Effectiveness of health promotion intervention on knowledge regarding psychological dependence on the internet and social media among adolescents in South India

ABSTRACT

Background:

The internet is being used extensively worldwide, especially among adolescents and young people. Early detection and creating awareness related to psychological dependence among the adolescent population, along with prompt measures towards sound use of technology, is essential.

Materials and Methods:

A randomized control trial was conducted among 100 participants (50 in each group) in secondary schools of the Bidar district. The study was approved by the Institutional Ethics Committee. Participants were selected using simple random sampling. Data was collected using a self-structured questionnaire and a standardized internet addiction test (IAT). Data was analyzed using SPSS (v. 20, IBM Corporation, New York, United States).

Results:

The study revealed that all the adolescents (100%) were using the internet and social media (SM), among which 81 (81.0%) adolescents had psychological dependence. There was a significant difference in the score across different points in the experimental group (mean score within groups = 13.15 at P < 0.001). A significant association was found between the level of knowledge and selected socio-demographic variables like age (P = 0.024) and educational status (P = 0.035).

Conclusion:

Health promotion intervention was found effective in enhancing knowledge regarding psychological dependence on the internet and SM. Thereby reducing the level of psychological dependence among adolescents.

Introduction

The flourishing of the internet is one of the most prominent features of the information society. In recent years, access to the internet has become widespread with the rapid development of smartphones. As of April 2023, there were 5.18 billion internet users worldwide, which amounted to 64.6% of the global population. There were 692.0 million internet users in India at the start of 2023, when internet penetration stood at 48.7%. India was home to 467.0 million social media (SM) users in January 2023, equating to 32.8% of the total population. Today, SM (e.g. WhatsApp, Instagram, Facebook, etc.) has enjoyed such rapid growth in popularity.[1] After China, India, and Indonesia, Iran ranks fourth in terms of using SM.[2] Nowadays, people’s daily lives have become inseparable from the internet, and the internet is widely used by school and college students for multiple purposes, including learning, entertainment, and communication.[1] While SM may appear to be a mindless and relaxing source of entertainment, it has a profound impact on your brain. Each time you log into your favourite apps, dopamine signals in your brain increase, triggering a sense of pleasure. This surge of dopamine reinforces the idea that using SM is a rewarding activity that should be repeated.[3]

Young defined internet addiction (IA) as “an impulse control disorder unaffected by addictive substances.”[2] Types of IA include online gambling addiction, cybersex addiction, video game addiction, and SM addiction.[4] Kwok et al. found that IA results in various negative effects, including sleep deprivation, lack of exercise, eye discomfort, stiff shoulders, cyberbullying victimization, and debt problems.[5] IA is typically characterized by psychomotor agitation, anxiety, craving, depression, hostility, substance experience, preoccupation, loss of control, withdrawal, impairment of function, reduced decision-making ability, and constant online surfing despite negative effects on social and psychological welfare.[6]

Adolescence is a period characterized by vulnerability and change. During this phase, crucial developmental milestones occur simultaneously with a significant restructuring of the brain. This fundamental restructuring in various regions appears to create a foundation for heightened susceptibility to the onset of mental disorders.[5] In recent years, the number of internet addicts has also gradually increased, among whom internet-addicted teenagers accounted for a relatively high proportion. Teenagers are in an important period of physical and mental development. IA will have varying degrees of adverse effects on their physical and mental development, as well as their study and life, and may lead to crime in serious cases.[7] The excessive use of video games and internet applications has been growing (particularly during the ongoing coronavirus disease (COVID-19) pandemic), which underlines the need for prevention and early intervention.[8]

Chung et al. demonstrated that psychological intervention for internet-addicted teenagers can better relieve the negative temperament of their parents and improve the quality of life of teenagers.[9] Kim et al. found that positive psychological intervention is beneficial to the emotional development of internet-addicted teenagers and can improve their social adaptability.[10] Lo et al. found that cognitive behavioral therapy has a positive effect on improving the self-efficacy of internet-addicted teenagers.[11] Though the above methods have certain effects on internet-addicted teenagers, some problems still exist in the process of application. Intervention treatment is particularly important for internet-addicted teenagers. At present, although the conventional intervention method is more effective.

