Journal of Psychosocial Nursing and Mental Health Services

CNE Article 

Effectiveness of a Nurse-Led Intervention for Adolescents With Problematic Internet Use

Preeti Mathew, MSc; Raman Krishnan, MBBS, MD; Adhin Bhaskar, PhD

Abstract

The current study assessed the effect of an intervention on problematic internet use (PIU), biopsychosocial functioning, and academic performance in 100 adolescents with PIU in grades 9 and 11 in Ernakulam District, Kerala, India. Students from four comparable schools were randomly assigned to experimental and wait-list control groups after being screened for PIU. The experimental group participated in a 10-week intervention and parents of these adolescents were provided with two sessions. The wait-list control group received the intervention after the posttest. A PIU questionnaire, sociodemographic data, internet usage pattern, a biopsychosocial functioning tool, and academic performance were used to assess participants at baseline and immediately after and 3 months postintervention. Findings revealed significant differences in PIU; physical, psychological, and social functioning; and academic performance immediately and 3 months postintervention (p < 0.05). Thus, the intervention was effective in reducing PIU among adolescents and improved their physical, psychological, and social functioning and academic performance. [Journal of Psychosocial Nursing and Mental Health Services, 58(7), 16–26.]

Abstract

The current study assessed the effect of an intervention on problematic internet use (PIU), biopsychosocial functioning, and academic performance in 100 adolescents with PIU in grades 9 and 11 in Ernakulam District, Kerala, India. Students from four comparable schools were randomly assigned to experimental and wait-list control groups after being screened for PIU. The experimental group participated in a 10-week intervention and parents of these adolescents were provided with two sessions. The wait-list control group received the intervention after the posttest. A PIU questionnaire, sociodemographic data, internet usage pattern, a biopsychosocial functioning tool, and academic performance were used to assess participants at baseline and immediately after and 3 months postintervention. Findings revealed significant differences in PIU; physical, psychological, and social functioning; and academic performance immediately and 3 months postintervention (p < 0.05). Thus, the intervention was effective in reducing PIU among adolescents and improved their physical, psychological, and social functioning and academic performance. [Journal of Psychosocial Nursing and Mental Health Services, 58(7), 16–26.]

The internet is an indispensable part of people's life today. From 2010 to 2016, the reported worldwide penetration rate increased more than 900% (Fuchs et al., 2018). Over the past few decades, as occurs with most significant innovative and ground-breaking technological developments, unanticipated and negative consequences of internet access have emerged (Tam, 2017). With the accessibility of new media, internet addiction, or problematic internet use (PIU), has become a potential problem. PIU refers to compulsive and excessive use of the internet, defined as preoccupied with or loss of control over internet use that interferes with daily life (Valkenberg & Peter, 2011).

Based on growing research (Young, 1998), the American Psychiatric Association sought to include Internet Use Disorder for the first time in the appendix of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), acknowledging the problems arising from this type of addictive disorder (Liu et al., 2011; Mishra et al., 2015). However, to date, the DSM-5 does not include PIU as an addictive disorder (Machimbarrena et al., 2019).

Evidence suggests that individuals with PIU have brain makeups similar to individuals with chemical dependency (e.g., drugs, alcohol), specifically affecting the amount of gray and white matter in regions of the prefrontal cortex. PIU, similar to other dependency disorders, affects the pleasure center of the brain, triggering a release of dopamine. Over time, more and more of the activity is needed to induce the same pleasurable response, creating a dependency. According to the variable ratio reinforcement schedule theory (Wang, 2019), the reason one becomes addicted to internet activity (e.g., gaming, gambling, shopping, watching pornography) is because it provides multiple layers of rewards. Biological predispositions to PIU may also be a contributing factor to the disorder. Individuals with this disorder may have deficient levels of dopamine and serotonin compared to the general population. Oftentimes, if an individual has anxiety or depression, they may turn to the internet to cope with these conditions or fill a void. Similarly, individuals who are shy or socially awkward might also be at higher risk for PIU, because internet use does not require interpersonal interaction and can be emotionally rewarding (Gregory, 2019).

PIU has been recognized as a global concern, but its prevalence varies widely across countries as reported by various epidemiological studies. A multinational meta-analysis of 80 studies (from 1996 to 2012), which constituted 89,281 participants from 31 countries, reported a global PIU prevalence of 6%, with the highest prevalence in the Middle East (10.9%) and lowest in northern and western Europe (2.6%) (Cheng & Li, 2014). High variation in prevalence (ranging from 8.1% to 50.9%) was shown among young adults and adolescents of Asia. Studies conducted in Europe and the United States found the prevalence of PIU to be 7.9% to 25.2% among adolescents, whereas in studies from the Middle East and Africa, prevalence ranged from 17.3% to 23.6%. The prevalence rate of PIU in western and eastern countries (e.g., Singapore, China, Hong Kong, Japan) has been estimated to be 1.4% to 17.9% (Maheshwari & Sharma, 2018).

