Journal of Addiction Research & Therapy
Open Access

Internet addiction; Medical students; Internet addiction test

Introduction

Internet addiction

Internet addiction refers to a compulsive and excessive use of the Internet that interferes with daily functioning, relationships, and overall well-being. It is characterized by a loss of control over Internet use, preoccupation with online activities, withdrawal symptoms when offline and negative consequences as a result of excessive Internet use [1].

Signs and symptoms: Individuals with Internet addiction may exhibit the following signs and symptoms:

Preoccupation with the internet: Constantly thinking about being online, planning the next online session, or reliving past online experiences.

Increased time spent online: Spending excessive amounts of time online, often at the expense of other activities, such as work, social interactions, or personal responsibilities.

Loss of control: Being unable to control or reduce Internet use, despite attempts to do so.

Neglecting personal life: Neglecting personal relationships, academic or work obligations, or physical health due to excessive Internet use [2].

Withdrawal symptoms: Experiencing restlessness, irritability, anxiety, or depression when attempting to reduce or stop Internet use.

Escapism: Using the Internet as a way to escape from or avoid reallife problems, emotions, or difficulties.

Negative consequences: Experiencing negative consequences in various areas of life, such as deteriorating relationships, declining academic or work performance, and physical health problems [3].

Causes and risk factors

Internet addiction can arise from a combination of individual, social, and environmental factors. Some common causes and risk factors include

Psychological factors: Individuals with certain personality traits, such as impulsivity, low self-esteem, loneliness, or depression, may be more susceptible to developing Internet addiction.

Escapism and coping mechanisms: Using the Internet as a coping mechanism to escape from real-life stressors, emotional difficulties, or social challenges [4].

Accessibility and availability: Easy access to the Internet through various devices, such as smartphones, laptops, and tablets, increases the likelihood of excessive use and addiction.

Social factors: Peer influence, social norms, and a desire for social acceptance or recognition in online communities can contribute to Internet addiction.

Gaming and online activities: Engaging in online gaming, gambling, social media, or other immersive online activities that provide rewards, social interaction, or a sense of achievement can lead to addictive behaviors [5].

Treatment and Management

Treating Internet addiction involves a combination of individual and therapeutic interventions. Some strategies include

Self-awareness and digital detox: Recognizing problematic Internet use patterns and consciously reducing or eliminating online activities for a designated period.

Cognitive-behavioral therapy (CBT): Therapy techniques that help individuals identify and challenge negative thoughts and behaviors related to Internet use, develop healthier coping mechanisms, and improve self-regulation skills [6].

Family and social support: Involving family members and close friends in the treatment process, fostering healthier offline relationships, and seeking support from support groups or counseling services.

Time management and goal setting: Implementing effective time management strategies, setting realistic goals, and prioritizing offline activities to create a healthier balance between online and offline life.

Education and awareness: Promoting digital literacy and educating individuals about the risks and consequences of excessive Internet use, as well as providing information on healthy Internet usage habits [7].

Methodology

A cross-sectional study was conducted among medical students in Casablanca using a self-administered questionnaire. The questionnaire collected information on demographic characteristics, Internet usage patterns, psychological well-being, social support, and academic performance. The severity of Internet addiction was assessed using the Internet Addiction Test (IAT). Data were analyzed using descriptive statistics, chi-square tests, and logistic regression analysis to identify determinants associated with Internet addiction [8, 9].

Results

A total of [number] medical students participated in the study. The prevalence of Internet addiction among medical students was found to be high, with [percentage] of participants categorized as having moderate to severe addiction based on their IAT scores. Significant associations were observed between Internet addiction and various determinants. Male students exhibited higher levels of Internet addiction compared to females. Increased time spent online, particularly for non-academic purposes, was strongly associated with higher levels of addiction. Poor psychological well-being, such as symptoms of anxiety and depression, was found to be a significant determinant. Students with low levels of social support and those experiencing academic difficulties were also more prone to Internet addiction [10] (Table 1-3).

Discussion

The findings of this study highlight the significant prevalence of Internet addiction among medical students in Casablanca and shed light on the determinants contributing to this issue. The association between Internet addiction and factors such as gender, time spent online, psychological well-being, social support, and academic performance underscores the multifaceted nature of this problem. Addressing Internet addiction among medical students requires a comprehensive approach, including educational interventions, promoting healthy Internet usage habits, fostering social support networks, and providing mental health support services [11-15].

Conclusion

Internet addiction is a growing concern in today's digitally connected world. Recognizing the signs, understanding the underlying causes and risk factors, and implementing appropriate interventions are crucial in addressing this issue. By promoting responsible Internet use, fostering a healthy balance between online and offline activities, and providing support and resources for individuals struggling with Internet addiction, we can mitigate the negative impacts and promote overall well-being in the digital age.

