Final Project: Literature Review 1 Literature Review (Autism) Felicia Rzepczynski Southern New Hampshire University 2 Literature Review (Autism) In the article Continuity and change from early childhood to adolescence in autism written by McGovern and Sigman (2005) opine that there is a need for more research to improve social behavior from middle childhood/early adolescence to young adulthood since parents perceive their autistic children as less symptomatic. The study adds to the research topic on how social behavior helps improve autism spectrum disorder (ASP) in young adults. His findings concur with previous researches that highlighted the change in adaptive behavior and behavioral responsiveness to the emotions of others reduces the severity of Autism in middle school children. However, the study was limited by a lack of information regarding the children's experiences in their families, schools, and intervention programs. Another flaw of the study is the small sample size of 48 children with Autism aged 2-5 years. It implies the findings of the study and variations in techniques used cannot be generalized across studies. “The results of this study provide evidence of both continuity and change in the developmental trajectory of children with autism from early childhood to late adolescence. Diagnosis of autism spectrum disorder shows very strong stability over time in that almost all the children continue to meet diagnostic criteria as adolescents and young adults even when current behavioral observations were used to establish diagnosis.”(McGovern & Sigman, 2005). In the article Daily living skills in individuals with autism spectrum disorder from 2 to 21 years of age written by Bal et al. (2015) reverberates McGovern and Sigman (2005) findings and use longitudinal studies to demonstrate that persons with ASD benefit from daily living skills (DLS). “Daily living skills (DLS), such as personal hygiene, meal preparation, and money management, are important to independent living. Research suggests that many individuals with autism spectrum disorder exhibit impairments in daily living skills relative to their cognitive 3 skills”.(Bal et. All, 2015). The research embraces mixed modelling to investigate trajectories of DLS and the effects of early predictors such as diagnosis and language skills in children aged two. The experiment is extended to older individuals and contributes to the broader aspect of my research topic since it ascertains if children with ASD showed different trajectories of DLS compared to children with non-spectrum diagnoses. It hypothesized that children with nonspectrum diagnoses show more significant gains in DLS compared to children with ASD. The authors illustrate that emphasize that individuals with ASD and individuals with Down syndrome in adolescence and early 20s gained most from DLS compared to children. Adults and children have different patterns in DLS attainment. The article contributes to the research topic because I can learn more about interpreting results from the qualitative study conducted. The study exhibits no flaw in the logic of interpretation / systematic errors in sample size. In the article, Age related differences of executive functioning problems in everyday life of children and adolescents in the autism spectrum written by Van den Bergh et. All, The research examines the impact of executive functioning (EF) challenges in individuals with ASD. “The theory of executive dysfunction suggests that some autism symptoms might stem from executive functioning deficits. EF refers to cognitive skills that serve independent, purposive, goal-directed, and self-serving behavior” (Van de Bergh, et. All, 2014). The authors' Van den Bergh et al. (2014) use laboratory task performances on 118 children aged 6-18. They use the Behavior rating inventory of executive function (BRIEF) and discover that inhibition problems are typical among young children, unlike planning which proved to be a problem among adolescents between 12- to 14-year-old. Similar to other previous studies, the researchers illustrated that each one with ASD faces the issue of executive functioning, which relates positively to some ASD signs such as repetitive behavior. Notably, not all people with ASD have 4 clinically significant EF deficits because they evolve in their EF skills (Van Den Bergh et al., 2014). The outcome that cognitive flexibility and planning occur in individuals with ASD is inconsistent, and information on the developmental patterns of cognitive flexibility and planning in people with ASD is scanty. The study is flawed since some authors argue that BRIEF does not measure actual EF. It is in my research interest to delve deeper and comprehend how cognitive behavior affects ASD from a developmental perspective and individual differences. In the article, Analysis and detection of autism spectrum disorder using machine learning techniques written by Raj and Masood (2020) allude that neurological disease can be detected