In recent years, due to the widespread use of the internet in Asian countries, its overuse among adolescents has become a growing problem. In one study of 5,366 adolescents ages 12 to 18 from six Asian countries (i.e., China, Hong Kong, Japan, South Korea, Malaysia, and the Philippines), overall prevalence of smartphone ownership was 62%, ranging from 41% in China to 84% in South Korea. Moreover, participation in online gaming ranged from 11% in China to 39% in Japan. Hong Kong had the highest number of adolescents reporting daily internet use (68%). PIU was highest in the Phillipines (Mak et al., 2014).

According to one study, internet addiction in India is prevalent and at least 24.6% of adolescents have PIU (Sharma et al., 2016). Several smaller studies restricted to the cities of Jaipur, Mumbai, and Jabalpur found mid-level PIU in 24% to 34% of individuals and moderate addiction between 7% and 24% (Maheshwari & Sharma, 2018). The Indian Council of Medical Research funded a survey of 2,755 people ages 18 to 65 from Bengaluru and found that 1.3% were addicted to the internet, 4.1% to smartphones, 4% to online shopping, 3.5% to social networking sites, 2% to online pornography, and 1.2% to online gambling (Barthakur & Sharma, 2012).

Existing U.S. data suggest that 93% of adolescents and adults between ages 12 and 29 use the internet (Moreno et al., 2011). Thus, PIU is a substantial risk for this age group, and unhealthy internet use may result in negative effects, especially in adolescents (Günlü & Ceyhan, 2017). Compared with adults, adolescents are more vulnerable to PIU (Lortie & Guitton, 2013). Approximately all adolescents use the internet, >80% use it daily, and >50% consider it indispensable (Frees & Koch, 2015; Riedl et al., 2016). Access to relevant technologies has become a precondition for educational and occupational advancement; thus, internet “abstinence” is not an option for most youth today (Durkee et al., 2012; Frees & Koch, 2015; Riedl et al., 2016).

Adolescence occurs between ages 11 and 18 and is defined as the stage between childhood and adulthood. During this time, there is an increased risk for emotional crises, which are often accompanied by mood changes, anxiety, and depression (Karacic & Oreskovic, 2017). Today's adolescents experience a complex bidirectional relationship between what is occurring offline and what is occurring online. According to the co-construction model, adolescents shape their reality by connecting their offline and online worlds, with the latter being the dominate world (Subrahmaanyam & Smahel, 2011). Children and adolescents are abandoning traditional past-times (e.g., playing outside, reading) and substituting them with internet surfing. They are especially attracted to new technological methods of communication, which offer interaction with others and at the same time provide anonymity, a feeling of belonging, and a sense of acceptance (Karacic & Oreskovic, 2017).

Adolescents are drawn to the internet as a form of release, which can lead to addiction over time and possible risk of psychological health issues. Therefore, the promotion of healthy internet use and prevention of social networking addiction are important early on in safeguarding individuals' mental wellness (Tsang, 2014). Several studies in the United States and abroad, and numerous anecdotal media reports, suggest possible links between overuse of the internet by adolescents and young adults and negative health consequences such as depression, attention-deficit/hyperactivity disorder, excessive daytime sleepiness, problematic alcohol use, or self-harm (Moreno et al., 2011).

A growing body of evidence indicates that PIU is associated with a broad spectrum of somatic and psychosocial problems as well as psychiatric comorbidity. With respect to psychosocial behavior, dysregulated internet use has been found to be associated with tobacco use, less time spent with real-life peers, and physical inactivity or sedentary lifestyle. PIU has also been associated with self-destructive behavior in adolescents (Fuchs et al., 2018). Negative somatic effects of excessive internet use in adolescents include sleeping problems, not sleeping at all, overweight, poor nutrition, back and musculoskeletal issues, vision problems, carpel tunnel syndrome, and neglect of personal hygiene and cleanliness (Moreno et al., 2013). PIU is associated with less physical activity and diverse negative neurophysiological and psychosocial consequences in adolescents (Throuvala et al., 2019). In addition, children and adolescents often consider life without the internet as boring, leading to loneliness and isolation and affecting personal relationships, school life, and development of new relationships (Gregory, 2019).

