Volume 19, Issue 1 (Spring 2018)                   Vol. , No. , Season & Year , Serial No. | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Kasirian N, Mirzaie H, Pishyareh E, Farahbod M. Investigating the Patterns of Attention Performance in Children With Mathematical Learning Disorder, With Using “Test of Everyday Attention for Children”. jrehab. 2018; 19 (1) :76-85
URL: http://rehabilitationj.uswr.ac.ir/article-1-2215-en.html
1- Department of Occupational Therapy, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
2- PhD Department of Occupational Therapy, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran. , hooshang_mirzaie@yahoo.com
3- Exceptional Children’s Research Institute, Institute for Educational Studies, Tehran, Iran.
Abstract:   (1113 Views)
Objective Mathematical learning disorder is a type of neurodevelopmental disorder detected by three types of working memory deficits, procedural and visual-spatial problems. The limited capacity of attention and a lot of environmental stimuli have encountered children with learning disorders with the problems. Since attention is one of the most important cognitive functions in the development of mathematics learning, it is important to recognize and evaluate a variety of attention deficits in this group of disorders. Therefore, considering to the three-factor model of Manly, based on sustained attention, selective attention, and control attention, in this study difference of patterns of attention in children with mathematical learning disorder using “Test of Everyday Attention for Children” was investigated.
Materials & Methods The present study was a descriptive-analytic study in a community of students aged 7-11 years with a learning disorder in Tehran, Iran. The selection was based on the early diagnosis of learning disorder with psychiatric and the standard intelligence scores of the Wechsler test in the academic records. Accordingly, 17 male and female students aged 7-11 years with the mathematical disorder were selected from five public learning centers in Tehran and 17 normal children were matched in age and gender. Initially, the demographic information questionnaire was completed by families. Then A version of “Test of everyday attention for children” was taken by the researcher during the standard period in the calming room. Accordingly, two groups with a mathematical learning disorder and normal peers were compared in three domains of sustained attention, selective, control in “Test of Everyday Attention for Children.”
Results The results of the Shapiro-Wilk test indicated that the distribution of values of all variables, except “sky search dual task” (sustained attention) and the speed of “creatures counting” (control attention), have a normal distribution in the learning disorder group (P>0.05). While the values of variables such as “Score” (sustained attention), “Opposite worlds”, accuracy of “creatures counting” (control attention), and “walk don’t walk”(sustained attention) do not follow a normal distribution in the control group (P<0.05).
In sustained attention and control attention domains, the results of the nonparametric tests indicated that have a significant difference in two groups in the subtests of “Score”, “walk don’t walk”, “sky search dual task”, “creatures counting” and "opposite worlds." Homogeneity of variances with the Leven test, reports that equality of variances. Accordingly, the results of independent t-test indicated that children with mathematical learning disorder were worse than the control group in the "Code Transition" and “Score Dual Task" subtests. In the domain of selective attention, the results of independent t-test indicated that significant difference in the subtests of "map mission" and the speed and accuracy of "sky search" in the two groups. Therefore, all domains of sustained and control attention (P<0.001) and selective attention (P<0.05) were significantly different in the two groups.
Conclusion The results demonstrate that children with mathematical learning disorders were significantly worse than their normal peers in all three domains. Findings indicated that “Test of Everyday Attention for Children” has the potential to evaluate the attention deficits in mathematical learning disorder as compared with normal peers. Therefore, it can be an appropriate tool for the evaluation in this group.
Full-Text [PDF 5167 kb]   (1407 Downloads) |   |   Full-Text (HTML)  (586 Views)  
Type of Study: Original | Subject: Occupational Therapy
Received: 5/09/2017 | Accepted: 21/01/2018 | Published: 1/02/2018

