Wednesday 13 March 2024

LA FP BÁSICA: UNA TRAMPA EN LA DIVERSIDAD

LA FORMACIÓN PROFESIONAL BÁSICA: LA ALTERNATIVA FALLIDA A LA EDUCACIÓN CONVENCIONAL


Manuel Ojea Rúa
 

Diario LA REGIÓN, 13/03/2024




FP Básica: la incoherencia de la FP actual... seguir leyendo 




Thursday 7 March 2024

PÓSTER PRESENTADO AL CONGRESO AUTISMO PUEBLA (MÉXICO)

 CONGRESO AUTISMO PUEBLA (MÉXICO)

LA TEORÍA CÍCLICA GLOBAL EXPLICATIVA DEL PENSAMIENTO EN PERSONAS CON TRASTORNO DEL ESPECTRO AUTISTA

Prof. Dr. Manuel Ojea Rúa
Con la colaboración de Lourdes Rivas Otero




Friday 16 February 2024

PROGRAMAS DE ATENCIÓN A LA DIVERSIDAD O METODOLOGÍA DIDÁCTICA REGULAR (INSTITUTIONAL PROJECTS OF DIVERSITY VS. REGULAR DIDACTIC)

              Volume 07 Issue 02 February 2024



PhD. Manuel Ojea Rúa
https://orcid.org/0000-0002-9787-2520


ABSTRACT

The teaching and learning of students with Autism Spectrum Disorder (ASD) requires the design of diversity projects at the different institutional levels of the educational centre. However, if these projects are not well adapted to the specific needs of the students, they will not achieve the expected effective results. In a study conducted with a total of 145 participants from different schools, it was shown that the presence of specific institutional educational projects was not a sufficient condition to respond effectively to the needs of the participants, whose curricular and social improvements were not shown to be significant (sig: .66). Even in the absence of these high-scale projects, when the usual methodology was well adapted to the specific needs of students with ASD, the improvements found in the academic and social, that´s coded as dependent variable (DV): improving, domains were highly significant (sig: .00) in terms of the use of meaningful didactics based on the creation of networks of relationships between informative content or highly meaningful learning. Now, the interactive constant of both components, i.e. the intersection of a project design when these have been appropriately adapted to the particular needs, then both variables became the explanatory variance of the academic and social of DV of students with ASD (constant t for the sum of nodal relationships + project: 3.70 (sig: .00), to which was added the explanatory variance of the students' age intervals (constant t for the sum of nodal relationships + project + age: 4.07, sig: .00): 3.70 (sig: .00), to which was also added the explanatory variance of the students´age intervals (constant t for the sum of nodal relationships + project + age: 4.07, sig: .00). 70 (sig: .00), to which the explanatory variance of the students´ age intervals were also added (constant t for the sum of nodes + project + age: 4.07, sig: .00). In conclusion, the design of general institutional projects, even if they cover all levels of education, are not effective on their own unless they are specifically tailored to the particular needs of the target student’s variable: “improving”.

KEYWORDS:

Autism spectrum disorder. Significant learning. Educational projects. Adapted regular teaching.


REFERENCES

1) American Psychiatric Association (APA) (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. https://www.psychiatry.org/psychiatrists/practice/dsm


2) Aracı, N., Melekoğlu, M. A., & Çetin, M. E. (2023). Impact of a mnemonic strategy on learning science concepts for middle school students with specific learning disabilities. Learning Disabilities: A Contemporary Journal 2(1), 69–85. https://psycnet.apa.org/record/2024-32302-005

3) Baddeley, A. D. (1999). Essentials of human memory. Washington: Psychology Press. https://psycnet.apa.org/record/1999-02729-000

4) Baker, S., Gersten, R., & Lee, D. (2002). A synthesis of empirical research on teaching mathematics to low-achieving students. The Elementary School Journal, 103, 51–73. https://www.researchgate.net/publication/249134736_A_Synthesis_of_Empirical_Research_on_Teaching_Mathematics_to_Low-Achieving_Students

5) Biancarosa, G., & Snow, C. E. (2004). Reading next. A vision for action and research in middle and high school literacy: A report to Carnegie Corporation of New York. Washington, DC: Alliance for Excellence in Education. https://media.carnegie.org/filer_public/b7/5f/b75fba81-16cb-422d-ab59-373a6a07eb74/ccny_report_2004_reading.pdf

6) Boekaerts, M., & Cascallar, E. (2006). How far have we moved toward the integration of theory and practice in self-regulation? Educational Psychology Review, 18(3), 199–210. https://www.researchgate.net/publication/227279167_How_Far_Have_We_Moved_Toward_the_Integration_of_Theory_and_Practice_in_Self-Regulation

7) Boon, R. T., Urton, K., Grünke, M., & Rux, T. A. (2019). Mnemonic strategies in mathematics instruction for students with learning disabilities: A narrative review. Learning Di¬sabilities: A Multidisciplinary Journal, 24(1), 49–62. https://doi.org/10.18666/LDMJ- 2019-V24-I2-9901

8) Caron, M. J., Mottron, L., Berthiaume, C., & Dawson, M. (2006). Cognitive mechanisms, specificity and neural underpinnings of visuospatial peaks in autism. Brain, 129, 1789–802. https://pubmed.ncbi.nlm.nih.gov/16597652/

9) Carter, E. W., Common, E. A., Sreckovic, M. A., Huber, H. B., Bottema-Beutel, K., Gustafson, J. R., ... & Hume, K. (2014). Promoting social competence and peer relationships for adolescents with autism spectrum disorders. Remedial and Special Education, 35(2), 91–101. https://doi.org/10.1177/07419332513514618

10) Center on Multi-Tiered Systems of Support. (2022). Implementation. https://mtss4success.org/implementation

11) Cioca, L., & Nerisanu, R. A. (2020). Enhancing creativity: Using visual mnemonic devices in the teaching process in order to develop creativity in students. Sustainability, 12(5), 1985. https://doi.org/10.3390/su12051985

12) Cook, B., & Cook, S. (2013). Unravelling evidence-based practices in special education. The Journal of Special Education, 47(2), 71–82. https://doi.org/10.1177/0022466911420877

