Volkmar FR. The Diagnosis of Autism: From Kanner to DSM-III to DSM-5 and Beyond. J Autism Dev Disord 2021; 51:4253-4270. [PMID: 33624215 PMCID: PMC8531066 DOI: 10.1007/s10803-021-04904-1] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/27/2021] [Indexed: 12/27/2022]
Abstract
In this paper we review the impact of DSM-III and its successors on the field of autism-both in terms of clinical work and research. We summarize the events leading up to the inclusion of autism as a "new" official diagnostic category in DSM-III, the subsequent revisions of the DSM, and the impact of the official recognition of autism on research. We discuss the uses of categorical vs. dimensional approaches and the continuing tensions around broad vs. narrow views of autism. We also note some areas of current controversy and directions for the future.
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Affiliation(s)
| | | | - Fred R. Volkmar
- Yale University, New Haven, USA
- Southern Connecticut State University, New Haven, USA
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30
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Liu F, Scheeren AM, Grove R, Hoekstra RA, Wang K, Guo D, Wang C, Begeer S. Exploring Cultural Differences in Autistic Traits: A Factor Analytic Study of Children with Autism in China and the Netherlands. J Autism Dev Disord 2021; 52:4750-4762. [PMID: 34741233 DOI: 10.1007/s10803-021-05342-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/24/2021] [Indexed: 10/19/2022]
Abstract
Autism spectrum disorders are diagnosed globally, but recognition, interpretation and reporting may vary across cultures. To compare autism across cultures it is important to investigate whether the tools used are conceptually equivalent across cultures. This study evaluated the factor structure of the parent-reported Autism Spectrum Quotient Short Form in autistic children from China (n = 327; 3 to 17 years) and the Netherlands (n = 694; 6 to 16 years). Confirmatory factor analysis did not support the two-factor hierarchical model previously identified. Exploratory factor analysis indicated culturally variant factor structures between China and the Netherlands, which may hamper cross-cultural comparisons. Several items loaded onto different factors in the two samples, indicating substantial variation in parent-reported autistic traits between China and the Netherlands.
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Affiliation(s)
- Fangyuan Liu
- Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anke M Scheeren
- Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rachel Grove
- Faculty of Health, University of Technology Sydney, Sydney, Australia
| | - Rosa A Hoekstra
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ke Wang
- Department of Social Psychology, Zhou Enlai School of Government, Nankai University, 38 Tongyan Road, Tianjin, China
| | - Dehua Guo
- Department of Special Education, Guangxi College for Preschool Education, Nanjing, China
| | - Chongying Wang
- Department of Social Psychology, Zhou Enlai School of Government, Nankai University, 38 Tongyan Road, Tianjin, China.
| | - Sander Begeer
- Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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31
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Perochon S, Di Martino M, Aiello R, Baker J, Carpenter K, Chang Z, Compton S, Davis N, Eichner B, Espinosa S, Flowers J, Franz L, Gagliano M, Harris A, Howard J, Kollins SH, Perrin EM, Raj P, Spanos M, Walter B, Sapiro G, Dawson G. A scalable computational approach to assessing response to name in toddlers with autism. J Child Psychol Psychiatry 2021; 62:1120-1131. [PMID: 33641216 PMCID: PMC8397798 DOI: 10.1111/jcpp.13381] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 08/15/2020] [Accepted: 12/04/2020] [Indexed: 12/26/2022]
Abstract
BACKGROUND This study is part of a larger research program focused on developing objective, scalable tools for digital behavioral phenotyping. We evaluated whether a digital app delivered on a smartphone or tablet using computer vision analysis (CVA) can elicit and accurately measure one of the most common early autism symptoms, namely failure to respond to a name call. METHODS During a pediatric primary care well-child visit, 910 toddlers, 17-37 months old, were administered an app on an iPhone or iPad consisting of brief movies during which the child's name was called three times by an examiner standing behind them. Thirty-seven toddlers were subsequently diagnosed with autism spectrum disorder (ASD). Name calls and children's behavior were recorded by the camera embedded in the device, and children's head turns were coded by both CVA and a human. RESULTS CVA coding of response to name was found to be comparable to human coding. Based on CVA, children with ASD responded to their name significantly less frequently than children without ASD. CVA also revealed that children with ASD who did orient to their name exhibited a longer latency before turning their head. Combining information about both the frequency and the delay in response to name improved the ability to distinguish toddlers with and without ASD. CONCLUSIONS A digital app delivered on an iPhone or iPad in real-world settings using computer vision analysis to quantify behavior can reliably detect a key early autism symptom-failure to respond to name. Moreover, the higher resolution offered by CVA identified a delay in head turn in toddlers with ASD who did respond to their name. Digital phenotyping is a promising methodology for early assessment of ASD symptoms.