early using machine learning-based models. “Autism Spectrum Disorder (ASD) is a neuro disorder in which a person has a lifelong effect on interaction and communication with others. Autism can be diagnosed at any stage in once life and is said to be a “behavioral disease” because in the first two years of life symptoms usually appear. According to the ASD problem starts with childhood and continues to keep going on into adolescent and adulthood” (Raj et. All, 2020). According to them, ASD is a behavioral disease that can be noticed at any stage in a person's life. Raj and Masood (2020) screen 292 instances with 21 attributes and 704 instances with 21 attributes and use Logistic Regression and Support Vector Machine, among other mechanisms to predict and analyze ASD problems in a child, adolescents, and adults using three data sets. The article will help develop the research topic because ASD can be detected in good time and improve patients' mental and physical health with the increased machine learning-based models. The conclusion has no logical flaws since the authors use performance evaluation metrics to evaluate the precise model performance, such as accuracy and sensitivity. In the article, The autism puzzle: Diffuse but not pervasive neuroanatomical abnormalities in children with ASD written by Sussman et al. (2015) develop novel findings that 5 show a difference in cortical, subcortical and cerebellar between males and females. “Autism Spectrum Disorder (ASD), a life-long neurodevelopmental condition, is clinically diagnosed based on its socio-behavioral characteristics which include impaired social communication and interaction, and repetitive behavior and restricted interests. Efforts to understand this developmental condition have focused on characterizing any accompanying age-related neuropathophysiology” (Sussman et. All, 2015). A cortical analysis demonstrated that diagnosis-byage and diagnosis-by-sex interaction effects significantly impact total brain volume rather than the mean cortical thickness of the ASD respondents. Region-based cortical thickness analysis showed changes in regional changes in the left orbitofrontal cortex and left posterior cingulate gyrus. The study examining brain volume in children with ASD between the ages of 4 and 18 years shows that the brain undergoes an abnormal short overgrowth in early postnatal life, after which it is followed by growth arrest in later childhood. The findings are flawed since they represent a miniature of children who develop autism later. Besides, age-related differences in brain volume can be attributed to abnormal maturation of the cerebral cortex (Sussaman et al., 2015). Previously, studies had failed to conduct a comprehensive investigation of the cortical, subcortical, and cerebellar anatomy of children and adolescents with ASD. However, this research has shown extensive cohort studies of neurodevelopmental patterns from early childhood through adolescence, indicating brain changes with age in the participants with ASD compared with the matched controls. The findings will help advance my research and further examine whether brain development in females with ASD differs significantly from males. 6 References Bal, V. H., Kim, S., Cheong, D., & Lord, C. (2015). Daily living skills in individuals with autism spectrum disorder from 2 to 21 years of age. Autism, 19(7), 774784. https://doi.org/10.1177/1362361315575840 McGovern, C. W., & Sigman, M. (2005). Continuity and change from early childhood to adolescence in autism. Journal of Child Psychology and Psychiatry, 46(4), 401408. https://doi.org/10.1111/j.1469-7610.2004.00361.x Raj, S., & Masood, S. (2020). Analysis and detection of autism spectrum disorder using machine learning techniques. Procedia Computer Science, 167, 9941004. https://doi.org/10.1016/j.procs.2020.03.399 Sussman, D., Leung, R., Vogan, V., Lee, W., Trelle, S., Lin, S., Cassel, D., Chakravarty, M., Lerch, J., Anagnostou, E., & Taylor, M. (2015). The autism puzzle: Diffuse but not pervasive neuroanatomical abnormalities in children with ASD. NeuroImage: Clinical, 8, 170-179. https://doi.org/10.1016/j.nicl.2015.04.008 Van den Bergh, S. F., Scheeren, A. M., Begeer, S., Koot, H. M., & Geurts, H. M. (2014). Age related differences of executive functioning problems in everyday life of children and adolescents in the autism spectrum. Journal of Autism and Developmental Disorders, 44(8), 1959-1971. https://doi.org/10.1007/s10803-014-2071-4 1 Literature Review-Autism 2 Literature review-Autism Current literature points out the challenges children with autism spectrum disorder go through: labeling, anxiety, depression, difficulties in learning and segregation (Reicher, 2020), sleep problems (Liu, 2020), problems with motor skills (Jallot et al., 2021), and parent-child interaction challenges (Bontink et al., 2018). The effects of COVID-19 disruptions on children with ASD and their families have also been outlined as; loss, worry, and mood swing (Asbury et al., 2020). In