Assessment of Knowledge, Beliefs and Level of Internet Addiction among Nursing Students at Minia University

Introduction

The Internet has become one of the most important tools for knowledge, work opportunities, education and amusement involving social media platforms and networking and is increasingly developed to be a structural element of our daily life (Thakur al., 2018). Over the past fifteen (15) years, Internet use has grown very fast: in current society about 40% of the global population is online ( Kuss et al., 2014). The growing popularity and frequency of internet use has resulted in the appearance of clinical conditions manifesting abuse symptoms identified as Internet addiction (IA) (Spada, 2014). Internet addiction is classically defined as a condition where an individual has impaired control of their internet use and proceed to use the internet too much to the point where he/she suffers problematic effects which ultimately have negative consequences on his/her life(Smyth et al., 2019). Internet addiction primarily put forward by Ivan Goldberg in 1995 and since then, it has become a social-psychological problem and a lot of researchers have been studying this topic (Dongyun et al., 2018; Wiederhold, 2018& Griffiths, 2018). Even though IA was not formally added into the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) in 2013, Internet Gaming Disorder (IGD) has been involved in sector III, highlighting the significance of this area for further study (Petry & O’brien, 2013; Cho et al., 2014; Hahn et al., 2017& Spada, 2014).

Assessment of knowledge and beliefs regarding safe usage of the internet is necessary. Ong and Tan (2014) in a study aimed to assess IA in young people showed that knowledge of IA among the public is a pertinent factor in the prevention efforts regarding IA. Maheri et al., (2017)  showed that improving college students'  knowledge and attitude about the addictive nature of the internet and side effects of IA are crucial for the prevention of IA(Maheri et al., 2018).The role of the nurse is to contribute to the preventive and therapeutic intervention to face this phenomenon. The nurse should help students to understand the effects of excessive internet usage on themselves physically and mentally and how to overcome these impacts of internet addiction(Hamzaa, 2017). Considering the globalization and the complexity of IA community health nurses must establish an effective program for the management of the addiction as well as the daily problems that such condition raises. Within the clinical context of mental health, nurses can have an effective role not only in the assessment, diagnosis, and treatment of  IA but in the prevention of that phenomenon as well
(Fradelos et al., 2016).

Significance of The study

Internet addiction (IA) is a worldwide phenomenon with different levels and it ranges from five to twenty-five percent among students in the united states (US), China, South Korea, England, Australia, Taiwan, Japan, and other countries in Eastern and Western Europe (Maheri et al., 2017).  Internet World Stats revealed that Egypt has the second-highest number of internet users in Africa after Nigeria. On average, Egyptians stay 26 hours a week on the internet according to the MidEast Media Survey ‘Media Use in the Middle East’ in 2017 (Eltigani, 2019). University students are particularly at risk for encountering dependence on the Internet, greater than other segments of the community. This can be attributed to numerous factors as the availability of time, easiness of use, limitless access to the Internet and limited or no familial supervision (MMIN, 2017). Assessment of IA among university students is a pertinent factor for its prevention effort.

Aim of the Study

The current study aimed to assess knowledge, beliefs and level of internet addiction among nursing students at Minia University

Theoretical Framework

One of the most commonly applied models in explaining and adopting healthy behaviors such as the protective behavior of addiction is the  Health Belief Model (HBM)  (Zadeh et al., 2014). The HBM was created in the US in 1950 by the Department of Public Health Service to understand the reasons for the ineffectiveness of public health services directed toward the prevention of health problems. The application of the model after that extended for comprehending the adherence with clinical remedy (Orji et al., 2012).Health Belief Model explains that health-related behaviors of people are based on their perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and perceived self-efficacy (Zadeh et al., 2014).

 Subjects and Methods

Research Design

Descriptive research design was utilized in the current study.

Setting:

The study was conducted at faculty of nursing at Minia University.

Sample size

Sample size was calculated based on Cochran formula, (1963) while n= t²×p (1-p)/ m² considering 41.5% prevalence rate of internet addiction according to Abdelghani, M et al., (2018).

Inclusion criteria for the study sample

(1)            Undergraduate students at faculty of nursing  at Minia University

(2)            Currently using the internet for at least 3 hours/day  and in the past 6 months

Study Tools

Tool 1: A self-administered questionnaire developed by the researcher based on HBM and consisted of 4 parts as following:

Part I: sociodemographic data of the students such as: Age, sex, faculty grade, residence, parents' education, family income, quality of relation with parents and friends, residence during studying, smoking status and academic average.