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Affiliation(s)
- Sam Perochon
- Department of Electrical and Computer Engineering, Duke University
| | | | - Rachel Aiello
- Department of Psychiatry and Behavioral Sciences, Duke University
| | | | | | - Zhuoqing Chang
- Department of Electrical and Computer Engineering, Duke University
| | - Scott Compton
- Department of Psychiatry and Behavioral Sciences, Duke University
| | - Naomi Davis
- Department of Psychiatry and Behavioral Sciences, Duke University
| | | | | | | | - Lauren Franz
- Department of Psychiatry and Behavioral Sciences, Duke University
| | | | - Adrianne Harris
- Department of Psychiatry and Behavioral Sciences, Duke University.; Department of Psychology & Neuroscience, Duke University
| | - Jill Howard
- Department of Psychiatry and Behavioral Sciences, Duke University
| | - Scott H. Kollins
- Department of Psychiatry and Behavioral Sciences, Duke University
| | - Eliana M. Perrin
- Department of Pediatrics, Duke University.; Duke Center for Childhood Obesity Research
| | - Pradeep Raj
- Department of Electrical and Computer Engineering, Duke University
| | - Marina Spanos
- Department of Psychiatry and Behavioral Sciences, Duke University
| | - Barbara Walter
- Department of Psychiatry and Behavioral Sciences, Duke University
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32
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Chang Z, Di Martino JM, Aiello R, Baker J, Carpenter K, Compton S, Davis N, Eichner B, Espinosa S, Flowers J, Franz L, Harris A, Howard J, Perochon S, Perrin EM, Krishnappa Babu PR, Spanos M, Sullivan C, Walter BK, Kollins SH, Dawson G, Sapiro G. Computational Methods to Measure Patterns of Gaze in Toddlers With Autism Spectrum Disorder. JAMA Pediatr 2021; 175:827-836. [PMID: 33900383 PMCID: PMC8077044 DOI: 10.1001/jamapediatrics.2021.0530] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Accepted: 02/05/2021] [Indexed: 12/18/2022]
Abstract
Importance Atypical eye gaze is an early-emerging symptom of autism spectrum disorder (ASD) and holds promise for autism screening. Current eye-tracking methods are expensive and require special equipment and calibration. There is a need for scalable, feasible methods for measuring eye gaze. Objective Using computational methods based on computer vision analysis, we evaluated whether an app deployed on an iPhone or iPad that displayed strategically designed brief movies could elicit and quantify differences in eye-gaze patterns of toddlers with ASD vs typical development. Design, Setting, and Participants A prospective study in pediatric primary care clinics was conducted from December 2018 to March 2020, comparing toddlers with and without ASD. Caregivers of 1564 toddlers were invited to participate during a well-child visit. A total of 993 toddlers (63%) completed study measures. Enrollment criteria were aged 16 to 38 months, healthy, English- or Spanish-speaking caregiver, and toddler able to sit and view the app. Participants were screened with the Modified Checklist for Autism in Toddlers-Revised With Follow-up during routine care. Children were referred by their pediatrician for diagnostic evaluation based on results of the checklist or if the caregiver or pediatrician was concerned. Forty toddlers subsequently were diagnosed with ASD. Exposures A mobile app displayed on a smartphone or tablet. Main Outcomes and Measures Computer vision analysis quantified eye-gaze patterns elicited by the app, which were compared between toddlers with ASD vs typical development. Results Mean age of the sample was 21.1 months (range, 17.1-36.9 months), and 50.6% were boys, 59.8% White individuals, 16.5% Black individuals, 23.7% other race, and 16.9% Hispanic/Latino individuals. Distinctive eye-gaze patterns were detected in toddlers with ASD, characterized by reduced gaze to social stimuli and to salient social moments during the movies, and previously unknown deficits in coordination of gaze with speech sounds. The area under the receiver operating characteristic curve discriminating ASD vs non-ASD using multiple gaze features was 0.90 (95% CI, 0.82-0.97). Conclusions and Relevance The app reliably measured both known and new gaze biomarkers that distinguished toddlers with ASD vs typical development. These novel results may have potential for developing scalable autism screening tools, exportable to natural settings, and enabling data sets amenable to machine learning.
