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Universitas Psychologica

Print version ISSN 1657-9267

Univ. Psychol. vol.9 no.3 Bogotá Sept./Dec. 2010

 

Cognitive Inhibitory Control and Arithmetic Word Problem Solving In Children with Attention Deficit/ Hyperactivity Disorder: A pilot study*

Control inhibitorio cognitivo y resolución de problemas verbales aritméticos en niños con déficit de atención e hiperactividad: un estudio piloto

SIGEM SABAGH-SABBAGH **

DAVID A. PINEDA ***

* Research article in Neuropsychology.

** Universidad de San Buenaventura, Medellín, Colombia, Correo electrónico: sigemsabagh@hotmail.com

*** Universidad de Antioquia, Medellín, Colombia, Correo electrónico: dpineda12@hotmail.com

Recibido: marzo 10 de 2009 Revisado: octubre 14 de 2009 Aceptado: noviembre 19 de 2009


Para citar este artículo

Sabagh-Sabbagh, S. & Pineda, D.A. (2010). Cognitive Inhibitory Control and Arithmetic Word Problem Solving In Children with Attention Deficit/ Hyperactivity Disorder: A pilot study. Universitas Psychologica, 9 (3), 761-772.


Abstract

A sample of 30 subjects, 10 with Attention Deficit and Hyperactivity Disorder (ADHD) and 20 non-ADHD children, statistically controlled by age, gender, academic grades and normal full scale intelligence quotient, was selected. To measure cognitive inhibitory control, a math problem solving ability test containing four problems for each level with verbal and numerical irrelevant content was administered. ADHD children exhibited significantly inferior performance in choosing correct answers (p = 0.011) with a large effect size (d = 1.00) and a significantly superior number of irrelevant answers (p= 0.004) with a very large effect size. In conclusion ADHD children showed a cognitive inhibitory control disorder, measured by math problem solving ability.

Keywords authors : Cognitive inhibitory control, arithmetic problem solving, ADHD.

Keywords plus : Attention Deficit Disorder with Hyperactivity, Cognitive Grammar (LC), Arithmetic, Problems, Exercises.


Resumen

Se midió el control inhibitorio cognitivo en una muestra de 10 participantes con trastorno de déficit de atención con hiperactividad (TDAH) y 20 sin TDAH, controlados estadísticamente por edad, sexo, notas del colegio y coeficiente intelectual. La medición se hizo mediante una prueba de resolución de problemas aritméticos con cuatro problemas para cada nivel, con contenido verbal y numérico irrelevante. Los niños con TDAH tuvieron muchas menos respuestas correctas y un más alto nivel de trastorno de control inhibitorio cognitivo.

Palabras clave autores : Control cognitivo, inhibitorio, resolución de problemas verbales aritméticos, TDAH.

Palabras clave descriptor : Trastorno por déficit de atención con hiperactividad, gramática cognoscitiva, aritmética, problemas, ejercicios.


Attention deficit and hyperactivity disorder (ADHD) is a very common problem among school-aged children, and its prevalence has been estimated at 8-12% in the United States (American Psychiatric Association, 2000; Biederman, 2005). In Colombia the prevalence of ADHD symptoms was estimated between 16 and 22% in school children (Pineda et al., 1999). A final prevalence, using psychiatric gold standard diagnosis was calculated between 12 and 16% in children and adolescents, with a significantly different distribution by gender, where males predominated 2:1 (Cornejo et al., 2005; Pineda et al., 2003).

Neuropsychological studies have proposed that ADHD has underlain an executive function (EF) deficit associated with high variability between cases (Sengupta et al., 2008; Willcut et al., 2005). This EF deficit could explain the difficulties that ADHD children have to perform sequential, controlled and planned tasks (Sengupta et al., 2008). This deficit has been attributed to the cognitive inhibitory control (CIC) on the working memory (WM), which fails to monitor the strategies and step-by-step performance, of complex and multimodal tasks (Barkley, 1997; Passolunghi, Marzocchi & Fiorillo, 2005; Rapport et al., 2001). This hypothesis is supported by convergent data derived from neuropsychological and neuroimaging studies, which implicate inhibitory deficit related to fronto-striato-cerebellar dysfunctions in ADHD children and adolescents (Castellanos et al., 2002; Chadderdon & Sporns, 2006; Durston, 2003; Giedd et al., 2001, Willcut et al., 2005).

Because the main goal in mathematic teaching and learning is to develop the ability to resolve a variety of complex step by step organized tasks, mathematical problem solving (MPS) has special importance in the study of ADHD. It represents a very ecological approach similar to school work, where ADHD children and adolescents have the most severe difficulties (Wilson, Fernandez & Hadaway, 2007).

