cyberspace addiction

Given that academic procrastination originates from various factors, two of the most important factors in this field are cyberspace addiction and executive functions. Therefore, this research aims to model structural equations for predicting academic procrastination based on cyberspace addiction and executive functions. The research method is a descriptive-correlation type of structural equation modeling. The statistical population of this research includes 8150 female first-secondary school students in the city of Kerman in the academic year 2022-2023; according to Morgan's table, 384 people have been selected as a sample using stratified random sampling. Widyanto and McMorran's (2004) cyberspace dependence, Brief's (2000) executive functions, and Solomon and Rothbloom's (1984) academic procrastination questionnaires were used to collect data. Data analysis was done with SPSS25 and AMOS24 software, and descriptive and inferential statistics such as mean, standard deviation, and structural equation modeling were used. The research results showed that the model for predicting academic procrastination based on dependence on cyberspace and executive functions has an acceptable fit. There is a significant relationship between cyberspace addiction, executive functions, and academic procrastination (p<0.05), so cyberspace addiction and executive functions simultaneously explain 0.70 of the variance of academic procrastination. Therefore, it can be concluded that the high dependence on cyberspace and spending much time aimlessly in this space cause students to procrastinate in doing their homework and to suffer from a kind of procrastination in academic subjects. Also, defects in executive functions aggravate the academic procrastination of students.

The present study aimed to predict cyberspace addiction among the employees of Azad University based on mindfulness through the mediation of cognitive emotion regulation strategies. This study was applied in terms of its purpose and descriptive in terms of its method, and was correlational in type. The statistical population of this study consisted of all employees of Tehran Azad Universities in 2024, from which 310 people were selected using the convenience sampling method. The research tools included the Freiburg Mindfulness Inventory-Short Form by Walach et al. (2006); the Cognitive Emotion Regulation Questionnaire by Garnefski et al. (2001), and the Mobile-Based Social Network Addiction Questionnaire by Khajeh Ahmadi et al. (2016). The results showed that cyberspace addiction in employees is predicted based on mindfulness (P<0.01). Cyberspace addiction in employees is predicted based on cognitive emotion regulation strategies (P<0.01). Cyberspace addiction in employees is predicted based on mindfulness through the mediation of adaptive and maladaptive cognitive emotion regulation strategies (P<0.05).