The effects of cognitive-behavioral group therapy for reducing symptoms of internet addiction disorder and promoting quality of life and mental health

Abstract Introduction Internet addiction disorder has reportedly become an important cause of health and social problems. The aim of this study was to investigate the effectiveness of cognitive-behavioral group therapy for internet addiction symptoms, quality of life, and mental health of students with internet addiction. Methods This was a quasi-experimental study with pretest-posttest measures and a control group. The statistical population of the study consisted of all students at Tehran universities in the academic year of 2018-19. The target group was selected through an internet addiction test and a clinical interview using a targeted sampling method and was divided into experimental and control groups by randomization. The experimental group participated in fifteen 90-minute cognitive-behavioral group therapy sessions. Before, immediately after, and 3 months after the treatment, the internet addiction symptoms of both groups were evaluated to assess mental health with the IAT, quality of life (QOL), and SCL-90-R questionnaires. Data were analyzed with ANCOVA analysis using SPSS Statistics 20 software. Results After treatment, cognitive-behavioral therapy groups showed reductions in internet addiction scores (p < 0.05). Results showed that the cognitive-behavioral group therapy was effective for improving quality of life (p < 0.05) and mental illnesses (p < 0.05) in students with internet addiction. Conclusions Cognitive-behavioral group therapy can enhance awareness and mental health of students with internet addiction. Therefore, this intervention can be used as a beneficial treatment to reduce internet addiction symptoms and improve the condition of people with behavioral addictions such as internet dependency.


Introduction
Internet addiction or internet dependency is a worldwide social issue and can exist at any age and in any social, economic, or educational strata. In some countries, such as Iran, behavioral addictions including internet addiction (IA) are considered a public health concern. 1,2 Internet addiction is considered a growing health concern in many countries of the world, with prevalence rates of 1-2% in Europe, 3 up to 24.5% in some Middle Eastern countries, 4 and 26.9% among Iranian students. 5 Internet addiction (IA) has been associated with psychiatric disorders such as anxiety, depression, personality disorders, and obsessive compulsive disorder (OCD), which cause a great deal of harm to quality of life. 6 Also, clinical research has demonstrated that internet addiction disorder is accompanied by loss of interests, decreased psychological functioning, social withdrawal, and heightened psychosocial distress. People with this disorder start to miss important deadlines at work, spend less time with their families, and slowly withdraw from their normal routines. They neglect social connections with their friends, coworkers, and communities; ultimately, their lives become unmanageable because of the internet. 7 They become consumed with their internet activities, preferring online games, chatting with online friends, or gambling over the internet, and ignoring family and friends in exchange for solitary time in front of the computer. While there are many studies assessing clinical features of persons with IA, 6 knowledge about the effectiveness of treatment sessions is limited.
Many treatment programs have been developed for patients with internet addition (IA), including pharmacotherapy 8 and psychological treatments such as cognitive-behavioral therapy. 3,[9][10][11][12][13] Lee et al. reported that antidepressants are useful for treating internet addiction. 14 Han and Renshaw reported that bupropion may reduce depressive mood in patients with comorbid online addiction and depression. 15 However, the role of anti-craving properties of antidepressants should be further evaluated in the long-term and in controlled studies. 16 Cognitive-behavioral therapy (CBT) was performed once a week for 10 weeks and findings suggested that the sessions were effective to reduce internet addiction symptoms. 17 Young recommended a uniquely designed model to treat internet addiction, called cognitive-behavioral therapy for internet addiction (CBT-IA). 9 This study was the first to measure treatment outcomes using CBT-IA to treat cases of internet addiction. Internet addiction disorder has been the subject of many studies since the last decade, but there is a need for an experimental or randomized controlled design for the topic, rather than cross-sectional studies. 19 However, studies that have been conducted were limited, their insufficient samples were not powerful enough to support the results of previous studies, and no standard clinical protocols have been developed to treat internet addiction. 16 Few studies focused on promotion of quality of life, treatment of IA symptoms, and reduction of mental illnesses such as anxiety, depression, somatization, and low self-esteem. 12 Moreover, developing preventive measures, especially for students, is of high importance. 5

Research objectives
In this study, we aimed to collect the first data on the effectiveness of cognitive-behavioral group therapy for decreasing internet addiction symptoms such as craving for internet use. Furthermore, we also hypothesized that 15 sessions of therapy reduce some mental illnesses such as anxiety and depression. Lastly, we further expected that decreased craving for internet use and mental illnesses symptoms would be associated with promotion of quality of life, improvements in social relationships, and physical and psychological health in students.