Distrust and dishonesty issues can also arise, as individuals with PIU may try to hide or deny the amount of time they spend online (Gregory, 2019). These individuals try to establish and maintain online relationships and prefer seeking online help for most issues. In addition, these individuals may create alternate online personas to mask their online behaviors. They neglect family; tend to have frequent conflicts with family, relatives, or peers; and neglect household activities. Individuals with PIU also tend to be aggressive and angry and may have mood fluctuations, depression, and experience unease if not online. PIU has also been associated with negative academic consequences, such as missed classes, lower grades, and even academic dismissal (Moreno et al., 2011). According to Aydogan (2008), fear of failure in academic life can make individuals fail to complete assignments on time, resulting in academic procrastination. These delays can negatively affect adolescents' academic performance and may lead to frequent absenteeism from school, poor grades, and dropout (Günlü & Ceyhan, 2017).

Current scientific consensus calls for the development of well-controlled, methodologically robust interventions for PIU that are grounded in empirical evidence and theory. As adolescents show limited treatment motivation and high therapy avoidance, systematic approaches for PIU, such as school-based programs, seem most promising (Lindenberg et al., 2017).

The school system is increasingly used as a venue to drive prevention efforts and address health promotion and public health concerns. These efforts can take the form of teacher and parent training and student education, raising awareness and possibly enhancing protective factors and reinforcing positive behaviors or aspects of the environment that reduce the likelihood of negative occurrences. School-based efforts are efficient in that they offer access to large numbers of students in a cost-effective way (Throuvala et al., 2019).

Literature on treatment outcomes in PIU remains underdeveloped and heterogeneous in many ways, especially in Indian settings. Many practitioners are unaware of PIU and its effect on adolescents' lives and are consequently unprepared to treat these individuals (Ibrahim & Fouad, 2014). However, using current evidence-based knowledge, nurses and other health care providers can contribute toward therapeutic and preventive intervention of PIU by providing therapies that increase insight into a person's behavior (Radwan, 2013). Thus, the aim of the current study was to assess biopsychosocial functioning and academic performance in adolescents with PIU to contribute to the understanding of PIU among this population and design an intervention for PIU.

Study Objectives and Hypotheses

The current study objectives were to: (a) screen adolescents for PIU among selected schools; (b) compare pre- and posttest scores of PIU, biopsychosocial functioning, and academic performance among adolescents with PIU in experimental and wait-list control groups to determine the effectiveness of a nurse-led intervention; (c) determine any correlation between pretest scores of PIU and biopsychosocial variables and academic performance among adolescents with PIU; and (d) identify the association between select sociodemographic variables and pretest scores of PIU.

Three hypotheses (H) drove the current study as follows:

H1: There is a statistically significant difference in the mean posttest scores of PIU, biopsychosocial variables, and academic performance in adolescents in the experimental group who underwent the nurse-led intervention compared to adolescents with PIU in the wait-list control group.

H2: A significant correlation exists between the total pretest scores of PIU, biopsychosocial variables, and academic performance of adolescents with PIU in the experimental and wait-list control groups.

H3: A significant association exists among PIU, biopsychosocial functioning, academic performance, and select sociodemographic variables of adolescents with PIU.

Method

Participants

The current study included adolescents in grades 9 and 11 studying in private and private-aided schools in the Ernakulam District, India. Passive information and consent forms were sent to parents/guardians. After screening for PIU, adolescents with mild to moderate PIU were randomized to experimental and wait-list control groups based on prespecified inclusion and exclusion criteria. Participants were assured of confidentiality and anonymity, and they were made aware of their right to withdrawal from the study at any time.

Inclusion and Exclusion Criteria

Inclusion criteria were students in grades 9 and 11 in secondary and higher secondary schools who had mild to severe PIU, were willing to participate in the study, and whose parents/guardians signed the informed consent form. Exclusion criteria were failure to participate in the program for more than 2 weeks and having any condition that impaired communication (e.g., physical illness, comorbid psychiatric illness).

Study Design

An experimental pre/posttest design was used. The intervention was conducted over 12 weeks and included 100 adolescents with similar characteristics.

Measures

Several measures were used to collect participant data.

Sociodemographic Form. This form was used to assess sociodemographic characteristics of participants, including age, gender, religion, grade, residence, type of family, educational status of parents, occupational status of parents, socioeconomic status, number of siblings, relationship with parents, and parenting style.

Internet Usage Pattern. Data regarding internet use included age at which internet use began, device used, place of internet access, purpose of internet use, most frequently visited website, privacy settings, login status, money spent online, preferred time of day when internet is accessed, and average duration of access (i.e., daily and weekly).

Parent-Child Internet Addiction Test. This tool, developed by Young (2016), comprises 20 items that measure characteristics and behaviors associated with internet use, including compulsivity, escapism, and dependency. Responses for each item are rated on a 5-point Likert scale ranging from 1 (rarely) to 5 (always), where scores ≤30 indicate no internet use, scores 31 to 49 indicate mild internet use, scores 50 to 79 indicate moderate internet use, and scores ≥80 indicate severe internet use.

