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Development and validation of Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS) for Internet Gaming Disorder (IGD) and factor analytic assessment.
Psychiatry Research 2023 April 2
OBJECTIVE: To develop and validate Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime version (K-SADS-PL) for Internet Gaming Disorder (IGD) in adolescents.
METHODS: Questions and threshold criteria of the K-SADS-IGD was generated based on the related section of K-SADS-PL. Then, the sample consist of IGD group and matched control group with no significant difference in psychiatric comorbidities from clinical settings were included to assess the psychometric properties of the K-SADS-IGD. Exploratory and Confirmatory Factor analysis were conducted to evaluate and compare DSM model of IGD and two different Models of IGD proposal in adolescents.
RESULTS: Exploratory Factor Analysis of K-SADS-IGD revealed a single factor explaining 61.469% of the total variance. Confirmatory Factor Analysis indicates that although the K-SADS-IGD model fit indices were also acceptable, Model 1, which excluded the 7th criterion of IGD criteria of DSM-5 showed better fit in adolescent population. The Likelihood Ratio Positive and the Likelihood Ratio Negative estimates for the diagnosis of K-SADS-IGD were 31.4 and 0.12, respectively, suggesting that K-SADS-IGD was beneficial for determining the presence and the absence of IGD in adolescents. Also, K-SADS-IGD could detect disordered gamers with significantly low functionality (even after controlling the impact of comorbidities) from non-disordered gamers.
CONCLUSION: K-SADS-IGD was found to be a reliable and valid instrument in adolescents. The model excluding 7th criteria of DSM-5 IGD was found to be more consistent than the current DSM-5 IGD model in the adolescent population. Therefore, the diagnostic criteria might be required to adjust according to the age group since the clinical symptomatology of IGD in adolescents may differ from that in adults. The K-SADS-IGD may meet the need for a certain and standardized tool to assess IGD in this population.
METHODS: Questions and threshold criteria of the K-SADS-IGD was generated based on the related section of K-SADS-PL. Then, the sample consist of IGD group and matched control group with no significant difference in psychiatric comorbidities from clinical settings were included to assess the psychometric properties of the K-SADS-IGD. Exploratory and Confirmatory Factor analysis were conducted to evaluate and compare DSM model of IGD and two different Models of IGD proposal in adolescents.
RESULTS: Exploratory Factor Analysis of K-SADS-IGD revealed a single factor explaining 61.469% of the total variance. Confirmatory Factor Analysis indicates that although the K-SADS-IGD model fit indices were also acceptable, Model 1, which excluded the 7th criterion of IGD criteria of DSM-5 showed better fit in adolescent population. The Likelihood Ratio Positive and the Likelihood Ratio Negative estimates for the diagnosis of K-SADS-IGD were 31.4 and 0.12, respectively, suggesting that K-SADS-IGD was beneficial for determining the presence and the absence of IGD in adolescents. Also, K-SADS-IGD could detect disordered gamers with significantly low functionality (even after controlling the impact of comorbidities) from non-disordered gamers.
CONCLUSION: K-SADS-IGD was found to be a reliable and valid instrument in adolescents. The model excluding 7th criteria of DSM-5 IGD was found to be more consistent than the current DSM-5 IGD model in the adolescent population. Therefore, the diagnostic criteria might be required to adjust according to the age group since the clinical symptomatology of IGD in adolescents may differ from that in adults. The K-SADS-IGD may meet the need for a certain and standardized tool to assess IGD in this population.
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