The Influence of Internet Addiction on the Psychological Well-being of Students at the American University of Nigeria in the Post-COVID Era

Momoh Lawal Hussaini^1*, Madueke Akachukwu²

¹General Education Department, School of Arts and Sciences, American university of Nigeria, Yola, Nigeria

²Communication and Multimedia Design Department, School of Arts and Sciences, American University of Nigeria, Yola, Nigeria

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Abstract

This study examined the influence of internet addiction on the psychological well-being of students in the American University of Nigeria (AUN), Yola, Adamawa State, Nigeria in the post Covid era. University students are particularly vulnerable to internet addiction due to the pressures of academic life, social expectations, and the widespread availability of digital technology. The study employs a quantitative cross-sectional survey design, which allows for the collection of data at a single point in time. The study administered 100 questionnaires due to the regulatory admission of students in line with the American styled education. A combination of convenience sampling and snowball sampling was employed to recruit participants for the study. Data analysis included descriptive statistics (means, percentages) and inferential statistics (Pearson’s r, regression, t-tests/ANOVA) performed using SPSS, with a significance level of p < 0.05. The results indicate that internet addiction negatively impacts all six dimensions of psychological well-being, with environmental mastery and self-acceptance showing the strongest correlations. A multiple regression analysis was conducted to determine whether internet addiction predicts psychological well-being dimensions. The regression model was statistically significant (F (6, 93) = 7.85, p < 0.001), with an R² of 0.45, indicating that internet addiction accounts for 45% of the variance in psychological well-being. Early intervention and support are essential for addressing internet addiction and promoting psychological well-being among university students. Essentially, the research demonstrates a clear link between internet addiction and compromised psychological well-being in university students. This therefore highlights the need for awareness, prevention strategies, and support systems to help students maintain a healthy balance between their online and offline activities.

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Introduction

Background and Context of the Study

3). Consequently, concerns have escalated regarding Internet Addiction (IA), characterized by excessive internet use that significantly impairs daily functioning. Research has consistently demonstrated associations between IA and adverse psychological outcomes, including heightened stress and anxiety (Wang et al.⁴). University students, globally, are identified as a particularly vulnerable demographic due to their heavy dependence on smartphones and online resources (Kuss & Griffiths²).

Regional and Specific Context

In Sub-Saharan Africa, the rapid expansion of digital infrastructure has profoundly influenced student behaviors. However, research in this region remains limited (Ogundipe & Adebayo⁶). Nigeria, experiencing a dramatic increase in mobile internet penetration, presents a unique context. Students at private institutions, such as the American University of Nigeria (AUN), face distinct pressures due to their access to advanced digital technology. This study aims to investigate the relationship between Internet Addiction (IA) and Psychological Well-being (PWB) among AUN students, thereby addressing a critical research gap within the Nigerian academic landscape.

Objectives of the Study

The primary objective of this study is to investigate the influence of internet addiction on the psychological well-being of AUN students. Specific goals include:

• Assessing the prevalence of internet addiction among AUN students.
• Examining the relationship between internet addiction and psychological dimensions such as stress, anxiety, social relationships, and academic performance.

Research Questions

1. What is the prevalence of internet addiction among AUN students?
2. How does internet addiction influence various aspects of psychological well-being?

The Problem

Statement of the Issue

The rise in internet dependence among university students has led to growing concerns about Internet Addiction (IA) and its potential consequences on mental health and overall psychological well-being. IA is characterized by excessive internet use that interferes with daily life, academic responsibilities, and social relationships. It manifests in several ways, including compulsive browsing, gaming addiction, and social media dependency.

At AUN, where students rely heavily on digital platforms for academic and social engagement, excessive internet use may lead to negative psychological effects such as:

• Stress and Anxiety: Overwhelming academic demands combined with internet overuse can increase stress and anxiety levels.
• Social Isolation: Students may experience loneliness due to reduced in-person social interactions.
• Academic Underperformance: Internet-related distractions can hinder academic productivity.
• Sleep Disturbances: Irregular sleep patterns resulting from late-night browsing and social media use.

