Structural relationships of internet tendency with temperament and character, diurnal preferences, and identity styles as mediated by anxiety

Document Type : Research Paper

Authors

1 Department of psychology, Khomeynishahr Branch, Islamic Azad University, KhomeyniShahr, Iran

2 Associate Professor, Department of Psychology, Naein Branch, Islamic Azad University, Naein, Iran

Abstract

This study aimed to investigate internet tendency based on temperament and character, diurnal preferences, and identity styles mediated by anxiety among students in Isfahan, Iran. The research population comprised students of Islamic Azad University, Khomeini Shahr Branch, Isfahan. A sample of 384 students was selected via cluster sampling and responded to the Internet Addiction Test (IAT), the Temperament and Character Inventory (TCI), the Morningness-Eveningness Questionnaire, the Identity Style Inventory (ISI), and the Beck Anxiety Inventory. The results showed that self-directedness, normative identity style, diffuse-avoidant identity and novelty-seeking affect internet tendency. Anxiety mediated the relationship of harm avoidance, diffuse-avoidant identity, diurnal preference, and cooperation with internet tendency.
Introduction: The youth constitute the main users of social networks on the internet and their lifestyles have been greatly influenced by the cyberspace (Xuan & Amat, 2020). The prevalence of internet tendency among teenagers and university students is reported as 0.9% to 33% (Devine et al., 2022). Studies have shown that personality traits play a role in internet tendency (Gervasi et al., 2017). Cloninger's neurobiological model (1987) takes the genotypic aspects of personality as the basis of individual differences in self-regulation cognitive processes (Moreira et al., 2021). Individual differences in the circadian rhythm are determined by the individual’s biological clock and specific preferences (Khaleghipour et al., 2014). Based on literature, diurnal preference is associated with internet addiction mediated by depression (Kang et al. 2015). Chou and Lee (2017) noted that users' personality and identity characteristics are associated with how they use the internet. The role of identity and attachment has been stressed in the addiction to online games and social networks (Monacis et al., 2017). According to research, internet tendency increases as anxiety grows (Przepiorka, Blachnio & Cudo, 2021). In their study, Bai et al. (2022) showed that internet addiction is associated with mental health disorders and quality of life. Soulioti et al. (2018) reported that younger internet users have addictive behaviors toward this technology, and there is a moderate relationship between anxiety symptoms and internet addiction. As the excessive use of the cyberspace can lead to psychological and academic problems, it is crucial to examine the antecedents of excessive internet use. Therefore, this study was conducted to respond to the question of whether anxiety mediates the relationship of internet tendency with temperament and character, diurnal preferences, and identity styles.
Methodology: This was a descriptive research using structural equation modeling (SEM). The statistical population comprised the students of Islamic Azad University, Khomeinishahr Branch, Isfahan, Iran, in 2021, selected by multi-stage cluster sampling based on an infinite population of 384 people. The research instruments were:
The Internet Addiction Test (IAT)
The 20-item IAT was developed by Young (1996) and is scored on a Likert scale (0 to 4). Total scores range from 0 to 80. The validity and reliability of IAT were reported as 0.88 and 0.72, respectively.
The Temperament and Character Inventory (TCI)
This 125-item inventory was developed by Cloninger (1994) and includes four dimensions for temperament and three dimensions for character. Items are scored 0 or 1. The reliability of its dimensions has been reported with Cronbach's alpha more than 0.68.
The Morningness-Eveningness Questionnaire (MEQ)
This 19-item questionnaire was developed by Horne and Östberg (1976) and consists of three sub-scales, determining the respondents' diurnal preference. Scores range from 16 to 86, with higher scores indicating morningness and lower scores indicating eveningness. Chelminski et al. reported the reliability of MEQ with Cronbach's alpha of 0.78.
