TY - JOUR
T1 - Internet gaming disorder clustering based on personality traits in adolescents, and its relation with comorbid psychological symptoms
AU - González-Bueso, Vega
AU - Santamaría, Juan José
AU - Oliveras, Ignasi
AU - Fernández, Daniel
AU - Montero, Elena
AU - Baño, Marta
AU - Jiménez-Murcia, Susana
AU - Del Pino-Gutiérrez, Amparo
AU - Ribas, Joan
PY - 2020
Y1 - 2020
N2 - In recent years, the evidence regarding Internet Gaming Disorder (IGD) suggests that some personality traits are important risk factors for developing this problem. The heterogeneity involved in problematic online gaming and differences found in the literature regarding the comorbid psychopathology associated with the problem could be explained through different types of gamers. Clustering analysis can allow organization of a collection of personality traits into clusters based on similarity. The objectives of this study were: (1) to obtain an empirical classification of IGD patients according to personality variables and (2) to describe the resultant groups in terms of clinical and sociodemographic variables. The sample included 66 IGD adolescent patients who were consecutive referrals at a mental health center in Barcelona, Spain. A Gaussian mixture model cluster analysis was used in order to classify the subjects based on their personality. Two clusters based on personality traits were detected: type I "higher comorbid symptoms" (n = 24), and type II "lower comorbid symptoms" (n = 42). The type I included higher scores in introversive, inhibited, doleful, unruly, forceful, oppositional, self-demeaning and borderline tendency traits, and lower scores in histrionic, egotistic and conforming traits. The type I obtained higher scores on all the Symptom Check List-90 items-Revised, all the State-Trait Anxiety Index scales, and on the DSM-5 IGD criteria. Differences in personality can be useful in determining clusters with different types of dysfunctionality.
AB - In recent years, the evidence regarding Internet Gaming Disorder (IGD) suggests that some personality traits are important risk factors for developing this problem. The heterogeneity involved in problematic online gaming and differences found in the literature regarding the comorbid psychopathology associated with the problem could be explained through different types of gamers. Clustering analysis can allow organization of a collection of personality traits into clusters based on similarity. The objectives of this study were: (1) to obtain an empirical classification of IGD patients according to personality variables and (2) to describe the resultant groups in terms of clinical and sociodemographic variables. The sample included 66 IGD adolescent patients who were consecutive referrals at a mental health center in Barcelona, Spain. A Gaussian mixture model cluster analysis was used in order to classify the subjects based on their personality. Two clusters based on personality traits were detected: type I "higher comorbid symptoms" (n = 24), and type II "lower comorbid symptoms" (n = 42). The type I included higher scores in introversive, inhibited, doleful, unruly, forceful, oppositional, self-demeaning and borderline tendency traits, and lower scores in histrionic, egotistic and conforming traits. The type I obtained higher scores on all the Symptom Check List-90 items-Revised, all the State-Trait Anxiety Index scales, and on the DSM-5 IGD criteria. Differences in personality can be useful in determining clusters with different types of dysfunctionality.
KW - Internet gaming disorder
KW - Cluster analysis
KW - Video game
KW - Video game addiction
KW - Personality
KW - Comorbidity
UR - https://www.scopus.com/pages/publications/85081073028
U2 - 10.3390/ijerph17051516
DO - 10.3390/ijerph17051516
M3 - Article
C2 - 32111070
SN - 1660-4601
VL - 17
JO - International Journal of Environmental Research and Public Health
JF - International Journal of Environmental Research and Public Health
IS - 5
ER -