PIU Questionnaire. This valid and reliable tool is a self-report survey developed by Demetrovics et al. (2008) to identify the components of PIU and measure the problems associated with excessive internet use. Permission to use the tool was obtained from the authors. The tool comprises 18 items with three domains: obsession, neglect, and control disorder. Total score ranges from 18 to 90, where scores ≤18 indicate no PIU, 18 to 36 indicate mild PIU, 36 to 54 indicate moderate PIU, and ≥55 indicate severe PIU.

Biopsychosocial Functioning Profile. This instrument, developed by the current researcher to assess adolescents' subjective health and well-being and distress, has three domains: physical functioning, psychological functioning, and social functioning.

The physical functioning profile comprises subjective and objective assessment. Objective assessment includes height, weight, and body mass index. Subjective assessment consists of three subscales: general health (one item), physical activity (11 items), and bodily discomfort (25 items)/physical hygiene (five items). General health, bodily discomfort, and physical hygiene are scored using a 5-point Likert scale, ranging from 1 (never) to 5 (always). Physical activity is rated on a 3-point Likert scale, ranging from 1 (not at all) to 3 (restricted). Scoring was as follows: ≤46 = very high physical functioning, 47 to 92 = high physical functioning, 93 to 138 = moderate physical functioning, and 139 to 185 = low physical functioning.

The psychological functioning profile comprises 35 items to assess general well-being and distress among adolescents due to internet use. Items are scored on a 5-point Likert scale ranging from 1 (never) to 5 (always), with a minimum score of 35 and maximum score of 175. Scores ≤35 indicate low psychological functioning, 36 to 70 indicate moderate psychological functioning, 71 to 105 indicate high psychological functioning, 106 to 140 indicate very high psychological functioning, and 141 to 175 indicate excellent psychological functioning.

The social functioning profile comprises 30 items to assess adolescents' online and offline interaction with family, friends, and society in general. The scale consists of 11 positive items and 19 negative items (reverse scored) scored using a 5-point Likert scale from 1 (never) to 5 (always), with total scores ranging from 30 to 150, where ≤30 indicates low social functioning, 31 to 60 indicates moderate social functioning, 61 to 90 indicates high social functioning, 91 to 120 indicates very high social functioning, and 121 to 150 indicates excellent social functioning.

Academic Performance Form. This tool was used to assess the cumulative academic performance of adolescents during the study intervention, where >80 is excellent, 60 to 80 is good, 40 to 59 is average, and <40 is poor.

Nurse-Led Intervention

This intervention was developed based on group behavioral therapy, motivational interviewing, and life skill practices and aimed to reduce PIU and improve adolescents' biopsychosocial functioning and academic performance. The intervention was delivered over 3 months, taking the academic calendar into consideration.

The intervention comprised 12 sessions provided once per week for 45 minutes to 1 hour. For adolescents, the sessions comprised four modules and sub-modules focusing on (a) psycho-education on PIU and its causes, incidence and prevalence, prevention, and management (one session); (b) motivational interview (two sessions); (c) behavioral modifications (three sessions); and (d) life skills to manage psychological problems, improve social skills, and prepare for academic examinations (six sessions). Two sessions were provided for parents on family psychoeducation and relapse prevention.

Students were divided into groups of six or seven, with an assigned group leader. The group leader changed every session, and group members were changed after every module. The mode of instruction included a didactic lecture followed by interactive sessions with students using audiovisual aids, a blackboard, charts, handouts, PowerPoint® presentations, video clips, and role playing. Homework was assigned to strengthen the establishment of therapeutic changes required to modify everyday behavior. Students were also taught to express their anxiety, fears, and concerns about peers, family, or academics, and they were provided with situations to develop life skills. The sessions were conducted by the researcher (P.M.) and a psychologist.

Ethical Issues

The pilot study was conducted after receiving approval from the Institutional Ethical Committee of Saveetha Institute of Medical Science and Technology (SIMATS) University. Administrative sanctions from concerned authorities (i.e., Directorate of Higher Secondary Education, Director of Public Instructor, and principals and head mistresses of participating schools in Ernakulum) were also obtained. Approval was also sought from the Parent Teacher Association from the respective schools. Because the students were minors, written consent from their parents was obtained; informed consent was also obtained from students before the initiation of data collection. The purpose and nature of the study were explained to students and their parents. Confidentiality and anonymity of participants were assured and maintained throughout the study period. Participants were made aware that they could withdraw from the study at any time.

Data Collection

For initial screening of PIU among adolescents, data were obtained from 100 parents using the Parent-Child Internet Addiction Tool, which was administered during the school's open house or a parent teacher meeting.