13) Cook, B., & Odom, S. L. (2013). Evidence-based practices and implementation science in special educa¬tion. Exceptional Children, 79(2), 135–144. https://doi.org/10.1177/001440291307900201

14) Cook, B., Cook, S. C., & Collins, L. W. (2016). Terminology and evidence-based practice for students with emotional and behavioral disorders: Exploring some devilish details. Beyond Behavior, 25(2), 4–13. https://doi.org/10.1177/107429561602500202

15) Council of Europe. (2018). CEFR companion volume with new descriptors. https://www.researchgate.net/publication/338178234_Council_of_Europe_2018
_Common_European_Framework_of_Reference_for_Languages_
Learning_Teaching_Assessment_Companion_Volume_with_
New_Descriptors_Strasbourg_Council_of_Europe_Publishing_Authors_B_North_E

16) Dembo, M. H., & Eaton, M. J. (2000). Self- regulation of academic learning in middlelevel schools. Elementary School Journal, 100(5), 473–490. https://www.jstor.org/stable/1002280

17) Dunn, M., & Miller, D. (2016). Improving story writing: Integrating the story mnemonic stra¬tegy with iPad apps for art and keyboarding. International Journal for Research in Learning Disabilities, 3(1), 11–28. https://www.semanticscholar.org/paper/Improving-Story-Writing%3A-Integrating-the-Story-with-Dunn-Miller/d9444d49593320391a1127fade56be4843b6e323

18) Fleury, V. P., Hedges, S., Hume, K., Browder, D., Thompson, J., Fallin, K., El Zein, F., Reutebuch, C., & Vaughn, S. (2014). Addressing the academic needs of adolescents with autism spectrum disorder in secondary education. Remedial and Special Education, 35(2), 68–79. https://doi.org/10.1177/0741932513518823

19) Frith, C. (2004). Is autism a disconnection disorder? The Lancet Neurology, 3(10), 577. https://doi.org/10.1016/s1474-4422(04)00875-0

20) Frith, U. (1989). Autism: Explaining the enigma. Oxford: Blackwell. https://www.scirp.org/(S(lz5mqp453edsnp55rrgjct55))/reference/referencespapers.aspx?referenceid=1268296

21) Frost, K. M., Brian, J., Gengoux, G. W., Hardan, A., Rieth, S. R., Stahmer, A., & Ingersoll, B. (2020). Identifying and measuring the common elements of naturalistic developmental behavioral interventions for autism spectrum disorder: Development of the NDBI-Fi. Autism. 24(8), 2285-97. https:// doi. org/10. 1177/ 13623 61320 944011.

22) Gersten, R., Chard, D., Jayanthi, M., Baker, S., Morphy, P., & Flojo, J. (2009). A meta-analysis of mathematics instructional interventions for students with learning disabilities: A technical report. Los Alamitos, CA: Instructional Research Group.

23) Gore, M. C. (2010). Inclusion strategies for secondary classrooms: Keys for struggling learners. Corwin Press: SAGE. https://doi.org/10.4135/9781483350424

24) Happé, F. G. (1999). Autism: Cognitive deficit or cognitive style? Trends in Cognitive Sciences, 3(6), 216–222. Doi: 10.1016/s1364-6613(99)01318-2

25) Happé, F., & Frith, U. (2006). The weak central coherence account: Detail- focused cognitive style in autistic spectrum disorders. Journal of Autism and Developmental Disorders, 36, 5–25. https://pubmed.ncbi.nlm.nih.gov/16450045/

26) Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77, 81–112. https://journals.sagepub.com/doi/abs/10.3102/003465430298487

27) Hume, K., Odom, S. L., Steinbrenner, J. R., DaWalt, S., Hall, L. J., Kraemer, B. ... & Bolt, D. M. (2022). Efficacy of a School-Based Comprehensive Intervention Program for Adolescents with Autism. Exceptional Children, 88(2), 23–240. DOI:10.1177/00144029211062589. https://pubmed.ncbi.nlm.nih.gov/33449225/

28) Larkan-Skinner, K., & Shedd, J. M (2021). Real-Time Data and Predictive Analytics: Where Does IR Fit? New Directions for Institutional Research, 2020(185-186), 11–24. DOI:10.1002/ir.20326. https://onlinelibrary.wiley.com/doi/abs/10.1002/ir.20326

29) Liu, A. Y, Lacoe, J., Lipscomb, S., Halmson, J., Johson, D. R., Thurlow, M. ... & Sllverberg, M. (2018). Preparing for life after high school: The characteristics and experiences of youth in special education. Findings from the national longitudinal transition study 2012. Vol. 3: Comparisons over Time (Full Report) (NCEE 2018-4007). Washington, DC: U.S. Department of Education, Institute of Education Sciences. https://files.eric.ed.gov/fulltext/ED580934.pdf

30) Lubin, J., & Polloway, E. A. (2016). Mnemonic instruction in science and social studies for students with learning problems: A review. Learning Disabilities: A Contemporary Journal, 14(2), 207–224. https://www.semanticscholar.org/paper/Mnemonic-Instruction-in-Science-and-Social-Studies-Lubin-Polloway/e2eb55c26e0cde6a31c33ead248288def86625f4

31) Maenner, M. J., Shaw, K. A., & Baio, J. (2020). Prevalence of autism spectrum disorder among children aged 8 years autism and developmental disabilities monitoring network, 11 sites, United States, 2016. MMWR Surveillance Summaries, 69(4), 1–12. https://doi.org/10.15585/mmwr.ss6904a1

32) Mandinach, E. B. (2012). A perfect time for data use: Using data-driven decision making to inform practice. Educational Psychologist, 47(2), 71–85. DOI: 10.1080/00461520.2012.667064.