The concern becomes critical in the absence of institutional awareness or intervention programs addressing IA and its psychological implications in the Nigerian educational context.

Significance of the Study

This research provides valuable insights into how internet addiction affects university students' psychological well-being at AUN. Its findings can inform the following stakeholders:

• University Administrators: To design policies promoting responsible internet use.
• Mental Health Practitioners: To develop counseling and support services tailored to students' unique needs.
• Academic Advisors: To incorporate digital wellness education into student orientation and advising programs.

Additionally, this study contributes to the broader academic discourse on mental health in Nigerian higher education, highlighting an understudied area with significant implications for educational policies and student welfare.

Scope of the Study

The study focuses on undergraduate and graduate students at the American University of Nigeria. Its scope includes:

• Geographic Focus: AUN campus in Yola, Nigeria.
• Age Range: Students aged 16 and above enrolled in various degree programs.
• Data Collection Timeline: One semester during the academic year.
• Key Variables: Internet addiction levels and psychological well-being indicators, including stress, anxiety, social isolation, and academic performance.

Limitations

• Self-Reporting Bias: Respondents may underreport or exaggerate internet use and psychological well-being issues.
• Sample Size Constraints: The study's sample size of 100 participants, while adequate for detecting moderate to large effects, is smaller than the initial target of 150. This reduction, primarily due to challenges in data collection during exam periods, may limit the generalizability of the findings to a broader population of Nigerian university students.
• Context-Specific Findings: Results may not reflect broader Nigerian university populations due to AUN’s unique academic and socio-cultural environment.

Brief Review of Literature

Theoretical Framework

Understanding the relationship between internet addiction and psychological well-being is grounded in established psychological theories:

1. Cognitive-Behavioral Theory (CBT) of Internet Addiction: This theory suggests that maladaptive thinking patterns drive excessive internet use. Students may use the internet as an escape mechanism for stress or personal insecurities, reinforcing a cycle of dependence.
2. Self-Determination Theory (SDT):  SDT posits that human behavior is driven by the need for autonomy, competence, and relatedness. When these psychological needs are unmet in the offline world, students may seek validation and engagement online, potentially leading to internet addiction.
3. Uses and Gratifications Theory: This theory explains why individuals use media, focusing on specific gratifications like entertainment, information, and social connections. Students’ desire for instant feedback, information, and socialization can lead to compulsive internet use.

Empirical Studies on Internet Addiction and Psychological Well-being

Global Perspectives

Several international studies have explored the effects of internet addiction on psychological well-being:

• Kuss & Griffiths²: Found that heavy internet use contributes to depression, anxiety, and sleep disturbances among university students.
• Tokunaga⁹: Reported gender differences, with males exhibiting higher gaming-related IA.
• Young¹⁰: Identified withdrawal symptoms, impaired social relationships, and academic decline among individuals with internet addiction.
• Adeyemi & Salami⁵: Conducted a meta-analysis showing that internet addiction correlates with depression, anxiety, and social isolation.

Nigerian Context

Research on internet addiction within Nigerian universities is still emerging:

• Ifeagwazi et al.¹: Found a significant association between problematic internet use and depression among Nigerian university students.
• Ogundipe & Adebayo⁶: Identified internet addiction as a factor in declining academic performance in Nigerian higher institutions.

These studies align with AUN’s context but lack depth on private university dynamics or gender-specific trends.

Internet Addiction in the Nigerian Context

Socio-Cultural Factors

Nigeria's increasing digital connectivity has reshaped how students access information and interact socially. Mobile internet availability, affordability of data packages, and the widespread use of social media platforms like WhatsApp, Instagram, and TikTok have led to increased online activity among students.

However, the country’s limited mental health infrastructure and stigma surrounding psychological issues may exacerbate the negative effects of internet addiction, making it harder for affected students to seek help.