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Affiliation(s)
- Zhuoqing Chang
- Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina
| | - J. Matias Di Martino
- Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina
| | - Rachel Aiello
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | - Jeffrey Baker
- Department of Pediatrics, Duke University, Durham, North Carolina
| | - Kimberly Carpenter
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | - Scott Compton
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | - Naomi Davis
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | - Brian Eichner
- Department of Pediatrics, Duke University, Durham, North Carolina
| | - Steven Espinosa
- Office of Information Technology, Duke University, Durham, North Carolina
| | - Jacqueline Flowers
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | - Lauren Franz
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
- Duke Global Health Institute, Duke University, Durham, North Carolina
| | - Adrianne Harris
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
- Department of Psychology & Neuroscience, Duke University, Durham, North Carolina
| | - Jill Howard
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | - Sam Perochon
- Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina
- Ecole Normale Supérieure Paris-Saclay, Cachan, France
| | - Eliana M. Perrin
- Department of Pediatrics, Duke University, Durham, North Carolina
- Duke Center for Childhood Obesity Research, Duke University, Durham, North Carolina
| | | | - Marina Spanos
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | - Connor Sullivan
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | | | - Scott H. Kollins
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
| | - Geraldine Dawson
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
- Duke Global Health Institute, Duke University, Durham, North Carolina
- Duke Institute for Brain Sciences, Duke University, Durham, North Carolina
| | - Guillermo Sapiro
- Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina
- Department of Biomedical Engineering, Mathematics, and Computer Sciences, Duke University, Durham, North Carolina
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White K, Stetson L, Hussain K. Integrated Behavioral Health Role in Helping Pediatricians Find Long Term Mental Health Interventions with the Use of Assessments. Pediatr Clin North Am 2021; 68:685-705. [PMID: 34044994 DOI: 10.1016/j.pcl.2021.02.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
This article explores the role of assessments in integrated behavioral health within a pediatric primary care setting, specifically exploring what valid and reliable standardized assessments may be used and for what concerns the assessment be of most use. The article also considers how assessments used by integrated behavioral health may inform the type of evidenced-based intervention that would be most appropriate and efficacious for the patient, as well as assist in determining if longer term or more formal mental health treatment may be required.
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Affiliation(s)
- Katie White
- Division of Pediatric Psychology, Western Michigan University School of Medicine, 1000 Oakland Drive, Kalamazoo, MI 49008, USA.
| | - Lydia Stetson
- Division of Pediatric Psychology, Western Michigan University School of Medicine, 1000 Oakland Drive, Kalamazoo, MI 49008, USA
| | - Khadijah Hussain
- MD Candidate Class of 2022, Western Michigan University Homer Stryker, MD School of Medicine, 1000 Oakland Drive, Kalamazoo, MI 49008, USA
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34
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Corona LL, Weitlauf AS, Hine J, Berman A, Miceli A, Nicholson A, Stone C, Broderick N, Francis S, Juárez AP, Vehorn A, Wagner L, Warren Z. Parent Perceptions of Caregiver-Mediated Telemedicine Tools for Assessing Autism Risk in Toddlers. J Autism Dev Disord 2021; 51:476-486. [PMID: 32488583 PMCID: PMC7266386 DOI: 10.1007/s10803-020-04554-9] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Telemedicine tools have potential for increasing access to diagnostic services for children with autism spectrum disorder (ASD). Past work has utilized tele-assessment procedures in which remote psychologists observe administration of interactive screening instruments by trained, on-site providers. Although promising, this approach relies on two clinicians, limiting its efficiency and scalability. The present study examined the use, acceptability, and parents’ perceptions of two caregiver-mediated tools for assessing ASD risk in toddlers, in which remote clinicians guided parents to complete interactive screening activities with their children. Most parents found tele-assessment to be comfortable, and many reported liking the parent-led nature of these tools. Parents also offered constructive feedback, which was used to modify the tele-assessment process for future study.
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Affiliation(s)
- Laura L Corona
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA. .,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA. .,Vanderbilt University Medical Center, 1207 17th Avenue, Suite 202, Nashville, TN, 37203, USA.
| | - Amy S Weitlauf
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeffrey Hine
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Anna Berman
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alexandra Miceli
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Amy Nicholson
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Psychiatry & Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Caitlin Stone
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Neill Broderick
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sara Francis
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - A Pablo Juárez
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Psychiatry & Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Special Education, Vanderbilt University, Nashville, TN, USA
| | - Alison Vehorn
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Liliana Wagner
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zachary Warren
- Vanderbilt Kennedy Center/Treatment and Research Institute for Autism Spectrum Disorders, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Psychiatry & Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Special Education, Vanderbilt University, Nashville, TN, USA
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35
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Abstract
This paper, written in honor of Professor Ed Zigler, focuses on some of the themes in developmental disabilities research that were so central to his work. It has now been nearly 80 years since Leo Kanner first identified the prototypic form - early infantile autism - of what is now autism spectrum disorder. In this article we summarize the development of the concept and the important accumulation of knowledge over time that has now led us to the recognition of a broader autism phenotype just as, at the same time, the current official diagnostic system in the USA has narrowed the concept. We also address current controversies regarding autism as the diagnosis is impacted by age and developmental factors, gender, and cultural issues. In parallel to the work on intellectual deficiency and development pioneered by Zigler and his colleagues, we summarize some of the challenges for the years ahead.