33) McFarland, J., Hussar, B., Zhang, J., Wang, X., Wang, K., Hein, S. ... & Barmer, A. (2019). The condition of education 2019 (NCES 2019-144). IES. National Center for Education Statistics. https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2019144

34) Morin, K. L., Sam, A., Tomaszewski, B., Waters, V., & Odom, S. L. (2021). Knowledge of evidence-based practices and frequency of selection among school-based professionals of students with autism. The Journal of Special Education, 55(3), 143–152. DOI: 10.1177/0022466920958688. journalofspecialeducation.sagepub.com

35) Mursi, N. B., Sulaimani, M. F. (2022). Influence of context related factors on Saudi special education teacher´s understanding of evidence, evidence- based, and evidence- based practices. Problems of Education in the 21st Century, 80(4), 588–600. https://doi.org/10.33225/pec/22.80.588

36) Odom, S. L., Collet-Klinenberg, L., Rogers, S., & Hatton, D. (2010). Evidence-based practices in interventions for children and youth with autism spectrum disorders. Preventing School Failure: Alternative Education for Children and Youth, 54, 275–282. https://www.tandfonline.com/doi/full/10.1080/10459881003785506

37) Ojea, M. (2023). Autism: New conceptual propositional hypothesis. European Journal of Theoretical and Applied Sciences, 1(6), 115–124. https://ejtas.com/index.php/journal/article/view/437

38) Reichow, B., & Volkmar, F. R. (2011). Evidence-based practices in autism: Where we started. In B. Reichow, P. Doehring, D. V. Cicchetti, & F. R. Volkmar (Eds.), Evidence-based practices and treatments for children with autism (pp. 3–10). Springer. https://psycnet.apa.org/record/2010-25555-001

39) Selçuk, Z. (2018). Eğitim psikolojisi [Education Psychology]. Nobel Akademi. https://www.academia.edu/36316637/E%C4%9Fitim_Psikolojisi

40) Spencer, T., Detrich, R., & Slocum, T. A. (2012). Evidence-based practice: A framework for making effective decisions. Education and Treatment of Children, 35(2), 127–151. https://doi.org/10.1353/etc.2012.0013

41) Test, D. W., Smith, L. E., & Carter, E. W. (2014). Equipping youth with autism spectrum disorders for adulthood: Promoting rigor, relevance, and relationships. Remedial and Special Education, 35(2), 80–90. https://doi.org/10.1177/0741932513514857

42) Vaughn, S., Gersten, R., & Chard, D. J. (2000). The underlying message in LD intervention research: Findings from research syntheses. Exceptional Children, 67, 99–114. https://psycnet.apa.org/record/2001-00001-007

43) Vaughn, S., Wanzek, J., Murray, C. S. (2012). Intensive interventions for students struggling in reading and mathematics. A Practice Guide. Portsmouth, NH: Center on Instruction at RMC Research Corporation. https://files.eric.ed.gov/fulltext/ED531907.pdf

44) Wong, C., Odom, S. L., Hume, K., Cox, A. W., Fettig, A., Kucharczyk, S. ... & Schultz, T. R. (2015). Evidence based practices for children, youth, and young adults with autism spectrum disorder: A comprehensive review. Journal of Autism and Developmental Disorders, 45, 1951–1966. https://doi.org/10.1007/s10803-014-2351-z

45) Yamamoto, S. H., & Alverson, C. Y. (2023). Post-high school outcomes of students with autism spectrum disorder and students with intellectual disability: Utilizing predictive analytics and state data for decision making. Journal of Intellectual Disabilities, 27(3) 633–647. DOI: 10.1177/17446295221100039. journals.sagepub.com/home/jid

46) Zhang, J., Martella, R. C., Kang, S., & Yenioglu, B. Y. (2023). Response to Intervention (RTI)/ Multi-Tiered Systems of Support (MTSS): A nationwide analysis. Journal of Educational Leadership and Policy Studies, 7(2), 1–26. https://files.eric.ed.gov/fulltext/EJ1396417.pdf

47) Ziviani, J., Wilkinson, S., Hinchliffe, F., & Feeney, R. (2015). Mapping allied health evidence-based practice: providing a basis for organisational realignment. Australian Health Review, 39(3), 295–302. https://doi.org/10.1071/AH14161


Wednesday 31 January 2024

MALTRATO ESCOLAR (SOCIAL)

 El maltrato escolar y social como una cuestión sistémica: el que maltrata no solo es el maltratador; quien chismorrea, calla o ríe la gracia también lo es.

Diario La Región, 31-1-2024



ACOSO ESCOLAR: UNA CUESTIÓN DE SISTÉMICA GLOBAL
El acoso entre iguales como consecuencia de las actitudes y los comportamientos en el contexto socio- educativo

 Prof. Dr. Manuel Ojea Rúa

 A pesar de los avances actuales en las medidas educativas, relacionadas con la elaboración de programas para hacer frente al acoso escolar, estadísticamente, no solo persiste su existencia, sino que, en la actualidad, está aumentando considerablemente en cuanto un elemento sistémico que afecta al conjunto del sistema socio- educativo, lo cual merece dedicarle una reflexión en profundidad.

En efecto, en el ámbito de los centros educativos, tanto desde la acción tutorial debidamente planificada, de la estructura del Plan de Convivencia, así como, desde los programas específicos de prevención, propuestos por la legislación educativa actual, se trata de proponer formas preventivas y de actuación inmediata frente al acoso escolar y sus graves consecuencias en el ámbito psico- social de las personas que lo sufren.

Y, aunque, asimismo, son muy evidentes las teorías conceptuales que hacen hincapié en las hipótesis basadas en la presencia de perfiles de las personas acosadoras, que ejercen el maltrato entre sus iguales más sensitivos, esta concepción proposicional de entender el proceso del maltrato escolar no es tan lineal como puede parecer, pues, un perfil específico concreto, que sea sensible, puede convertirse en colaborador del grupo acosador y así poder protegerse del efecto del maltrato, hallando así un modo de pertenencia, que evita su propia autodestrucción individual.

Pues bien, en materia de bullying, ya dediqué algunos artículos en este mismo Xornal Escolar, cuando publiqué un protocolo de actuación ante el acoso escolar (La Región, 11-2-2016), que, luego, amplié con el análisis de la detección del mobbing existente entre los docentes (La Región, 24-5-2016), por lo que, en este artículo, intento centrarme en la consideración sistémica del concepto del maltrato escolar, pues sin esta acepción hipotética, difícilmente, este podrá erradicarse.