Part II: the student's knowledge about IA such as:definition, signs, causes, types of IA, its physical, psychological and social effects, and management of IA.

Scoring system

The scores for knowledge part of the questionnaire were calculated based on one point (1) for the correct answer and zero (0) for the wrong answer or don’t know respectively. Therefore the participants were considered to have a very good level of knowledge if the total score >75 %, good if the total score ranged from 60-75% and poor if the total score < 60% MMIN, M. (2017).

Part III:  A five-point Likert scale based on HBM assessed the students' beliefs toward IA. The scale consisted of six subscales as following: Perceived susceptibility (one question) and perceived severity (5 questions), perceived barriers (9 questions), perceived benefits (6 question), cues to action (2 questions) and perceived self-efficacy (5questions).

Scoring system

The statements of this part were scored on a five-point likert-type scale as following: strongly disagree (1), disagree (2), neutral (3), agree (4), and strongly agree (5). The entire score for each subscale was calculated by summing up of all of its statements. With summed scores > 60% indicates a higher level of the HBM subscale/construct while a summed score ≤ 60% indicates a lower level of the subscale for each one.

Tool 2:  The Arabic version of Internet Addiction test (IAT):  It is a self-rated scale developed by Young (1998) to assess the existence and severity of IA.  This tool consists of twenty (20) items; These 20 items involve distraction, compulsivity, and dependency. The items also assess conflicts in personal, social, or occupational life that may arise from the addictive use of the internet. The Arabic version of IAT has been validated in a study conducted in Lebanon by
Hawi (2013).

Scoring system

The statements of the IA test were scored on a five-point Likert-type scale, rarely (1), occasionally (2), frequently (3), often (4), always (5). Sum of the scores that ranged from 0 to 30 points indicated a normal level of internet usage; scores of 31 to 49 reflected a mild level of IA; scores of 50 to 79 indicated a moderate level, and scores of 80 to 100 indicated severe internet dependence (Young, 1998).

Content Validity of the Tools

The content validity of the study tools was tested by five experts in community health nursing. The tools were examined for content coverage, sequence of items, clarity, relevance, applicability, words length, format, and overall appearance. Based on experts` comments, recommendations and modifications were made.

Reliability of the Tools

Reliability of the study questionnaire was calculated using Cronbach’s alpha. Based on data analysis, coefficient alpha for the knowledge part  was 0.78,  perceived severity was 0.81, perceived barriers was 0.82, perceived benefits was 0.76, cues to action was 0.68, self efficacy was 0.92 , for all the subscales of the HBM was 0.080, and for the entire questionnaire was 0.70.  As regard to the reliability of the IAT, it was 0.93.

Procedure

Before conducting the study an official permission was taken from the dean of the faculty of nursing to conduct the study. The interview with the students of each grade was held at their specialized faculty class. The researcher first introduced herself to the students, explained to them the purposes of the study briefly and an oral consent for participation was obtained. The tools of the study were filled by the students and aided by the researcher. The time required to fill the questionnaire was about 15 minutes.

Pilot study

It was applied on 10% of the calculated sample to assess the validity of the questionnaire and to assess acceptability of the students to the topic of the research.  The results of pilot study were included in the final results of the research as there were no major modifications were done in the tools of the study

Statistical Analysis

Data entry and statistical analysis were done using SPSS 24.0 statistical software package. Data presented using descriptive statistics in the form of frequencies and percentages for qualitative variables, and means and standard deviations for quantitative variables. The Chi square used in tests of relationship. Probability (P-value) less than 0.05 was considered significant. (p < 0.05).

Ethical considerations

A written approval obtained from the ethics and research committee of the faculty of nursing at Minia University. Oral consent obtained from students after explaining the nature and objectives of the study to gain their cooperation. Each assessment sheet was coded for the purpose of privacy and confidentiality. Participants were free to withdraw from the study at any time.

Results

Table (1) Distribution of the studied Minia university nursing students according to their socioemographic characteristics in the academic year of 2018/2019 (n=370)

Table (1) shows that 65.9% of the participants are in the age group 18 – 21 yrs with a mean score± SD 20.78 ± 1.30, 59.5% of the participants are females, 75.1% live in rural areas, 96.8% have a good relationship with their parents, 62.4% are residents with their parents during the study, 5.4% are smokers, and 42.2% their academic performance is very good. The table also shows that 34.6% of the participants their fathers' education is a secondary education, 31.4% their mothers don't read or write, 44.9% of the participants their monthly family income is less than 2000 L.E

Table (2) Distribution of the studied Minia University nursing students according to their knowledge about definition and signs of IA (N=370)

                                ^#Mutual exclusive more than one answer

Table (2) shows that 69.7% of the participants' definition of IA is incomplete while 4.3% don't know the definition of IA. Regarding knowledge about signs of IA 57.8% mention jeopardizing a significant relationship or responsibilities as a sign of IA while 7.3% doesn't know any signs of IA.