Material and methods
In this quasi-experimental study, data were collected from 50 internet addicts (25 in a control group and 25 in an experimental group) who consecutively presented at counseling centers for internet addiction at their universities (randomized clinical sample).
These patients were selected from an initial clinical sample of about 60 people seeking treatment. Ten (16.3%) of these students were excluded because they did not meet the inclusion criteria: 5 students were normal internet users and 5 refused to participate.
The entire sample (50 students) was asked to provide demographic data for scientific processing and provided written informed consent.
Inclusion criteria were as follows: 1) students aged 18-30 years (male or female); 2) diagnosed as an internet addict based on the standardized clinical interview and the internet addiction test (IAT) semi-structured interview for the assessment of internet addiction; and 3) willingness to participate in the study.
Exclusion criteria were as follows: 1) history of severe physical or psychological problems, including other addictive disorders, psychotic disorders, major depression, borderline personality disorder, or antisocial personality disorder based on the clinical psychologist's view or observations and oral questioning); and 2) lack of participation in cognitive-group therapy sessions.
Students who reported using medication for psychiatric disorders and those who were undergoing other psychotherapeutic treatments were also excluded from the study.

Instruments
Data were collected using the instruments described below.

Internet Addiction Test (IAT)
The IAT is a self-report questionnaire based on the DSM diagnostic criteria for drug addiction and  [20][21][22][23] The Persian version of IAT was used in this study. It has a Cronbach's alpha of 0.89, and its reliability (testretest) was 0.68 after 2 weeks. Therefore, it is a valid and reliable tool that can be used in psychological and psychiatric studies to screen normal internet users and internet addicts. 24

WHO-QOL-BREF
The WHO-QOL-BREF is a self-report questionnaire

Semi-structured interview
This semi-structured interview was performed by a clinical psychologist to diagnose behavioral addictions such as internet addiction. These interviews were performed by a psychologist trained in diagnosis of behavioral addiction in general and internet addiction disorder in particular. The criteria for diagnosing internet addiction were based on adapted DSM-5 criteria for gambling disorder and substance-related disorders 27 (e.g., preoccupation, loss of control, withdrawal, negative consequences, tolerance, and craving).

Symptom Checklist-90-Revised (SCL-90-R)
The SCL-90-R is a self-administered symptom Before implementing the survey, a pilot test was also administered to 3 randomly selected students to assess the time required to finish the sessions, to clarify ambiguities and problems with the format if there were any, and to determine each session's items. Thus, 15 sessions were held with the following titles (Table 1).
These cognitive-behavioral sessions were led by a clinical psychologist trained to diagnose and treat internet addiction. The content validity of sessions was checked and approved by 10 clinical and cognitivebehavioral psychologists.

Procedures
In a randomized and quasi-experimental clinical trial with students from Tehran universities, 50 students with internet addiction disorder were selected based on IAT scores and a semi-structured interview.
Pre-therapy and post-therapy assessments measured changes in students' internet addiction symptoms, quality of life (QOL), and metal health (depression, anxiety, and somatization symptoms using the SCL-90-R). This design is well-documented in clinical and counseling literature on evaluating the effects of behavioral interventions and change over time. 29 All addicted internet users received standard behavioral treatment and were randomly divided into 2 groups. Written informed consent and assent were obtained from the students. Participants in the intervention group received cognitive-behavioral group therapy, while those in the control group only received standard individual psychotherapy. Both groups were evaluated before and after the intervention.

Results
Five of the 60 patients in the study did not meet the study's inclusion criteria and 5 refused to participate. All of the 50 students who participated in the study completed the baseline assessment and were randomized into 2 groups (Figure 1).
A total of 41 remaining students were evaluated. Introducing stimulants or factors that lead a person to excessive use of Internet Self-directed selfknowledge a) The ways to promote selfawareness or self-knowledge b) The therapist will formulate a plan to achieve specific goals.
Craving and its coping methods

Third session
Behavioral techniques to cope with craving Changing patterns of behavior Self-control Doing practices such as Delayed Selfpunishment    Table 2.
The mean ± SD scores for internet addiction, quality of life, and SCL-90-R at the pretest, posttest, and follow-up stages are reported in Table 3.
Differences were observed between scores before and after the intervention and in the follow-up phase for quality of life, mental health, and internet addiction ( Table 3). The quality of life and mental health scores improved and the internet addiction scores decreased.
The results of ANCOVA showed significant differences in quality of life between the experimental and control groups at the posttest stage (p < 0.05) ( Table 4).

Discussion
This study was among the first to survey a therapeutic package (15 sessions such as a lack of physical energy and weakened immunity. 30,31 In another two similar studies, in 2012 and 2013, the findings reported revealed that compulsivity, ruminative thoughts about internet, and cheating to access the internet were also reduced using CBT techniques. 13,32 Another study showed that CBT intervention programs for internet addiction were said to slowly rekindle offline relationships over time. 10

Conclusions
The principal conclusion of this study was that cognitive-behavioral group therapy is an impressive treatment to improve lifestyle and reduce internet addiction. In this study, the behavioral package focused on modifying the individual's thoughts, lifestyle, mental health, cognitive errors, emotional regulation, and problem-solving. Relaxation therapy and stress management may also be related to this study's positive outcomes. The