year 9, Issue 8 (autumn 2020 2020)                   frooyesh 2020, 9(8): 213-228 | Back to browse issues page

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Parhoon K, Parhoon H. A systematic review and Qualitative meta-analysis on the Identification patterns in Specific Learning Disorder. frooyesh. 2020; 9 (8) :213-228
1- Postdoc researcher in cognitive psychology, Kharazmi University, Tehran, Iran.
2- Assistant professor, Department of psychology, Razi University, Kermanshah, Iran. ,
Abstract:   (282 Views)
An accurate identification serves as the pathway that can guide the therapist towards the ultimate goal of adopting appropriate therapeutic and rehabilitation methods. Therefore, the present study aimed to systematically review and qualitative meta-analysis on the identification patterns in Specific Learning Disorder (SLD). The data in this qualitative meta-analysis was all study related to keywords and in line with the purpose of the research. 30 pieces of research were analyzed and evaluated in the present study. This study found the pattern of IQ-achievement discrepancy is more often seen as a “waiting for failure” method. Furthermore, the pattern of response to intervention has a serious problem due to poor psychometric properties for initial diagnosis and lack of true positive diagnosis. Therefore, specialists in this field have introduced a pattern of strengths and weaknesses (PSW), to reduce diagnostic problems in this field. This pattern with providing cognitive and educational profiles of students is particularly accurate in identifying potential learning difficulties, and can be used to distinguish children with SLD from children with learning problems and slow learner, and planning to perform cognitive processing-based interventions. In sum, the PSW pattern with a comprehensive assessment of cognitive and academic abilities of students with SLD and by identifying their diagnostic components can lead to increased validity of SLD diagnosis.
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Type of Article: systematic review | Subject: Educational Psychology
Received: 2020/05/9 | Revised: 2020/11/15 | Accepted: 2020/05/24 | ePublished: 2020/10/31

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