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36
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Are Developmental Monitoring and Screening Better Together for Early Autism Identification Across Race and Ethnic Groups? J Autism Dev Disord 2021; 52:203-218. [PMID: 33666797 DOI: 10.1007/s10803-021-04943-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2021] [Indexed: 10/22/2022]
Abstract
National Surveys of Children's Health (NSCH, 2016-2018) data were analyzed to determine if conjoint monitoring and screening showed stronger associations with children under 5 identified with ASD compared to monitoring alone, screening alone or no monitoring or screening; and investigate relationships between monitoring and screening across racial/ethnic subgroups. 86 of 332 children with ASD received their diagnosis in a timeframe suggesting potential monitoring and screening for identification purposes. Analyses showed that conjoint monitoring and screening and monitoring alone, but not screening alone, was associated with early identified ASD cases across race groups. Caution is warranted as interpreting NSCH monitoring and screening items solely for identification purposes is inaccurate in many cases. More research on monitoring with screening is needed.
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37
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Parikh C, Iosif AM, Ozonoff S. Brief Report: Use of the Infant-Toddler Checklist in Infant Siblings of Children with Autism Spectrum Disorder. J Autism Dev Disord 2021; 51:1007-1012. [PMID: 32219636 PMCID: PMC7529925 DOI: 10.1007/s10803-020-04468-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Few studies have explored autism spectrum disorder (ASD) screening in the first year of life. The current investigation examines the psychometric properties of the Infant-Toddler Checklist starting in the first year of life in a sample at elevated and average risk for ASD based on family history. 283 participants were followed from 6 to 36 months, when diagnostic outcome was determined. The results indicated low to moderate sensitivity, specificity, and positive predictive value across ages for broadly distinguishing any delays from typical development, as well as for more narrowly discriminating children with ASD from those who were typically developing. Implications for utilizing ASD screening tools in the first year of life with high risk samples are discussed.
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Affiliation(s)
- Chandni Parikh
- Department of Psychiatry & Behavioral Sciences, MIND Institute, University of California-Davis Health, 2825 50th Street, Sacramento, CA, 95817, USA.
| | - Ana-Maria Iosif
- Department of Public Health Sciences, University of California-Davis, Davis, CA, USA
| | - Sally Ozonoff
- Department of Psychiatry & Behavioral Sciences, MIND Institute, University of California-Davis Health, 2825 50th Street, Sacramento, CA, 95817, USA
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38
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Dai YG, Porto KS, Skapek M, Barton ML, Dumont-Mathieu T, Fein DA, Robins DL. Comparison of the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F) Positive Predictive Value by Race. J Autism Dev Disord 2021; 51:855-867. [PMID: 32125566 PMCID: PMC7483574 DOI: 10.1007/s10803-020-04428-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
The Modified Checklist for Autism in Toddlers, Revised, with Follow-Up (M-CHAT-R/F) is the most widely used screener for ASD. Despite the comparable rate of ASD in Black and White children, the M-CHAT-R/F was validated on a primarily White, Non-Hispanic sample. Few studies have assessed whether the screener performs adequately with racial minorities. This study compared the M-CHAT-R/F Positive Predictive Value (PPV), for ASD, and for any developmental condition, in Black and White children. We also examined M-CHAT-R/F item-level PPV by race. The PPVs for ASD and other developmental disorders were similar in both racial groups for total score and individual items. Therefore, our findings support the use of the M-CHAT-R/F with Black and White children.
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Affiliation(s)
- Yael G Dai
- Department of Psychological Sciences, University of Connecticut, 406 Babbidge Road, Unit 1020, Storrs, CT, 06269-1020, USA.
