Understanding the Evolution of Autism

Autism was first identified in 1943 by American psychiatrist Leo Kanner, who discovered it while observing 11 socially reclusive children (Harris, 2018). Through his studies, Dr. Kanner was able to differentiate the disorder from schizophrenia, suggesting that it was an issue that children were born with. In the decades following, a more sophisticated understanding of the issue and its impact has been developed, although many of Dr. Kanner’s original theories have held up (Wolff, 2004). An example of this can be found in the fact that scientists have been able to confirm that there is a genetic link to autism diagnosis, indicating that it is a condition that individuals possess at birth (O'Roak & State, 2008). This concept is further supported by research indicating that children are 8% more likely to have ASD if a sibling has previously been diagnosed (Fombonne, 2005). Interestingly, gender appears to also play a significant factor, with statistical data indicating that boys are 4 times more likely to be born with autism than girls (Fombonne, 1999). Autism is also classified as a high incidence disorder, with the National Council for Special Education recommending schools plan for an estimated 1.5 percent of their student population to be diagnosed with ASD (NCSE, 2015). While this figure is only an estimate, it allows schools to help allocate resources and support for students on the autism spectrum.

Autism is also often directly linked to a concept known as executive function (EF), which measures an individual’s ability to exert conscious control over their thoughts and actions (Najdowski, 2017). This is a relationship that will be explored further in this paper, as it is a topic that is often misunderstood in potentially harmful ways. In order to better understand the impacts that ASD has on learners, it is first important to explore the key features of the condition and how it is diagnosed. Identification of ASD which can be depended on as valid is now possible from infancy. Sound identification at such an early age is indispensable for early intervention access and if this occurs it can well lead to great progress in development and a very good prognosis for most people with ASD identified (Fountain et al., 2011). Early diagnosing of ASD also seems to be beneficial in terms of helping families to be less stressed, helping to decrease the cost to society and aiding in earlier identification of other developmental and medical conditions which may occur along with the main symptoms of autism. Through this study, it is possible to demonstrate the psychological theories for supporting individuals with ASD in practice and understanding of the strengths & challenges that arise from the profile of Autism & the relevance of need and appropriate responses in the practice.

Traditionally, autism has been identified through the detection of the presentations that commonly referred to as the Triad of Impairments, which refer to problems with social interaction, social imagination, and social communication (Wing, 1981). Social imagination refers to an individual’s ability to react with flexibility to changes in social environments and activities, as it is common for individuals with ASD to exhibit feelings of anxiety or stress when presented with sudden changes to their environment. As it can be argued that the other two elements relate to similar issues, a shift towards a more simplified dyad of impairments has occurred in recent years (Anseo, 2021). This new dyad consists of social communication impairments, and restricted or repetitive behaviors. The dyad is featured in the DSM-5 diagnostic manual, while the ICD-10 manual still uses the triad as its criteria for diagnosis (Skuse, 2020). It should be noted that the upcoming ICD-11, which is the revised and updated version of the ICD-10, will shift from the triad to the dyad (Skuse, 2020). Another common feature of ASD is sensitivity to sensory stimuli, as individuals with this condition will have a more pronounced response to changes in external environmental stimuli (Wing, et al., 2007). To further complicate the matter, the degree of severity is being considerably different amongst individuals diagnosed with ASD. These different levels of severity will require different levels of assistance and support, and correspondingly specialized interventions (Mythili & Shanavas, 2014). People diagnosed with higher functioning individuals of autism that will need little or no support, while those with more complex support needs of the spectrum will require a significant amount of help and assistance to complete basic daily tasks and responsibilities. The range and variability of ways in regards to how autism expresses itself can make it difficult to accurately plan approaches to support and intervention. In order to better understand the complexity of this matter, it is necessary to look at how ASD is diagnosed.

While autism can be diagnosed at any age, research has indicated that early detection is an important part of an effective autism support plan (Bryson et al., 2003). Detecting ASD at an early age allows for interventions to be applied while a child is still developing his or her cognitive and communication skills. Therefore, there is significant effort to diagnose this condition as early as possible, with the average age of diagnosis being only 38 months (Valicenti-McDermott et al., 2012).