Arithmetic word problems (AWP) contain not only numerical information, but also literature, and narrations, which introduce more complex information to challenge the CIC, regarding irrelevant, intrusive or non-related information. Hence, AWP may contain literal and numerical information which is irrelevant to its solution but enriches it semantically (Passolunghi et al., 2005; Marzocchi, Lucangeli, De Meo, Fini & Cornoldi, 2002). As suggested above, CIC is a self-conscious kind of mental activity directed to suppress irrelevant or unnecessary information from the working memory (Barkley, 1997; Rapport et al., 2001; Wilson & Kipp, 1998). ADHD children and adolescents have EF or motivational dysregulation, which would affect the quality and the quantity of errors in problem-focused activities, especially when the problem is a collection of interfering information (Sonuga-Barke, 2002).

The CIC shows notable development effects (Nigg, 2000). Children in second grade have impaired abilities to suppress the total amount of irrelevant information of the working memory (Bray, Hersh & Turner, 1985; Bray, Justice & Zahm, 1983). In third grade, children have a partial ability to suppress the irrelevant information. By fifth grade, apparently this kind of inhibition can be accomplished successfully (Harnishfeger & Pope, 1996). For the above reasons, comparative studies need to take into account children's school achievements and ages.

Actually, some studies have found that the CIC plays an important role in the subject's success while resolving AWP. Necessarily, the CIC is used to suppress the irrelevant information, while maintaining relevant information in the WM, and while using it in step-by-step problem solving (Passolunghi et al., 2005; Marzocchi et al., 2002).

The purpose of this paper is to challenge the hypothesis that Colombian ADHD children, attending fourth and fifth grade (levels in which AWP solving is taught and children have successfully gained the ability to suppress the irrelevant information from them by using CIC, according to Harnishfeger & Pope, 1996), in Schools in the city of Medellin-capital of the Department of Antioquia-whose inhabitants have been considered in several studies as genetically isolated, have a CIC deficiency when resolving AWP, compared to peer non ADHD children. If the hypothesis is correct, the significant variables of AWP could be used as part of neuropsychological protocol in future genetic ADHD studies.

Method

Participants

Medellin was selected to perform this study, because it has been proven by several genetic studies that the city has a population with high prevalence of ADHD when comparing it to other areas of the country (Cornejo et al., 2005; Pineda et al., 2003). Children of the fourth and fifth school levels where selected because, according to Harnishfeger and Pope (1996) AWP solving is taught at these levels and children normally have achieved the ability to suppress irrelevant information.

After a consent form was sent to the parents of 114 children, and the 50 children whose parents consented to their participation were assessed through the Checklist for parents and teachers, the WISC-III and the tests to measure skills in math and reading comprehension, a sample of 30 subjects was ultimately selected: 10 ADHD and 20 non-ADHD children, statistically controlled by age (9 to 12 years old), gender, grade level (fourth and fifth grade) and a normal full scale intelligence quotient (FSIQ), was intentionally selected (see Table 2). The Conners Rating Scale (CRS) for parents and teachers was used to select suspicious ADHD and non ADHD children of the group (Conners, 1996) which have been validated for ADHD diagnosis in Colombia (Pineda et al., 1999). All ADHD children scored over the 90 percentile (T score > 72), which is considered by Colombian standards as a possible indication of the presence of ADHD (sensitivity 100%; specificity 97%), non ADHD children scored under the 55th percentile (T score = 51), (sensitivity 93%; specificity: 100%) (Pineda et al., 1999). The instrument used to verify the diagnosis was the Evaluation of Attention Deficit and Hyperactivity Disorder Scale (EADH Scale) which has a liability coefficient of 0,91, a validity of 0,93 corrected alpha and a convergent validity EDAH/DSM-IV of 0,77 (Farre & Narbona, 2003). The EDAH scale found that ADHD children obtained a percentile of 98 + 2 considered as an indicative score for this disorder. Table 2 summarizes the scores of the variables' criteria (see Table 2).

In order to exclude children with reading comprehension disabilities and math learning disabilities, all the children selected were within the normal range, for the compound of reading comprehension skills (Children without ADHD: Mean 104, SD: 20; Children with ADHD: 97, SD: 12), and for math skills (Children without ADHD: Mean 102, SD: 6; Children with ADHD: Mean 96, SD: 8), according to the Academic Achievement Tests of the Woodcock-Johnson III Battery (Mather & Woodcock, 2005).

Materials

We used a number instruments in order to collect data. The Math Problem Solution Ability Test, SPM was specially created to measure inhibitory control in math problems solution. It presents four problems per school level, each containing verbal and numerical irrelevant content (see Annex A for an example).

In order to screen target children for the presence of ADHD, and to find out whether further assessment was needed, we used the Checklist for parents and Children has items based on the DSM-IV (Diagnostic and Statistical Manual of Mental Disorders) for the diagnosis of children with ADHD (Attention Deficit and Hyperactivity Disorder). Teachers completed the EDAH Scale (Evaluation of Attention Deficit and Hyperactivity Disorder Scale), which is a questionnaire used to diagnose the presence of ADHD in children.