Por lo que, más allá de la política escolar oficial, la cual, sin duda, debe ser clara, rotunda y altamente previsora de las situaciones conflictivas, los elementos esenciales están conformados por los comportamientos personales de los propios participantes en el medio interactivo socio- escolar, que conforman el proceso intrínseco bajo el cual subyacen las conductas luego emergentes negativas. No, en pocas ocasiones, los estudiantes acosadores no hacen sino imitar las actitudes despectivas y/o de intimidación observadas durante el proceso interactivo socio- escolar de forma, muchas veces, directa, pero, otras muchas, de forma indirecta, pero que ambas constituyen modos conductuales claramente observables dentro del contexto en sí mismo.

Estas situaciones pueden producirse, tanto en ámbitos formales, como son reuniones, comisiones y/o la propia dinámica del aula, como, sobre todo, en ambientes no formales e informales, como diálogos de pasillo, comentarios de café, opiniones en la sala de docentes, así como los comentarios de las familias durante entradas y salidas del colegio, en la que se pueden producir alegatos despectivos sobre esta o aquella cuestión, que terminan llegando al ámbito del aula de forma expresa o encubierta, en calidad de cultivos consecuentes con las situaciones posteriores de acoso y/o maltrato.

Pongamos algunos ejemplos intrínsecos de una consecuencia indirecta del acoso entre iguales. Desde un equipo directivo se produce una actitud despectiva hacia un determinado docente, la cual es reiterativa, que se evidencia en el contexto de las reuniones oficiales. Pues bien, esta situación siempre acaba teniendo una repercusión general en el centro. La desconsideración hacia ese docente se extiende encubierta dentro de la clase, de forma que, si ese docente valora la actitud o el trabajo de un determinado estudiante, ese mismo estudiante puede convertirse en un objetivo de los compañeros de perfil acosador. La situación persiste porque la mayoría acepta y calla ante este tipo de situaciones para no ganarse la enemistad, especialmente, cuando se trata de los denominados grupos de poder dentro del contexto socio- escolar.

Si dentro del contexto del aula, un docente estima en demasía o desestima la actitud y/o el trabajo de un determinado estudiante, que reitera asiduamente, si este se trata de estudiante sensitivo, ya puede convertirse en objeto de acoso entre iguales por los de mayor perfil acosador.

O, cuando, también, en el ámbito del aula, al mismo estudiante se le corrige en público sus aspectos más débiles reiteradamente o se le hace constantemente preguntas a sabiendas de su posible fracaso en la respuesta, este pronto se convierte en objetivo de risa en público, que, luego, esa misma situación se generaliza al área de ocio y tiempo libre.

Si, por el contrario, en el ámbito de clase, al mismo estudiante se le pone en público como ejemplo de perfección, sobredimensionando su individualidad, aunque así fuera, este podría convertirse en objetivo de acoso posteriormente, pues, sobredimensionar una cualidad, sino es autoatribuido, puede perjudicar más que beneficiar a dicho estudiante/ persona.

Durante las salidas o entradas, unas familias están haciendo comentarios negativos ocasionales o reiterados sobre otra determinada familia, el estudiante perteneciente a esa familia cuestionada, puede convertirse en un objetivo de los perfiles más acosadores en el contexto socio- educativo.

Cuando entre el propio grupo de estudiantes, se critica y/o deprecia la actitud social y/o escolar de un determinado compañero, el cual es más sensitivo, este puede convertirse en objetivo de una situación de bullying entre iguales, ya no solo desde el grupo que critica, sino que la situación puede generalizarse a otros grupos con perfiles acosadores dentro del contexto social y escolar.

Los efectos de todos estos y otros muchos ejemplos, van a ejercer una intensidad que va a depender de otros muchos elementos sistémicos educativos, es decir, de la cultura organizativa en sí, del estilo de liderazgo del centro y de la consideración de todos los factores organizativos internos que lo conforman. Pero, además, esta presión educativa no se halla aislada, sino que, por el contrario, está rodeada de múltiples interacciones sociales que giran alrededor de conceptos, dentro de los cuales, la presión grupal ejerce toda su influencia sobre un chivo expiatorio, que siempre coincide con alguien diferencial y/o de mayor debilidad/ sensibilidad psico- social.

Seguramente, ninguna de estas acciones se realiza con esta finalidad última, pero, de forma explícita o implícita, se convierten, siempre, en causas explícitas del acoso entre iguales.

En consecuencia, además de los planes y programas formales, bien estructurados, frente el acoso escolar, es preciso acompañarlos de las acciones cotidianas personales y sociales que no busquen antropomorfizar el trabajo grupal docente, ni gestionar la autoridad moral de determinados comentarios, que pueden ocasionar, consecuencias muy graves en el ámbito individual, que, a veces, son irreparables, aun cuando estas no hubieran tenido inicialmente tal intención.

Pues bien, todo cuanto estoy proponiendo no es en nada una opinión personal, ni la idea consecuente de la improvisación, por el contrario, responde a un conjunto de investigaciones empíricamente contrastadas y altamente refutadas en el ámbito internacional, relativa al acoso escolar, que son harto conocidas (Olweus, 1993; Fitch, 2005; Orpinas y Horne, 2006; Totura et al., 2009; Namie y Namie, 2000; Crothers, Kolbert y Barker, 2006; Hansen y otros, 2006; Gunsalus et al., 2007; Dellasega, 2009; Salmivali et al., 2010; Zapf et al., 2011; Richard, Schneider y Mallet, 2011; Carr, 2015). En todas ellas, así como, entre otros estudios ya más actualizados (Sharma et al., 2023; Saneleuterio et al., 2023; Irwin et al., 2023), el acoso escolar es una proposición en cuanto una entidad sistémica global, consecuencia de todas las interacciones y acciones sociales ejercidas, cuya influencia es mayor si esta procede de las posiciones de sobreextensión dimensionadas de los grupos institucionales de mayor poder, que, aun pareciendo acciones inocuas y/o pasivas, por medio del feedback social se convierten en procesos altamente activos, que pueden ser altamente aversivas y generadoras de maltrato en determinadas situaciones particulares dentro del contexto.