While the scientific community agrees that early detection is vital, inconsistencies in diagnostic methods and mental health resources can prevent diagnosis and, in some cases, even lead to misdiagnosis with other disorders (Steiner et al., 2011). This indicates a need for clear diagnostic criteria that are agreed upon by the scientific community, as inconsistencies can be found even within institutions in the same country. For example, a study conducted in 2009 found significant variation in the diagnostic criteria being employed between school boards in different parts of the U.S. (MacFarlane & Kanaya, 2009). The exact criteria that is used may vary between different professionals, which is one of the potential causes for ongoing concerns regarding consistency in regards to how this condition is classified and identified (Steiner, et al., 2011). It is common practice to observe how the subject behaves in relation to autisms dyad of impairments. Regarding diagnosis, there are currently two main categorization programs employed by professionals to indicate diagnostic decisions: The Psychiatric Association’s (APA) Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and the World Health Organization’s (WHO) International Statistical Classification of Diseases and Related Health Problems, Tenth Edition (ICD-10) (Kelly, et al., 2019). In DSM5, autism and Asperger’s syndrome have been removed and replaced with the single diagnostic term, ASC, as used in this essay (Steiner, et al., 2011). Additionally, whilst under the DSM4 a person needed to have six marks in order to obtain a diagnosis of ASC, this has been increased to seven marks in DSM5 (Steiner, et al., 2011). This decision was based on the opinion of professionals working in the areas of education and health (Kelly, et al., 2019). By contrast, in the case of ICD10, 'abnormal characteristics that appear in a child before the age of 30 months must concern one or more subsequent aspects: firstly, the language used to communicate socially, secondly, the development of social interaction, and lastly, behavioral or emblematic play' (Renty & Roeyers., 2006). Usually, autism is first noticed by a child’s teacher or parents, who will then seek the assistance of a team who will evaluate the child for autism (Renty & Roeyers., 2006).

There is also evidence indicating a link between the diagnosis of autism and a parent’s level of education. A 2019 study found that parents who had completed their A-levels or attended college had diagnosis rates for their children that were two times higher than those who did not (Kelly, et al., 2019). There are a number of challenges that may have a negative impact on children or adults who have been diagnosed with ASD. Bonis (2016) stated that many parents are unprepared to support the needs of a child who has been classified as being moderately or severely autistic. This is partially because autism is diagnosed after birth, meaning many parents are learning about the condition only after it has been detected. Home relationships between the child and their parents or siblings are also strained by the potentially disruptive patterns of communication and behavior that are often observed in children who are on the autism spectrum (Altiere & von Kluge, 2009). This presents a challenge, as while parents may want to be involved and help in the support and intervention process, they may not know how to. One of the reasons home relationships can be strained lies in the fact that some individuals with autism, or those who have been diagnosed with conditions such as Aspergers, have considerable difficulty regulating their emotional responses (Laurent & Rubin, 2004). This can make them volatile and reactive in social situations, which can have a detrimental impact on their ability to form and maintain relationships with those around them. This has consequences that impact more than a person’s home life, as it can affect their ability to form bonds with their peers at school or work. Beyond emotional regulation, there are a wide variety of other potentially harmful ways that ASD can appear in the population. Selective mutism is an example of an extreme condition that is often exhibited by children who have been diagnosed with autism, in which they refuse to, or are unable to communicate with certain people they encounter (Steffenburg, et al., 2018). Most commonly, selective mutism causes a child to stop responding to adults or authority figures, while demonstrating no reluctance or difficulty communicating with peers. Yet another way that this condition can have a negative impact on a child’s life is the fact that it is common for those diagnosed with ASD to have difficulty with memory and knowledge retention (Steele, et al., 2007). This is particularly concerning for children who are in school, as it can have a significant impact on their academic attainment and ability to participate in classroom activities. While these challenges are concerning, there is a growing body of evidence suggesting that there are also strengths associated with autism that can provide avenues for those who have been diagnosed to lead normal and fulfilling lives.

