Objective: The aim of this study was to investigate the direct and indirect roles of psychiatric symptoms, social support, and meaning in life in predicting internet addiction among university students.
Methods: The study was performed in a cross-sectional design by employing the path analysis to explore the model fitting. All the students at Kerman University of Medical Sciences constituted the research population. A total of 159 students were selected, by random cluster sampling method, as sample members. The questionnaires were utilized for data collection. 
Results: The results revealed that more than half of the participants were afflicted with the Internet addiction or were on the verge of addiction. Correlation coefficients results indicated a positive correlation between all the subscales of psychiatric symptoms and students’ Internet addiction and also a negative correlation between all the subscales of social support and Internet addiction. Moreover, a negative correlation was found between meaning in life (PML) and internet addiction. Among all the endogenous variables, depression accounted for most of the variances in Internet addiction. Social support and PML also accounted for a considerable part of the variances in Internet addiction, either directly or indirectly. In addition, the goodness of fit indices was indicative of an acceptable fitness (CFI=0.96, NFI=0.94, IFI=0.92, RMSEA=0.17).
Conclusion: Considering the fit indices, path coefficients, and the significance level, it can be maintained that the presented model for Internet addiction has an acceptable goodness of fit and that it explains 75% of the variance in participants’ Internet addiction.