SM use has been linked to poorer mental well-being, particularly when it begins to interfere with daily life and mental health. Practitioners are addressing this issue and working to improve users’ mental well-being through various interventions.[12] One critical approach involves the early detection and understanding of signs of IA by parents, school teachers, and adolescents themselves. Managing SM use and IA can be achieved by increasing the awareness and knowledge of these groups. By fostering a better understanding of the potential risks and warning signs, individuals and communities can take proactive steps to mitigate the negative effects of SM and promote healthier online habits.

This study aimed to estimate the pooled prevalence of problematic internet use (PIU) among school-going adolescents in India. PIU among students has become a significant mental health concern. Early detection of psychological dependence on the internet and SM among the adolescent population and prompt measures to redirect them towards sound use of technology are essential. So, to enhance knowledge and reduce the psychological dependence on the internet and SM, this study was planned.

Materials and Methods

Study design and setting

The study was a true experimental research design (randomized controlled trial). It has been conducted on the secondary school students (high school) of District Bidar, Karnataka.

Ethical consideration

Ethical clearance was obtained from the Research Ethical Committee at NIILM University (NU/RC/4003). Written informed consent from parents was obtained from the participant’s parents and assent was taken from participants. Privacy, anonymity, and confidentiality of the data were guarded.

Sample size and participants

The sample size was calculated using the formula (Z_1-α/2) + (Z_1-β) ² σ² [1+(m − 1) p]/m (d)², where a 95% confidence interval and at 80% power with 10% attrition rate, total 50 participants were selected for each group, resulting in a total sample size of 100 participants. Participants were selected through simple randomization with an allocation ratio of 1:1. The randomization sequence was generated using a computer-based randomization tool from www.randomization.com. To minimize selection bias, allocation concealment was ensured using the sequentially numbered, opaque, sealed envelopes method. Each envelope was sequentially numbered and contained information about the assignment to either the intervention group or the control group, which was kept unknown to the researcher. The study included students aged 13–17 years, enrolled in grades 9–12, who were willing to participate and able to understand, speak, and write in Kannada, Hindi, or English. Exclusion criteria included students unwilling to participate, those whose parents did not provide consent, and those undergoing treatment for mental disorders.

Data collection procedure

After receiving ethical clearance and approval to conduct the study in schools, participants were selected based on the inclusion and exclusion criteria and randomly allocated to the experimental or control group. The study’s purpose was explained, and written informed consent was obtained from both participants and their parents. Pre-intervention data were collected, and health promotion intervention regarding knowledge and psychological dependence on the internet and SM was provided to the participants. A post-test was conducted on the 14^th day after the intervention. Data was collected from September 7, 2021, to March 28, 2022, and took 15–20 min per participant.

Instruments: The tool was organized into three parts, which consisted of the following aspects:

• Section A: Socio-demographic: the socio-demographic data, which includes age, gender, class, residential area, type of family, father’s employment, mother’s employment, use of internet, and SM.

• Section B: Psychological dependence on the internet and SM: a self-structured questionnaire was prepared to assess the knowledge and psychological dependence on the internet and SM. It consists of 20 questions. Each correct response was awarded 1 point each. The highest score was 20 and the lowest was 0. The scoring criteria are 0–7, known as poor, 8–14 is average, and 15–20 is good. It was sent to 8–10 experts in the field of psychology, psychiatric nursing experts, and nursing faculty. The tool translations were done by two bilingual experts to ensure semantic equivalence. Reliability was established by the test-retest method, and the reliability of the tool was found to be 0.8.