While the challenges of ASD are concerning, a growing body of evidence has suggested that certain strengths associated with autism that can provide avenues for leading a healthy life. Thus, recognising the unique strengths associated with ASD and its characteristics is important. Hurwitz and Watson (2015) argued that autistic individuals can excel when given creative tasks or provided with the opportunity to work in a physical context or setting. In these scenarios, issues with memory retention and emotional control are emphasised less, which creates an ideal scenario for individuals with autism to find academic or professional success. Wilson and Brereton (2017) argued that expecting learners with severe forms of autism to achieve the same level of academic achievement as their peers is unfair. Instead, they advocated for an interest-based approach to learning for these students (Wilson & Brereton, 2017). In this approach, early identification of areas in which the student shows talent or interest is followed by the creation of opportunities for the student to learn and further develop his or her skills in those areas.

A wide variety of interventions can be utilised in the classroom learning environment as well. As children affecting from autism have been proven to struggle with tasks related to memory retention and focus, encouraging them to generate and answer questions while they are reading or studying is an effective way to improve knowledge retention and academic achievement (Randi et al., 2010). Doing so allows the learner to create an authentic reference from the material, thereby enabling his or her cognitive processes and supporting efforts to retain information. Advancements in technology are also creating new and exciting ways to support the needs of autistic learners in schools (Grynszpan et al., 2013). These improvements in digital media and mobile technology are allowing educators to design interventions that are interactive and engaging, thus creating another avenue of support for learners with autism.

The idea of Executive Function (EF) includes a number of mental abilities or skills such as memory, planning, impulse control and the initiation of action. When somebody has a considerably compromised degree of quality of EF they are thought of in the field as having executive dysfunction. While it is possible to define EF as how an individual interacts with their external environment, there is still a lack of consensus in the academic community as to what EF actually is or what EF actually is. For example, Hill describes EF as an umbrella term, which consists of a range of cognitive functions that govern an individual’s ability to interact with their environment (Hill, 2004). Hill goes on to state that functions related to inhibition, impulse control, and working memory are all intrinsically linked to EF. Najdowski expands on this, stating that EF refers to an individual’s ability to solve problems in order to accomplish tasks and goals, with the brain itself acting as the operating system that controls these cognitive processes (Najdowski, 2017). Here it can be observed that EF has already been described as being functions, an ability and an operating system. It has also been characterized as mental processes. There are a number of other definitions. This has led to some uncertainty and inconsistency in research into EF including its role in autism. Najdowski (2017) suggests that if somebody were not already familiar with EF it would probably sound like a complicated mess. She also stated that she felt this way the first time she'd heard about them. However, it wouldn't generally be disputed by people in the field that EF include things like impulse control, inhibition, self-awareness, problem solving and working memory, capacities which have an important role in organizing and carrying out general life tasks and dealing with life on the whole (Frazier, 2012). For example, Ozonoff (1997) stated that executive dysfunction has strong connections to conditions such as schizophrenia and attention deficit hyperactivity disorder, both of which are also considered to be high-prevalence disorders. The study is effective to review the theories and concepts of autism which further provides a scope to understand the symptoms of autism among the children and support them to overcome the issues. As per the study, the professionals try to intervene to support the children and conduct the Modified Checklist for Autism in Toddlers for understanding their activities and behavior. The study may include more children for conducting primary research so that it would be possible to analyze the presentations of the children, who are affected by autism in their early childhood.

Shortcomings in EF are often associated with autism and executive dysfunction has been proposed to underpin its main challenges (Ozonoff et al., 1991). Ozanoff et al. aimed to examine the relationship of ToM deficits and EF to each other with a group high-functioning children and adolescents with autism and comparison children. ToM deficits are involving first- and second-order false-belief and EF including planning and mental flexibility (Astle & Scerif, 2009). They reported planning ability to be impaired in autism and also reported considerable associations between selective EF (mental flexibility and planning) and ToM abilities in children. Moreover, the performance of children with autism was worse compared to comparison children on EF and ToM. However, they did not measure the proportion of individuals with autism who showed intact ToM with impaired EF.