Two compound skills indexes were also used: the Compound of Skills in Math of the Academic Achievement Tests of the Woodcock-Johnson III Battery (Mather & Woodcock, 2005), comprised of the results of the Arithmetic and Math fluency tests, applied to children to determine whether or not they have math skills according to their ages; and the Compound of Skills in Reading Comprehension of the same battery (Mather & Woodcock, 2005), comprised of the results of the tests: Text' comprehension and Reading vocabulary, they are applied to children to determine whether or not their reading comprehension skills there are appropriate for their age. The Wechsler Intelligence Scale for Children (WISC-III) was used to measure the IQ of children.

Procedures

The 30 children were assessed using the SPM. It was verified that the two groups had no statistical differences between them. Data was analyzed using SPSS version 15.0, the statistics used were to compare frequencies between the two groups and Chi Square statistic was used, an U of MannWhitney for non-normal distribution of the data and Student's t for normal distribution of the data. The effect size was also used for comparison of the variables. A significance level of 0.05 was used as the alpha to control type I error in the study, with a confidence level of 95 %.

Results

When comparing the math problem solving performance of the groups of children with and without ADHD, it was possible to reject the null hypothesis for the following variables:

The ability to choose the image which best represents the problem, namely the ability to represent. Was observed in a mean percentile of 38 (SD = 33) in children without ADHD, and a mean percentile of 20 (SD = 25) in the children with ADHD, suggesting a significant statistic difference between them (p = 0.049), with a medium Cohen d effect size (d = 0.61). Neither group of children reached the expected mean percentile (50, SD = 10).

Categorization was observed in a mean percentile of 46 (SD = 27) for the children without ADHD and of 18 (SD = 18) for the children with ADHD, showing a significant statistic difference between them (p = 0.009), with a very large effect size (d = 1.22). It was not possible to reject the null hypothesis for the remaining variables, meaning the results obtained are statistically similar (See Table 3).

The children without ADHD attained a mean of correct answers of 7 (SD = 3), while the children with ADHD only reached a mean of correct answers of 4 (SD = 3), showing a statistically significant difference between them (p = 0.011), and a large effect size (d = 1.00). Finally, the group of children without ADHD obtained a mean of 1 (SD = 1) of irrelevant answers, in comparison with the group of children with ADHD which obtained a mean of 3 (SD: 2) showing a statistically significant difference between them (p = 0.004) and a very large effect size (d = 1.26).

It was not possible to reject the null hypothesis for the rest of the variables, therefore, the results were not conclusive for them (See Table 4).

Discussion

The main finding of this study is a significantly lower performance when choosing correct answers (p = 0.011) with a large effect size (d = 1.00), which means that the data obtained did not overlap by 55.4%, besides, children with ADHD obtained a significantly higher number of irrelevant answers (p = 0.004) with a very large effect size, indicating that the data did not overlap in 65.3%. These findings replicate the ones obtained by Marzocchi et al. (2002) and Passolunghi et al. (2005). This data was obtained based on the number of correct, partial, incorrect and irrelevant answers chosen by the children in solving the problems presented to them.

Many authors state that cognitive inhibitory control is the process through which unnecessary or irrelevant information is suppressed, and consequently it has relevance to the solution of a problem (Aaron, 2007; Everett & Lajeunesse, 2000; Miyake, Friedman, Emerson, Witzki, Howerter & Wager, 2000; Roselli, Ardila, Pineda & Lopera, 1997; Wilson & Kipp, 1998; Witzki & Howerter, 2000). Generally neuroanatomically, the source of control is associated with the prefrontal cortex (PFC), and the control target with the posterior cortical and sub-cortical regions (Aaron, 2007). Examples of neuroanatomical connections between region or process sources, which have an active inhibitory effect over a region or process target, are: 1) The fronto-thalamic circuit, where the prefrontal cortex inputs into the reticular nucleus and the latter sends GABAergics to the thalamus, actively inhibiting the thalamic cells and potentially limiting information input; 2) The frontostriatal or fronto-subthalamic circuit; and 3) The front-amygdalin circuit, where the fronto-medial inputs to the amygdale excite the GABAergic cells, which suppress amygdaline activity (Amaral & Price, 1984; Quirk et al., cited by Aaron, 2007).

Not all the authors are in favor to the application of the term "inhibition" to cognitive control. One initial objection is that it is considered absurd that PFC should actively suppress the multiple cortical and sub-cortical focuses during the hours the human being is awake. Instead, it is considered more logic that the human being simply expands the relevant information through the top-down base of the sensorial areas (Miller & D'Esposito, 2005; Miller & Cohen, 2001; Hillyard & AnlloVento, 1998 cited by Aaron, 2007). A second objection questions the explicative usefulness of the inhibition inferred from the effects of injuries in the performance of subjects (Gregory, 1961; Kimberg & Farah, 1993; Morton & Munakata; 2002 cited by Aaron, 2007). However, as mentioned before, there are circuits that have been observed through functional magnetic resonance, which play a role in inhibitory function as a process which contradicts the objections expressed by the authors (Amaral & Price, 1984; Quirk et. al., cited by Aaron 2007).

