By Arianna Barroso
Many individuals affected with Reading Disorders (RD), are also affected by Math Disorders (MD) commonly referred to comorbidity. The study being critiqued aimed to investigate three domain-general cognitive ability components, which include processing speed, temporal processing, and working memory. The goal was to learn whether these three components were cognitive risk factors for reading or math disorders. Or, if they were also co-occurring symptoms for individuals with attention difficulties. The problem statement was clearly stated in the study; it also gave an explanation about the three cognitive ability components. The author explains that although there has been previous research on the components, it has always been associated with Specific Learning Disorders. But, there is still a large need to explore if there are separable or shared cognitive deficits for MD and RD. The purpose of the study was to investigate and understand if processing speed, memory skills, and temporal processing are risk factors for Reading Disorders or Math Disorders. Also, the research focused on investigating if having these disorders is attributed to attentional difficulties shown by the students. Processing Speed Deficits are co-occurring with attention difficulties. Deficits in rapid automatized deficits (RAN) showed the deficits of verbal processing speeds in the children. Temporal Processing according to the research is described as “verbal time estimation, time reproduction, and time discrimination skills”. (Moll, K., Göbel, S. M., Gooch, D., Landerl, K., & Snowling, M. J. 2016) Temporal Processing is especially prevalent in individuals with attention disorders, as well as reading disorders. Hence, the research to see the co-morbidity of RD and attention deficits.
Cognitive Risk Factors for Specific Learning Disorder: Processing Speed, Temporal Processing, and Working Memory
Research Problem
Many individuals affected with Reading Disorders (RD), are also affected by Math Disorders (MD) commonly referred to comorbidity. The study being critiqued aimed to investigate three domain-general cognitive ability components, which include processing speed, temporal processing, and working memory. The goal was to learn whether these three components were cognitive risk factors for reading or math disorders. Or, if they were also co-occurring symptoms for individuals with attention difficulties. The problem statement was clearly stated in the study; it also gave an explanation about the three cognitive ability components. The author explains that although there has been previous research on the components, it has always been associated with Specific Learning Disorders. But, there is still a large need to explore if there are separable or shared cognitive deficits for MD and RD.
The purpose of the study was to investigate and understand if processing speed, memory skills, and temporal processing are risk factors for Reading Disorders or Math Disorders. Also, the research focused on investigating if having these disorders is attributed to attentional difficulties shown by the students. Processing Speed Deficits are co-occurring with attention difficulties. Deficits in rapid automatized deficits (RAN) showed the deficits of verbal processing speeds in the children. Temporal Processing according to the research is described as “verbal time estimation, time reproduction, and time discrimination skills”. (Moll, K., Göbel, S. M., Gooch, D., Landerl, K., & Snowling, M. J. 2016) Temporal Processing is especially prevalent in individuals with attention disorders, as well as reading disorders. Hence, the research to see the co-morbidity of RD and attention deficits.
When reviewing this research, the approach used was a quantitative approach. Quantitative studies include numbers in the research, there were means, standard deviations, graphs and charts included to portrayed the information obtained from the sample of children. This allowed the readers to see the precise statistical summary of results. But, in a qualitative approach there is a narrative summary of the results. There is also precise description of the procedures in the research, a specific design control, and breaking down the phenomenon into different aspects for analysis. All of these aspects, are not found in qualitative methodologies.
There is a theoretical framework bases for the research, it is being completed to test theories and obtain more information on previous research that has been completed on the three cognitive components. The research findings will be meaningful and generalizable to all individualized diagnostic with Specific Learning Disorder, Reading Disorder, Math Disorder, Attention Disorders, and anyone who is interested in the three cognitive ability components. The research will also establish connections between facts and theories that have been created, and may be generalizable into classrooms and daily lives of those affected.