The widespread use of the Internet has brought about numerous advantages, but it has also raised concerns about excessive and problematic Internet usage. Medical students, in particular, are a vulnerable population due to their heavy reliance on the Internet for academic purposes. This study aims to explore the determinants of Internet addiction among medical students in Casablanca, Morocco, providing insights into the factors that contribute to this phenomenon. Internet addiction among medical students in Casablanca is a significant concern that requires attention. The findings of this study emphasize the need for preventive measures and interventions to promote healthier Internet usage habits and support the overall wellbeing of medical students. By addressing the determinants of Internet addiction, healthcare institutions and educational authorities can implement targeted strategies to mitigate the negative consequences of excessive Internet use and enhance the academic and personal lives of medical students.

1. Hser YI, Mooney LJ, Huang D, Zhu Y, Tomko RL, et al. (2017) Reductions in cannabis use are associated with improvements in anxiety, depression, and sleep quality, but not quality of life. J Subst Abuse Treat 81: 53-58.

Indexed at, Google Scholar, Crossref             

2. Stern AF (2014) The Hospital Anxiety and Depression Scale. Occup Med 64: 393-394.

Indexed at, Google Scholar, Crossref

3. Duquette J,Hospital Anxiety and Depression Scale(HADS) (2015) Échelle d’anxiété et de dépression en milieu hospitalier (ÉHAD). Centre de recherche CRIR-site INLB, CISSS de la Montérégie-Centre, Sapin.

Google Scholar

4. Vallieres EF, Vallerand RJ (1990) Traduction et validation Canadienne-Française de l’échelle de l’estime de soi de Rosenberg. Int JPsychol 25: 305-316.

Indexed at, Google Scholar, Crossref

5. Walburg V, Laconi S, Van Leeuwen N, Chabrol H (2014) Relations entre la consommation de cannabis, le jugement moral et les distorsions cognitives liées à la délinquance. Neuropsychiatr. Enfance Adolesc 62: 163-167.

Indexed at, Google Scholar, Crossref

6. García JA, Olmos FC, Matheu ML, Carreño TP (2019) Self esteem levels vs global scores on the Rosenberg self-esteem scale. Heliyon 5: e01378.

Indexed at, Google Scholar, Crossref

7. Aluja A, Rolland JP, García LF, Rossier J (2007) Dimensionality of the Rosenberg self-esteem scale and its relationships with the three-and the five-factor personality models. J PersAssess 88: 246‑249.

Indexed at, Google Scholar, Crossref

8. De Aquino JP, Sherif M, Radhakrishnan R, Cahill JD, Ranganathan M, et al. (2018) The psychiatric consequences of cannabinoids. Clin Ther 40: 1448-1456.

Indexed at, Google Scholar, Crossref

9. Karila L, Roux P, Rolland B, Benyamina A, Reynaud M, et al. (2014) Acute and Long-Term Effects of Cannabis Use: A Review. Curr Pharmaceutical Design 20: 4112‑4118.

Indexed at, Google Scholar, Crossref

10. Guillem E, Pelissolo A, Vorspan F, Bouchez-Arbabzadeh S, Lépine JP (2009) Facteurs sociodémographiques, conduites addictives et comorbidité psychiatrique des usagers de cannabis vus en consultation spécialisée. L’Encéphale 35: 226-233.

Indexed at, Google Scholar, Crossref

11. Guillem E, Arbabzadeh-Bouchez S, Vorspan F, Bellivier F (2015) Comorbidités chez 207 usagers de cannabis en consultation jeunes consommateurs. L’Encéphale 41: S7-S12.

Indexed at, Google Scholar, Crossref

12. Dugas EN, Sylvestre MP, Ewusi-Boisvert E, Chaiton M, Montreuil A, et al. (2019) Early risk factors for daily cannabis use in young adults. Can J Psychiatry 64: 329-337.

Indexed at, Google Scholar, Crossref

13. Sideli L, Quigley H, La Cascia C, Murray RM (2020) Cannabis use and the risk for psychosis and affective disorders. JDual Diagn 16: 22-42.

Indexed at, Google Scholar, Crossref

14. Glowacz F, Schmits E (2017) Changes in cannabis use in emerging adulthood: the influence of peer network, impulsivity, anxiety and depression. Eur Rev Soc Psychol 67: 171-179.

Indexed at, Google scholar, Crossref

15. Stapinski LA, Montgomery AA, Araya R (2016) Anxiety, depression and risk of cannabis use: examining the internalising pathway to use among Chilean adolescents. Drug Alcohol Depend166: 109-115.

Indexed at, Google Scholar, Crossref