This pilot study provides support to the hypothesis that one of the main problems in children with ADHD (included the difficulties to solve a mathematic problem) lies in a lack of cognitive inhibitory control reflected by the high number of irrelevant answers given by these children.

Evidence that supports the previous assertions exist, obtained through rapid event functional magnetic resonance, that there is an alteration in the neuro-anatomic substrate of cognitive control in children with ADHD, which shows a reduction in the frontal-striate-temporal-parietal connections, failure in the activation of the prefrontal cortex and the caudate nucleus, reduced magnitude and extension in the activation of frontal and left pre-motor regions, absence of frontal-right activation which is associated to an appropriated inhibitory answer and a weak activation of the right insula instead (Vahadilla, Bunge, Dudukovic, Zalecki, Elliott & Gariela, 2005); findings that have been supported by other research that equally show atypical frontal connections in children with ADHD (Durston et. al., 2003; Shweitzer et. al.. 2000; Bush et. al., 1999; Vaidya et. al. 1998).

For Barkley (1999) the main problem of children with ADHD does not lie in cognitive inhibitory control but in behavioral inhibitory control. Barkley (1999) considers that the problem in children with ADHD its purely behavioral, so he does not consider the possible existence of dysfunction of cognitive inhibitory control; but there are researchers that have proven otherwise and support the existence of alterations on it (Passolunghi et al., 2005; Vahadilla, Bunge, Dudokovic, Zalecki, Elliot & Gabriela, 2005; Durston et al., 2003; Marzocchi et al., 2002; Shweitzer et. al., 2000; Bush et. al., 1999; Rubia et. al. 1999; Vaidya et. al., 1998).

The test for mathematic problem solving ability (MPS test) (Lucangeli, Tressoldi & Cendron, 1998) controls comprehension, categorization, representation, operative solution, choosing of a solution strategy and self-evaluation; those are variables immersed in the dimensions of executive functioning (EF), except for the representation which is not a variable of EF but it is an important step within the math problem solution. Of the previously mentioned variables, altered ability of representation (p = 0.049) was altered, although with a medium effect size (d = 0.61), indicating a non overlapping of data in 38.2%. Categorization was also altered (p = 0.009) with a very large effect size (d = 1.22), which means that data was not overlapped in 62.2%. The alteration of the ability of representation and categorization in children with ADHD has been shown in other studies (Chelune, Ferguson, Koon & Dickey, 1986; Gorenstein, Mammatto & Sandy, 1989; Renz, Pugzles, Milich, Lemberger, Bodner & Welsh, 2003; Shue & Douglas, 1992). The prefrontal cortex is the anatomical substrate of executive functions (Slachevsky, Pérez, Silva, Orellana, Prenafeta, Alegría & Peña, 2005); neuroanatomically, particularities which explain difficulties in executive functioning in children with ADHD have also been found, such as morphological changes demonstrable in neuroimaging, in the prefrontal cortex (usually on the right side), basal ganglia, cgulate gyrus, corpus callosum, and cerebellum. At functional level, studies like PET and SPECT, have shown a reduction of metabolism of glucose in the right prefrontal cortex and a reduction of blood supply to the striatum and the motor cortical areas (Velez, et al. 2004).

It is important to emphasize that because cognitive inhibitory control is part of the executive functions (Aaron, 2007; Nigg, 2000) it is not surprising that the anomalies observed neuro-anatomically and neuro-functionally in children with ADHD in the performance of tasks which demand particular cognitive inhibitory control or other tasks which measure different dimensions of the executive function are similar or even equal, because they share the same neuro-anatomical substrate in the prefrontal cortex in relationship with other sub-cortical areas (Aaron, 2007). According to Barkley (1997) the executive functions are centered in behavioral self-regulation, hence, cognitive inhibitory control is not considered as part of them. However, once again, this is due to the theoretical position of Barkley (1997), who does not agree with their existence.

The variables deriving from the MPS test (Lucangeli et al., 1998) could be used to measure specific features of the executive function and could also have certain specificity and sensibility to the diagnosis of ADHD. The following could be said for the effect size founded for each variable: Choosing correct answers (d = 1.00) could have a possible specificity and sensibility of 84 to distinguish between children without and with ADHD (Cohen, 1988). Choosing irrelevant answers (d = 1.26) could have a possible specificity and sensibility of 90. Representation ( d =: 0.61) could have a possible specificity and sensibility of 73, and Categorization ( d = 1.22) could have a possible specificity and sensibility of 88. This could be determined if the test becomes validated.