Lopez et al. (2005) discovered that working memory, inhibition and cognitive flexibility, but not fluency or planning, seemed very likely to be related with repetitive and stereotyped behaviors in autistic adults. The authors used multiple regression analyses (multiple regression analysis is a statistical operation used to predict the value of a dependent variable based on the values of two or more independent variables) and found that no EF on its own could predict autistic spectrum disorder presentations but rather that the best predictive method for predicting autism was a model which included both relative cognitive strengths such as inworking memory and inhibition and relative cognitive weaknesses in for example flexibility and fluency (Lopez et al., 2005). Hill & Bird (2006) also discovered an association between ASD presentations and EF. The idea that executive dysfunction is strongly associated with autistic spectrum disorder is supported by results from brain imaging studies and these may relate to neuroimaging results which show structural and functional differences in the PFC (prefrontal cortex) (Castelli, 2002). Brain abnormalities have in the past been recorded in cortical volume and thickness in frontal regions of the brain and also in other regions in people with ASD (Libero et al., 2015) Another thing which has been reported between prefrontal and other areas of the cortex and subcortex is network connectivity which is abnormal and which seems to have an effect on EF. It should be noted that issues pertaining to EF are not unique to autism, as studies have proven that it also commonly a challenge for individuals who have suffered traumatic brain injuries, as well as those who possess a range of other cognitive disorders (Bosco, et al., 2018). This means that it is not a condition that is unique to autism, which makes it difficult to accurately use the concept of EF as means of explaining the presentations of ASD.

Notwithstanding a lot of research findings which seem to demonstrate a strong connection between autism and executive dysfunction, there is evidence that the association between autism's presentations and EF isn't as clear cut as some may feel (Jones et al., 2018). Many studies emphasize different EF subdomains and very few studies have looked at EF in all or most of the widely accepted portfolio of EF (Nomi & Uddin, 2015). As indicated earlier, the definition of what EF is somewhat vague and there doesn't appear to be a clear consensus. A more agreed profile of EF could well provide a greater understanding of the neural connections influencing or responsible for autism and consequently help with diagnosis, therapy and treatment. A factor which may also have an effect on equivocal results of studies is that studies do not consistently control for things which could potentially moderate the association between ASD and EF and the high cognitive variability in those with ASD (Kanner, 1943).

In summary, autism is a cognitive developmental disorder that can manifest with varying presentations and degrees of severity. Autism is generally identified through the presence of restricted or repetitive behaviours in combination with difficulties in communication and social interaction. Individuals who suffer from autism can function with minimal support in school and at the workplace, while those who have severe forms will likely need substantial assistance and support in their daily lives.

Much like autism, the concept of executive function is nuanced and varied. Thus, accurately comparing and evaluating the existing literature on executive function is difficult, as studies have focused on different aspects of executive function. Furthermore, current definitions for executive dysfunction are vague, causing a lack of consensus amongst mental health professionals regarding its diagnosis. Establishing an agreed-upon profile of executive function and dysfunction would enable a better understanding of their connection to autism. Thus, further studies focused on establishing this profile while considering the various aspects of executive function would be beneficial to the larger dialogue concerning cognitive impairment and mental health. Currently, the available evidence appears to suggest that the impairment of executive function is a condition that has a high rate of co-occurrence with autism.

Looking for further insights on Understanding factors which influence learning? Click here.

References

Altiere, M. J., & von Kluge, S. (2009). Searching for acceptance: Challenges encountered while raising a child with autism. Journal of Intellectual and Developmental Disability, 34(2), 142–152. https://doi.org/10.1080/13668250902845202.

Astle, D. E., & Scerif, G. (2009). Using developmental cognitive neuroscience to study behavioral and attentional control. Dev Psychobiol, 51(2), 107-118. https://doi.org/10.1002/dev.20350

Anseo, L. G. (2021). Autism/autistic spectrum disorders. National Council for Special Education.

Bonis, S. (2016). Stress and parents of children with autism: A review of the literature. Issues in Mental Health Nursing, 37(3), 153–163. https://doi.org/10.3109/01612840.2015.1116030.

