Autism Spectrum Disorder: The Problem
Autism Spectrum Disorder (ASD) is an umbrella term that refers to a group of developmental conditions mainly characterized by difficulties in social functioning and the occurrence of repetitive behaviors. Although scientists suspect that there might be some particularities in autistic children that could help them be distinguished from their neurotypical peers, there is currently no medical test to diagnose the disorder. Nowadays, researchers are working on selecting the most appropriate and accurate methods for diagnosing children with ASD in a laboratory setting, with the two most popular approaches being genetic tests and blood testing.
PICO Question
The introduction of genetic tests is practicable due to the evidence-based practice confirming the feasibility of early interventions on the grounds of detected Fragile X Syndrome, among other comorbidities (Roberts et al., 2020). In contrast, blood tests help eliminate the possibility of lead poisoning in children with ASD alongside the metabolite levels reflecting the presence of this disease (Qin et al., 2018; Barone et al., 2018). The purpose of my study is to discover which of these methods is more accurate, with the reason being the importance of early diagnosis of ASD, which leads to better treatment outcomes. Thus, my PICO question is: are blood tests (I) done on children aged 6-8 (P) more accurate in diagnosing ASD (O) compared to genetic tests, including Fragile X Syndrome as the main precondition of this type of disorder (C)?
Search History
After having examined a number of papers to ensure they meet the research criteria, I selected five for a more thorough exploration of their contents. Genovese and Butler (2020) reviewed the role of genetic and metabolic factors which might contribute to ASD causation. Roberts et al. (2020) used a multi-method approach to determine the ASD rate in preschoolers with Fragile X syndrome. Rubenstein and Chawla (2018) conducted a review of studies that quantified a percentage of parents of ASD children with the broader autism phenotype. Barone et al. (2018) investigated the blood metabolic profile connected to ASD diagnosis through blood analysis. Qin et al. (2018) collected blood samples of children with ASD to compare to those of unaffected kids in the city of Shenzhen.
Summary of Themes
When it comes to the common themes that appeared in the works, it is interesting to note that one of them is the impossibility of drawing definite conclusions due to various limitations. For instance, in terms of sample groups, the lack of diversity is concerning: research subjects of Barone et al. (2018) were exclusively Caucasian, whereas Qin et al. (2018) studied Chinese kids only. However, the authors of both these studies, as well as Rubenstein and Chawla (2018), admit that their results would be more convincing if their sample groups had been larger and more diverse.
Moreover, it was estimated that the differences found in autistic children as compared to their neurotypical peers might not necessarily be related to ASD. For example, Barone et al. (2018) explicitly state that they are not certain whether distinct metabolite differences – found in autistic children and used as a research subject – are actually related to ASD. Qin et al. (2018) came to the same conclusion in regard to their study: higher levels of concentration of harmful metals in blood in autistic children could be related to a number of factors. Therefore, it would be premature to make particular judgments in regard to these findings.
Taking all of that into consideration, it is no surprise that another thing that all of the papers have in common is their emphasis on the necessity of an integrated approach. Genovese and Butler (2020) note that advances in genomic testing, bioinformatics approaches, and computational predictions must all be combined to help recognize possible distinctive patterns of ASD in the future. Roberts et al. (2020) speak about how a number of various ASD-specific measures implemented by them in their study are the reason why they are so confident in the legitimacy of their outcomes. Moreover, they state that all researchers must learn to conceptualize the complexities associated with ASD diagnosis if they want to achieve more valid results (Roberts et al., 2020).
Additionally, Barone et al. (2018), Qin et al. (2018), and Rubenstein and Chawla (2018) all speak about the necessity to conduct further research to confirm or refute the conclusions they arrived at in their studies. One thing is clear: in attempting to diagnose and treat autism spectrum disorder, comprehensiveness is key. When studying such a complex issue as ASD diagnosis, it is injudicious to rely only on specific techniques and approaches and look at the problem from a particular angle. It might be considered the main theme that appears in all the works and unites them together.
Answering the PICO Question
Therefore, there is no definite answer to the PICO question, as neither blood tests nor genetic tests are more accurate in diagnosing ASD in children. The authors of the studies applying both methods say the same thing: further research is needed to confirm the relevance of their conclusions, as no separate study on such a complex subject is competent enough. Additionally, no single method in isolation from others will provide outcomes that are convincing so that they are to be regarded as the solution to the issue of determining ASD.
Study Implications
Various studies show that the earlier the intervention of treatment services occurs for autistic children, the more likely their development is enhanced. Caring about the well-being of children is vital from a Biblical standpoint as they are our future. They are blessings from God, as this verse states: “And he took the children in his arms, placed his hands on them and blessed them” (Mark 10:16, n.d.). Moreover, it might be possible that if definite causes of ASD were found, a treatment that could prevent the disease from developing at all would be designed. Therefore, scientists and researchers have to join their efforts – and healthcare establishments and programs have to provide them with resources for the opportunities to determine the causes of the emergence of ASD symptoms.
Further Research
In terms of further research, a lot of things are to be taken into consideration – and, most prominently, the boundaries are to be expanded. Expanding the boundaries means attempting to make use of the findings from other fields on the same subject, increasing sampling groups and testing time, and being extremely careful in drawing conclusions. These are the main approaches each researcher studying such a multifaceted issue as ASD diagnosing is to implement. Granted, many of them already do – but if all of them are to resort to these, possibly, the answer will be found sooner than we expect.
References
Barone, R., Alaimo, S., Messina, M., Pulvirenti, A., Bastin, J., Ferro, A., Frye, R. E., & Tabbì, G. (2018). A subset of patients with autism spectrum disorders show a distinctive metabolic profile by dried blood spot analyses. Frontiers in Psychiatry, 9(636), 1-11. Web.
Genovese, A., & Butler, M. G. (2020). Clinical assessment, genetics, and treatment approaches in autism spectrum disorder (ASD). International Journal of Molecular Sciences, 21(13), 4726. Web.
Mark 10:16. (n.d.). Bible Gateway. Web.
Qin, Y. Y., Jian, B., Wu, C., Jiang, C. Z., Kang, Y., Zhou, J. X., Yang, F., & Liang, Y. (2018). A comparison of blood metal levels in autism spectrum disorder and unaffected children in Shenzhen of China and factors involved in bioaccumulation of metals. Environmental Science and Pollution Research, 25(18), 17950-17956. Web.
Roberts, J. E., Bradshaw, J., Will, E., Hogan, A. L., McQuillin, S., & Hills, K. (2020). Emergence and rate of autism in fragile X syndrome across the first years of life. Development and Psychopathology, 32(4), 1335-1352. Web.
Rubenstein, E., & Chawla, D. (2018). Broader autism phenotype in parents of children with autism: A systematic review of percentage estimates. Journal of Child and Family Studies, 27(6), 1705-1720. Web.