Of the 100 students initially screened, 60 had mild to severe PIU and were included in the study. Thus, 30 adolescents were randomly assigned to the experimental and wait-list control groups, respectively. During the pretest, baseline information, PIU, and biopsychosocial functioning were assessed. Information pertaining to academic performance was obtained from each student's teacher. All study measures were administered in both groups during students' free periods and took approximately 45 minutes to complete. Any concerns were addressed at the end of the session.

After the pretest, the experimental group participated in the intervention, whereas the wait-list control group did not participate. A posttest was performed after Week 1 and Week 12 of the intervention in the experimental group. After the posttest, the intervention was then provided to the wait-list control group.

Data Analysis

Descriptive statistics were calculated to examine participants' demographic characteristics. Repeated measures analysis of variance (ANOVA) was applied to examine the overall effectiveness of the intervention. Post-hoc analysis with Tukey HSD correction was conducted for both groups to analyze the differences for all intervening variables—PIU, biopsy-chosocial functioning, and academic performance—among adolescents with PIU at three time periods: T1 (baseline), T2 (Week 1), and T3 (Week 12). Spearman's rho was calculated to find the correlation of PIU with biopsycho-social functioning and academic performance. t test and ANOVA were used to find the association of PIU with selected demographic variables. Statistical significance was set at p ≤ 0.05. Data analysis was performed using R software version 3.6.2.

Results

Initially, a sample of 100 adolescents were screened for PIU. Of these adolescents, 40 had no PIU, 45 had mild PIU, and 15 had moderate PIU, with an overall mean score on the Parent-Child Internet Addiction Test of 44.95 (SD = 9.83). Demographic data are presented in Table 1.

Participant Demographics (N = 60)

Table 1:

Participant Demographics (N = 60)

Table 2 shows internet usage patterns for those individuals with PIU. Of these 60 adolescents, 32 (53.3%) started using the internet between ages 10 and 12, and 10 (16.7%) started between ages 12 and 14. Craving internet use was reported by 31 (51.7%) adolescents. Most users (n = 51 [85%]) preferred to access the internet at home, and 47 (78.3%) adolescents used laptops. Adolescents preferred to be online throughout the day, with 19 (31.7%) accessing the internet 2 to 4 hours per day.

Internet Usage Pattern of Adolescents with Problematic Internet Use (N = 60)Internet Usage Pattern of Adolescents with Problematic Internet Use (N = 60)

Table 2:

Internet Usage Pattern of Adolescents with Problematic Internet Use (N = 60)

Table 3 shows the level of PIU; physical, psychological, and social functioning; and academic performance during the pretest. Of 60 adolescents, only two had mild PIU, 19 had moderate PIU, and 39 had severe PIU. Fifty-three adolescents reported high physical functioning and seven reported moderate physical functioning. Regarding psychological functioning, five adolescents reported low functioning, 33 reported moderate functioning, 18 reported high functioning, and four reported very high functioning. For social functioning, 30 adolescents reported moderate functioning, 29 reported high functioning, and only one had very high functioning. With respect to academic performance, five adolescents reported poor academic performance, 21 reported average performance, 21 reported good performance, and five reported very good performance.

Level of Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance of Adolescents with PIU (N = 60)

Table 3:

Level of Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance of Adolescents with PIU (N = 60)

Table 4 shows the comparison between experimental and wait-list control groups in regard to the effectiveness of the nurse-led multi-intervention using parametric test repeated measures ANOVA. A significant difference was noted between the experimental and wait-list control groups for PIU (F = 56.551, p < 0.001), physical functioning (F = 4.956, p < 0.03), and social functioning (F = 30.148, p < 0.001). However, significant differences were not seen for psychological functioning or academic performance. Hence, Hypothesis 1 was accepted.

Between-Group Comparison of Total Pre- and Posttest Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance Among Adolescents With PIU (N = 60)

Table 4:

Between-Group Comparison of Total Pre- and Posttest Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance Among Adolescents With PIU (N = 60)

Using the Tukey HSD post-hoc test, the nurse-led multi-intervention for PIU among adolescents was found to have a significant effect at T1, T2, and T3 in the experimental group (p < 0.01). No significant differences were seen in the wait-list control group during these same time periods. Similarly, in regard to physical, psychological, and social functioning, a significant difference was seen at the three time points for the experimental group, but no statistically significant differences were observed for the wait-list control group. Regarding academic performance, a difference was observed during T2 and T3 in the experimental group. In the wait-list control group, no significant differences were found during the three time points (Table 5).

Within-Group Comparison of Total Pre- and Posttest Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance Among Adolescents With PIU (N = 60)

Table 5:

Within-Group Comparison of Total Pre- and Posttest Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance Among Adolescents With PIU (N = 60)

Spearman's correlation coefficient was used to study the relationship between PIU and physical, psychological, and social functioning, and academic performance among adolescents, as data violate the normality assumption. A highly significant positive correlation was found between PIU and physical functioning (r = 0.385, p < 0.002), PIU and psychological functioning (r = 0.350, p = 0.006), and PIU and social functioning (r = 0.646, p < 0.001). However, no significant correlation was found between PIU and academic performance (r = 0.55, p = 0.677). Based on these findings, it can be inferred that a significant increase in PIU among adolescents may significantly impact physical, psychological, and social functioning. Thus, Hypothesis 2 was accepted.