| | - Katelynn S Porto
- Department of Psychological Sciences, University of Connecticut, 406 Babbidge Road, Unit 1020, Storrs, CT, 06269-1020, USA
| | - Mary Skapek
- Department of Psychological Sciences, University of Connecticut, 406 Babbidge Road, Unit 1020, Storrs, CT, 06269-1020, USA
| | - Marianne L Barton
- Department of Psychological Sciences, University of Connecticut, 406 Babbidge Road, Unit 1020, Storrs, CT, 06269-1020, USA
| | - Thyde Dumont-Mathieu
- Connecticut Children's Medical Center, 282 Washington Street, Hartford, CT, 06106, USA
| | - Deborah A Fein
- Department of Psychological Sciences, University of Connecticut, 406 Babbidge Road, Unit 1020, Storrs, CT, 06269-1020, USA
| | - Diana L Robins
- A.J. Drexel Autism Institute, Drexel University, 3020 Market Street, Suite 560, Philadelphia, PA, 19104, USA
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39
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Shahrokhi H, Ghiasi A, Gholipour K, Fanid LM, Shamekhi HR, Iezadi S. Considerations about the implementation of an autism screening program in Iran from the viewpoints of professionals and parents: a qualitative study. BMC Psychiatry 2021; 21:55. [PMID: 33485323 PMCID: PMC7825177 DOI: 10.1186/s12888-021-03061-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 01/19/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND The aims of this study were to explore to explore the viewpoints of parents of children with Autism Spectrum Disorders (ASD) and professionals regarding the implementation of screening programs for ASD, to explore the challenges of the implementation of a universal screening program for ASD in Iran from their viewpoints, and, to explore their recommendations to overcome the potential challenges. METHOD This qualitative study was conducted using an inductive content analysis, between June 2018 and December 2018, in East-Azerbaijan province of Iran. Data was collected through in-depth interviews and focus group discussions. The participants were purposively selected among two groups: representatives of health system and representatives of children with ASD. A sample of 32 parents and 30 professionals were recruited in this study. RESULTS Totally, 9 main themes and 23 sub-themes were extracted in three main areas including: viewpoints of the participants about universal screening for ASD, challenges in implementation of the universal screening program, and participants' recommendations about how to overcome the potential challenges. Main challenges in implementation of the universal screening program included: shortages of ASD screening tools, weakness of the health system, lack of coordination among the ASD service providers, and social and ethical issues. CONCLUSION The parents and the professionals had different viewpoints about the implementation of ASD universal screening program in Iran. According to the professionals, there is not enough rational to implement ASD screening program for all children. However, the parents believed that universal screening program is inevitable, and it should be implemented in primary health centers during the early child-care visits. The results of this study open up unspoken issues that could help in initiating the screening program not only in Iran but also in other low- and middle-income countries as well.
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Affiliation(s)
- Hassan Shahrokhi
- grid.412888.f0000 0001 2174 8913Research Center of Psychiatry and Behavioral Science, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Akbar Ghiasi
- grid.267572.30000 0000 9494 8951HEB School of Business & Administration, University of the Incarnate Word, San Antonio, TX USA
| | - Kamal Gholipour
- grid.412888.f0000 0001 2174 8913Tabriz Health Services Management Research Center, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Leila Mehdizadeh Fanid
- grid.412831.d0000 0001 1172 3536Division of Cognitive Neuroscience. Department of Psychology, Faculty of Education and Psychology. University of Tabriz, Tabriz, Iran
| | - Hamid Reza Shamekhi
- Education Development Office (EDO), Faculty of Medicine, Tabriz Azad Islamic University, Tabriz, Iran
| | - Shabnam Iezadi
- Hospital Management Research Center, Iran University of Medical Sciences, Tehran, Iran.
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40
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Toward Novel Tools for Autism Identification: Fusing Computational and Clinical Expertise. J Autism Dev Disord 2021; 51:4003-4012. [PMID: 33417138 PMCID: PMC7791904 DOI: 10.1007/s10803-020-04857-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/19/2020] [Indexed: 01/04/2023]
Abstract
Barriers to identifying autism spectrum disorder (ASD) in young children in a timely manner have led to calls for novel screening and assessment strategies. Combining computational methods with clinical expertise presents an opportunity for identifying patterns within large clinical datasets that can inform new assessment paradigms. The present study describes an analytic approach used to identify key features predictive of ASD in young children, drawn from large amounts of data from comprehensive diagnostic evaluations. A team of expert clinicians used these predictive features to design a set of assessment activities allowing for observation of these core behaviors. The resulting brief assessment underlies several novel approaches to the identification of ASD that are the focus of ongoing research.
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41
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Testing a Tailored Social-Ecological Model for Autism Spectrum Disorders. Matern Child Health J 2021; 25:956-966. [PMID: 33394274 DOI: 10.1007/s10995-020-03064-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/07/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To propose a tailored social ecological model for Autism Spectrum Disorders and explore relationships between variables in a large nationally-representative dataset. METHODS A tailored social-ecological model was developed and examined across variables in the 2016/2017 National Survey of Children's Health. A series of iterative multivariable logistic regressions were performed including individual, family, and community/neighborhood variables. A multivariable logistic regression using state-level fixed effects was performed to understand dynamics related to macro-level policies. RESULTS In the full model, gender, disability severity, certain types of insurance coverage and household income were significantly related to ASD diagnosis. Females had lower odds of a diagnosis compared to males (aOR: 0.27; CI:0.18-0.41). Children with at least one other moderate/severe disability had odds 7.61 higher (CI:5.36-10.82) of a diagnosis than children without moderate/severe disabilities. Children with public insurance only (aOR:1.66; CI:1.14-2.41) or both private and public insurance coverage (aOR: 2.62; CI:1.6-4.16) had higher odds of a diagnosis compared to children with private insurance only. For those who reported it was "somewhat" or "very often" hard to cover basics with their income, odds of a diagnosis were higher compared to those who reported it was "never" or "hardly ever" hard to cover basics (aOR: 1.676; CI:0.21-2.56). CONCLUSIONS FOR PRACTICE Patterns of ASD diagnosis are related to individual and family characteristics. There is some evidence that a child's environment has some relationship to reported ASD diagnosis. Professionals should be aware of an individual's environmental factors or context when assessing for ASD.