Bryson, S. E., Rogers, S. J., & Fombonne, E. (2003). Autism spectrum disorders: Early detection, intervention, education, and psychopharmacological management. The Canadian Journal of Psychiatry, 48(8), 506–516. https://doi.org/10.1177/070674370304800802

Castelli, F. (2002). Autism, Asperger syndrome and brain mechanisms for the attribution of mental states to animated shapes. Brain, 125(8), 1839-1849.

https://doi.org/10.1093/brain/awf189

Frazier, T. W. P. D., Youngstrom, E. A. P. D., Speer, L. P. D., Embacher ,R. B. S., Law, P. M. D. M. P. H., Constantino, J. M. D., Findling, R. L. M. D., Hardan, A. Y. M. D., & Eng, C. M. D. P. D. (2012). Validation of Proposed DSM-5 Criteria for Autism Spectrum Disorder. J Am Acad Child Adolesc Psychiatry, 51(1), 28-40.e23 .

https://doi.org/10.1016/j.jaac.2011.09.021

Fombonne, E. (1999). The epidemiology of autism: A review. Psychological Medicine, 29, 769–786. https://doi.org/10.4088/jcp.v67n1226a.

Fombonne, E. (2005). Epidemiology of autistic disorder and other pervasive developmental disorders. The Journal of Clinical Psychiatry, 66, 3–8. https://doi.org/

Fountain, C., King, M. D., & Bearman, P. S .(2011). Age of diagnosis for autism: individual and community factors across 10 birth cohorts. J Epidemiol Community Health, 65(6), 503-510. https://doi.org/10.1136/jech.2009.104588

Grynszpan, O., Weiss, P. L., Perez-Diaz, F., & Gal, E. (2013). Innovative technology-based interventions for autism spectrum disorder analysis. Autism, 18(4), 346–361. https://doi.org/10.1177/1362361313476767.

Harris, J. (2018). Leo Kanner and autism: a 75-year perspective. International Review of Psychiatry, 30(1), 3–17. https://doi.org/10.1080/09540261.2018.1455646

Hill, E. L. (2004). Executive dysfunction in autism. Trends Cogn Sci, 8(1), 26-32. https://doi.org/10.1016/j.tics.2003.11.003

Hill, E. L., & Bird, C. M. (2006). Executive processes in Asperger syndrome: Patterns of performance in a multiple case series. Neuropsychologia, 44(14), 2822-2835. https://doi.org/10.1016/j.neuropsychologia.2006.06.007

Hurwitz, S., & Watson, L. R. (2015). Joint attention revisited: Finding strengths among children with autism. Autism, 20(5), 538–550. https://doi.org/10.1177/1362361315593536.

Kanner, L. (1943). Autistic disturbances of affective contact. Nervous child, 2(3), 217- 25.

Jones, C. R. G., Simonoff, E., Baird, G., Pickles, A., Marsden, A. J. S., Tregay, J., Happé, F., & Charman, T. (2018). The association between theory of mind, executive function, and the symptoms of autism spectrum disorder. Autism Res, 11(1), 95-109.

https://doi.org/10.1002/aur.1873

Kelly, B., Williams, S., Collins, S., Mushtaq, F., Mon-Williams, M., Wright, B., ... & Wright, J. (2019). The association between socioeconomic status and autism diagnosis in the United Kingdom for children aged 5–8 years of age: Findings from the Born in Bradford Cohort. Autism, 23(1), 131–140. https://doi.org/10.1177/1362361317733182

Laurent, A. C., & Rubin, E. (2004). Challenges in emotional regulation in Asperger syndrome and high-functioning autism. Topics in Language Disorders, 24(4), 286–297. https://doi.org/10.1097/00011363-200410000-00006.

Lopez, B. R., Lincoln, A. J., Ozonoff, S., & Lai, Z. (2005). Examining the Relationship between Executive Functions and Restricted, Repetitive Symptoms of Autistic Disorder. J Autism Dev Disord, 35(4), 445-460. https://doi.org/10/1007.s10803-005-

MacFarlane, J. R., & Kanaya, T. (2009). What does it mean to be autistic? Inter-state variation in special education criteria for autism services. Journal of Child and Family Studies, 662(18). https://doi.org/10.1007/s10826-009-9268-8.