The Identity Style Inventory (ISI)
Developed by Berzonsky (1992), ISI is a 40-item inventory evaluating three identity styles. Scores range from 40 to 200 and items are scored from 1 (uncharacteristic) to 5 (characteristic). Its reliability has been reported with Cronbach's alpha above 0.62 for all the three styles.
The Beck Anxiety Inventory (BAI)
This inventory was developed by Beck (1990). It comprises 21 items measuring the severity of anxiety. Scores range from 0 to 63 on BAI. Its test-retest reliability over a one-week interval was reported as 0.75.
Results: The findings on the variables' data distribution showed that the significance level is above 0.05 for anxiety, diurnal preference, and internet tendency, while this assumption was rejected for the other variables; therefore, the data on the variables do not follow a normal distribution. Given that the normality test was not confirmed for most of the variables, SmartPLS software was used for testing the research hypotheses. Variance-based SEM was used to test the main research hypothesis.
According to Table 1, the standardized regression coefficient is 0.220 for the effect of harm avoidance on anxiety, 0.235 for diffuse-avoidant identity style on anxiety, 0.166 for diffuse-avoidant identity style on internet tendency, 0.389 for anxiety on internet tendency, 0.114 for diurnal preference on anxiety, 0.163 for self-directedness on anxiety, 0.184 for self-directedness on internet tendency, 0.146 for novelty seeking on internet tendency, 0.286 for cooperation on anxiety, and 0.174 for normative style on anxiety.
The mediatory role of anxiety was examined in the relationship of temperament and character, diurnal preference and identity styles with internet tendency. Using Baron and Coney's method (1986) (Table 2), anxiety mediates the relationship of harm avoidance (p=0.037), diffuse-avoidant identity (p=0.044), diurnal preference (p=0.034), self-directedness (p=0.048) and cooperation (p=0.039) with internet tendency. Based on the goodness-of-fit indices of the research model, the data have a proper and adequate fit for measuring the latent variables, and the model estimation results are reliable.
Discussion and Conclusion: The personality and identity traits of internet users are associated with anxiety. Novelty seeking affects internet tendency by reinforcing the behavioral activation system and low self-direction affects this tendency by making the individual not have any goals and be dependent on external stimuli and uncertainty avoidance. Based on the model of the incentive theory of motivation, reward and need, cooperation with others and receiving social support reduce the individual’s internet tendency by affecting anxiety. Furthermore, eveningness intensifies internet tendency through anxiety and the use of alternative solutions for neutralizing anxious behaviors. According to the neurobiological model, a high level of harm avoidance, which is characterized by traits such as escaping and avoiding dangerous situations, cautiousness, and isolation, acts as a barrier against internet tendency in those who are inclined to use the internet due to anxiety and to neutralize their worries and uncertainty; this group tends to reduce their anxiety by looking for information online and creating a temporary state of security for themselves. The diffuse-avoidant identity is associated with low self-efficacy and uncertainty about one's cognitive ability; emotion-focused strategies, which are associated with a low level of commitment, increase in people with this identity due to their anxiety, leading to poor processing of personal decisions and conflicts. To reduce this conflict and anxiety, these people become inclined toward temporary activities and transient pleasures such as internet use.
This study had some limitations. Only questionnaires were used to collect data. The hours of internet access, which could have affected the results, were not controlled. Given the mediating role of anxiety in the relationship of diurnal preference, temperament and character and identity styles with internet tendency, recommendations shall be made to curriculum developers for nurturing effective personality traits among students in order to manage their anxiety.