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42
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Schmengler H, Cohen D, Tordjman S, Melchior M. Autism Spectrum and Other Neurodevelopmental Disorders in Children of Immigrants: A Brief Review of Current Evidence and Implications for Clinical Practice. Front Psychiatry 2021; 12:566368. [PMID: 33815159 PMCID: PMC8012490 DOI: 10.3389/fpsyt.2021.566368] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 02/24/2021] [Indexed: 12/12/2022] Open
Abstract
Children of immigrants may have higher neurodevelopmental risks than those of non-immigrant populations. Yet, some evidence suggests that this group may receive late diagnosis, and therefore miss beneficial early interventions. Clinicians may misattribute symptoms of disorders to other social, behavioral or language problems. Likewise, there might be cultural differences in parents' likelihood of perceiving or reporting first developmental concerns to clinicians. Population-based standardized screening may play an important role in addressing ethnic inequalities in the age at diagnosis, although further research focusing on cross-cultural use is necessary. Once children are diagnosed, clinicians may rely on culturally sensitive procedures (translation services, cultural mediators) to increase the accessibility of interventions and improve adherence among immigrant families. In this brief review, we provide an overview about what is currently known about the epidemiology and risk factors of neurodevelopmental disorders, paying special attention to autism spectrum disorder (ASD), in children of immigrants and suggest the necessity of population-based screening and culturally sensitive care.
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Affiliation(s)
- Heiko Schmengler
- INSERM U1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Sorbonne Université, Paris, France.,École des Hautes Études en Santé Publique, Rennes, France.,Department of Interdisciplinary Social Science, Utrecht Centre for Child and Adolescent Studies, Utrecht University, Utrecht, Netherlands
| | - David Cohen
- Department of Child and Adolescent Psychiatry, Reference Centre for Rare Psychiatric Diseases, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique Hôpitaux de Paris, Sorbonne Université, Paris, France.,Institute for Intelligent Systems and Robotics, CNRS UMR 7222, Sorbonne Université, Paris, France
| | - Sylvie Tordjman
- Pôle Hospitalo-Universitaire de Psychiatrie de l'Enfant et de l'Adolescent, Université de Rennes 1 and Centre Hospitalier Guillaume-Régnier, Rennes, France.,Integrative Neuroscience and Cognition Center, CNRS UMR 8002 and University of Paris, Paris, France
| | - Maria Melchior
- INSERM U1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Sorbonne Université, Paris, France
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43
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Harris JF, Coffield CN, Janvier YM, Mandell D, Cidav Z. Validation of the Developmental Check-In Tool for Low-Literacy Autism Screening. Pediatrics 2021; 147:peds.2019-3659. [PMID: 33303635 DOI: 10.1542/peds.2019-3659] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/09/2020] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Persistent disparities exist in early identification of autism spectrum disorder (ASD) among children from low-income families who are racial and/or ethnic minorities and where English is not the primary language. Parental literacy and level of maternal education may contribute to disparities. The Developmental Check-In (DCI) is a visually based ASD screening tool created to reduce literacy demands and to be easily administered and scored across settings. In a previous study, the DCI showed acceptable discriminative ability between ASD versus non-ASD in a young, underserved sample at high-risk for ASD. In this study, we tested the DCI among an unselected, general sample of young underserved children. METHODS Six hundred twenty-four children ages 24 to 60 months were recruited through Head Start and Early Head Start. Parents completed the DCI, Modified Checklist for Autism in Toddlers, Revised with Follow-Up, and Social Communication Questionnaire. Children scoring positive on any measure received evaluation for ASD. Those screening negative on both Modified Checklist for Autism in Toddlers, Revised with Follow-Up and Social Communication Questionnaire were considered non-ASD. RESULTS Parents were primarily Hispanic, reported high school education or less, and had public or no insurance. The DCI demonstrated good discriminative power (area under the curve = 0.80), performing well across all age groups, genders, levels of maternal education, primary language, and included ethnic and racial groups. Item-level analyses indicated that 24 of 26 DCI items discriminated ASD from non-ASD. CONCLUSIONS The DCI is a promising ASD screening tool for young, underserved children and may be of particular value in screening for ASD for those with low literacy levels or with limited English proficiency.