There are two problematic elements in this study: 1) the variability of the data, and 2) that none of the children reached the expected mean for the variables measured by the test used (Mean = 50, SD = 10). This may be so because the mean used was derived from Italian population, which has different cultural and education characteristics, factors that have been established as influential in the solution of a mathematic problem (Puente, 1993). However, in the present study the impact of those factors has been reduced because the same standardized scoring was used for both children with and without ADHD.

Likewise, having established the influence of low IQ, arithmetic learning disorder and specific reading disorder, in the ability to solve a mathematic problem (Passolunghi et al., 2005; Marzocchi et al., 2002), these disorders have also been deemed possible comorbidities of ADHD. However, those factors were controlled by the design of the research, ensuring that none of the children included in the study had a previous diagnosis of those disorders, and it was also corroborated with the application of the WISC-III and the Academic Achievement Tests of the Woodcock-Johnson III Battery (Mather & Woodcock, 2005).


References

American Psychiatric Association. (2003). Manual de diagnóstico y estadístico de los trastornos mentales: DSM-IV-TR. Barcelona: Masson. [Spanish version of the revised fourth edition of the original work in English language (2002) Diagnostic and Statistical Manual of Mental Disorders: DSM-W-TR. Washington: Author]         [ Links ].

Aaron, A. R. (2007). The neural bases of inhibition in cognitive control. Neuroscientist, 13 (3), 214-228.         [ Links ]

Aaron, A. R., Schlaghecken, F., Fletcher, P C., Bullmore, E. T., Eimer, M., Barker, R. et al. (2003). Inhibition of subliminally primed responses is mediated by the caudate and thalamus: evidence from functional MRI and Huntington's disease. Brain: A Journal of Neurology, 126 (3), 713-723.         [ Links ]

Backman, M. E. (1972). Patterns of mental abilities: Ethnic, socioeconomic, and sex differences. American Educational Research Journal. 9, 1-12.         [ Links ]

Ban-Har, Y. (1998). Metacognition in Mathematical Problem Solving. De: http://www.aare.edu.au/98pap/yea98408.htm. Consultado el 10 de junio de 2007.         [ Links ]

Barkley, R. A. (1997). ADHD and the nature of self-control. New York: Guilford.         [ Links ]

Barkley, R. A. (1999). Hyperactive Children. Barcelona: Paidós.         [ Links ]

Barrós-Loscertales, A., Mesguer, V., Sanjuán, A., Belloch, V., Parcet, M.A., Torrubia, R. & évila, C. (2006). Behavioral inhibition system activity is associated with increased amygdala and hippocampal gray matter volume: A voxel-based morphometry study. Neuroimage. 33 (3), 1011-1015.         [ Links ]

Benbow, C. P, & Stanley, J. C. (1980). Sex differences in mathematical ability: Fact or artifact? Science. 210, 1262-1264.         [ Links ]

Borkowski, J. G. (1992). Metacognitive theory: A framework for teaching literacy, writing, and math skills. Journal of Learning Disabilities , 25 (4), 253-257.         [ Links ]

Bray, N. W., Hersh, R. E. & Turner, L. A. (1985). Selective remembering during adolescence. Developmental Psychology, 21, 290-294.         [ Links ]

Bray, N. W., Justice, E. M. & Zahm, D. N. (1983). Two developmental transitions in directed forgetting strategies. Journal of Experimental Child Psychology, 36, 43-55.         [ Links ]

Brown, J.S., & Burton, R.R. (1978). Diagnostic models for procedural bugs in basic mathematical skills. Cognitive Science. 155-192.         [ Links ]

Carpenter, T.P (1985). Learning to add and subtract: An exercise in problem solving. En E.A. Silver (Ed.), Teaching and Learning Mathematical Problem Solving: Multiple Research Perspectives. Hillsdale, N.J.: Lawrence Erlbaum Associates.         [ Links ]

Carpenter TP & Moser, J.M. (1984). The acquisition of addition and subtraction concepts in grades one through three. Journal of Research in Mathematics Education. 15, 170-202.         [ Links ]

Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/ BAS scales. Journal of Personality and Social Psychology. 67, 319-333.         [ Links ]

Chelune, G. J., Ferguson, W, Koon, R. & Dickey, T O. (1986). Frontal lobe disinhibition in attention deficit disorder. Child Psychiatry and Human Development, 16 (4), 221-234.         [ Links ]

Collins, V., Dickson, Sh., Simmons, D. & Kameenui, E. Metacognition and its relation to reading comprehension: A synthesis of the research. De:http://idea.uoregon.edu/~ncite/documents/techrep/tech23.html. Consultado el 12 de Junio de 2007.         [ Links ]