The researchers hypothesize that there will be a relationship between memory, processing speeds, and temporal processing and the children’s attention will be related regardless of the type of learning disorder. But, they also predicted that with controlled attention the cognitive profiles would be distinct with Reading Disorders and Math Disorders. The overall objective was again, to obtain information on whether or not processing speed, temporal processing, and working memory were risk factors for Reading Disorders or Math Disorders. The relationship between the research question and the hypothesis because the hypothesis is based on what they believe the outcome of the research will be. The research will go into discovering the effects of MD, RD, and Attention Deficits in cognitive ability, processing speed, temporal speed, and memory skills. The hypothesis is based on what the researchers believe the effect on the cognitive skills on each sub-group of students. It is later researched and the findings which includes data are later discussed and compared to the hypothesis.
Measurement
In the research, the continuous variable was the attention behavior and hyperactivity which were ratings completed by the parents of the students. The dependent variable is the covariance analysis with each cognitive risk factor that was being studied. The variables being research are if processing speed, temporal processing, and working memory can be used to risk factor predictors for individuals diagnosed with Reading Disorder, Math Disorder, both disorders together, and co-morbidity with attention deficit. The dependent variable in the research are the students and the independent variable are their diagnosis which includes Reading Disorders, Math Disorders, co-morbidity of both diagnosis, and attention difficulties and if the three cognitive factors can be used as risk factor predictors for students who are later diagnosed RD, MD, AD. The control group were the youngest in the sample.
The participants of this study included 99 children whom ages varied from 6 to 11 years old. The student’s disorders varied, 21 of the participants had been diagnosed with a Reading Disorder, 15 with a Math Disorder, 19 with a combination, and the control group of 44 students with average performance in reading and math. The students were selected based on a previous study that had been conducted. The families had been part of a study which researched children with and without family risk for dyslexia. The student’s younger siblings had taken part of this previous study, and were now selected to take part of this new study.
All of the students came from British White families, and lived in North Yorkshire, England. All of the children were reported to have learned English as their first language, and lived in similar parts. They researchers calculated the Socioeconomic status and found that the sample of students had a relatively high socioeconomic status. None of the children that participated in the study had been reported to have chronic illness, neurological disorder, or low school attendance rates.
In this study, children were classified as impaired if they had clinical diagnosis of the disorders or based on an education psychological comprehensive diagnostic test battery. The students could have also been classified as impaired because their scores were less than 85 which was the standard score in the literacy or/and the athematic test. Out of the sample of 24 students, 20 were classified impaired based on the criteria, and 3 scored half a standard deviation away from the mean. While, five children received clinical referrals for ADHD. No students received any medication during the testing and research, due to the researchers wanted to see the attention in the students and the cognitive deficits which are associated with the Reading Disorder or Math Disorder.
The measures used in the sample began with testing the literacy and arithmetic skills of the students using the “Wechsler Individual Achievement Test”. (2005) The subtest used were Word Reading, Spelling, and Numerical Operations which had a high test reliability for the three test. Next, the student’s attention was assessed using the “Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale” which was a parental questionnaire. The SWAN aimed to measure inattention, hyperactivity and impulsivity. The validity of the test was calculated, and it was proven to be a valid questionnaire.
The “Wechsler Abbreviated Scale of Intelligence” (WASI) was used to calculate the verbal and nonverbal IQ in order to see the general cognitive ability. Processing speed was assessed by the rapid automatized naming of digits which gave the researchers verbal processing speeds. The students were supposed to name 40 digits with one syllables, using speed and accuracy. While, the nonverbal processing speed was calculated through having the students identify unknown symbols. The students would have to cross off the unknown symbols amounts 84 strings in each line.
The temporal processing was tested using a time reproduction task on the computer. The goal was for the students to switch a lightbulb on for the amount of time presented to them. The times presented were 1,000 ms or 3,000 ms, this had 32 trials in randomized orders. The last skill tested was memory, in which the students completed two sub-test from “Working Memory Test Battery for Children”. The sub-test measured verbal and visuospatial memory skills for each of the students.