For PIU and sociodemographic variables, a significant association was found regarding relationship with parents (t = −2.228, p = 0.03). For PIU and internet use pattern, a significant association was found for beginning age of internet use (F = 6.77, p = 0.02), craving internet use (t = −2.01, p = 0.04), and amount of use per week (F = 3.836, p = 0.027). Thus, Hypothesis 3 was accepted.

Discussion

The aim of the current study was to identify the prevalence of PIU among adolescents and determine the effect of a nurse-led multi-intervention on PIU. The prevalence of PIU was 65%, with the ubiquitous presence of wireless internet access, smartphones, and social media potentially contributing to this high rate of PIU.

Mean age of adolescents in the current study was 14.55 (range = 13 to 18, SD = 1.12 years), an age at which some individuals may be more susceptible to excessive internet use as they tend to separate from family and move toward independence. More than one half of adolescents with PIU in the current study were female, which is consistent with findings of Porter et al. (2011) who reported more female adolescents as active users in their study. The internet may seem more attractive to female adolescents, as it may have give them a sense of belonging and ability to be anonymous.

Current results also indicate that PIU is correlated with computer (e.g., personal desktop, laptop) and smartphone ownership. Access to these devices, permanent logged-in status, and Wi-Fi connections promote significant use during the morning hours, as users read the news, check email, visit social networking sites, and play games. Location of internet access is another factor for PIU, as well as permanent logged-in status. These findings are consistent with those of Gedam (2017).

Of the 60 adolescents with PIU in the current study, 65% had severe PIU, 31.7% had moderate PIU, and 3.3% had mild PIU. These findings are contradictory to those of Mishra et al. (2015), in which their study reported 85% of students had no PIU and 14.5% had PIU.

It was hypothesized that the nurse-led multi-intervention would decrease PIU and improve psychosocial functioning and academic performance in the intervention group. This hypothesis (H1) was proven, as PIU significantly decreased in the intervention group within 3 months postintervention (pre-test mean score = 52.13 [SD = 9.44] vs. posttest mean score = 42.57 [SD = 9.99], p < 0.001). This decrease was achieved through the use of a structured psychoeducation program for PIU and its effects on physical, psychological, and social functioning and academic performance. This result is consistent with previous results of studies using school-based interventions, which have proven to be effective and feasible (Gholamian et al., 2019). In addition, the program took an interactive approach to reduce excess internet use by training adolescents in problem solving skills, behavioral modification, recreational activities, and life skills (Gholamian et al., 2019).

A significant difference was observed in the intervention group when compared to the wait-list control group at two time points (1 week after the intervention [T2] and 3 months after completion of the intervention [T3]) (F = 43.94, p < 0.001).

A significant positive correlation was seen for PIU and physical, psychological, and social functioning, and no relationship was found between PIU and academic performance. Based on these findings, it can be inferred that with an increase in PIU, there is an increase in physical functioning score, indicating impaired physical functioning. An et al. (2014) reported similar findings, finding a positive association between PIU and physical and psychological functioning. However, a contradictory finding was reported by Pandya and Korat (2015), where no significant relationship was found with psychological well-being. Regarding academic performance and PIU, the current findings are supported by those of Kakkar et al. (2015), who also found no relationship between PIU and academic performance.

A significant association was found between PIU and relationship with parents (t = − 2.228, p = 0.03). Excess internet use among adolescents may be associated with problematic family relationships or frequent family conflict. However, this finding was contradictory to a study by Kayastha et al. (2018), where a significant association was seen for age, gender, class, current residence, permanent residence, religion, type of family, and number of siblings.

Strength and Limitations

A strength of the current study was the use of valid and reliable instruments that have been tested and used in many studies. Limitations include the inability to generalize findings, as the study sample was small, including only students in grades 9 and 11 in one geographical area. The study also lacked long-term follow up due to limited time provided by the schools to conduct the study. Bias may have occurred during screening for PIU, as parents may have under- or overestimated adolescents' use. In addition, adolescents may have been worried about disclosing their responses due to fear of being judged by peers, school authorities, and parents.

