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Urban and Education Disparity for Autism Spectrum Disorders in Taiwan Birth Cohort Study

Introduction to Sampling Methods in Clinical Research

Autism spectrum disorder (ASD) occurs in the first 3 year of life that prognosis due to the neurodevelopment changes that lead to the lack of social interaction and communication issue. The prevalence of the autism spectrum disorder prevalence has been reported to 1-2% that has increased from the last two decades (Park et al., 2016). One of the issues that have been associated with Autism spectrum disorder is an issue with evident screening and diagnosis. Many disparities have increased the prevalence of the Autism spectrum disorder and there is a need to reduce these disparities to decrease prevalence (Parmeggiani et al., 2019). The critical review is one of the methods that are utilized to evaluate the quality of the study by assessing a different section of the article. Different tools have been utilized to improve the assessment of the article by evaluating all aspect of the study (Klerk & Pretorius, 2019). The CASP checklist is utilized to critically review the article by utilizing set criteria for the same type of study (CASP, 2020). The report will critically review the article “Urban and Education Disparity for Autism Spectrum Disorders in Taiwan Birth Cohort Study” to understand its quality. The report will utilize the CASP checklist for the cohort study to analyse the study over the set parameters.

Did the study address a focused issue?

The article started the research by clearly focused on the issue of the disparity that occurs due to the urban area and parental education concerning the diagnosis of the Autism Spectrum disorder. The study introduced the issue and added what are the different factors that need to be considered while the diagnosis of the Autism spectrum disorder (Lung et al., 2016). The research should introduce the issue for the research as it is important to help the reader to understand the need of the study by estimating the depth of the issue (Armağan, 2013). The study discussed the importance of Modified Checklist for Autism in Toddlers (M-CHAT) as a widely employed screening tool for Autism spectrum disorder that utilizes 23 questions for the early detection of the disorder. The study clearly states that the aim of the study to utilize the Newton-Raphson iteration to identify the optimal cut-off point for 66-month-old children. The study will also explore the disparities that have a direct impact on the prevalence of Autism spectrum disorder.

Was the cohort recruited acceptably?

The study state that for research they have utilized the four-stage dataset of the Taiwan Birth Cohort Study related to the information concerning the children were 66 months old. They have utilized the national household probability sampling that is the representation of all the children in Taiwan (Lung et al., 2016). The probability sampling helps the research to improve the generalization in the study and it decreases the judgmental perspective to the study. It improves the chances of every participant to be included in the study (Elfil & Negida, 2017). The study added that there are no exclusion criteria for the study and only inclusion parameter was used for the selection of the cohort that is the period from October 2003 to January 2004 (Lung et al., 2016). The strict inclusion and exclusion in the research increase the chances of bias cohort selection that can directly hamper the result of the study (Patino & Ferreira, 2018). The study has utilized two-stage of stratified random sampling out of which the first stage include primary sampling unit was cities and town. In the second stage, new-borns were selected from the different cities and town as per the birth rate. 

Was the outcome accurately measured to minimise bias?

The study has utilized the M-CHAT for the research and they use the version that is discriminative for the Autism spectrum disorders concerning the ethnic Chinese cohort. The researcher also discussed the use of the semi-structured interview for the home visit to identify the previous episode of the Autism spectrum disorder in the children. The findings from this are used as the base for the clinical diagnosis of Autism spectrum disorder in the study (Lung et al., 2016). The Modified Checklist for Autism in Toddlers is considered to be the best screening tool for toddlers between 16 to 30 months. This is utilized to use for the parent to interpret the developmental surveillance (M-CHAT, 2020). The semi-structured interview is considered to be one of the preferred styles of the interviewing as it utilizes the open-ended question to identify participation perspective (Jamshed, 2014). Statistical analysis has been utilized in the study by utilizing different tools that are important to bias-free results (Lung et al., 2016). The statistical analysis has been considered to be best as it utilizes the right method for collection of data followed by the proper analysis and it ends up with presenting the results accurately (Ali & Bhaskar, 2016). The study utilizes the SPSS 20.0 for the analysis of the demographic distribution and optimal cut off point concerning the M-CHAT was calculated by utilizing the Newton-Raphson iteration compared to the normal control. The difference between the distributions related to the M-CHAT cut-off point criteria and ASD diagnosis compared by the Chi-Square.