The measures of the study did seem to be valid and reliable. Each test given to the students was tested for its reliability, they all scored a high level of reliability. Furthermore, the assessments were valid because they measured what the researchers were looking for. Each test and sub-test gave the researchers data for the three cognitive ability skills they were looking to test. With the data provided by each of the assessments, the researchers were able to see if the three cognitive ability skills could be used to identify risk factors for Reading Disorders, Math Disorders, both, or attention difficulties.
Research Design
For this study, the research design used was a quantitative design. This is based on the researchers using means and standard deviations for the four groups being researched. The parental surveys of attention, and testing which included subtest were all used to obtain qualitative data. The data would allow the researchers to conclude if the three cognitive domains can be used to identify risk factors for Reading Disorders, Math Disorders, Attention Difficulties, or co-morbidity.
There was a series of analyses of covariance (ANCOVAs) were calculated with each of the cognitive risk factors. This was later done again with attention ratings. Reading and math factors were entered as fixed factors, and the children’s ages were covariates in each of the analysis. Using the ANCOVAs gave the researchers statistical data to see the results of each sub-test and its variations among the disabilities. For example, comparing the verbal processing speed for RD, MD, RD+MD, and the control group.
There may have been threats to the internal validity of the study. One of the threats may have been the location of the study, all of the students were from the same area and families whom had been researched previously. There is a regression threat to the internal validity, as the population being worked with is Special Education. Most of the students were low achieving scorers, as they all had MD, RD, or both. The control group of the students, were neurotypical students who did have regular standardized scores. External validity lacked because there was only a total of 99 participants were selected, they were families of participants of previous studies as well. The participants were also chosen from one region, with only one ethnic background, and native language. The subject results would be the most applicable to the same group of individuals with similar backgrounds, ethnicities, and age.
Sampling
The researchers target population was students effected with Reading Disorders, Math Disorders, both, and attention difficulties. The ultimate goal with targeting these populations was to see if the three cognitive factors being measured could be used as risk factor predictors for the disorders. The population of the study included 99 individuals from age 6 to 11, who were affected by RD, MD, both, or used as the control group. This was the ideal group for the researchers, the gender ratios were balanced when it came to female or male. Although, more females were affected by math disorders while more males in the sample were found with literacy difficulties.
The population in the sample was representative of what the researchers aimed to study. The goal was to conduct research on individuals affected by attention, reading, and mathematics difficulties which were used. But, it did not have a variety of heritages, nationalities, or location. The sample consisted of students found within the same region, and from families whom were already known to the researches. This was a population easily available to the researchers, and was not randomized. In order to have been representative of all individuals affected by the disorders. Although, it was a consistent sampling because it worked with the same group of students with similar backgrounds, social economic statuses, and age groups.
The sampling technique used was an accessible population for the targeted population. Meaning opportunity sampling, because the researchers chose families whom they had previously worked with who had children affected by the disorders that they were targeting in the study. The target population was individuals affected by RD, SD, or both. All of the students used in this sample fell into one of the categories. But, the research further explains that their families had worked in research previously.
External Validity may be threatened in this research because there was no variation in the individuals chosen. The individuals did not have different ethnic backgrounds, socioeconomic statuses, and ethnicity. They all went to similar school settings in the same region of their city. The disadvantage of using an opportunity sampling is that it may not be a representative sample. The sample was chosen based on its easy accessibility to the researchers.
Data Collection
The data was obtained using the “Wechsler Individual Achievement Test” (2005), the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale, “Wechsler Abbreviated Scale of Intelligence” and two sub-test from “Working Memory Test Battery for Children”.
The Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale was a rating scale completed by the parents of the students. The other research methods were formal test administered by the researchers, in a quiet room individually. The students were assessed individually within a separate space in the department.
The advantaged of using these methods is that these are widely known and used test. Using these test, allowed the researchers to know that they are reliable and valid instrumentations. They also measured exactly what the research was looking to understand and discover. The rating scale and questionnaire, allows the research to also include opinions from the parents and an informal assessment of the student behaviors. These data collection tools also allow the researchers to see the impact of the differences in attention per individuals, alongside using the three cognitive deficits in reading and math disorders.
