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Kalsen, H., Woerner, W., Wolke, D., Meyer, R., Overmeyer, S., Kaschnitz, W., Rothenberger, A., and Goodman, R., “Comparing the German Versions of the Strengths and Difficulties Questionnaire (SDQ-Deu) and the Child Behavior Checklist” European Child & Adolescent Psychiatry, Vol.9, No. 4, pp. 271-276, 2000.

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Article

Statistical Analysis of the Relationship between Diabetes and Psychological Disorders in Children

1College of Business Administration, Kuwait University


American Journal of Applied Mathematics and Statistics. 2018, Vol. 6 No. 1, 9-16
DOI: 10.12691/ajams-6-1-3
Copyright © 2018 Science and Education Publishing

Cite this paper:
Mohamed E. M. Abdelhafez. Statistical Analysis of the Relationship between Diabetes and Psychological Disorders in Children. American Journal of Applied Mathematics and Statistics. 2018; 6(1):9-16. doi: 10.12691/ajams-6-1-3.

Correspondence to: Mohamed  E. M. Abdelhafez, College of Business Administration, Kuwait University. Email: elwym@hotmail.com

Abstract

The main objective of this paper is to investigate the impact of diabetes on the psychological characteristics in children. The study investigated 302 children aged 7 to 13 years old who had diabetes type I in Kuwait. A questionnaire was administered to participants (Parents or Guardians) of diabetic children. The questionnaire has two parts; the first part has sociodemographic and clinical characteristics of the children and participants and the second part is the "strengths and difficulties questionnaire" (SDQ) [1]. The strengths and difficulties questionnaire (SDQ) was widely used for screening emotional and behavioral problems. Internal consistency of the sample and the strengths and difficulties questionnaire (SDQ) (Arabic version) were measured by Cronbach's alpha coefficient. The percentages of children whose scores are in the normal, borderline, and abnormal classes were calculated. The results indicate that regarding the mental health of the children, 69.1% were considered positive overall (55% abnormal and 14.1% borderline). Correlation analysis on the item-subscale level revealed that all items had the highest correlations to their respective subscales of origin. Further, subscale-subscale and subscale-total correlations were calculated. The results show significant correlations between the five subscales of the SDQ. Each subscale correlated significantly (p < 0.01) with every other subscale. A principal component analysis with varimax rotation was conducted to investigate the factorial structure of scales. A discriminant analysis was performed to classify the diabetic children into one of the three groups (Normal, borderline, and abnormal). The results show that 93.3% of the original grouped cases were correctly classified.

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