References
1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. Washington DC: American Psy-chiatric Association; 2013.
2. Najmeh H. [Investigating math learning disability in primary school boys and girls of Tehran and effects of functional training, chips strengthening and muscle relaxation in reducing their mathematical deficiency (Persian)]. Journal of Educa-tion. 2006; 13(2):119-36.
3. Geary DC, Hoard MK. Learning disabilities in arithmetic and mathematics. In Campbell JID, editor. Handbook of math-ematical cognition. Milton Park: Taylor & Francis; 2005.
4. Mirsky AF, Anthony BJ, Duncan CC, Ahearn MB, Kellam SG. Analysis of the elements of attention: A neuropsychological approach. Neuropsychology Review. 1991; 2(2):109–45. doi: 10.1007/bf01109051 [DOI:10.1007/BF01109051]
5. Posner MI, Petersen SE. The attention system of the human brain. Virginia: DTIC Document; 1989.
6. Manly T, Anderson V, Nimmo Smith I, Turner A, Watson P, Robertson IH. The differential assessment of children's atten-tion: The Test of Everyday Attention for Children (TEA-Ch), normative sample and ADHD performance. The Journal of Child Psychology and Psychiatry and Allied Disciplines. 2001; 42(8):1065-81. PMID: 11806689 [DOI:10.1111/1469-7610.00806] [PMID]
7. Cooley EL, Morris RD. Attention in children: A neuropsychologically based model for assessment. Developmental Neu-ropsychology. 1990; 6(3):239–74. doi: 10.1080/87565649009540465 [DOI:10.1080/87565649009540465]
8. Lee CK. The association of inattention and children's math development: A longitudinal study. Baltimore County: Univer-sity of Maryland; 2011.
9. Askenazi S, Henik A. Attentional networks in developmental dyscalculia. Behavioral and Brain Functions. 2010; 6(1):2. doi: 10.1186/1744-9081-6-2 [DOI:10.1186/1744-9081-6-2]
10. Rubinsten O, Henik A. Double dissociation of functions in developmental dyslexia and dyscalculia. Journal of Educational Psychology. 2006; 98(4):854–67. doi: 10.1037/0022-0663.98.4.854 [DOI:10.1037/0022-0663.98.4.854]
11. Lindsay RL, Tomazic T, Levine MD, Accardo PJ. Attentional function as measured by a continuous performance task in children with dyscalculia. Journal of Developmental & Behavioral Pediatrics. 2001; 22(5):287–92. doi: 10.1097/00004703-200110000-00002 [DOI:10.1097/00004703-200110000-00002]
12. Eghlidi J, Koobasi F, Nejati V, Tabatabaee SM. A comparative study of sustain attention to auditory and visual stimulus in children with Mix learning disorder and normal peers. Journal of Research Rehabilitation Science. 2013; 9(3):435-44.
13. Bayrami M, Peyman Nia B, Mousavi Giyeh E. [Comparison of executive function in Students with Dyscalculia disorder and normal counterparts (Persian)]. Biquarterly Journal of Cognitive Strategies in Learning. 2014; 1(1):15-29.
14. Commodari E, Di Blasi M. The role of the different components of attention on calculation skill. Learning and Individual Differences. 2014; 32:225–32. doi: 10.1016/j.lindif.2014.03.005 [DOI:10.1016/j.lindif.2014.03.005]
15. Chapparo C. Perceive, Recall, Plan and Perform (PRPP): Occupation-centred task analysis and intervention system. Occu-pation-Centred Practice with Children. Hoboken: Wiley & Sons. doi: 10.1002/9781444319699.ch9 [DOI:10.1002/9781444319699.ch9]
16. Manly T, Robertson IH, Anderson V, Nimmo Smith I. TEA-Ch: The test of everyday attention for children. London: Pear-son; 2007.
17. Heaton SC, Reader SK, Preston AS, Fennell EB, Puyana OE, Gill N, et al. The test of Everyday Attention for Children (TEA-Ch): Patterns of performance in children with ADHD and clinical controls. Child Neuropsychology (Neuropsy-chology, Development and Cognition: Section C). 2002; 7(4):251–64. doi: 10.1076/chin.7.4.251.8736 [DOI:10.1076/chin.7.4.251.8736]
18. Anderson TF, Manly TV. Attentional skills following traumatic brain injury in childhood: A componential analysis. Brain Injury. 1998; 12(11):937–49. doi: 10.1080/026990598121990 [DOI:10.1080/026990598121990]
19. Berl MM, Terwilliger V, Scheller A, Sepeta L, Walkowiak J, Gaillard WD. Speed and complexity characterize attention problems in children with localization-related epilepsy. Epilepsia. 2015; 56(6):833–40. doi: 10.1111/epi.12985 [DOI:10.1111/epi.12985]
20. De Vries PJ, Gardiner J, Bolton PF. Neuropsychological attention deficits in Tuberous Sclerosis Complex (TSC). American Journal of Medical Genetics Part A. 2009; 149A(3):387–95. doi: 10.1002/ajmg.a.32690 [DOI:10.1002/ajmg.a.32690]
