Predicting LD on the basis of motivation, metacognition, and psychopathology: an ROC analysis.

Full Abstract

We examined how strongly motivation, metacognition, and psychopathology acted as predictors of learning disabilities (LD). The results from five studies suggested that level of motivation (as shown through self-efficacy, motivational force, task avoidance, goal commitment, or self-concept) was highly accurate in classifying students with or at risk for LD. Metacognition and psychopathology were also strong predictors. Classification accuracy using receiver operating characteristic (ROC) curves ranged between 77% and 96%. These rates were much higher than the chance-level (i.e., 50%-55%) rates sometimes yielded by cognitive indices. Linear discriminant function (LDF) analysis substantiated classification accuracy. These results suggest that motivation, metacognition, and psychopathology are strong predictors of LD. Understanding the influence of these characteristics may help researchers and practitioners more accurately screen and treat students with LD.

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Author information

Author/s: Sideridis, Georgios D (GD); Morgan, Paul L (PL); Botsas, George (G); Padeliadu, Susana (S); Fuchs, Douglas (D);

Affiliation: Department of Psychology, University of Crete, Rethimnon. sideridis(-atsign-)psy.soc.uoc.gr

Journal and publication information

Publication Type: Journal Article

Journal: Journal of learning disabilities (J Learn Disabil), published in United States. (Language: eng)

Reference: -2006 May-Jun; vol 39 (issue 3) : pp 215-29

Dates: Created 2006/05/26; Completed 2006/06/28;

PMID: 16724794, status: MEDLINE (last retrieval date: 12/26/2008)

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Child
Cognition Disorders - diagnosis; epidemiology
Female
Humans
Learning Disorders - diagnosis
Male

Male
Mental Disorders - diagnosis; epidemiology
Motivation
Neuropsychological Tests
Predictive Value of Tests
ROC Curve

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