Internet addiction test

The internet addiction test (IAT) scale was used to assess the psychological dependence on the internet and SM. It is a standardized questionnaire developed by Young. It consists of 20 items. The minimum and maximum scores are 0 and 100. It is a five-point Likert scale with 0 = Not Applicable, 1 = Rarely, 2 = Occasionally, 3 = Frequently, 4 = Often, and 5 = Always with the scoring of 0 to 30 points considered normal, 31 to 49 as mild level, 50 to 79 as moderate, and a score of 80 to 100 as severe dependence upon the internet. In a study on adolescents, the scale has a reliability of 0.85.

Intervention

Content explaining the internet, SM meaning, causes, symptoms, consequences and preventive measures of internet and SM, psychological dependence and its psychological effect on health was prepared by the researcher as per APA guidelines and with the consultation of experts, and validity was established.

Data analysis

The data analysis was conducted using SPSS software version 20 (IBM Corporation, New York, United States), with the data following a normal distribution. A significance level of 0.05 was set. Both descriptive and inferential statistics were applied to analyze the data in line with the study’s objectives and hypotheses. In the descriptive analysis, frequencies, percentages, means, and standard deviations were calculated. Inferential statistics, including the t-test, were used to compare the means of two groups, and the Chi-square test was employed to examine the association between knowledge of psychological dependence on the internet and SM among adolescents and selected socio-demographic variables.

Results

Table 1 reveals that the majority of participants in both the experimental (40%) and control (30%) groups were 17 years old. In the experimental group, 64% were male, compared to 56% in the control group. Most participants in both groups were in the 11^th standard (30% in the experimental group, 26% in the control group). Most came from urban areas (80% experimental, 78% control). While 56% of participants in the experimental group were from nuclear families, 60% in the control group came from joint families. Most participants had working fathers (92% experimental, 90% control). Chi-square tests confirmed both groups were homogenous (P > 0.05).

Table 1.

Frequency and percentage distribution of participants’ characteristics in experimental and control groups (n=100)

	Frequency (%)		χ 2	P
	Experimental group (n=50)	Control group (n=50)
Age (years)
15	15 (30)	16 (32)	0.49	0.73
16	10 (20)	13 (26)
17	20 (40)	15 (30)
18	5 (10)	6 (12)
Gender
Male	32 (64)	28 (56)	0.89	0.41
Female	18 (36)	22 (44)
Educational status (Standard)
9th	13 (26)	12 (24)	0.96	0.30
10th	11 (22)	13 (26)
11th	15 (30)	13 (26)
12th	11 (22)	12 (24)
Residential area
Urban	40 (80)	39 (78)	0.74	0.51
Rural	10 (20)	11 (22)
Type of Family
Nuclear	28 (56)	20 (40)	0.34	0.13
Joint	22 (44)	30 (60)
Father’s employment
No	4 (08)	5 (10)	0.45	0.82
Yes	46 (92)	45 (90)
Mother’s employment
Yes	6 (12)	8 (16)	0.42	0.85
No	44 (88)	42 (84)
Use the internet and social media
Yes	50 (100)	50 (100)

Figure 1 shows participants’ knowledge levels on psychological dependence before and after the intervention in both groups. Pre-intervention, both groups had similar knowledge distributions, with no participants classified as having good knowledge. Post-intervention, the experimental group showed significant improvement, with 56% achieving good knowledge and a decrease in poor knowledge from 66% to 24%. The control group showed no improvement.

Figure 1.

Bar graph showing distribution of the level of knowledge regarding psychological dependence

Table 2 depicts that the experimental group showed a significant improvement in knowledge about psychological dependence on the internet and SM after the intervention. In contrast, the control group did not show a significant change, suggesting that the intervention was effective in increasing knowledge in the experimental group.

Table 2.

Comparison of pre- and post-intervention level of knowledge regarding psychological dependence of internet and social media among experimental and control groups (n=50)

Groups	Time points	Mean±SD	Within-group comparison (t)	P
Experimental group	Pre-intervention	7.25±3.36	13.15	0.0002*
	Post-intervention	14.89±2.36
Control group	Pre-intervention	7.05±2.98	1.872	0.07
	Post-intervention	8.21±3.21

*Significant at 0.05. SD=Standard deviation

Figure 2 shows that pre-intervention, the majority in both the experimental (52%) and control (50%) groups had mild psychological dependence on the internet and SM. Post-intervention, 40% of the experimental group had no dependence. This suggests that the intervention had a positive effect on reducing psychological dependence in the experimental group, while the control group showed more modest changes.