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Affiliation(s)
- Jill F Harris
- Children's Specialized Hospital, New Brunswick, New Jersey;
| | | | | | - David Mandell
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Zuleyha Cidav
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
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44
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Oner O, Munir KM. Modified Checklist for Autism in Toddlers Revised (MCHAT-R/F) in an Urban Metropolitan Sample of Young Children in Turkey. J Autism Dev Disord 2020; 50:3312-3319. [PMID: 31414260 DOI: 10.1007/s10803-019-04160-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The study assessed the feasibility of using a Turkish-version of the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R/F) as a screening tool for an urban low risk population of young children. M-CHAT-R/F was completed for 6712 children between ages 16 and 36 months living in Istanbul, Turkey. Autism Diagnostic Observation Schedule-2 was served as the main measure for diagnosis. M-CHAT-R/F screen was positive for 9.8% of children. At follow up interview, 39.7% of initial screen-positive children met criteria for ASD. The study identified 57 (1 in 117) children with ASD (0.8%; 95% CI 0.063-1.05%). M-CHAT-R/F performed comparably in Turkey as in United States. Implications of the study for future universal screening for autism in Turkey is also discussed.
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Affiliation(s)
- Ozgur Oner
- Department of Child Psychiatry, Bahcesehir University School of Medicine, Istanbul, Turkey.
| | - Kerim M Munir
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
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Use of the TELE-ASD-PEDS for Autism Evaluations in Response to COVID-19: Preliminary Outcomes and Clinician Acceptability. J Autism Dev Disord 2020; 51:3063-3072. [PMID: 33125622 PMCID: PMC7596626 DOI: 10.1007/s10803-020-04767-y] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2020] [Indexed: 01/19/2023]
Abstract
The COVID-19 pandemic has caused unprecedented disruptions to healthcare, including direct impacts on service delivery related to autism spectrum disorder (ASD). Caregiver-mediated tele-assessment offers an opportunity to continue services while adhering to social distancing guidelines. The present study describes a model of tele-assessment for ASD in young children, implemented in direct response to disruptions in care caused by the COVID-19 pandemic. We present preliminary data on the outcomes and provider perceptions of tele-assessments, together with several lessons learned during the period of initial implementation.
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Kerub O, Haas EJ, Meiri G, Bilenko N, Flusser H, Michaelovski A, Dinstein I, Davidovitch N, Menashe I. Ethnic Disparities in the Diagnosis of Autism in Southern Israel. Autism Res 2020; 14:193-201. [DOI: 10.1002/aur.2421] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 08/02/2020] [Accepted: 10/08/2020] [Indexed: 01/08/2023]
Affiliation(s)
- Orly Kerub
- Department of Health Systems Management Ben‐Gurion University of the Negev Beer‐Sheva Israel
- Southern district Ministry of Health Beer‐Sheva Israel
| | - Eric J. Haas
- Southern district Ministry of Health Beer‐Sheva Israel
| | - Gal Meiri
- Pre‐School Psychiatry Unit Soroka University Medical Center Beer‐Sheva Israel
| | - Natalya Bilenko
- Southern district Ministry of Health Beer‐Sheva Israel
- Department of Public Health Ben‐Gurion University of the Negev Beer‐Sheva Israel
| | - Hagit Flusser
- Zusman Child Developmental Center Soroka University Medical Center Beer‐Sheva Israel
| | - Analya Michaelovski
- Zusman Child Developmental Center Soroka University Medical Center Beer‐Sheva Israel
| | - Ilan Dinstein
- Department of Psychology Ben‐Gurion University of the Negev Beer‐Sheva Israel
- Zlotowski Center for Neuroscience Ben‐Gurion University of the Negev Beer‐Sheva Israel
| | - Nadav Davidovitch
- Department of Health Systems Management Ben‐Gurion University of the Negev Beer‐Sheva Israel
| | - Idan Menashe
- Department of Public Health Ben‐Gurion University of the Negev Beer‐Sheva Israel
- Zlotowski Center for Neuroscience Ben‐Gurion University of the Negev Beer‐Sheva Israel
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Tang C, Zheng W, Zong Y, Qiu N, Lu C, Zhang X, Ke X, Guan C. Automatic Identification of High-Risk Autism Spectrum Disorder: A Feasibility Study Using Video and Audio Data Under the Still-Face Paradigm. IEEE Trans Neural Syst Rehabil Eng 2020; 28:2401-2410. [PMID: 32991285 DOI: 10.1109/tnsre.2020.3027756] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
It is reported that the symptoms of autism spectrum disorder (ASD) could be improved by effective early interventions, which arouses an urgent need for large-scale early identification of ASD. Until now, the screening of ASD has relied on the child psychiatrist to collect medical history and conduct behavioral observations with the help of psychological assessment tools. Such screening measures inevitably have some disadvantages, including strong subjectivity, relying on experts and low-efficiency. With the development of computer science, it is possible to realize a computer-aided screening for ASD and alleviate the disadvantages of manual evaluation. In this study, we propose a behavior-based automated screening method to identify high-risk ASD (HR-ASD) for babies aged 8-24 months. The still-face paradigm (SFP) was used to elicit baby's spontaneous social behavior through a face-to-face interaction, in which a mother was required to maintain a normal interaction to amuse her baby for 2 minutes (a baseline episode) and then suddenly change to the no-reaction and no-expression status with 1 minute (a still-face episode). Here, multiple cues derived from baby's social stress response behavior during the latter episode, including head-movements, facial expressions and vocal characteristics, were statistically analyzed between HR-ASD and typical developmental (TD) groups. An automated identification model of HR-ASD was constructed based on these multi-cue features and the support vector machine (SVM) classifier; moreover, its screening performance was satisfied, for all the accuracy, specificity and sensitivity exceeded 90% on the cases included in this study. The experimental results suggest its feasibility in the early screening of HR-ASD.