Nursing Implications

In addition to clinical practice, nurses can work as counselors, educators, therapists, or special consultants in school settings to assess, diagnose, and prevent PIU (Liu et al., 2017). Nurses can educate adolescents on the effect of excessive internet use on psychosocial functioning, create awareness regarding the prevalence of PIU, and discuss the advantages and disadvantages of internet use, as well as the role the school and administration can play in curbing PIU. At the community level, families can be provided with psychoeducation on excessive internet use, its consequences, how to check use and establish limits, and how to divert attention to different activities. Nurses also need to develop protocols and effective programs for the management of addiction.

Future Research

Future studies on PIU should include a more representative sample of different ages, grades, and geographic locations. For example, studying the effects of PIU between children ages 6 to 12, teenagers ages 13 to 19, and adults ages 20 to 40 may provide better insight on internet use. Individual interviews are also recommended along with completion of questionnaires.

Conclusion

With the ubiquity of high-speed internet and widespread use of technology, problems in physical and psychosocial functioning due to PIU are on the rise, especially among adolescents. Thus, health professionals need to address these problems to improve affected individuals' health and well-being. Provision of an intervention, such as the one in the current study, along with education, screening, and early intervention could reduce harm caused by PIU. Further carefully designed studies are warranted to evaluate the efficacy of different treatments in different populations.

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Participant Demographics (N = 60)

Variablen (%)
Age (years)
  13 to 1529 (48.3)
  16 to 1831 (51.7)
Gender
  Male29 (48.3)
  Female31 (51.7)
Religion
  Hindu43 (71.7)
  Christian14 (23.3)
  Muslim3 (5)
Grade
  9th30 (50)
  11th30 (50)
Residence
  Urban37 (61.7)
  Rural23 (38.3)
Type of family
  Nuclear40 (66.7)
  Joint20 (33.3)
Socioeconomic status (rupees)
  >30,00011 (18.3)
  >20,000 to 30,00012 (20)
  >15,000 to 20,00016 (26.7)
  >10,000 to 15,00018 (30)
  5,000 to 10,0003 (5)
No. of siblings
  117 (28.3)
  236 (60)
  >26 (10)
  None1 (1.7)
Relationship with family
  Good34 (56.7)
  Problematic20 (33.3)
  Frequent conflict6 (10)
Parenting style
  Strict29 (48.3)
  Democratic12 (20)
  Lenient16 (26.7)
  Negligent3 (5)

Internet Usage Pattern of Adolescents with Problematic Internet Use (N = 60)

Variablen (%)
Beginning age of internet use (years)
  <1017 (28.3)
  10 to <1232 (53.3)
  12 to <1410 (16.7)
  14 to 161 (1.7)
Felt cravings to use the internet
  Yes31 (51.7)
  No29 (48.3)
Device used
  Laptop47 (78.3)
  Desktop8 (13.3)
  Tablet3 (5)
  All of the above2 (3.3)
Place of internet access
  Home51 (85)
  Internet café4 (6.7)
  School library3 (5)
  Friend's house2 (3.3)
Purpose of internet use
  Blogging11 (18.3)
  Instant messaging6 (10)
  Downloading/listening to music5 (8.3)
  Retrieving information pertaining to education5 (8.3)
  Academic3 (5)
  Interactive games2 (3.3)
  Online shopping1 (1.7)
  Chat room1 (1.7)
  Social networking (Facebook®, Twitter®)1 (1.7)
  All of the above25 (41.7)
Mostly used website/search engine
  Google27 (45)
  YouTube8 (13.3)
  Yahoo7 (28.3)
  Facebook7 (11.7)
  Other1 (1.7)
Privacy (i.e., parental supervision)
  Low35 (58.3)
  Medium8 (13.3)
  High14 (23.3)
Login status
  Always34 (56.7)
  When necessary26 (43.3)
Money spent on internet use (rupees)
  10028 (46.7)
  >100 to 3008 (13.3)
  >300 to 50024 (40)
Preferred time of the day
  Throughout the day26 (43.3)
  When necessary15 (25)
  Morning10 (16.7)
  Evening9 (15)
Average duration of access per day (hours)
  <112 (20)
  1 to 217 (28.3)
  >2 to 419 (31.7)
  >412 (20)
Average duration of access per week (hours)
  <728 (46.7)
  7 to 149 (15)
  >14 to 2822 (36.7)
  >281 (1.7)

Level of Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance of Adolescents with PIU (N = 60)