Have the authors identified all-important confounding factors?

The study has included all the necessary factors that are important to improve the relevancy of the results concerning the study. The statistical analysis has considered the negative predictive value, sensitivity positive predictive value and specificity. These factors help to improve the accuracy of the results by improving the perspective of the analysis that is important for the study (Lung et al., 2016). The confounding factors are important to understand the impact of the dependent and independent variables over the study. It helps to understand the association raise between the above and beyond in the study to find a true association (Skelly et al., 2012).

Have they take account of the confounding factors in the design and/or analysis?

The studies have accurately incorporated the confounding factor in the study to improve the analysis of the study. The including the confounding factors in the study are important to balance out the cases and control that will help to improve the efficacy of the results which will improve the justification of the aim of the research (Pourhoseingholi et al., 2012). The result of the study indicates that the two failing criteria for M-CHAT include failing of 3 of the 23 and 2 of the 6 that leads to the optimal cut off of 20. This lead to the confounding factors positive predictive value is 0.79%, negative predictive value 99.80%, sensitivity 72.22% and specificity 59.68%. The optimal cut off revealed from the Newton-Raphson iteration that results in the positive predictive value 15.69%, negative predictive 99.60%, sensitivity 90.91% and specificity 99.79% that is better from the original cut-off point.

Was the follow up of subjects complete enough?

The fourth stage of the cohort study followed in the research and the last stage includes the use of the dataset for the study. This includes the follow up of the 20,095 families to evaluate their understanding concerning the Autism spectrum disorder different aspect. The Taiwan Birth Control COHORT study protocols were utilized after the approval from the institutional review board of teaching hospital Taiwan. This is followed by the informed consent from the parents for the participation in the study and follow up process (Lung et al., 2016). The study presented by Howe et al. (2013) discussed that follow up is considered to be important in the cohort study to understand the overall effectiveness of the efforts that are discussed in the study. The losses of follow up in the cohort study lead to the less accurate internal validity of the results concerning the study.

Was the follow up of subjects long enough?

The study has doesn’t mention about the duration of the following to identify that time duration is enough or not concerning the study (Lung et al., 2016). The article presented by Setia, (2016) discussed that the follow up should be maintained in such a way that both short term and long term effect can be evaluated. The duration of the follow up is not stagnant and it varies from 4 months to 3 years concerning the type of study.

What are the results of this study?

 The study has utilized the Chi-square test for the analysis that reveals that there is a significantly high percentage of the population that has been diagnosed with the Autism spectrum disorder living in the city that is p= .001. The parental levels of education have the borderline difference between those who are diagnosed with Autism spectrum disorder that is mother = 0.058 and father 0.059. The M-CHAT off score of 13/14 reveals no significant difference in the location of the residence but the difference was significant concerning the level of parental education. The study also evaluated the relation between the maternal level of education, residence location and their combined impact over the diagnoses of the Autism spectrum disorder. The results reveal that children belong to the mother with better than average level of education followed by living in the rural area has 1.14 times greater chances to be diagnosed by M-CHAT compared with the mother having low level than average education and living in the rural area. 1.79 time more chances of screened via M-CHAT in the population were mothers education level is lower than the average level of education but living in an urban area compared to the rural is the mother. The overall result indicates increase changes in the screening with M-CHAT of the lower level of education and livings in the city are highest.

How precise are the results?

The result of the study reveals that M-CHAT can be adequately utilized for the screening of 66-month-old Taiwanese children. The results also discussed that there were low cut off point but total score performed was better than the critical score in the screening of the Autism spectrum disorder (Lung et al., 2016). The finding also supported by Robins et al. (2014) by stating that one of the effective tools for the screening of the Autism spectrum disorder is M-CHAT. The integration of the screening with the surveillance decrease the age in which Autism spectrum disorder is diagnosed that improves the chances of early treatment by optimizing the prognosis.