Everett, J. & Lajeunesse, C. (2000). Cognitive inhibition and psychopathology: Toward a less simplistic conceptualization. Elsevier Health Science Journals, 26 (2), 13-20.         [ Links ]

Farré, A. & Narbona, J. (2003). EDAH. Evaluación del Trastorno por Déficit de Atención con Hiperactividad. Madrid: TEA Ediciones.         [ Links ]

Fennema, E & Sherman, J. (1977). Sex-related differences in mathematics achievement, spatial visualization and affective factors. American Educational Research Journal. 14 (1), 51-71.         [ Links ]

Fennema, E. & Sherman, J. (1978). Sex-related differences in mathematics achievement and related factor: A further study. Journal of Research in Mathematics Education. 9 (3), 189-203.         [ Links ]

Goldberg, J. (2000). Book review: ADHD and nature of self-control (three years after publication). De: http://www.ualberta.ca/~jpdasddc/ARTICLES/2000(1)/pp89-98GOLDBERG,DAS.doc. Consulted on June 18th 2007.         [ Links ]

Gorenstein, E. E., Mammatto, C. A. & Sandy, J. M. (1989). Performance of inattention-overactive children on selected measures of prefrontal-type function. Journal of Clinical Psychology, 45 (4), 619-632.         [ Links ]

Greeno, J. (1980). Some examples of cognitive task analysis with instructional implications. En R.E. Snow, P Federico y W.E. Montague (Eds.), Aptitude, Learning and Instruction. Vol. 1. Hillsdale, N.J.: Erlbaum.         [ Links ] Groen, G. & Parkman, J. M. (1972). A chronometric analysis of simple addition. Psychological Review. 79, 329-343.         [ Links ]

Halmos, P (1980). The Heart of Mathematics. The American Mathematical Monthly. 87 (7), 519-524.         [ Links ]

Hayes, J.R. Waterman, D.A. & Robinson C.S. (1977). Identifying the relevant aspects of a problem text. Cognitive Science. 1, 297-313.         [ Links ]

Harnishfeger, K. K. & Pope, R. S. (1996). Intending to forget: The development of cognitive inhibition in directed forgetting. Journal of Experimental Child Psychology, 63, 292-315.         [ Links ]

Hegarty, M., Mayer, R. E. & Monk, C. (1995). Comprehension of arithmetic word problems: A comparison of successful and unsuccessful problem solvers. Journal of Educational Psychology. 87, 18-32.         [ Links ]

Hinshaw, S.P (2003). Impulsivity, emotion regulation, and developmental psychopathology: specificity versus generality of linkages. Annals Of The New York Academy Of Sciences. 1008, 149-159.         [ Links ]

Hinsley, D. Hayes, J.R. & Simon, H. (1977). From words to equations: Meaning and representation in algebra word problems. En M.A. Just y P.A. Carpenter (Eds.), Cognitive Processes in Comprehension. Hillsdale, N.J.: Erlbaum.         [ Links ]

Johnston, P H., & Winograd, P N. (1985). Passive failure in reading. Journal of reading Behavior. 17 (4), 279-301.         [ Links ]

Kameenui, E. & Griffin, C. (1989). The National Crisis in Verbal Problem Solving in Mathematics: A Proposal for Examining the Role of Basal Mathematics Programs. The Elementary School Journal. 89 (5), 575-593.         [ Links ]

Larkin, J., McDermott, P., Simon, D.P. & Simon, H.A. (1980). Expert and novice performance in solving physics problems. Science. 208, 1335-1542.         [ Links ]

Lester, F.K. (1978). Mathematical problem solving in the elementary school: Some educational and psychological considerations. En L.L. Hatfield & D.A. Broadbard (Eds.), Mathematical Problem Solving: Papers from Research Workshop. Columbus, Ohio: ERIC/SMEAC.         [ Links ]

Lester, F.K. (1983). Trends and issues in mathematical problem solving. En R. Lesh & M. Landau (Eds.), Acquisition of Mathematics Concepts and Processes. New York: Academic Press.         [ Links ]

Lorsbach, T.C. & Reimer, J.F. (1997). Developmental changes in the inhibition of previously relevant information. Journal of Experimental Child Psychology. 64, 317-342.         [ Links ]

Lucangeli, D., Tressoldi, P E. & Cendron, M. (1998). Test delle abilitá di soluzione del problemi matematici. Trento: Erickson.         [ Links ]

Maccoby, E. E.& Jacklin, C. N.(1974): The Psychology of Sex Differences. Stanford University Press.         [ Links ]

Mariani, M.A. & Barkley, R.A. (1997). Neuropsychological and academic functioning in pre-school boys with attention deficit hyperactivity disorder. Developmental Neuropsychology. 13, 111-129.         [ Links ]

Marzocchi, G. M., Lucangeli, D., De Meo, T, Fini, F. & Cornoldi, C. (2002). The disturbing effect of irrelevant information on arithmetic problem solving in inattentive children. Developmental Neuropsychology, 21, 73-92.         [ Links ]