her work, Reicher (2020) debates on the issue of distant education during COVID-19 for youngsters with high functioning autism spectrum disorder (ASD) opine that the children have become used to learning from their homesteads and are jittery about resuming physical learning. Reicher also attributes this to the hidden school curriculum comprising rules, values, behaviors, procedures, and norms. The unspoken curriculum in mainstream education systems leads to misunderstanding, disheartenment, and isolation among children with ASD. Reicher adds that the absence of the hidden curriculum in schools liberates children and encourages them to learn comfortably. According to her, what is known is that for now, remote learning favors children with ASD, but for the long term, it is unknown how it will play out in older children in high school and workplaces. The shortcoming of the study includes the lack of quantitative data and is based on a case study; hence may not be generalized. On the other hand, Liu et al., (2021) examined sleep issues of children with Autism and their parents' sleep. Quality of sleep is conceptualized from a multifaceted idea comprising an individual's physical, mental, social relationships, personal beliefs, and other life pieces. The study's objective was to check how the parental quality of sleep affects their ability to offer good care to the children, hence affecting the child's development. Data for the study was collected 3 using a self-administered questionnaire to further the entire family. A sample of 440 children with ASD and a control group of 344 children without ASD was used as a sample. The results showed that sleep disturbances in children with ASD affect parental QOL differently from normally growing children. Lavenne-Collot et al., (2021), on their part, looked at early motor skills in children with ASD and whether that age is marked by less frequent hand and knees crawling. The research had 79 children with ASD and a control group of 100 children with normal development. Data was collected using a questionnaire. The study was limited by its reliance on parental memory of a child's development and convenient sampling to gather the control group sample, which may not be representative hence affecting the ability to generalize the results. Bontink et al., (2018) examined the moderating role of coding strategy in parent-child interactions among children with ASD. Coding strategy is conceptualized as indicative when children have social-communicative issues like gaze following, joint attention, verbal and nonverbal communication. The study relied on existing data on 16 mothers with children who have ASD. Data collection initially involved observation and recording and later content analysis. The study's shortcoming is that it lacks the currency of the data and may not be generalized to a large group. The results indicated that; caregivers providing more arrangement and superior quality instructions had a higher incidence of creativities. This analysis has contributed to COVID -19 on the mental health of children with ASD and their families. It has identified the sleep of caregivers as directly related to the care the ASD child receives, how children with ASD prefer to learn from home rather than going to school. The review also showed that most of the studies relied on the memory of the caregivers to give observations of their child development or case studies. Opportunities identified for further 4 research are getting larger samples, recruiting parents to record their children's behaviors for a long period, and using random samples for the control group. 5 References Asbury, K., Fox, L., Deniz, E., Code, A., & Toseeb, U. (2021). How is COVID-19 affecting the mental health of children with special educational needs and disabilities and their families?. Journal of Autism and Developmental Disorders, 51(5), 1772-1780. Bontinck, C., Warreyn, P., Meirsschaut, M., & Roeyers, H. (2018). Parent-child interaction in children with autism spectrum disorder and their siblings: choosing a coding strategy. Journal of Child and Family Studies, 27(1), 91-102. Lavenne-Collot, N., Jallot, N., Maguet, J., Degrez, C., Botbol, M., & Grandgeorge, M. (2021). Early Motor Skills in Children With Autism Spectrum Disorders Are Marked by Less Frequent Hand and Knees Crawling. Perceptual and Motor Skills, 128(5), 2148-2165. Liu, R., Dong, H., Wang, Y., Lu, X., Li, Y., Xun, G., ... & Zhao, J. (2021). Sleep problems of children with Autism may independently affect the parental quality of life. Child Psychiatry & Human Development, 52(3), 488-499. Reicher, D. (2020). Debate: Remote learning during COVID‐19 for children with high functioning autism spectrum disorder. Child and adolescent mental health, 25(4), 263264. Reicher, D. (2020). Debate: Remote learning during COVID‐19 for children with high functioning autism spectrum disorder. Child and adolescent mental health, 25(4), 263-264.
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