Ahora, dentro de cada uno de nosotros/as, cabe reflexionar sobre nuestras propias acciones y aportaciones dentro del ámbito socio- familiar y escolar, tanto en referencia a la escuela primaria, secundaria, como a la enseñanza superior, para tratar de mejorar de verdad esta situación, pues, más allá de la certeza de las teorías de la personalidad sobre los tipos cognitivos, que, en efecto, son ciertas, también las variables interactivas, tales como las actitudes y comportamientos personales, grupales y/o acciones colegiadas pueden desencadenar un proceso grave de maltrato con todas las consecuencias que esto puede suponer en cualquiera de las fases de su desarrollo en una persona concreta, aun cuando, la intención inicial del grupo no había sido esta.




Friday 26 January 2024

¿PROCESO PERCEPTUAL DE CURACIÓN EN EL TRASTORNO DEL ESPECTRO AUTISTA O ERROR DIAGNÓSTICO INICIAL? HEALING PERCEPTUAL PROCESS IN AUTIMS SPECTRUM DISORDER OR INITIAL MISDIAGNOSIS?

¿PROCESO PERCEPTUAL DE CURACIÓN DEL TRASTORNO DEL ESPECTRO AUTISTA O ERROR DIAGNÓSTICO INICIAL?

HEALING PERCEPTUAL PROCESS IN AUTISM SPECTRUM DISORDER OR INITIAL MISDIAGNOSIS?


European Modern Studies Journal, 7(6), 152-161. 2024.


VER ARTÍCULO COMPLETO

SEE FULLY ARTICLE


SUMMARY

Autism spectrum disorder is characterized by the presence of particularities over neural networks of the information flexible transmission, which affects the perceptual-cognitive and socio-behavioural levels of the disorder. This research appoints a longitudinal Single Case Study performed throughout 32 years, structured in five intervals-evolutionary phases (0–4.5; 4.6–9: 9.1–12; 12.1–16.5; 16.6–32 years-old), that confirms the importance of the influence of neural networks variable on criteria that had enclosed to disorder symptomatic group.

The successive differential changes through the five phases of analysis, in relation to the variables “perceptive”, “social” and “behaviour” of the analysis found highly significant, which have been found through the Friedman comparative test; while the “nodes” variable has remained constant, with high evolutive development level. Likewise, it has been shown by Pearson correlation analysis, the variables relationship is significantly related at .1 critical level. The conclusions confirm that variable related to nodal relationships "nodes" decisively influences the evolutionary improvement to other variables investigated, that has been progressively modified the symptomatic group of the disorder to this Case Study.

The fundamental conclusion has been suggested that neuropsychological variables of processing, especially related to the functional ability to relational networks of information processing must be exhaustively gave additionally to the socio-behavioural criteria along the disorder evaluation process to avoid possible initial errors in the diagnostic conclusions.

 KEYWORDS

Autism spectrum disorder. Autism diagnosis. Perceptive- cognition. Semantic memory.

REFERENCES

American Psychiatric Association (APA) (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. https://www.psychiatry.org/psychiatrists/practice/dsm

Arenella, M., Cadby, G., 3, Witte, W. de, Jones, R. M., Whitehouse, A. J. O., Moses, E. K., ... & Bralten, J. (2022). Potential role for immune-related genes in autism spectrum disorders: Evidence from genome-wide association meta-analysis of autistic traits. Autism, 26(2), 361–372. Doi: 10.1177/13623613211019547

Bowers, M. E., Buzzell, G. A., Bernat, E. M., Fox, N. A., & Barker, T. V. (2018). Time-frequency approaches to investigating changes in feedback processing during childhood and adolescence. Psychophysiology, 55, e13208. https://psycnet.apa.org/record/2018-41005-001

Caron, M. J., Mottron, L.,  Berthiaume, C., & Dawson, M. (2006). Cognitive mechanisms, specificity and neural underpinnings of visuospatial peaks in autism. Brain, 129, 1789–802. https://pubmed.ncbi.nlm.nih.gov/16597652/

Courchesne, E., & Pierce, K. (2005). Why the frontal cortex in autism might be talking only to itself: local over-connectivity but long-distance disconnection. Current Opinion in Neurobiology, 15(2), 225–230. https://pubmed.ncbi.nlm.nih.gov/15831407/

de la Torre-Ubieta, L., Won, H., Stein, J. L., & Geschwind, D. H. (2016). Advancing the understanding of autism disease mechanisms through genetics. Nature Medicine, 22(4), 345–361. https://pubmed.ncbi.nlm.nih.gov/27050589/

Dong, W. K., & Greenogh, W. T. (2004). Plasticity of nonneuronal brain tissue: Roles in developmental disorders. Mental Retardation and Developmental Disabilities Research Reviews,10(2), 85–90. https://doi.org/10.1002/mrdd.20016

Etkin, A., Buchel, C., & Gross, J. J. (2015). The neural bases of emotion regulation. Nature Reviews Neuroscience, 16, 693–700. Doi:10.1038/nrn4044

Fox, M. D., & Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience, 8(9), 700–711. https://www.nature.com/articles/nrn2201

Frith, C. (2004). Is autism a disconnection disorder? The Lancet Neurology, 3(10), 577. https://doi.org/10.1016/s1474-4422(04)00875-0

Frith, U. (1989). Autism: Explaining the enigma. Oxford: Blackwell. https://www.scirp.org/(S(lz5mqp453edsnp55rrgjct55))/reference/referencespapers.aspx?referenceid=1268296

Grove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R. K., Won, H., . . . & Børglum, A. D. (2019). Identification of common genetic risk variants for autism spectrum disorder. Nature Genetics, 51(3), 43–444. https://pubmed.ncbi.nlm.nih.gov/30804558/

Happé, F. G. (1999). Autism: Cognitive deficit or cognitive style? Trends in Cognitive Sciences, 3(6), 216–222. Doi: 10.1016/s1364-6613(99)01318-2