Mythili, M. S., & Shanavas, A. R. M. (2014). A study on autism spectrum disorders using classification techniques. International Journal of Soft Computing and Engineering, 4(5), 88–92.

Najdowski, A. C. (2017). Flexible and focused: Teaching executive function skills in individuals with autism and attention disorders. Academic Press.

National Council for Special Education. (2015). Supporting students with autism spectrum disorder in schools. National Council for Special Education.

Nomi, J. S., & Uddin, L. Q. (2015). Developmental changes in large-scale network

connectivity in autism. Neuroimage Clin, 7(C .741-732 ,)

https://doi.org/10.1016/j.nicl.2015.02.024

O’Roak, B. J., & State, M. W. (2008). Autism genetics: Strategies, challenges, and opportunities. Autism Research, 1(1), 4–17. https://doi.org/10.1002/aur.3.

Ozonoff, S. (1997). Components of executive function in autism and other disorders. In J. Russell (Ed.), Autism as an executive disorder (pp. 179–211). Oxford University Press.

Ozonoff, S., Pennington, B. F., & Rogers, S. J. (1991). Executive function deficits in high-functioning autistic individuals: Relationship to theory of mind. Journal of Psychology and Psychiatry, 32(7), 1081–1092. https://doi.org/10.1111/j.1469-7610.1991.tb00351.x.

Randi, J., Newman, T., & Grigorenko, E. L. (2010). Teaching children with autism to read for meaning: Challenges and possibilities. Journal of Autism and Developmental Disorders, 40, 890–902. https://doi.org/10.1007/s10803-010-0938-6.

Renty, J., & Roeyers, H. (2006). Satisfaction with formal support and education for children with autism spectrum disorder: The voices of the parents. Child: Care, Health and Development, 32(3), 371–385. https://doi.org/10.1111/j.1365-2214.2006.00584.x.

Skuse, D., 2020. Autism – 25 years on: A lot has changed!. Clinical Child Psychology and Psychiatry, 25(3), pp. 721-725.

Steele, S. D., Minshew, N. J., Luna, B., & Sweeney, J. A. (2007). Spatial working memory deficits in autism. Journal of Autism and Developmental Disorders, 37(August), 605–612. https://doi.org/10.1007/s10803-006-0202-2.

Steffenburg, H., Steffenburg, S., Gillberg, C., & Billstedt, E. (2018). Children with autism spectrum disorders and selective mutism. Neuropsychiatric Disease and Treatment, 14, 1163–1169. https://doi.org/10.2147/NDT.S154966

Steiner, A. M., Koegel, L. K., Koegel, R. L., & Ence, W. A. (2011). Issues and theoretical constructs regarding parent education for autism spectrum disorder. Journal of Autism and Developmental Disorders, 42, 1218–1227. https://doi.org/10.1007/s10803-011-1194-0

Valicenti-McDermott, M., Hottinger, K., Seijo, R., & Shulman, L. (2012). Age at diagnosis of autism spectrum disorders. Journal of Pediatry, 161(3), 554–556. https://doi.org/10.1016/j.jpeds.2012.05.012

Wilson, C., & Brereton, M. P. B. (2017). Digital strategies for supporting strengths-and interests-based learning with children with autism. Assests 17: Proceedings of the 19th International ACM SIGAACCESS Conference on Computers and Accessibility, pp. 52–61. https://doi.org/10.1145/3132525.3132553

Wing, L., Gould, J. L. S. R., Nieto, C., & Libby, S. (2007). Describing the sensory abnormalities of adults with autism. Journal of Autism and Developmental Disorders, 37, 894–910. https://doi.org/10.1007/s10803-006-0218-7.

Wing, L. (1981). Language, social, and cognitive impairments in autism and severe mental retardation. Journal of Autism and Developmental Disorders, 11(1), 31–44.

Wolff, S. (2004). The history of autism. European Child and Adolescent Psychiatry, 13(10.1007/s00787-004-0363-5), 201–208. https://doi.org/10.1007/s00787-004-0363-5