Figure 2.

Bar graph showing the distribution of the level of psychological dependence on the internet and social media

From Table 3, it is evident that there is no significant association between pre-test knowledge level and demographic variables like gender, residential area, type of family, father and mother employment, and use of the internet and SM at the 0.05 level. There is a significant association between pre-test knowledge level with age and education at the 0.05 level of significance.

Table 3.

Association between level of knowledge and participant’s characteristics (n=100)

Demographic variables	Category	Participant	Frequency (%)		χ 2	P
			≤median (n=55)	Above median (n=45)
Age (in years)	15	31	16 (29)	15 (33)	6.23*	0.024
	16	23	10 (18)	13 (29)
	17	35	23 (42)	12 (27)
	18	11	6 (11)	5 (11)
Gender	Male	60	35 (58)	25 (42)	0.762	0.32
	Female	40	20 (50)	20 (50)
Class	9th	25	15 (27)	10 (22)	5.63*	0.035
	10th	24	12 (22)	12 (27)
	11th	28	15 (27)	13 (29)
	12th	23	13 (24)	10 (22)
Residential area	Urban	79	40 (51)	39 (49)	0.98	0.98
	Rural	21	15 (71)	6 (29)
Type of family	Nuclear	48	28 (58)	20 (42)	0.56	0.89
	Joint	52	27 (52)	25 (48)
Residential area	Urban	79	40 (51)	39 (49)	0.98	0.11
	Rural	21	15 (71)	6 (29)
Father employment	No	09	4 (07)	05 (11)	1.23	0.510
	Yes	91	51 (93)	40 (89)
Mother employment	Yes	14	8 (57)	6 (43)	0.96	0.714
	No	86	47 (55)	39 (45)
Use of the internet and social media	Yes	100	55 (100)	45 (100)

*Significant at 0.05, χ²=Chi-square

Discussion

The study showed that health promotion intervention effectively increased knowledge and reduced psychological dependence on the internet and SM in the experimental group compared to the control group. Among the participants, 82% in the experimental group and 80% in the control group had psychological dependence. These findings align with an Italian study where 28% were fully dependent, and 34.7% exhibited internet abuse behavior.[13] A German study found 43.69% of participants had internet dependence 18 months after the COVID-19 pandemic onset.[14] Another study reported 13.5% with moderate and 1.5% with severe dependence.[15] An Indian review (2022) showed that 21.5% of adolescents had moderate and 2.6% severe dependence,[16] while a 2019 review among college students reported prevalence ranging from 19.9% to 40.7%.[17] In Southeast Asia (2018), severely PIU ranged from 0 to 47.4%, and possible IA ranged from 7.4% to 46.4% among students.[18] A study in Kentucky (2021) found 56.8% of pharmacy students had moderate, 24.5% mild, and 18.2% severe IA.[19] In China, 38% were dependent, and 37.7% showed abusive behavior,[20] while in Saudi Arabia, 68% of adolescents had mild to severe addiction.[21] IA is higher in Kentucky and Saudi Arabia compared to India, but lower in China.

In the context of knowledge regarding psychological dependence on the internet and SM, the majority of participants in both the groups, like 66% in the experimental group and 70% in the control group had poor knowledge whereas 34% in the experimental and 30% in the control group had average knowledge. These findings are in line with a study conducted in Tamil Nadu by Lavanya that revealed 51.67% had inadequate knowledge, 46.67% had moderate knowledge, and only 1.67% had adequate knowledge.[22] In Punjab, 36.7% had average knowledge about substance abuse,[23] while in Gujarat, 50% showed moderate knowledge, and 30% had inadequate knowledge.[24] A contradictory study found 72.5% had average knowledge, 27.5% low knowledge, and none high knowledge.[25] In Dehradun, 75% had average knowledge, 23% good, and 2% poor knowledge.[26] In South India, 86% showed good knowledge and a positive attitude,[27] while in Bihar, 84% had good and 16% average knowledge.[28] Knowledge levels about internet use and abuse vary across India.