Keywords

Main Subjects


Alavi, S. S. Eslami, M. Marasy, M., Najafi M, Jannatifard F. (2010). Psychometric properties of young internet addiction test. International Journal of Behavioral Sciences4(3), 183-189. (Text in Persian).
Andreassen, C.S., Pallesen, P. (2014). Social network site addiction - an overview. Current Pharmaceutical Design, 20 (25), 4053-4061. https://doi.org/10.2174/13816128113199990616
Askarian, F., Shakeri, M. T., Ghavami, V., & Jamali, J. (2020). The relationship between internet addiction and anxiety, stress, and depression in students of Mashhad University of Medical Sciences. Medical journal of mashhad university of medical sciences62(6), 1866-1903. https://doi.org/10.22038/mjms.2020.15617 (Text in Persian).
Agbaria, Q., & Bdier, D. (2021). The role of self-control and identity status as predictors of internet addiction among Israeli-Palestinian college students in Israel. International Journal of Mental Health and Addiction19(1), 252-266. https://link.springer.com/article/10.1007/s11469-019-00172-4
Awobamise, A., Jarrar, Y., & Nweke, G. E. (2022). Social Communication Apprehension, Self-Esteem and Facebook Addiction Among University Students in Uganda. Contemporary Educational Technology14(2), ep354. https://doi.org/10.30935/cedtech/11542
Bai, W., Cai, H., Wu, S., Zhang, L., Feng, K. X., Li, Y. C. & Xiang, Y. T. (2022). Internet addiction and its association with quality of life in patients with major depressive disorder: a network perspective. Translational psychiatry12(1), 1-7. https://doi.org/10.1038/s41398-022-01893-2
Bal, Z. E., Solmaz, M., Aker, D. A., Akin, E., & Kose, S. (1970). Temperament and character dimensions of personality in patients with generalized anxiety disorder. Psychiatry and Behavioral Sciences7(1), 1-10. http://dx.doi.org/10.5455/jmood.20170214015231
Bhuiyan, M. A. H., Griffiths, M. D., & Mamun, M. A. (2020). Depression literacy among Bangladeshi pre-university students: Differences based on gender, educational attainment, depression, and anxiety. Asian journal of psychiatry50. https://doi.org/10.1016/j.ajp.2020.101944
Bayrami, M., Hashme Nosratabad, T., Esmaeilpour, K., & Shiri, A. (2021). Effectiveness of Emotion Efficacy Therapy on Internet Dependency and Negative Cognitive Emotion Regulation Strategies among Students Addicted to Internet: A Quasi-Experimental Design. Clinical Psychology Studies, 31(12), 927-933. ‎(Text in Persian).
Berzonsky, M. D., & Papini, D. R. (2014). Identity processing styles and value orientations: The mediational role of self-regulation and identity commitment. Identity14(2), 96-112. https://psycnet.apa.org/doi/10.1080/15283488.2013.858228
Ceyhan, E., Boysan, M., & Kadak, M. T. (2019). Associations between online addiction attachment style, emotion regulation depression and anxiety in general population testing the proposed diagnostic criteria for internet addiction. Sleep and Hypnosis21(2), 123-139. https://psycnet.apa.org/doi/10.5350/Sleep.Hypn.2019.21.0181
Chou, C., & Lee, Y. H. (2017). The moderating effects of internet parenting styles on the relationship between Internet parenting behavior, Internet expectancy, and Internet addiction tendency. The Asia-Pacific Education Researcher26(3), 137-146. http://dx.doi.org/10.1007/s40299-017-0334-5
Chung, J. S., Choi, E., Lee, A. R., Kim, S. Y., Lee, K., Kim, B. N., & Park, M. H. (2020). The difference in sleep, depression, anxiety, and Internet addiction between Korean adolescents with different circadian preferences. Indian Journal of Psychiatry62(5), 524.
Chelminski, I., Petros, T. V., Plaud, J. J., & Ferraro, F. R. (2000). Psychometric properties of the reduced Horne and Ostberg questionnaire. Personality and Individual Differences29(3), 469-478. https://psycnet.apa.org/doi/10.1016/S0191-8869(99)00208-1
Devine, D., Ogletree, A. M., Shah, P., & Katz, B. (2022). Internet addiction, cognitive, and dispositional factors among US adults. Computers in Human Behavior Reports6, 100180. https://doi.org/10.1016/j.chbr.2022.100180
El Fiky, R., Mansour, M., Fekry, M., ElHabiby, M., Elkholy, H., & Morsy, M. (2022). Occurrence of problematic Internet use and its correlates among Egyptian adolescent students in international schools in Cairo. Middle East Current Psychiatry29(1), 1-10.
Fathi, M., Sohrabi F, Saiedian M. (2013). Comparison of the characteristics and identity style of Internet addicts and non-addicts' students. Journal of Research in Behavioural Sciences11(2), 90-99. (Text in Persian).
Ghazanfari, A., (2004). A Study of the reliability and validity of Identity style Questionnaire (ISI - 6G). Foundations of Education.1 (5). 1-8. https://doi.org/10.22067/fe.v5i1.1824  (Text in Persian).
Gervasi, A. M., La Marca, L., Lombardo, E., Mannino, G., Iacolino, C., & Schimmenti, A. (2017). Maladaptive personality traits and internet addiction symptoms among young adults: a study based on the alternative DSM-5 model for personality disorders. Clinical neuropsychiatry14(1).
Gruber, R., Fontil, L., Bergmame, L., Wiebe, S. T., Amsel, R., Frenette, S., & Carrier, J. (2012). Contributions of circadian tendencies and behavioral problems to sleep onset problems of children with ADHD. BMC psychiatry12(1), 1-11. https://doi.org/10.1186/1471-244x-12-212
Hossain, A., Munam, AM. (2022). Factors influencing facebook addiction among Varendra University students in the lockdown during the COVID-19 outbreak. Computers in Human Behavior Reports6, 100181. https://doi.org/10.1016/j.chbr.2022.100181