Happé, F., & Frith, U. (2006). The weak central coherence account: Detail- focused cognitive style in autistic spectrum disorders. Journal of Autism and Developmental Disorders, 36, 5–25. https://pubmed.ncbi.nlm.nih.gov/16450045/

Harper, J., Malone, S. M., & Bernat, E. M. (2014). Theta and delta band activity explain N2 and P3 ERP component activity in a go/no-go task. Clinical Neurophysiology, 125, 124–132. https://pubmed.ncbi.nlm.nih.gov/23891195/

Hull, J. V., Jacokes, Z. J., Torgerson, C. M., Irimia, A., & Van Horn, J. D. (2016). Resting-state functional connectivity in autism spectrum disorders: A review. Frontiers in Psychiatry, 7, Article 205. Doi:10.3389/fpsyt.2016.00205

Jones, R. M. (2015). MACROD2 gene associated with autistic- like traits in a general population sample. Psychiatric Genetics, 24(6), 241–248. https://journals.lww.com/psychgenetics/Abstract/2014/12000/MACROD2_gene_associated_with_autistic_like_traits.2.aspx

Just, M., Cherkassky, V., Keller, T., & Minshew, N. J. (2004) Cortical activation and synchronization during sentence comprehension in high-functioning autism: evidence of underconnectivity. Brain, 127(8), 1811–1821. https://pubmed.ncbi.nlm.nih.gov/15215213/

Kim, S. H., Buzze, B., Faja, S., Choi, Y. B., Thomas, H. R., Brito, N. H., ... & Fox, N. (2020). Neural dynamics of executive function in cognitively able kindergarteners with autism spectrum disorders as predictors of concurrent academic achievement. Autism, 24(3), 780–794. https://doi.org/10.1177/136236131987492

Leibenluft, E. (2017). Pediatric irritability: A systems neuroscience approach. Trends in Cognitive Sciences, 21, 277–289. Doi:10.1016/j.tics.2017.02.002

Li, H., Xue, Z., Ellmore, T. M., Frye, R. E., & Wong, T. C. (2014). Network–based analysis reveals stronger local diffusion-based connectivity and different correlations with oral language skills in brains of children with high functioning autism spectrum disorders. Human Brain Mapping, 5(2), 396–413. https://pubmed.ncbi.nlm.nih.gov/23008187/

Mevel, K., Fransson, P., & Bölte, S. (2015). Multimodal brain imaging in autism spectrum disorder and the promise of twin research. Autism, 19(5), 527–541. Doi: 10.1177/1362361314535510

Ojea, M. (2023a). Autism: New conceptual propositional hypothesis. European Journal of Theoretical and Applied Sciences, 1(6), 115–124. https://ejtas.com/index.php/journal/article/view/437

Ojea, M. (2023b). Interrelations between perceptive- cognitive factors and behavioural variables to level diagnosis of people with autism spectrum disorder. RA Journal of Applied Research, 9(11), 540–548. http://www.rajournals.in/index.php/rajar/article/view/1254

Ojea, M. (2023c). Perceptual behavioural precision scale (PB. PS- ASD). Lima. Ed. Barcelona. https://libreriaites.com/producto/escala-de-precision-perceptivo-conductual-ep-pc-tea/

Polleux, F., & Lauder, J. M. (2004). Toward a developmental neurobiology of autism. Mental Retardation and Developmental Disabilities Research Reviews, 10(4), 303–317. https://doi.org/10.1002/mrdd.20044

Shah, A., & Frith, U. (1993). Why do autistic individuals show superior performance on the block design task? Journal of Child Psychology and Psychiatry, and Allied Disciplines, 34(8), 1351–1364.  https://doi.org/10.1111/j.1469-7610.1993.tb02095.x

Tick, B., Bolton, P., Happé, F., Rutter, M., & Rijsdijk, F. (2016). Heritability of autism spectrum disorders: A meta-analysis of twin studies. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 57(5), 585–595. https://pubmed.ncbi.nlm.nih.gov/26709141/

 


Thursday 18 January 2024

PRESENTACIÓN DE LA ESCALA DE PRECISIÓN DIAGNÓSTICA DEL AUTISMO (PRESENTATION OF THE AUTISM DIAGNOSTIC ACCURACY SCALE)

PRESENTACIÓN DE LA ESCALA DE PRECISIÓN DIAGNÓSTICA DEL TRASTORNO DEL ESPECTRO AUTISTA

PRESENTATION OF THE DIAGNOSTIC ACCURACY SCALE FOR AUTISM SPECTRUM DISORDER

Ayer, día 17 de enero de 2024, se ha presentado la Escala de Precisión Diagnóstica del Trastorno del Espectro Autista (TEA), en el el Salón de Grados, de la Facutad de Educación y Trabajo Social, de Ourense, con la participación del Prof. Dr. Ricardo Fandiño, la Prof. Dra. María Dapía y el autor de la Escala, el Prof. Dr. Manuel Ojea.

Quiero expresar mi más sincero agradecimiento a los profesores/as que me han acompañado en la mesa presidnecial, así como a todos los profesores/as, miembros de los departamentos de orientación de toda la provincia y otros profesores/as de los diferentes niveles educativos e integrantes de Gabinetes Psicopedagógicos y Asociaciones Específicas, que habéis llenado la Sala de Grados durante la presentación- formación de la Escala. 

A todos y todas: GRACIAS.







SÍNTESIS 

Las conclusiones básicas hacen referencia a dos principios fundamentales:
1) Una nueva conceptualización del TEA, basada en la Teoría Cíclica Global, que se fundamenta en el proceso de transmisión GABAérgica de la formación, que afecta al conjunto del sistema perceptivo- cognitivo del procesamiento neuropsicológico.
2) El solapamiento hallado durante el proceso de codificación empírica entre los niveles actuales del TEA, especialmente en los nivles 1 y 2, de forma que se requiere una reflexión en profundidad sobre los actuales grados existentes del TEA en las clasificaciones internacionales actuales.