Variable (Score Range)n (%)
PretestPosttest 1Posttest 2
PIU
  Normal (≤18)000
  Low (19 to 36)2 (3.33)21 (35)8 (13.34)
  Moderate (37 to 54)19 (31.67)15(25)26 (43.33)
  Severe (55 to 90)39 (65)24 (40)26 (43.33)
Physical functioning
  Very high (0 to 46)000
  High (47 to 92)53 (88.33)57 (95)55 (91.67)
  Moderate (93 to 138)7 (11.67)3 (5)5 (8.33)
  Low (139 to 185)000
Psychological functioning
  Low (≤35)5 (8.33)01 (1.67)
  Moderate (36 to 70)33 (55)28 (46.67)30 (50)
  High (71 to 105)18 (30)32 (53.33)29 (48.33)
  Very high (106 to 140)4 (6.67)00
  Excellent (141 to 175)000
Social functioning
  Low (≤30)000
  Moderate (31 to 60)30 (50)30 (50)20 (33.33)
  High (61 to 90)29 (48.33)29 (48.33)39 (65)
  Very high (91 to 120)1 (1.67)1 (1.67)1 (1.67)
  Excellent (121 to 150)000
Academic performance
  Poor (≤40)5 (8.33)2 (3.33)2 (3.33)
  Average (41 to <60)21 (35)19 (31.67)21 (35)
  Good (60 to <80)29 (48.33)37 (61.67)35 (58.34)
  Excellent (≥80)5 (8.33)2 (3.33)2 (3.33)

Between-Group Comparison of Total Pre- and Posttest Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance Among Adolescents With PIU (N = 60)

Variable/GroupMean (SD)Between Group F (p Value)
PretestPosttest 1Posttest 2
PIU56.651 (<0.001)
  Experimental52.13 (9.44)34.33 (7.84)42.57 (9.99)
  Wait-list control61.27 (12.09)60.93 (12.01)62.03 (11.67)
Physical functioning4.956 (0.03)
  Experimental75.17 (12.71)67.73 (6.50)71.93 (10.98)
  Wait-list control79.10 (12.29)77.40 (11.53)76.50 (12.40)
Psychological functioning0.591 (0.445)
  Experimental63.10 (17.09)75.30 (15.33)72.23 (15.80)
  Wait-list control76.20 (19.64)70.00 (12.49)73.43 (15.01)
Social functioning30.148 (<0.001)
  Experimental50.50 (10.82)70.53 (8.63)62.23 (11.15)
  Wait-list control73.63 (12.91)73.27 (12.01)71.33 (11.15)
Academic performance4.740 (0.034)
  Experimental67.10 (10.78)68.20 (8.58)67.33 (8.72)
  Wait-list control61.33 (10.61)65.53 (9.27)62.53 (9.11)

Within-Group Comparison of Total Pre- and Posttest Problematic Internet Use (PIU); Physical, Psychological, and Social Functioning; and Academic Performance Among Adolescents With PIU (N = 60)

Variable/GroupMean (SD)Within Group F (p Value)
PretestPosttest 1Posttest 2
PIU43.94 (<0.001)
  Experimental52.13 (9.44)a34.33 (7.84)a42.57 (9.99)a
  Wait-list control61.27 (12.09)a60.93 (12.01)b62.03 (11.67)c
Physical functioning6.153 (0.006)
  Experimental75.17 (12.71)a67.73 (6.50)a71.93 (10.98)a
  Wait-list control79.10 (12.29)a77.40 (11.53)b76.50 (12.40)a
Psychological functioning33.578 (<0.001)
  Experimental63.10 (17.09)a75.30 (15.33)a72.23 (15.80)a
  Wait-list control76.20 (19.64)a70.00 (12.49)a,b73.43 (15.01)a
Social functioning27.165 (<0.001)
  Experimental50.50 (10.82)a70.53 (8.63)a62.23 (11.15)a
  Wait-list control73.63 (12.91)a73.27 (12.01)b71.33 (11.15)c
Academic performance0.977 (0.355)
  Experimental67.10 (10.78)b68.20 (8.58)a67.33 (8.72)a
  Wait-list control group61.33 (10.61)a65.53 (9.27)a62.53 (9.11)b
Authors

Ms. Mathew is Associate Professor and PhD Scholar, Saveetha Institute of Medical Science and Technology (SIMATS) University, Dr. Krishnan is Consultant Psychiatrist and Professor, Department of Psychiatry, Saveetha Medical College, Thandalam, and Dr. Bhaskar is Scientist B, Department of Statistics, Indian Council of Medical Research–National Institute for Research in Tuberculosis, Chetpet, Chennai, Tamil Nadu, India.

The authors have disclosed no potential conflicts of interest, financial or otherwise.

The authors thank the principals and PTA of the participating schools for granting permission to conduct the study and the adolescents and parents who participated in the study, and Mrs. Ancy Sebastian for translating the tool into Malayalam.

Address correspondence to Preeti Mathew, MSc, Associate Professor and PhD Scholar, Saveetha Institute of Medical Science and Technology (SIMATS) University, No. 162, Poonamallee High Road, Velappanchavadi, Chennai, Tamil Nadu 600077, India; email: mathew.preeti@gmail.com.

Received: January 03, 2020
Accepted: March 23, 2020
Posted Online: May 12, 2020

10.3928/02793695-20200506-03

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