Hosseini Mehrabadi, H. S., & Abdi Zarrin, S. (2021). Prediction of Psychological Well-being and Social Responsibility in terms of Family Function and Identity Styles in Female Students of Qom University in The Academic Year of 2017-18. Women Studies12(35), 43-68. https://doi.org/10.30465/ws.2021.27747.2803 (Text in Persian).
Jamei, S. and Beshrpour, S. (2019). The role of nature and character in predicting addiction to cyberspace among second-year high school male students, Ardabil, the first national conference on psychopathology ، https://civilica.com/doc/1151569 (Text in Persian).
Kaviani, H., & Mousavi, A. S. (2008). Psychometric properties of the Persian version of Beck Anxiety Inventory (BAI). Tehran University Medical Journal. 65(2): 136-40. (Text in Persian).
Khaleghipour, S., Masjedi, M., & Kelishadi, R. (2015). Circadian type, chronic fatigue, and serum IgM in the shift workers of an industrial organization. Advanced biomedical research, 61(4), 1-7. https://doi.org/10.4103/2277-9175.151882
Khaleghipour, S., & Bagherian- Sararoudi, R. (2013). Relationship between circadian type, chronic fatigue and M immunoglobulin serum level in shift staff J Res Behav Sci; 10(7): 645-53.
Kocyigit, S., Guzel, H. S., Acikel, B., & Cetinkaya, M. (2021). Comparison of smartphone addiction level, temperament and character and parental attitudes of adolescents with and without attention deficit hyperactivity disorder. International Journal of Mental Health and Addiction19(4), 1372-1384. https://doi.org/10.1007/s11469-021-00494-2
Kang, D. W., Soh, M., & Lee, T. K. (2015). Relationship between internet addiction and circadian rhythm in adults. Sleep Medicine and Psychophysiology22(2), 57-63. http://dx.doi.org/10.14401/KASMED.2015.22.2.57
Lee, K., Lee, H. K., Jhung, K., & Park, J. Y. (2017). Relationship between chronotype and temperament/character among university students. Psychiatry Research251, 63-68. https://doi.org/10.1016/j.psychres.2017.01.071
Moreira, P. A., Inman, R. A., Rosa, I., Cloninger, K., Duarte, A., & Robert Cloninger, C. (2021). The psychobiological model of personality and its association with student approaches to learning: Integrating temperament and character. Scandinavian Journal of Educational Research65(4), 693-709. http://dx.doi.org/10.1080/00313831.2020.1739137
Milić, J., Milić Vranješ, I., Krajina, I., Heffer, M., & Škrlec, I. (2020). Circadian typology and personality dimensions of Croatian students of health-related university majors. International journal of environmental research and public health17(13), 4794. https://doi.org/10.3390/ijerph17134794
Malekian A, Ahmad zade G. (2007). Depression and anxiety in cancer patients. Journal of Behavior Science Research; 5:114-118. (Text in Persian).
Monacis, L., de Palo, V., Griffiths, M. D., & Sinatra, M. (2017). Exploring individual differences in online addictions: The role of identity and attachment. International journal of mental health and addiction15(4), 853-868. https://doi.org/10.1007/s11469-017-9768-5
Monteith, S., Bauer, M., Alda, M., Geddes, J., Whybrow, P. C., & Glenn, T. (2021). Increasing cybercrime since the pandemic: Concerns for psychiatry. Current psychiatry reports23(4), 1-9.
Przepiorka, A., Blachnio, A., & Cudo, A. (2021). Procrastination and problematic new media use: the mediating role of future anxiety. Current Psychology, 1-9. https://doi.org/10.1007/s12144-021-01773-w
Saif, M.H. and Kazemi, K. (2019). Examining the role of sensation seeking and the aspects of nature and character on internet addiction among first grade high school students in Bastak under the conditions of the Corona epidemic, the first national conference of cognitive science and education, Shiraz. https://civilica.com/doc/1142760. (Text in Persian).
Soulioti, E., Stavropoulos, V., Christidi, S., Papastefanou, Y., & Roussos, P. (2018). The relationship of internet addiction with anxiety and depressive symptomatology. Psychiatriki. 29(2), 160–171. https://doi.org/10.22365/jpsych.2018.292.160
Veiga Simão, A. M., Costa Ferreira, P., Pereira, N., Oliveira, S., Paulino, P., Rosa, H., & Trancoso, I. (2021). Prosociality in cyberspace: Developing emotion and behavioral regulation to decrease aggressive communication. Cognitive Computation13(3), 736-750. https://link.springer.com/article/10.1007/s12559-021-09852-7
Wang, Y., Liu, Wang, Y., Liu, H., Du, y., Fang, J., Wang, Z. (2021). Relationship between circadian typology and risk-taking behaviors in adolescents: A cross-sectional study. Annales Médico-psychologiques, revue psychiatrique, 8(179).694-699.
Sun, Y. (2018). Internet Addiction Motivation among Chinese Young People: A Qualitative Analysis. China Media Research14(1).
Xuan, Y. J., & Amat, M. A. C. (2020). Social media addiction and young people: A systematic review of literature ture. J Crit. Rev7(13), 537-541. http://dx.doi.org/10.31838/jcr.07.13.97
Yücens, B., & Üzer, A. (2018). The relationship between internet addiction, social anxiety, impulsivity, self-esteem, and depression in a sample of Turkish undergraduate medical students. Psychiatry research267, 313-318. https://doi.org/10.1016/j.psychres.2018.06.033
Ziaei M, Amiri SH, Molavi H. (2007). The relationship between circadian type scores and reaction time in the morning and evening. Adv Cogn Sci. 9(2):47-53. (Text in Persian).