Data Analysis
When the researchers analyzed the data of the trials, from the test given to the students the researchers were able to obtain a mean, standard deviation, and group effects. The researchers aimed to use processing speed, temporal processing, and working memory as cognitive factors for individuals with Specific Learning Disorders who have Reading Disorders and/or Math Disorders. The objectives of the data allowed the researchers to “investigate which domain-general cognitive deficits are associated with RD and/or MD”. (Moll, Göbel, Gooch, Landerl, and Snowling, 2016)
By completing testing in the three cognitive risk factors, the researchers were able to identify if these could be used to determine risk factors for individuals affected by Specific Learning Disorder. Individuals with Specific Learning Disorders have reading and math difficulties, and may commonly be affected by attention difficulties which were also studied and observed in the research study. Moll, Göbel, Gooch, Landerl, and Snowling were able to research their objectives, with their target population, to obtain data to support their research question.
Results
The results of the trials showed the results of the four groups being tested in the study. The data results showed what was hypothesized, the students who had difficulties with literacies had lower scores than the control group and the students affected by the math disorder. The children with math difficulties had lower arithmetic scores than those who had difficulties with reading and the control group. The group of students with comorbidity had the lowest score of all the groups being tested in the research.
Next, ANCOVAs were calculated in order to obtain the cognitive profiles for RD and MD. The covariates of attention were significant in all the groups of students. The IQ of the students all varied. But, it was found throughout the study that those who suffered from comorbidity and MD had lower IQ scores than the RD and the control group. In the verbal memory, all of the groups were significantly low in comparison to the IQ.
Processing Speed was one of the three cognitive risk factors being measured. Processing speeds in the group of RD was slower than the other groups whom did not have a RD. There was no strong significant relationship between MD and processing speeds. The effect of RD was still portrayed, but reduced when attention ratings were taken into consideration. Nonverbal processing speeds were not significantly affected by RD or MD.
When analyzing temporal processing, standard time intervals were assessed for each student. There were no significant differences when the groups were assigned to turn on the lightbulbs for 1,000ms. But, in the 3,000ms condition the math disorder group showed lower conditions than any of the other group. There was no significant effect on the individuals who had a reading disorder. The students with RD outperformed all the students who had any difficulties in math. Although, the group of students with RD performed equal to the control group. There was a significance difference among the groups, including when the attention ratings were taken into account in the students.
Memory skills was the last cognitive risk factor tested, the verbal memory in both the RD and MD group were less than the scores from the control groups. In visual memory examinations, the two groups effected by a math disorder performed lesser than all the other groups. Although, all the groups affected by RD and LD were obtaining below average scores. The most significant effect was in the group of comorbidity, meaning that both of the disabilities combined led to significant effects in the memory skills.
The data concluded that lower performances in the three domains were affected by difficulties with attention in the students. “RD but not MD status was associated with deficits in verbal processing speed and MD, but not RD status, with temporal processing deficits, as measured by a 3,000 ms time reproduction task”. (Moll, Göbel, Gooch, Landerl, and Snowling, 2016) In verbal memory, RD was significant when nonverbal IQ was a covariant. Moll, Göbel, Gooch, Landerl, and Snowling (2016), conclude that “any effects found in the single deficit groups are likely to be additive for the comorbid group.”
Implications of the Findings
The authors conclude that there was definitely a correlation between the three domain general cognitive abilities and attention problems with students affected by Reading Disorder and Math Disorder. The student’s poor performance on assignments was associated with the poor performance, which reflected on the attention ratings given by the parent’s scale.
The hypothesis was confirmed through the research, students affected with RD had delayed verbal processing speed and poor verbal memory. While, MD students were affected in the cognitive areas of time reproduction, temporal processing, and limits in the verbal and visuospatial memory.
The individuals affected with comorbidity of RD and attention problems, are a slow processing speed is a definite risk factor for both groups. Verbal processing domain deficits are a definite risk factor for reading disorders, even if the child has not been reported to have attention problems. The researchers point out that, it is important to observe attention behavior problems in the student otherwise temporal processing could be overestimated and not properly diagnosed for students with RD.
