الفهرس 
Introduction and Aim of the WorkOnly 14 pages are availabe for public view
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Abstract
Internet addiction is seen as a serious problem among teenagers and young adults; it is characterized by severe web use that has a detrimental effect on one’s employment, personal life, emotional well-being, or physical well-being. The proposal to include “Internet addiction disorder” in the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) was brought forward. DSM-5 acknowledged the growing concern about internet use and related problems, but they claimed there was “insufficient peer-review.’’
The aim of the current study was to determine the prevalence of internet addiction and identify its determinants among preparatory school students in Alexandria. A cross-sectional study on a sample of 1128 pupils from preparatory schools was carried out to achieve this goal. The sample was chosen using a multistage stratified random sampling technique. Stratification was based on educational districts, type of school (private and public), boys’ and girls’ schools, and grade level. from the eight educational districts, three were chosen at random. from each selected educational district, two public schools (one for boys and one for girls) and two private schools (one each for males and females) were selected randomly. from each grade, one class from the chosen schools was randomly selected (i.e., first, second, and third grades). This included 12 classes from each district, adding up to a total of 36 classes.
For the execution of this work, the students were subjected to:
I) A pre-designed, structured, self-administered questionnaire to collect the following data (Appendix I)
1. Socio-demographic data included the following:
a. Name and type of the school.
b. Students’ age, sex, academic year, number of siblings and birth order.
c. Family size.
d. Mothers’ and fathers’ educational level, occupation, and working status.
e. The socioeconomic score was calculated.
2. Relationships with family members, colleagues, and teachers.
3. Number of friends, scholastic achievement, and physical exercise.
4. Medical history of chronic illness and mental illness of the student (e.g. depression, anxiety, etc.).
5. History of smoking and substance abuse by the student.
6. Data concerning internet use: numbers of hours spent, timing of use, number of internet accounts, purpose of use, place of use, having mobile and free internet access at home. Psychological testing All participating students were subjected to the Arabic version of Young Internet Addiction Test.
The Arabic version of Young Internet Addiction Test (Appendix II) (Hawi, 2013).
Hawi in Lebanon had validated the Arabic version of this measure that was used in this investigation. Internal consistency was used to evaluate the reliability of the Arabic version of the Young’s Internet Addiction Test (YIAT). Internal consistency (Cronbach’s alpha) was computed and was considered adequate (0.92).
The original test was developed by Young (1998).
III) School records
The school records were checked for scholastic achievement in some public schools, as they were not available to be checked in all schools due to administrative difficulties.
The results of the present study revealed the following:
The study sample included 1128 students. The chosen educational zones were represented, with 34.6% from El-Montaza, 31% from Wassat, and 34.4% from Shark. The three selected preparatory grades (1st, 2nd, and 3rd grades) were represented by 33.0%, 34.2%, and 32.8%, respectively.
Male and female students were nearly equally represented. The students’ ages ranged from 12 to 16, with a mean age 13.76 ± 0. 96. Concerning socio-economic status, the largest proportion of sampled students belonged to the high socio-economic status group (47.8%), and the least proportion belonged to the low socio-economic status group (8.0%). The prevalence of IA among the study sample was 28.7%.
Determinants of internet addiction
The older age group of 14-16 (2 = 6.86, p = 0.03).
Being an adolescent with divorced parents (2 =19.75, p = 0.01).
Poor degree of school performance (2 = 38.45, p = 0.00).
Students who were absent from school for more than 2 weeks and dropped out due to staying up late on the internet (2=12.34, p = 0.01 and 2 = 101.55, p = 0.00, respectively).
Smoking cigarettes (2 = 33.88, p = 0.00).
Suffering from mental illness but not suffering from chronic illness (2 = 6.76, p = 0.034, and 2 = 64.10, p = 0.00, respectively).
Poor relationships with parents (2 = 49.28, p = 0.00), and students with bad relationships with their teachers (2 = 72.16, p = 0.00).
The presence of internet access at home (2 = 18.28, p = 0.00) and the number of internet accounts (2 = 80.05, p = 0.00).
Summary, Conclusion and Recommendations
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Opening the internet immediately after waking up (2 = 187.08, p = 0.00) and having a meal while using the internet (2 = 197.30, p = 0.00).