Educational Environment

The academic environment at institutions like AUN emphasizes online learning tools such as Moodle and Google Classroom. While these platforms enhance academic engagement, they may inadvertently contribute to internet overuse, especially when academic and personal digital activities overlap.

Gaps in the Literature

Despite growing research on internet addiction and psychological well-being, significant gaps remain:

• Limited Nigerian-Focused Studies: Most studies have centered on Western contexts, overlooking the unique cultural and technological environment in Nigeria.
• University-Specific Data: Research rarely targets private universities like AUN, where internet access is integral to students' academic lives.
• Holistic Approaches: Few studies adopt a multidimensional view of psychological well-being, encompassing stress, anxiety, social relationships, and academic performance.

Methods

Research Design

This study employs a quantitative cross-sectional survey design, which allows for the collection of data at a single point in time. The design is appropriate for assessing the prevalence of internet addiction and its impact on psychological well-being among AUN students.

The survey approach ensures cost-effectiveness and efficiency in gathering data from a large sample while providing statistical insights into the relationship between internet addiction and psychological health variables such as stress, anxiety, and social relationships.

Participants

Population:

The target population includes all undergraduate and graduate students at the American University of Nigeria (AUN), Yola.

Sample Size:

The study initially targeted 150 responses to ensure sufficient statistical power but achieved 100 completed surveys due to the minima number of students in the school, in line with the American standard of education. This sample size was deemed adequate based on a priori power analysis conducted using G*Power software. For a Pearson’s correlation test detecting a moderate effect size (r = 0.3), with α = 0.05 (two-tailed) and power (1 - β) = 0.80, a minimum sample of 84 was required. For multiple regression with one predictor (IA) and six dependent variables (PWB dimensions), anticipating a medium effect size (f² = 0.15), α = 0.05, and power = 0.80, a sample of 98 was sufficient. Thus, n = 100 exceeds these thresholds, supporting reliable detection of moderate-to-large effects, though smaller effects (e.g., r < 0.2) may require cautious interpretation.

Sampling Method:

A combination of convenience sampling and snowball sampling was employed to recruit participants. Initially, a convenience sample was obtained by personally approaching students on campus and inviting them to participate. Subsequently, snowball sampling was utilized by encouraging these initial participants to share the survey link with their peers via SMS, WhatsApp, and email. Additionally, official email invitations were sent through the Student Government Association (SGA), with reminders sent every three days to maximize participation.

Demographic Details:

Relevant demographic details include:

• Age
• Gender
• Academic year
• Program of study

These demographics were included to enable subgroup analysis and explore potential variations in internet addiction and psychological well-being.

Instruments

Survey Questionnaire:

The questionnaire consisted of three sections:

1. Demographics: Age, gender, year of study, and program of study.
2. Internet Addiction Assessment:
   • Young’s¹⁰ Internet Addiction Test (IAT): A 20-item scale assessing symptoms of internet addiction on a 5-point Likert scale (1 = rarely to 5 = always). Scores were classified as follows:
     • 20-49: Average internet use
     • 50-79: Moderate internet addiction
     • 80-100: Severe internet addiction
3. Psychological Well-Being Measures:

Ryff’s⁸ Psychological Well-being Scale (RPWB): This standardized tool measures six PWB dimensions: autonomy, environmental mastery, personal growth, positive relationships, purpose in life, and self-acceptance. Each dimension comprises multiple items (e.g., 3-9 items per subscale, depending on the version used; this study used the 18-item short form). Respondents rated items on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). For each participant:

1. • Subscale Scores: Individual items within each dimension were summed to produce a raw subscale score, then averaged to a 1-5 scale for consistency across domains (e.g., a 6-item subscale score of 18 would average to 3).
   • Total PWB Score: The mean of the six subscale averages was calculated to yield an overall PWB score (range: 1-5), where higher scores reflect greater well-being.
   • Handling: Subscale scores were retained separately for domain-specific analysis and combined for an aggregate PWB measure.