Thursday 4 January 2024

BASES TEÓRICAS DE LA ESCALA DE PRECISIÓN DIAGNÓSTICA

BASES TEÓRICAS DE LA ESCALA DE PRECISIÓN DIAGNÓSTICA PUBLICADA EN LA EUROPEAN JOURNAL OF THEORETICAL AND APPLIED RESEARCH, 1(6), 18-45, 2024.

Por Manuel Ojea.


VER VÍDEO EXPLICATIVO DEL AUTOR 

LA TEORÍA CÍCLICA GLOBAL



AUTISM PERCEPTUAL- BEHAVIOURAL PRECISION SCALE

 Autism Perceptual – Behavioural Precision Scale


European Journal of Theoretical and Applied Sciences, 2(1), 18-45. 2024

PhD. Manuel Ojea Rúa

SEE FULLY ARTICLE



Abstract

The perceptual-Cognitive-Behavioural Diagnostic Precision Scale for Autism Spectrum Disorder allows to complement the analysis of the autism diagnosis through the measurement of variables the neuropsychological processing of human information to avoid high errors over ASD diagnosis currently existing, derived from unilateral analysis of the behaviour criteria component of the actual Scales. The empirical scoring of the Scale has been verified to N= 75, being 38 participants belonging to the TEA-1 level, 24 to TEA-2 and 13 to TEA-3, has allowed find a statistical reliability of Cronbach's Alpha average greater to .91 in the ten dimensions of the Scale:  1) comprehension, 2) significant, 3) categories, 4) intercategorical 5) relationships-neural-nodes, 6) semantic recovery, 7) social interaction, 8) social communication, 9) stereotyped behaviours, and 10) restrictive behaviours. These ten dimensions have been statistically grouped around three great categories to analysis: 1) perceptual-cognitive processing, 2) social interaction, and 3) behaviour. The conclusive statistical analyses indicate that perceptual-cognitive process category explains 88.52% of total accumulated explicative variance, social category: 10.19% and behaviour: 1.28%; which shows the importance of the perceptual-cognitive dimensional factor analysis, in order to conclude with the mean percentiles of the diagnostic conclusion regarding each ASD´ level, according to International Classification of the American Psychiatric Association DSM-5 (APA, 2023).

References

Adams, C., Lloyd, J., Aldrede, C., & Baxendale, J. (2006). Exploring the effects of communication intervention for developmental pragmatic language impairments: A signal- generation study. International Journal of Language and Communication Disorders, 41(1), 41-65. http://taylorandfrancis.metapress.com/link.asp?target=contribution&id=G617W0516556G008

American Psychiatric Association (APA) (2013). Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Arlington, VA. https://psychiatry.org/psychiatrists/practice/dsm

Bauminger-Zviely, N., & Shefer, A. (2021). Naturalistic evaluation of preschoolers’ spontaneous interactions: The Autism Peer Interaction Observation Scale. Autism, 25(6), 1520-1535. DOI: 10.1177/1362361321989919. journals.sagepub.com/home/au

Bishop, D. V. (2000). Pragmatic language impairment: A correlate of SLI, a distinct subgroup, or part of the autistic continuum? In D. V. M. Bishop & L. Leonard (Eds.), Speech and language impairments in children: Causes, characteristics, intervention and outcome (pp. 99-114). Hove: Psychology Press. https://www.taylorfrancis.com/chapters/edit/10.4324/9781315784878-12/pragmatic-language-impairment-correlate-sli-distinct-subgroup-part-autistic-continuum-dorothy-bishop

Bishop, D. V. (2013). The children’s communication checklist- 2. London: Harcourt. https://www.pearsonclinical.co.uk/store/ukassessments/en/c/Children%27s-Communication-Checklist/p/P100009204.html

Bölte, S., Mahdi, S., de Vries, P., Granlund, M., Robison, J., Shulman, C., … & Segerer, W. (2019). The Gestalt of functioning in autism spectrum disorder: Results of the international conference to develop final consensus International Classification of Functioning, Disability and Health core sets. Autism, 23(2), 449-467. DOI: 10.1177/1362361318755522

Cain, K., & Oakhill, J. (Eds.). (2007). Children's comprehension problems in oral and written language: A cognitive perspective. Challenges in language and literacy. New York, NY: Guilford Publications. http://www.guilford.com

Dellapiazza, F., Vernhet, C., Blanc, N., Miot, S., Schmidt, R., & Baghdadli, A. (2018). Links between sensory processing, adaptive behaviours, and attention in children with autism spectrum disorder: A systematic review. Psychiatry Research, 270, 78-88. DOI: 10.1016/j.psychres.2018.09.023

Eggum-Wilkens, N. D., Fabes, R. A., Castle, S., Zhang, L., Hanish, L. D., & Martin, C. L. (2014). Playing with others: Head start children’s peer play and relations with kindergarten school competence. Early Childhood Research Quarterly, 29(3), 345-356. https://doi.org/10.1016/j.ecresq.2014.04.008

Frazier, T. W., Youngstrom, E. A., Kubu, C. S., Sinclair, L., & Rezai, A. (2008).  Exploratory and confirmatory factor analysis of the Autism Diagnostic Interview- Revised. Journal of Autism and Developmental Disorders, 38(3), 474-480. https://doi.org/10.1007/s10803-007-0415-z

Harris, P. L. (2017). Tell, ask, repair: Early responding to discordant reality. Motivation Science, 3(3), 275-286. https://doi.org/10.1037/mot0000075

Howes, C., & Matheson, C. C. (1992). Sequences in the development of competent play with peers: Social pretend play. Developmental Psychology, 28(5), 961-974. https://doi.org/10.1037/0012-1649.28.5.961

Kim, S. H., & Lord, C. (2012a). Combining information from multiple sources for the diagnosis of autism spectrum dis-orders for toddlers and young preschoolers from 12 to 47 months of age. Journal of Child Psychology and Psychiatry and Allied Disciplines, 53(2), 143-151. https://doi.org/10.1111/j.1469-7610.2011.02458.x