Mather, N. & Woodcock, R. (2005). Manual of the examiner. Woodcock-Jonhson III. Pruebas de aprovechamiento. Itasca, Il: Riverside Publishing.         [ Links ]

Mayer, R.E. (1986). Thinking, Problem solving & cognition. Barcelona: Paidós.         [ Links ]

Mayer, R. E. (1992). Thinking, problem solving & cognition. New York: Freeman.         [ Links ]

Marshall, S. P (1980). Sex differences in sixth grade children's problem solving. Journal for Research in Mathematics Education. 11, 335-345.         [ Links ]

Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A. & Wager, T. (2000). The unity and diversity of executive functions and their contributions to complex "frontal lobe" tasks: A latent variable analysis. Cognitive Psychology, 41, 49-100.         [ Links ]

Nigg, J. T (2000). On inhibition/disinhibition in developmental psychopathology: Views from cognitive and psychology and a working inhibition taxonomy. Psychological Bulletin, 126, 220-246.         [ Links ]

Nigg, J. T (2003). Response inhibition and disruptive behaviors: Toward a multiprocess conception of etiological heterogeneity for ADHD combined type and conduct disorder early-onset type. Annals of The New York Academy of Sciences, 1008, 170-182.         [ Links ]

Nyberg, L.; Bohlin, G.; Berlin, L. & Janols, L. (2003). Inhibition and Executive Functioning in Type A and ADHD boys. Nord J. Psychiatry. 57, 437-445.         [ Links ]

Palacio, J.D. (2004). Trastorno por déficit de atención e hiperactividad. En Vélez H., Rojas W., Borrero J. & Restrepo J. (Eds.). Fundamentos de medicina, Psiquiatría. (4a Ed.). (p.p. 363-370). Medellín: Coporación para Investigaciones Biológicas (CIB).         [ Links ]

Passolunghi, M. C.; Cornoldi, C. & De Liberto, S. (1999). Working memory and intrusions of irrelevant information in a group of poor problem solvers. Memory and Cognition. 27, 779-790.         [ Links ]

Passolunghi, M. C., Marzocchi, G. M. & Fiorillo, F. (2005). Selective effect of inhibition of literal or numerical irrelevant information in children with attention deficit hyperactivity disorder (ADHD) or arithmetic learning disorder (ALD). Developmental Neuropsychology, 28 (3), 731-753.         [ Links ]

Pedrotty, D. (2005). Math Disability: An Overview. De: http://www.schwablearning.org/articles.asp?r=1001.Consulted on June 18th 2007.         [ Links ]

Pineda, D. A., Kamphaus, R.W., Mora, O., Restrepo, M. A., Puerta, I. C., Palacio, L. G. et al. (1999). Sistema de evaluación multidimensional de la conducta. Escala para padres y maestros de niños de 6 a 11 años, versión colombiana. Revista neurològica, 28, 672-681.         [ Links ]

Polya, G. (1965). Mathematical Discovery: On Understanding, Learning, and Teaching Problem Solving. Vol. 2. New York: Wiley.         [ Links ]

Pozo, J.I., Del Puy M., Domínguez, J. Gómez, M.A. & Postigo, Y. (1994). La solución de problemas. Madrid: Editorial Santillana.         [ Links ]

Puente, A. (1993). Modelos mentales y habilidades en la Solución de Problemas Aritméticos Verbales. Revista de Psicología Aplicada, 46 (2), 149-160.         [ Links ]

Pugalee, D. (2001). Writing, mathematics, and metacognition: Looking for connections through students' work in mathematical problem solving. School Science and Mathematics. 101, 236-245.         [ Links ]

Renz, K., Pugzles, E., Milich, R., Lemberger, C., Bodner, A. & Welsh, R. (2003). On-line story representation in boys with attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 31 (1), 93-104.         [ Links ]

Resnick, LB. (1976). Task analysis in instructional design: Some cases from mathematics. In Klahr, D (Ed.), Cognition and instruction. Hillsdale, NJ: Erlbaum.         [ Links ]

Robinson, C. S., and Hayes, J. R. (1978). Making inferences about relevance in understanding problems. In Revlin, R., and Mayer, R. E., (Eds.), HumanReasoning. Washington, DC: V.H. Winston and Sons.         [ Links ]

Roseboom, P., Nanda, S.A., Bakshi, V.P., Trentani, A., Newman, S. & Kalin N.H. (2007). Predator threat induces behavioral inhibition, pituitary-adrenal activation and changes in amygdala CRF-binding protein gene expression. Psychoneuroendocrinology. 32 (1), 44-55.         [ Links ]

Rosselli, M., Ardila, A., Pineda, D. & Lopera, F. (1997). Neuropsicologia infantil. Medellin: Prensa Creativa.         [ Links ]