Validity and Reliability:

• Both scales have been validated globally with high reliability coefficients (α > 0.80).
• A pilot test was conducted on a small group of students to ensure clarity and comprehensibility of the survey items.

Procedure for Data Collection

1. Ethical Considerations:
   • Ethical approval was obtained from AUN’s Institutional Review Board (IRB) prior to data collection. Participants received a pre-survey disclaimer via Google Forms detailing the study’s purpose (examining IA and PWB), confidentiality measures (no identifiable data collected), and voluntary nature (option to withdraw at any time without consequence). Informed consent was secured electronically by requiring participants to click “Agree” before proceeding. Data was stored on a password-protected server accessible only to the research team, with anonymized responses coded numerically (e.g., P001-P100).
2. Pilot Testing:
   • A pilot test was conducted with 10 AUN students (excluded from the final sample) to refine the survey. Feedback confirmed item clarity and comprehension, with minor adjustments made to phrasing (e.g., simplifying “How often do you find that you stay online longer than intended?” to “Do you often stay online longer than planned?”). Reliability checks during the pilot yielded Cronbach’s α > 0.80 for both IAT and RPWB scales, consistent with prior validations.
3. Survey Administration:
   • An The survey was distributed via an SGA email blast containing the Google Forms link, supplemented by direct sharing through SMS, WhatsApp, and personal emails to interested students. Data collection spanned three weeks (November 2024), with reminders sent every three days to boost participation amidst academic schedules.
4. Data Collection Timeline:
   • Data collection occurred during the Fall 2024 semester, aligning with the academic calendar to capture typical student internet use patterns. The survey remained open for three weeks to provide ample time for student participation.

Data Analysis Techniques

Data analysis included descriptive statistics (means, percentages) and inferential statistics (Pearson’s r, regression, t-tests/ANOVA) performed using SPSS, with a significance level of p < 0.05.

1. Descriptive Statistics:
   • Frequencies and percentages were computed for demographic variables.
   • Means and standard deviations were computed for the total PWB score and each subscale to describe overall and domain-specific well-being (Figure 2).
2. Inferential Statistics:
   • Pearson’s Correlation Analysis: Conducted separately for each PWB dimension against Internet Addiction Test (IAT) scores to assess domain-specific relationships (e.g., IA vs. autonomy, IA vs. environmental mastery).
   • Multiple Regression Analysis: Each PWB dimension was modeled as a dependent variable, with IA scores as the predictor, to evaluate its unique impact on each domain. The total PWB score was also regressed on IA to assess overall predictive power.
   • T-tests/ANOVA: Subgroup differences (e.g., gender) were tested for both total PWB and individual dimensions.
3. Statistical Tools:
   • Data was analyzed using SPSS (Statistical Package for the Social Sciences)  v27 for accurate statistical computation.
   • Significance Level: A p-value of < 0.05 was considered statistically significant.

Results

This section presents the findings from the survey conducted among 100 students at the American University of Nigeria (AUN). Data analysis includes descriptive statistics, inferential tests, and hypothesis testing to evaluate the relationship between internet addiction and psychological well-being.

Descriptive Statistics

Demographic Characteristics

Table 1 summarizes key demographic data of the respondents.

Table 1

Variable	Frequency (n)	Percentage (%)
Gender
Male	55	55%
Female	45	45%
Age Range
18-20 years	40	40%
21-23 years	50	50%
24+ years	10	10%
Academic Year
Freshman	20	20%
Sophomore	30	30%
Junior	25	25%
Senior	25	25%

Internet Addiction Levels

Based on Young’s¹⁰ Internet Addiction Test (IAT), scores were classified into three categories. (Table 2)

Table 2

IAT Score Range	Classification	Frequency (n)	Percentage (%)
20-49	Average Internet Use	45	45%
50-79	Moderate Internet Addiction	40	40%
80-100	Severe Internet Addiction	15	15%

Figure 1

The majority of students (45%) had average internet use, while 40% exhibited moderate internet addiction, and 15% showed severe internet addiction. (Figure 1)

Psychological Well-being Scores

Table 3 summarizes scores for the six dimensions of psychological well-being.