Kim, S. H., & Lord, C. (2012b). New autism diagnostic inter-view-revised algorithms for toddlers and young pre- schoolers from 12 to 47 months of age. Journal of Autism and Developmental Disorders, 42, 82-93. https://doi.org/10.1007/s10803-011-1213-1

Kim, S. H., Thurm, A., Shumway, S., & Lord, C. (2013). Multisite study of new Autism Diagnostic Interview-Revised (ADI- R) algorithms for toddlers and young preschoolers. Journal of Autism and Developmental Disorders, 43(7), 1527-1538. https://doi.org/10.1007/s10803-012-1696-4

Kirsty, L., Coulter, K. L., Barton, M. L., Boorstein, H., Cordeaux, C., Dumont-Mathieu, T., … & Fein, D.A. (2021). The Toddler Autism Symptom Inventory: Use in diagnostic evaluations of toddlers. Autism, 25(8), 2386-2399. DOI: 10.1177/13623613211021699. journals.sagepub.com/home/aut

Lecavalier, L., Aman, M. G., Scahill, L., McDougle, C. J., McCracken, J. T., Vitiello, B., & Cronin, P. (2006). Validity of the Autism Diagnostic Interview–Revised. American Journal on Mental Retardation, 111(3), 199-215. DOI: 10.1352/0895-8017(2006)111[199:VOTADI]2.0.CO;2

Lord, C., Rutter, M., Dilavore, P. C., Risi, S., Gotham, K., & Bishop, S. L. (2012). Autism Diagnostic Observation Schedule, second edition (ADOS-2). Western Psychological Services. DOI: 10.1007/978-1-4419-1698-3_896

Mayer, J. L. (2017). The relationship between autistic traits and atypical sensory functioning in neurotypical and ASD adults: A spectrum approach. Journal of Autism and Developmental Disorders, 47(2), 316-327. DOI: 10.1007/s10803-016-2948-5

McQuaid, G. A., Pelphrey, K. A., Bookheimer, S. Y, Dapretto, D., Webb, S. J., Bernier, R. A., … & Wallace, G. L. (2021). The gap between IQ and adaptive functioning in autism spectrum disorder: Disentangling diagnostic and sex differences. Autism, 25(6), 1565-1579. DOI: 10.1177/1362361321995620.  journals.sagepub.com/home/aut

Miller, L. E., Perkins, K. A., Dai, Y. G., & Fein, D. A. (2017). Comparison of parent report and direct assessment of child skills in toddlers. Research in Autism Spectrum Disorders, 41, 57-65. https://doi.org/10.1016/j.rasd.2017.08.002

National Institute for Health and Care Excellence. (2013). Autism: The management and support of children and young people on the autism spectrum [National Clinical Guideline Number 170]. DOI: 10.1136/archdischild-2013-305468

Nevill, R., Hedley, D., Uljarević, M., Butter, E., & Mulick, J. A. (2017). Adaptive behavior profiles in young children with autism spectrum disorder diagnosed under DSM-5 criteria. Research in Autism Spectrum Disorders, 43-44, 53-66. https://shop.tarjomeplus.com/UploadFileEn/TPLUS_EN_3157.pdf

Ojea, M. (2018). RELATEA Program. Development of conceptual categories in students with autism spectrum disorders. Madrid: Pirámide. https://www.edicionespiramide.es/libro.php?id=5151744

Ojea, M. (2023a). Perceptual-Behavioral Accuracy Scale. Lima: Ed. Barcelona. https://libreriaites.com/producto/escala-de-precision-perceptivo-conductual-ep-pc-tea/

Ojea, M. (2023b). Autism: New conceptual propositional hypothesis. European Journal of Theoretical and Applied Sciences, 1(6), 115-124. https://ejtas.com/index.php/journal/article/view/437

Portellano, J. A., Mateos, R., Martínez, R, Granados, M. J., & Tapia, A. (2002). Cuestionario de Madurez Neuropsicológica Infantil. Madrid: TEA. https://web.teaediciones.com/CUMANIN-2-Cuestionario-de-Madurez-Neuropsicologica-Infantil-2.aspx

Pugliese, C. E., Anthony, L., Strang, J. F., Dudley, K., Wallace, G. L., & Kenworthy, L. (2015). Increasing adaptive behavior skill deficits from childhood to adolescence in autism spectrum disorder: Role of executive function. Journal of Autism and Developmental Disorders, 45(6), 1579-1587. https://doi.org/10.1007/s10803-014-2309-1

Rutter, M., LeCouteur, A., & Lord, C. (2003). Autism Diagnostic Interview, Revised. Los Angeles: Western Psychological Services. https://link.springer.com/referenceworkentry/10.1007/978-1-4419-1698-3_894

Sacrey, L. A., Zwaigenbaum, L., Bryson, S., Brian, J., Smith, I. M., Roberts, W., ... & Garon, N. (2018). Parent and clinician agreement regarding early behavioral signs in 12- and 18- month-old infants at-risk of autism spectrum disorder. Autism Research, 11(3), 539-547. https://doi.org/10.1002/aur.1920

Serafini, G., Engel-Yeger, B., Vazquez, G. H., Pompili, M., & Amore, M. (2017). Sensory processing disorders are associated with duration of current episode and severity of side effects. Psychiatry Investigation, 14(1). DOI: 10.4306/pi.2017.14.1.51

Snow, A. V., Lecavalier, L., & Houts, C. (2009). The structure of the Autism Diagnostic Interview-Revised: Diagnostic and phenotypic implications. Journal of  Child Psychology and Psychiatry, 50(6), 734-742. https://doi.org/10.1111/j.1469-7610.2008.02018.x

Williams, K., Kirby, A., Watson, L., Sideris, J., Bulluck, J., & Baranek, G. T. (2018). Sensory features as predictors of adaptive behaviors: A comparative longitudinal study of children with autism spectrum disorder and other developmental disabilities. Research in Developmental Disabilities, 81, 103-112. DOI: 10.1016/j.ridd.2018.07.002

Wing, L., & Gould, J. (1979). Severe impairments of social interaction and associated abnormalities in children: Epidemiology and classification. Journal of Autism and Developmental Disorders, 9, 11-29. DOI: 10.1007/BF01531288