Signing with a real name (2 = 18.03, p = 0.00) and adding real personal information (2 = 8.90, p = 0.01).
Signing in to sites doesn’t want to be known by parents (2 =156.79, p = 0.00); lying and hiding time spent on the internet (2 =141.51, p = 0.000); and closing websites when parents enter (2 =119.69, p = 0.00).
Staying up late because of the internet (2 =194.68 p = 0.00).
Using the internet for more than 4 years (2 = 50.44, p = 0.00), spending more than 5 hours per day on average (2 =196.32, p = 0.00).
Failure to decrease time spent on the internet (2 =104.63, p = 0.00).
Problems between students and their parents, which are caused by the duration of internet usage (2 =129.01, p = 0.00).
Students who preferred to use the internet in other places rather than home, such as friends’ home, (2 = 24.38, p = 0.00), school (2 =11.39, p = 0.00), and Cyber-cafe (2 = 26.72, p = 0.00).
Instagram as a preferred application used by students (2 = 15.80, p = 0.00).
Using the internet for educational purposes was found to be inversely related to IA (2 = 35.887, p = 0.00), while using the internet for entertainment purposes was a strong predictor for IA (2 = 17.599, p = 0.00).
Results of the logistic regression analysis of correlates show that : mental illness (yes); opening the internet immediately after waking up (sometimes); having meals while using the internet (sometimes); signing in to sites that didn’t want to be known by parents (yes); duration of internet usage (3-5 hours); duration of internet usage causing problems with the student family (sometimes); trying to decrease time spent on the internet (try and fail); students who didn’t use the internet of educational purposes; students who skipped school due to staying up late on the internet (sometimes) were proved to be significant predictors of internet addiction while students who didn’t sign in with their real names were less likely to have internet addictions.
Based on the present study, the following is recommended:
I- Recommendations concerning family and students
Universal health education programs about the normal development of children’s behavior and internet addiction, concerning its nature, risk factors, early manifestations, consequences, and when and where to seek help.
Health education activities to keep raising awareness and sharing information about the risks and unfavorable effects of IA.
Parents should encourage the good uses of the internet, e.g., studying or researching, and highlight them.
Control the child’s internet use by establishing rules to limit their internet use.
Parents should set an internet-free time on weekends and holidays.
Before 6 years of age, smart devices (phones, tablets, and computers) must not be available for use.
Parents should encourage their children to have hobbies and play sports on a regular basis.
Summary, Conclusion and Recommendations
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In order to design treatments, it is necessary to focus future research on mediating and moderating factors, protective and harm-reducing factors, and consumer requirements.
II-Recommendations concerning school
Early screening of school children for internet addiction should be integrated into the health assessment services of school programs. This can be accomplished by social workers and school physicians.
Schools might organize regular parent-child sessions highlighting the negative impacts of excessive screen usage and social media use.
High-risk children should be referred to a psychiatrist for a full clinical diagnosis and assessment.
The students should be encouraged to practise different activities, especially those requiring teamwork, to raise their self-esteem.
Teachers should be educated on the value of positive interactions with students.
A healthy relationship with teachers based on mutual respect provides the students with emotional support to express their feelings and problems freely.
Identification of students at risk, especially those with disturbed relationships with their family, peers, and teachers.
The continuous follow-up of internet-addicted students should be addressed.
Mental health integrity should be checked as part of a routine comprehensive medical examination in schools.
Special training courses should be available for normal child development, directed at school physicians, teachers, and social workers.
Improving the capacity of schools to promote mental health. As teachers, parents, and students, we need to be convinced of the importance of good mental health.
III-Recommendations concerning community
Policy-makers and decision-makers should be aware of the importance of internet addiction to be able to plan the most suitable strategies for the prevention of internet addiction in schools at all levels.
Internet addiction can be prevented by educating students and their families in clubs and youth centers about the causes and effects of internet addiction.
The government should provide safe places for children and adolescents to play sports and nurture their talents and skills under the supervision of specialists.
Educational programs about internet addiction should be available on TV, radio, and the internet to raise awareness about possible causes, symptoms, and ways of avoiding online dependency.