In this study, a cluster analysis was performed by creating a data set from students' personality traits and academic procrastination behaviours. Correlation analysis was done to examine the relationship between the variables, and the characteristics of the formed clusters and the association of the clusters with the perceived socioeconomic status were examined. Cluster analysis is a simple and practical method for classifying a set of complex data based on certain variables and making them more meaningful and using the results as an aid to decision-making. Clustering algorithms handle such data effectively, making it more meaningful. Following the analysis, it was revealed that two clusters had formed. The first of the clusters includes 65.2 % of the sample population; the level of procrastination and the mean score of neurotic personality traits were calculated higher than the other cluster. The remaining part of the sample population (34.8 %) constitutes the second cluster. The mean scores of studying systematically habits and extroversion, agreeableness, conscientiousness, and openness to experience personality traits of the students forming this cluster are higher than the other cluster. No association was observed between the clusters and the perceived socioeconomic levels of the students. The distributions of socioeconomic levels within the clusters are similar to each other. When the correlations of these variables are examined; positive relationships were found between the level of procrastination and neurotic personality traits. Procrastination behaviour and neurotic personality traits were also negatively correlated with other variables.

Due to the notably increased penetration of smartphone use among university students and the alarming risk it poses to both physical and mental health, this study investigated mobile phone addiction among university students concerning student characteristics, mobile phone usage behaviors, and mobile phone use purposes and situations. The participants of this study were 600 university students, who were selected according to the convenience sampling method from different departments in Türkiye. The data were collected using the student characteristics form and the Mobile Phone Addiction Scale. The correlational research method was followed in the study. The data were analyzed using descriptive and inferential statistics. The results showed that students clustered as addicted and non-addicted had different mobile phone use behaviors on account of daily smartphone use duration, internet use duration on a smartphone, and daily smartphone check frequency. Being a female at a lower grade level and using mobile phones mostly at night made students more vulnerable to mobile phone addiction. Additionally, the results indicated a significant positive moderate correlation between internet use duration, daily smartphone use duration, daily smartphone check frequency, and mobile phone addiction scores. Lastly, checking social media apps, messaging, and editing photos significantly contributed to mobile phone addiction scores. Among the mobile phone use situations, when getting bored, during lessons, when watching TV or movies, and when being alone significantly contributed to mobile phone addiction scores. This study provided a thorough discussion and a set of recommendations.