The study presented by Lung et al. (2016) also added that urbanization is also one of the factors that lead to the disparity in the diagnosis of the Autism spectrum disorder. The results are supported by Lauritsen et al. (2014) also concluded that geographical variation is also one of the major disparity in the Autism spectrum disorder that is associated with rural and urban. The results presented by Lung et al. (2016) discussed that parental education also contributes the diagnosis of the Autism spectrum disorder and the mother with a lower level of education but living in urban have the positive result of the children over the M-CHAT. The article presented by Durkin et al. (2017) also revealed that parent education is one of the factors that impact over the screening of the Autism spectrum diagnosis. The article also added that parental education integration with the geographical location has a strong impact on the diagnosis of the Autism spectrum disorder.

Do you believe the results?

The different aspects that are included in the study increase the reliability of the outcome so the study and the results accurately justify every point with proper statistical analysis results. The study has accurately added the confounding factors to improve the association in the variable to increase understanding (Lung et al., 2016). The study presented by Fedak et al. (2014) discussed the nine important associations aspect of the Bradford Hill's that are utilized to analyse the association between the occupation and environmental exposure concerning the disease outcome. The aspect includes the strength of association, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment and analogy. The results presented by (Lung et al., 2016) have accurately justified all the aspect of the study that increases the efficacy of the results concerning the issue.

Can the results be applied to the local population?

The results are suitable to be used in the local population as the results are associated with the population-based cohort study. The results are generalised concerning the methodology of the study thus they can be utilized for the local population.

Do the results of this study fit with other available evidence?

 The results of the study are evident and they are also supported by another article concerning the disparity related to the screening and diagnosis of the Autism spectrum disorder. The article presented by Hoang et al. (2019) also discussed the disparity created by the socio-demographic factor over the diagnosis of the Autism spectrum disorder. The study presented by Bradshaw et al. (2018) also added that parental education also influences the rate of the diagnosis of the Autism spectrum disorder in 66-month-old children’s.

What are the implications of this study for practice?

The results associated with the study can be utilized to improve the screening and diagnosis method concerning the different disparities. The findings can also be used to improve the perfective of the health care workforce and their clinical practise that will increase the chances of early diagnosis of the Autism spectrum disorder. The care services can be improved concerning the findings of the study to improve the condition of the underserved children that directly decrease delayed diagnosis. These improvements can be useful to increase the perspective of the care which is important for the early diagnosis of the Autism spectrum disorder to decrease further complication.

Conclusion on Sampling Methods in Clinical Research

The critical review of the article reveals that the researcher has utilized the right methodology concerning the cohort study to improve the results. The different section that has been analysed justified the requirement of the research which is important to improve the accuracy of the results. The studies have accurately considered the different factors that are important to evaluate the different aspect that impacts the diagnosis of the Autism spectrum disorder. The study accurately justified the different factor that includes demographic and parental education directly influences the diagnosis of the Autism spectrum disorder. The studies have conducted the research considering the generalised approach that is important for the utilization of the findings in the local population that is important to address the issue. The findings of the study are applicable to improve the practice to address the delayed diagnosis of the Autism spectrum disorder. The findings of the study are important to improve the care perspective which will eventually improve the diagnosis pattern of the Autism spectrum disorder that leads to early detection followed by immediate treatment. The overall quality of the study was able to justify the requirement but it lacks to mention the follow-up stage duration in the methodology that is important of the cohort study that can hamper the findings.

References for Sampling Methods in Clinical Research

Ali, Z. & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anaesthesia60(9), 662–669. DOI: 10.4103/0019-5049.190623

Armağan A. (2013). How to write an introduction section of a scientific article? Turkish Journal of Urology39(Suppl 1), 8–9. DOI: 10.5152/tud.2013.046

Bradshaw, J., Bearss, K., McCracken, C., Smith, T., Johnson, C., Lecavalier, L., Swiezy, N. & Scahill, L. (2018). Parent education for young children with autism and disruptive behavior: Response to active control treatment. Journal of Clinical Child and Adolescent Psychology: The Official Journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 5347(sup1), S445–S455. DOI: 10.1080/15374416.2017.1381913

Durkin, M. S., Maenner, M. J., Baio, J., Christensen, D., Daniels, J., Fitzgerald, R., Imm, P., Lee, L. C., Schieve, L. A., Van Naarden Braun, K., Wingate, M. S. & Yeargin-Allsopp, M. (2017). Autism spectrum disorder among us children (2002-2010): Socioeconomic, racial, and ethnic disparities. American Journal of Public Health107(11), 1818–1826. DOI: 10.2105/AJPH.2017.304032

Elfil, M., & Negida, A. (2017). Sampling methods in clinical research; An educational review. Emergency (Tehran, Iran)5(1).