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Wallis KE, Guthrie W. Identifying Autism Spectrum Disorder in Real-World Health Care Settings. Pediatrics 2020; 146:peds.2020-1467. [PMID: 32632020 PMCID: PMC7397729 DOI: 10.1542/peds.2020-1467] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/27/2020] [Indexed: 12/26/2022] Open
Affiliation(s)
- Kate E. Wallis
- Division of Developmental and Behavioral Pediatrics,,Center for Autism Research, and,PolicyLab, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; and,Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Whitney Guthrie
- Division of Developmental and Behavioral Pediatrics,,Center for Autism Research, and,Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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Carbone PS, Campbell K, Wilkes J, Stoddard GJ, Huynh K, Young PC, Gabrielsen TP. Primary Care Autism Screening and Later Autism Diagnosis. Pediatrics 2020; 146:peds.2019-2314. [PMID: 32632024 PMCID: PMC7397730 DOI: 10.1542/peds.2019-2314] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/20/2020] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVES To describe the proportion of children screened by the Modified Checklist for Autism in Toddlers (M-CHAT), identify characteristics associated with screen completion, and examine associations between autism spectrum disorder (ASD) screening and later ASD diagnosis. METHODS We examined data from children attending 18- and 24-month visits between 2013 and 2016 from 20 clinics within a health care system for evidence of screening with the M-CHAT and subsequent coding of ASD diagnosis at age >4.75 years. We interviewed providers for information about usual methods of M-CHAT scoring and ASD referral. RESULTS Of 36 233 toddlers, 73% were screened and 1.4% were later diagnosed with ASD. Hispanic children were less likely to be screened (adjusted prevalence ratio [APR]: 0.95, 95% confidence interval [CI]: 0.92-0.98), and family physicians were less likely to screen (APR: 0.12, 95% CI: 0.09-0.15). Compared with unscreened children, screen-positive children were more likely to be diagnosed with ASD (APR: 10.3, 95% CI: 7.6-14.1) and were diagnosed younger (38.5 vs 48.5 months, P < .001). The M-CHAT's sensitivity for ASD diagnosis was 33.1%, and the positive predictive value was 17.8%. Providers routinely omitted the M-CHAT follow-up interview and had uneven referral patterns. CONCLUSIONS A majority of children were screened for ASD, but disparities exist among those screened. Benefits for screen-positive children are improved detection and younger age of diagnosis. Performance of the M-CHAT can be improved in real-world health care settings by administering screens with fidelity and facilitating timely ASD evaluations for screen-positive children. Providers should continue to monitor for signs of ASD in screen-negative children.
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Affiliation(s)
| | | | - Jacob Wilkes
- Pediatric Analytics, Intermountain Healthcare, Salt
Lake City, Utah
| | | | - Kelly Huynh
- Pediatric Analytics, Intermountain Healthcare, Salt
Lake City, Utah
| | | | - Terisa P. Gabrielsen
- Department of Counseling, Psychology, and Special
Education, Brigham Young University, Provo, Utah; and
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Vargason T, Grivas G, Hollowood-Jones KL, Hahn J. Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements. Semin Pediatr Neurol 2020; 34:100803. [PMID: 32446437 PMCID: PMC7248126 DOI: 10.1016/j.spen.2020.100803] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.
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Affiliation(s)
- Troy Vargason
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY
| | - Genevieve Grivas
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY
| | - Kathryn L Hollowood-Jones
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY
| | - Juergen Hahn
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY; Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY.
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