Table 3

PWB Dimension	Mean Score (SD)	Classification
Autonomy	4.2 (0.9)	Moderate to High
Environmental Mastery	3.8 (1.1)	Moderate
Personal Growth	4.5 (0.8)	High
Positive Relationships	3.6 (1.0)	Moderate
Purpose in Life	4.3 (0.7)	High
Self-Acceptance	3.9 (0.9)	Moderate

Figure 2

Students scored relatively high on personal growth and purpose in life but showed moderate levels of environmental mastery, positive relationships, and self-acceptance. (Figure 2)

Inferential Statistics

Correlation Analysis

Pearson’s correlation analysis revealed significant negative correlations between internet addiction and psychological well-being dimensions. (Table 4)

Table 4

PWB Dimension	r-value	p-value	Interpretation
Autonomy	-0.48	0.001	Significant Negative
Environmental Mastery	-0.52	0.000	Significant Negative
Personal Growth	-0.34	0.012	Moderate Negative
Positive Relationships	-0.41	0.004	Significant Negative
Purpose in Life	-0.37	0.009	Moderate Negative
Self-Acceptance	-0.49	0.001	Significant Negative

The results indicate that internet addiction negatively impacts all six dimensions of psychological well-being, with environmental mastery and self-acceptance showing the strongest correlations.

Regression Analysis

A multiple regression analysis was conducted to determine whether internet addiction predicts psychological well-being dimensions. The regression model was statistically significant (F(6, 93) = 7.85, p < 0.001), with an R² of 0.45, indicating that internet addiction accounts for 45% of the variance in psychological well-being. (Table 5)

Table 5

Predictor Variable	B (Unstandardized Coefficient)	Beta (Standardized Coefficient)	t-value	p-value
Internet Addiction	-0.75	-0.62	-6.45	0.000

This result supports the hypothesis that internet addiction is a significant predictor of lower psychological well-being.

Subgroup Analysis

An independent samples t-test showed gender differences:

• Male students: Higher internet addiction scores (M = 60.3, SD = 12.1)
• Female students: Lower internet addiction scores (M = 55.7, SD = 11.4)

The gender difference was statistically significant (t(98) = 2.15, p = 0.034), indicating that male students are more likely to exhibit internet addiction than female students.

Discussion and Conclusion

This section interprets the research findings, connects them to prior studies, and outlines the implications of internet addiction on psychological well-being among students at the American University of Nigeria (AUN). It also highlights limitations, recommendations for future research, and conclusions drawn from the study.

Interpretation of Findings

The study confirms a significant negative relationship between IA and PWB (H1 supported, r-values in Table 2), with 55% of AUN students showing moderate-to-severe IA (Figure 1). Regression analysis (R² = 0.45) supports H2, indicating IA predicts poorer PWB, notably in environmental mastery and self-acceptance (Table 2). These align with Kuss & Griffiths², who tied heavy internet use to diminished control, and Young¹⁰, who noted social disconnection—patterns evident in AUN’s data (Figure 2). Males’ higher IA scores (t (98) = 2.15, p = 0.034) reflect Tokunaga’s⁹ findings on gender-specific risks, possibly due to gaming tendencies.

Key findings expanded:

1. Prevalence of Internet Addiction:
   • A considerable number of students (55%) showed moderate to severe levels of internet addiction, emphasizing its widespread impact. This prevalence aligns with prior research by Kuss & Griffiths², indicating that university students are particularly vulnerable due to their increased reliance on technology for both academic and social purposes.
2. Psychological Well-being Dimensions Affected:
   • The most affected dimensions were environmental mastery and self-acceptance, indicating that students with high internet addiction struggled with controlling their surroundings and accepting themselves. This result aligns with the findings of Young¹⁰, who emphasized the loss of personal control as a critical consequence of internet addiction.
   • Autonomy, positive relationships, and purpose in life were also negatively affected, though to a lesser extent, indicating that social disconnection and reduced personal fulfillment can result from prolonged internet use.
3. Predictive Impact:
   • Regression analysis confirmed that internet addiction significantly predicts all six dimensions of psychological well-being, accounting for 45% of the variance. This finding is consistent with studies like those by Park et al.⁷, which found that high internet use leads to increased stress, depression, and diminished life satisfaction.
4. Gender Differences:
   • Male students reported significantly higher levels of internet addiction compared to females. This finding supports prior research by Tokunaga⁹, which noted that males are more likely to engage in online gaming and other addictive internet behaviors, potentially leading to increased vulnerability.

Implications of the Study

The findings have several practical implications for AUN administrators, counselors, and policymakers:

1. University Policies:
   • AUN could introduce internet usage guidelines, emphasizing balanced internet habits. This might include restrictions on non-academic internet use during study hours or campus-wide initiatives promoting digital well-being.
2. Counseling and Support Services:
   • Establishing internet addiction awareness campaigns and mental health support services can help students manage internet use. AUN’s counseling center could offer workshops on time management and coping strategies.
3. Curricular Integration:
   • Integrating modules on digital literacy and responsible technology use into the academic curriculum could foster healthier internet use among students.
4. Parental and Peer Involvement:
   • Collaborative programs involving parents, academic advisors, and peer groups could further strengthen efforts to mitigate internet addiction's negative effects.

Limitations of the Study

While the findings provide valuable insights, certain limitations should be acknowledged:

1. Sample Size and Scope:
   • The study was limited to 100 students from a single university, which may limit generalizability. Future research should consider a larger, more diverse sample from multiple universities in Nigeria.
2. Self-Reported Data:
   • The reliance on self-reported data may introduce biases such as social desirability or underreporting of internet addiction. Incorporating behavioral tracking in future research could enhance accuracy.
3. Cross-Sectional Design:
   • The cross-sectional nature of the study captures a single time point, limiting the ability to establish long-term cause-effect relationships. A longitudinal study design could address this limitation.
4. Measurement Tools:
   • While validated instruments like Young’s¹⁰ IAT and Ryff’s⁸ PWB scale were used, cultural adaptations may be necessary for a more context-specific assessment.

Recommendations for Future Research

To understand the complex interplay between internet usage and psychological well-being in students, research should explore longitudinal trends, psychopathology (e.g., depression), chronic stress, burnout, competitive anxiety, and negative coping strategies (e.g., avoidance via internet). Specifically, longitudinal studies are crucial, tracking students' internet usage and psychological well-being over multiple semesters to capture evolving trends and the potential impact of these factors over time.

Further recommendations include:

1. Comparative Studies:
   • Compare internet addiction and psychological well-being among students from different universities, regions, and socio-economic backgrounds to explore broader contextual differences.
2. Intervention Programs:
   • Evaluate the effectiveness of intervention programs such as digital detox workshops, online behavior counseling, and mindfulness training for reducing internet addiction.
3. Qualitative Research:
   • Conduct in-depth interviews or focus group discussions to gain a deeper understanding of students' lived experiences with internet use and mental health challenges.
4. Behavioral Analytics:
   • Utilize advanced analytics and artificial intelligence to monitor actual internet usage patterns while ensuring data privacy and ethical compliance.

Conclusion

The study establishes that internet addiction significantly negatively impacts the psychological well-being of students at the American University of Nigeria. It highlights that students with high levels of internet addiction struggle with personal control, social relationships, and emotional stability. These findings underscore the urgent need for proactive measures by university administrators, mental health professionals, and policymakers to promote balanced internet usage and support students' mental health.

By fostering an academic environment that promotes digital literacy, responsible internet use, and psychological support, universities can create a healthier, more productive educational experience for their students. Future research should explore broader contexts, alternative methodologies, and intervention strategies to better address this pressing issue.

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