Fedak, K. M., Bernal, A., Capshaw, Z. A. & Gross, S. (2015). Applying the Bradford Hill criteria in the 21st century: How data integration has changed causal inference in molecular epidemiology. Emerging Themes in Epidemiology12(14). DOI: 10.1186/s12982-015-0037-4

Hoang, V. M., Le, T. V., Chu, T., Le, B. N., Duong, M. D., Thanh, N. M., Tac Pham, V., Minas, H. & Bui, T. (2019). Prevalence of autism spectrum disorders and their relation to selected sociodemographic factors among children aged 18-30 months in northern Vietnam, 2017. International Journal of Mental Health Systems13(29), 1-19. DOI: 10.1186/s13033-019-0285-8

Howe, L. D., Tilling, K., Galobardes, B. & Lawlor, D. A. (2013). Loss to follow-up in cohort studies: bias in estimates of socioeconomic inequalities. Epidemiology (Cambridge, Mass.)24(1), 1–9. DOI: 10.1097/EDE.0b013e31827623b1

Jamshed S. (2014). Qualitative research method-interviewing and observation. Journal of Basic and Clinical Pharmacy5(4), 87–88. DOI: 10.4103/0976-0105.141942

Klerk, W. & Pretorius, J. (2019). Guideline for conducting critical reviews in psychology research, Journal of Psychology in Africa, 29(6), 645-649, DOI: 10.1080/14330237.2019.1691793

Lauritsen, M. B., Astrup, A., Pedersen, C. B., Obel, C., Schendel, D. E., Schieve, L., Yeargin-Allsopp, M. & Parner, E. T. (2014). Urbanicity and autism spectrum disorders. Journal of Autism and Developmental Disorders44(2), 394–404. DOI: 10.1007/s10803-013-1875-y

Lung, F.-W., Chiang, T.-L., Lin, S.-J. & Shu, B.-C. (2016). Urban and education disparity for autism spectrum disorders in Taiwan birth cohort study. Journal of Autism and Developmental Disorders, 47(3), 599–606. DOI:10.1007/s10803-016-2980-5 

M-CHAT. (2020). About. Retrieved from: https://m-chat.org/

Park, H. R., Lee, J. M., Moon, H. E., Lee, D. S., Kim, B. N., Kim, J., Kim, D. G. & Paek, S. H. (2016). A short review on the current understanding of autism spectrum disorders. Experimental Neurobiology25(1), 1–13. DOI: 10.5607/en.2016.25.1.1

Parmeggiani, A., Corinaldesi, A. & Posar, A. (2019). Early features of autism spectrum disorder: a cross-sectional study. Italian Journal of Pediatrics, 45(1). DOI:10.1186/s13052-019-0733-8 

Patino, C. M. & Ferreira, J. C. (2018). Inclusion and exclusion criteria in research studies: definitions and why they matter. Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia44(2), 84. DOI: 10.1590/s1806-37562018000000088

Pourhoseingholi, M. A., Baghestani, A. R. & Vahedi, M. (2012). How to control confounding effects by statistical analysis. Gastroenterology and Hepatology from Bed to Bench5(2), 79–83.

Robins, D. L., Casagrande, K., Barton, M., Chen, C. M., Dumont-Mathieu, T. & Fein, D. (2014). Validation of the modified checklist for Autism in toddlers, revised with follow-up (M-CHAT-R/F). Pediatrics133(1), 37–45. DOI: 10.1542/peds.2013-1813

Setia M. S. (2016). Methodology series module 1: Cohort studies. Indian Journal of Dermatology61(1), 21–25. DOI: 10.4103/0019-5154.174011

Skelly, A. C., Dettori, J. R., & Brodt, E. D. (2012). Assessing bias: The importance of considering confounding. Evidence-based Spine-Care Journal3(1), 9–12. DOI: 10.1055/s-0031-1298595

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