21. Bottcher L, Flachs EM, Uldall P. Attentional and executive impairments in children with spastic cerebral palsy. Develop-mental Medicine & Child Neurology. 2009; 52(2):e42–e47. doi: 10.1111/j.1469-8749.2009.03533.x [DOI:10.1111/j.1469-8749.2009.03533.x]
22. Chan RC, Hoosain R, Lee TM. Reliability and validity of the Cantonese version of the Test of Everyday Attention among normal Hong Kong Chinese: A preliminary report. Clinical Rehabilitation. 2002; 16(8):900–9. doi: 10.1191/0269215502cr574oa [DOI:10.1191/0269215502cr574oa]
23. Manly T, Robertson IH, Anderson V, Nimmo Smith I. TEA-Ch: The test of everyday attention for children. London: Pear-son; 2007.
24. Fathi N, Hassani Mehraban A, Akbarfahimi M, Mirzaie H. Validity and Reliability of the Test of Everyday Attention for Children (TEACh) in Iranian 8-11 year old normal students. Iranian Journal of Psychiatry and Behavioral Sciences. 2016; 11(1). doi: 10.5812/ijpbs.2854 [DOI:10.5812/ijpbs.2854]
25. Cherry RS, Kruger B. Selective auditory attention abilities of learning disabled and normal achieving children. Journal of Learning Disabilities. 1983; 16(4):202–5. doi: 10.1177/002221948301600405 [DOI:10.1177/002221948301600405]
26. Amiriani F, Kamali M. Comparative evaluation of auditory attention in 7 to 9 year old learning disabled students. Bi-monthly Audiology-Tehran University of Medical Sciences. 2011; 20(1):54-63.
27. Kraus N, McGee TJ, Carrell TD, Zecker SG, Nicol TG, Koch DB. Auditory neurophysiologic responses and discrimina-tion deficits in children with learning problems. Science. 1996; 273(5277):971–3. doi: 10.1126/science.273.5277.971 [DOI:10.1126/science.273.5277.971]
28. Narimani M, Pouresmali A, Andalib KM, Aghajanei S. A comparison of Stroop performance in students with learning dis-order and normal students. Journal of Learning Disabilities. 2012; 2(1):138-58.
29. Zhang H, Wu H. Inhibitory ability of children with developmental dyscalculia. Journal of Huazhong University of Science and Technology. 2011; 31(1):131–6. doi: 10.1007/s11596-011-0164-2 [DOI:10.1007/s11596-011-0164-2]
30. Toll SWM, Van der Ven SHG, Kroesbergen EH, Van Luit JEH. Executive functions as predictors of math learning disabili-ties. Journal of Learning Disabilities. 2010; 44(6):521–32. doi: 10.1177/0022219410387302 [DOI:10.1177/0022219410387302]
31. Szucs D, Devine A, Soltesz F, Nobes A, Gabriel F. Developmental dyscalculia is related to visuo-spatial memory and inhi-bition impairment. Cortex. 2013; 49(10):2674–88. doi: 10.1016/j.cortex.2013.06.007 [DOI:10.1016/j.cortex.2013.06.007]
32. Pieters S, Desoete A, Roeyers H, Vanderswalmen R, Van Waelvelde H. Behind mathematical learning disabilities: What about visual perception and motor skills? Learning and Individual Differences. 2012; 22(4):498–504. doi: 10.1016/j.lindif.2012.03.014 [DOI:10.1016/j.lindif.2012.03.014]
33. Garje Mona P, Dhadwad V, Yeradkar MR, Adhikari A, Setia M. Study of visual perceptual problems in children with learn-ing disability. Indian Journal of Basic and Applied Medical Research. 2015; 4(3):492-97.
34. Baddeley A. Exploring the central executive. The Quarterly Journal of Experimental Psychology Section A. 1996; 49(1):5–28. doi: 10.1080/713755608 [DOI:10.1080/713755608]
35. Van der Sluis S, de Jong PF, Leij A van der. Inhibition and shifting in children with learning deficits in arithmetic and reading. Journal of Experimental Child Psychology. 2004; 87(3):239–66. doi: 10.1016/j.jecp.2003.12.002 [DOI:10.1016/j.jecp.2003.12.002]
36. Yeniad N, Malda M, Mesman J, van IJzendoorn MH, Pieper S. Shifting ability predicts math and reading performance in children: A meta-analytical study. Learning and Individual Differences. 2013; 23:1–9. doi: 10.1016/j.lindif.2012.10.004 [DOI:10.1016/j.lindif.2012.10.004]
37. Posner MI. Orienting of attention. Quarterly Journal of Experimental Psychology. 1980; 32(1):3–25. doi: 10.1080/00335558008248231 [DOI:10.1080/00335558008248231]
38. Corbetta M, Shulman GL. Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neurosci-ence. 2002; 3(3):215–29. doi: 10.1038/nrn755 [DOI:10.1038/nrn755]
39. Price GR, Holloway I, Räsänen P, Vesterinen M, Ansari D. Impaired parietal magnitude processing in developmental dy-scalculia. Current Biology. 2007; 17(24):R1042–R1043. doi: 10.1016/j.cub.2007.10.013 [DOI:10.1016/j.cub.2007.10.013]

Add your comments about this article : Your username or Email:
CAPTCHA code

Send email to the article author


© 2018 All Rights Reserved | Archives of Rehabilitation

Designed & Developed by : Yektaweb