Saint Louis University. Success in mathematics. De: http://euler.slu.edu/Dept/SuccessinMath.html. Consultado el 4 de Junio de 2007.         [ Links ]

Scheres, A.; Oosterlaan, J.; Geurts, H.; Morein-Zamir, Sh.; Meiran, N.; Schut, H.; Vlasveld, L. & Sergeant, J. A. (2004). Executive Functioning in boys with ADHD: primarily an inhibition deficit?. Archives of Clinical Neuropsychology. 19, 569-594.         [ Links ]

Shallice, T.; Marzocchi, G. M.; Coser, S.; Del Savio, M.; Meuter, R. F. & Rumiati, R. I. (2002). Executive Function Profile of Children with Attention Deficit Hyperactivity Disorder. Developmental Neuropsychology. 21 (1), 43-71.         [ Links ]

Scholten, M.R.; Van Honk, J.; Aleman, A. & Kahn, R. S. (2006). Behavioral inhibition system (BIS), behavioral activation system (BAS) and schizophrenia: relationship with psychopathology and physiology. Journal Of Psychiatric Research. 40 (7), 638-645.         [ Links ]

Shue, K. L. & Douglas, V. I. (1992). Attention deficit hyperactivity disorder and the frontal lobe syndrome. Brain and Cognition, 20, 104-124.         [ Links ]

Servera-Barceló, M. (2005). Modelo de autorregulación de Barkley aplicado al trastorno por déficit de atención con hiperactividad: una revisión. Revista de Neurología. 40 (6), 358-368.         [ Links ]

Sibley, B.A, Etnier, J.L & Le Measurier, G.C. (2005). Effects of an acute bout of exercise on inhibition and cognitive performance. De: http://aahperd.confex.com/aahperd/2005/preliminaryprogram/abstract_6590.htm. Consulted on June 7th 2007.         [ Links ]

Slachevsky, A., Pérez, C., Silva, J., Orellana, G., Prenafeta, M., Alegría, P & Peña, M. (2005). Córtex prefrontal y trastornos del comportamiento: modelos explicativos y métodos de evaluación. Revista Chilena de Neuropsiquiatría, 43 (2), 109-121.         [ Links ]

Sternberg, R. J. (1987). Razonamiento, solución de problemas e inteligencia. En R.J. Sternberg (Ed.), Inteligencia humana, II. Cognicion, personalidad e inteligencia. Buenos Aires: Paidós.         [ Links ]

Stins, J. F., Polderman, J. C., Boomsma, D. I. & Geus, E. C. J. A comparison among three measures of response inhibition. De: http://www.tweelingenregister.org/nederlands/verslaggeving/congresbezoek/stins.pdf. Consulted on February 20th 2007.         [ Links ]

Swanson, H. L. (1989). Strategy instruction: Overview of principles and procedures for effective use. LearningDisability Quarterly. 12 (1), 3-14.         [ Links ]

Vaidya, Ch., Bunge, S., Dudukovic, N., Zalecki, Ch., Elliott, G. & Gabrieli, J. (2005). Altered neural substrates of cognitive control in childhood ADHD: Evidence from functional magnetic resonance imaging. The American Journal of Psychiatry, 162 (9), 1605-1613.         [ Links ]

Vale, W.; Spiess, J.; Rivier, C. & Rivier, J. (1981). Characterization of a 41-residue ovine hypothalamic peptide that stimulates secretion of corticotropin and beta-endorphin. Science. 213, 1394-1397.         [ Links ]

Wilson, J., Fernandez, M. & Hadaway, N. (2007). Mathematical Problem Solving. Recuperado el 4 de junio de 2007, de http://jwilson.coe.uga.edu/EMT725/EMT725.html        [ Links ]

Wilson, S. P & Kipp, K. (1998). The development of efficient inhibition: Evidence from directed-forgetting tasks. Developmental Review, 18, 86-123.         [ Links ]

Zacks, R. T & Hasher, L. (1994). Directed ignoring: Inhibitory regulation of working memory. In D. Dagenbach & T H. Carr (Eds.), Inhibitory processes in attention, memory, and language (pp. 241-264). New York: Academic Press.         [ Links ]

Zentall, S. S. (1990). Fact-retrieval automatization and math problem solving by learning disabled, attention-disordered, and normal adolescents. Journal of Educational Psychology. 82, 856-865.         [ Links ]

Zentall, S. S. & Ferkis, M. A. (1993). Mathematical problem solving for youth with ADHD, with and without learning disabilities. Learning Disabilities Quarterly. 16, 6-18.         [ Links ]

Zentall, S. S.; Smith, Y. N.; Lee, Y. B. & Wieczorek, C. (1994). Mathematical outcomes of attention-deficit hyperactivity disorder. Journal of Learning Disabilities. 27, 510-519.         [ Links ]

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