Furthermore, the researchers explain that attention difficulties will have to be considered when more research is conducted on temporal processing skills in the students diagnosed with Reading Disorders. Attention Difficulties and Math Disorders were commonly shared with impaired temporal processing.
The only risk factor that was found commonly among reading disorder and math disorder was the verbal memory. All of the groups in the research had their verbal memory affected as per the research. The core cognitive deficits in RD and MD have been proven and shown to be domain specific. There may be more deficits for individuals affected with attention problems, which had not been explored or research during this time. The research showed that Reading Disorders and Math Disorders are the consequence of a combination of risk factors. The researchers reiterate that attention difficulties need to be taken into account when conducting research on individuals with Specific Learning Disorders which including math disorder and reading disorder.
The significance of the findings for my area of interest is that in my classroom I have many students who have been diagnosed with Specific Learning Disorders. The students with Specific Learning Disorders have reading and math disorder effects, which effect three general cognitive ability domains. The students in my classroom have deficits in processing speeds, temporal processing, and memory skills. I found it significant that the parents rated the attention of their students. This is significant as most of the students in my classroom have attention deficits, and it effects other cognitive domains. But, I am not sure that the results of the study would directly relate to my student population. The students came from White backgrounds, and had English as their first language. Most of my students, come from Hispanic backgrounds with English as their second language and a variety of ethnic backgrounds.
Student’s Contribution
If this study were to be conducted again, the writer would begin with including a larger sample sizes. By enlarging the sample size, the writer will include students that come from different backgrounds, socioeconomic statuses, and native languages. Although, the researchers did do a good job with keeping an equal ratio among the disabilities, as well as the gender ratio of the participants in the study.
In the study, the writer would have changed the way that the parameters of the research question. Rather than focusing on both processing speed, temporal processing, and memory skills as risk factors, as well as the co-occurring attention difficulties. The writer would have focused either only on the three cognitive-domain risk factors or the attention difficulties as a co-occurring problem for reading and math disorders.
The writer would have changed the location that the study took place, as well as the way that the participants were chosen for the study. The participant’s families had participated in other studies which focused on dyslexia. The students were an accessible population to the researchers. The writer would have focused on one school district, and surveyed the students affected by RD and MD. Then, the writer could have sent home permission slips and chosen from the student’s families that would want to participate. This would have given the researchers more variation of data and results in the research.
From this research, the writer would keep the testing used in the research as well as the attention questionnaire given to the parents. The measures and procedures used in the study were valid and reliable. These procedures were accurate measures of what the researchers were aiming to investigate. The way that the instrumentation was chosen for the study gave an accurate representation of the goal of the study. Using these instruments, the researchers were able to obtain the data to analyze in order to calculate mean, standard deviations, and graphs.
The writer would have also analyzed the data the same way that the researchers had completed it in the article. The standard deviation, mean, and group effects for the cognitive measures and attention. The data were analyzed into tables and graphic organizer which allowed the data to be easily displayed, interpreted, and understood.
When it comes to deleting in the article, the writer would have removed the article focused very much into explaining the cognitive deficits. This is something that the writer would have included in the introduction of research and explained as an introductory. In the problem statement, the researcher would have deleted one of the parts being researched. Either, including researching only the three cognitive domains or the attention deficits that were brought by RD or MD.
Overall, the research made a large step towards identifying if the three cognitive domains could be used to calculate risk factors for RD and MD. This was the first time that research had been done on the three cognitive domains in the relation for Specific Learning Disorders and attention deficits in correlation with reading and math disorders. The research is especially interesting for the writer’s classroom as many of the students in the classroom population have been affected by these disorders.
References
Moll, K., Göbel, S. M., Gooch, D., Landerl, K., & Snowling, M. J. (2016). Cognitive Risk Factors for Specific Learning Disorder: Processing Speed, Temporal Processing, and Working Memory. Journal of Learning Disabilities, 49(3), 272-281 doi.org10.1177/0022219414547221
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