The studies show that most adolescents and students have moderate to severe psychological dependence on the internet and SM, as measured by the IAT. Psychological dependence is prevalent among early and late adolescents and college students. Few adolescents had adequate knowledge about this dependence, consistent with the present study. Psychological dependence on the internet and SM is often overlooked due to a focus on academics. Increasing knowledge about its effects on life is essential for promoting positive experiences and responsible technology use. The study highlights limited awareness of psychological dependence but emphasizes the potential to enhance knowledge and develop effective interventions.

A study of 43 Chinese college students found that short-term intensive cognitive behavioral therapy reduced IA symptoms and procrastination, and improved sense of coherence, but did not significantly reduce daily internet use or stress.[1] Another trial with 100 internet-addicted teenagers showed that social-psychological intervention improved self-efficacy, corrected poor online habits, and enhanced social adaptability and quality of life.[7]

A randomized trial with 46 college students examined the effects of 12 weeks of physical exercise on sleep quality, mood, and heart rate variability in those with IA.[13] In contrast, another trial limited SM use to 10 min daily but proved ineffective, as participants replaced it with instant messaging, leaving overall device use unchanged.[29]

The findings suggest that interventions like education, awareness programs, and adolescent-friendly clinics effectively reduce adolescents’ psychological dependence on the internet and SM. These simple measures raise awareness of digital technology’s effects without disrupting academics, promoting healthier usage. Health promotion interventions are highlighted as effective in reducing dependence and increasing awareness.

A significant association was found between knowledge level and characteristics like age and education (P < 0.05). In India, IA among teenagers was linked to challenges in academics, sports, socializing, and emotional well-being.[30] Similarly, a study in Iran found IA significantly associated with family functioning, daily internet use, and being male.[31] However, another study found no significant link between adolescents’ knowledge levels and demographic variables.[32] As grade level increases, the tendency for IA and the number of individuals affected gradually rise.[33] It may be connected to some factors that psychological dependence on the internet and SM was found to be associated with gender, duration of internet usage, family functioning, academic activities, sports, socializing, etc., So, it is recommended that not only adolescents but also their parents receive education regarding the safe and sound use of technology. The majority of studies on the internet and SM focus primarily on interventions and their effects. However, this study investigates both the level of knowledge and the degree of dependence on the internet and SM. Additionally, it demonstrates that the intervention effectively enhances adolescents’ knowledge, which plays a crucial role in reducing their dependence on the internet.

Limitations and recommendations

The study’s reliance on rating scales poses a limitation due to the risk of social desirability bias. Future research could explore more factors related to psychological dependence by incorporating open-ended questions and conducting focused group discussions. In-depth exploratory studies, including cohort and prospective designs, could help identify the underlying causes of psychological dependence. Additionally, implementing systematic education programs as part of the classroom routine could further address this issue.

Conclusion

The study revealed that psychological dependence on the internet and SM is a concern that may impact mental health, with adolescents and college students showing limited awareness. Hence, there is a need to administer special psychological modules, psychologically led health interventions, and nurse-led health promotion interventions to reduce dependence and increase the knowledge regarding psychological dependence on the internet and SM. The findings showed a significant increase in knowledge following the interventions and a significant association between knowledge levels and socio-demographic factors such as age and educational status.

Implication

• The findings of this study can help encourage education of the student population regarding psychological dependence on the internet and SM and the problems that can arise.

• Various hybrid workshops regarding various psychological dependencies on the internet and SM, and how to prevent and manage internet and SM use.

• The study contributes to starting de-addiction centers for the internet and SM-addicted population in every district of India.

• The administrators might motivate teachers to deepen their understanding of IA, including its causes, symptoms, and the psychological issues it can lead to.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.