Table (3) Distribution of the studied Minia University nursing according to their knowledge about causes and social effects of IA (n=370)

                ^#Mutual exclusive more than one answer

Table (3) shows that 54.9% of the participants mention free time and boredom as a cause of IA while 5.7% don't know causes of IA. In relation to knowledge about social effects of IA, 63.7% mention low academic performance while 18.4% don't know its social effect

Fig. (1) Distribution of the studied Minia university nursing students according to their total level of knowledge about IA

Table (4a) Distribution of the studied Minia University nursing students according to their health beliefs toward IA (n=370)

Table (4a) shows that 28.9% of the participants disagree they are susceptible to IA. As regards to their Perceived severity of IA, 43.2% disagree that IA is a serious disease of the era. In the same domain of perceived severity, 45.4% disagree that thinking about the negative effects of IA on health is a restless issue, 43.5% disagree that IA may negatively affect their health, 41.6 agree that IA may negatively affect their academic performance, and 27.6% of the participants agree that IA may socially isolate them from their family.

Regarding the participants' perceived barriers toward reducing internet use, the same table shows that 26.5% agree that reducing internet time limit their social contact with friends and relatives, 31.4 agree that life seems boring without internet, 28.9% disagree they will feel lost if they reduce their internet time, 27.8% disagree that they will be an old fashioned if they reduced their internet time, 34.1% disagree that nobody encourages them to reduce their internet time, 23.8% agree they will feel lonely if reduce their internet time, 32.2% disagree that reducing internet time may negatively affect their self-esteem, 27.6% strongly agree that there is no other way to relieve stress if they reduced their internet use, and 28.1% agree that nobody will help them in their decision making if they reduce internet use.

Table (4b) Distribution of the studied Minia University nursing students according their health beliefs toward IA (n=370)

Table (4b) shows that 30.2% of the participants are neutral about giving priority to important life issues as perceived benefits of reducing internet,  42.2% agree that reducing the time of using the internet has a positive effect on their academic achievements, 29.2% are neutral about the benefit of improving their family and friends relation quality if they reduce internet time, 38.1% agree that reducing their internet time will make them self satisfied, 32.7% are neutral about enjoying more personal privacy as a benefit of reducing internet time, and 43.8% disagree that reducing internet time has positive effects on their health. 

As regards to cues to action toward IA, the same table shows that 38.4% of the participants agree that their parents asking for reducing internet time, 31.6% disagree that their teachers ask them to reduce their internet time. Concerning perceived self-efficacy toward reducing internet time, 24.6% are neutral that they have the ability finding suitable ways to reduce internet usage, 40.8% strongly disagree that it is easy to reduce internet time, 30.8% disagree that they have a plenty of ideas how to reduce internet time, and 30.8% are neutral about their intention to reduce daily hours of internet use.

Fig. (2) Distribution of the studied Minia University nursing students' level of health beliefs toward IA

Fig. (3) Level of IA among the studied Minia university nursing students, according to Young’s IAT (1998)

Fig. (3) Illustrates that, 44.6% of the participants had a mild level of IA followed by 38.9% had a moderate level, and 3.5% had a severe level of IA.

Table (5): Relation between the studied Minia University nursing students^' total level of IA and their socio-demographic data(n=370)

* Statistical significant difference,   Chi‑squared test.

Table (6) shows that there are significant statistical differences between the level of IA and  gender of the participants while males have a significant sever level of IA compared to females where the p-value is 0.001. The same table shows that there are significant statistical differences between the level of IA and faculty grade of the participants where the p-value is 0.002. An additional statistically significant difference is found between the level of IA and monthly family income of the participants  while participants with a monthly family income ranges from 2000-3000 LE have a significant severe level of IA compared to others where the p-value is 0.008. Another statistically significant dereference is found between the level of IA and smoking status of the participants while non-smokers have a significant severe level of IA  compared to smokers where the p-value is 0.01.  The same table shows that there are significant statistical differences between the level of IA and academic level of the participants while participants whose academic performance is pass/weak have a significant severe level of IA compared to those with higher academic performance where the p-value is 0.001.