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Resilience as a predictor of internet addictive behaviours: a study among Ghanaian and Saudi samples using structural equation modelling approach

BMC Psychology volume 13, Article number: 77 (2025) Cite this article

Abstract

This study aimed to examine the relationship between resilience and internet addictive behaviours, focusing on cross-cultural contexts involving tertiary education students in Ghana and Saudi Arabia. Using a cross-sectional survey design, data were collected from 738 students across selected universities in both countries. Structural equation modeling (SEM) techniques were employed to analyse the data. The findings indicated that most respondents exhibited low resilience levels alongside a high prevalence of internet addictive behaviours. A significant positive relationship was identified between resilience levels and various dimensions of internet addiction, as well as the overall composite of internet addictive behaviours. Interestingly, while low resilience levels were found to increase the risk of internet addiction, higher resilience levels also appeared to heighten susceptibility to addictive behaviours. These results suggest the need for targeted interventions to address internet addiction. Programs should focus on enhancing resilience through resilience-building initiatives, promoting digital well-being, and integrating mental health support services. These approaches can help mitigate the risks associated with internet addiction while fostering healthier coping mechanisms in students across diverse cultural settings.

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Introduction

Internet addiction (IA), characterized by excessive and uncontrolled internet use, has emerged as a critical mental health concern, particularly among youth and young adults [77]. IA has been associated with a range of adverse outcomes, including academic underperformance, social isolation, and mental health disorders [7, 32, 60]. Addiction is well documented in the literature and involves several facets [5, 28]. Among the many addictive behaviors that are making waves in scholarly research is internet addiction [13, 39, 55]. Internet addiction is also termed internet addiction disorder. In terms of definition, an individual is considered to have an internet addiction when they experience an uncontrollable urge to spend excessive amounts of time online, sacrificing other crucial aspects of their life, such as personal relationships, professional obligations, or well-being [4, 18]. As a compulsive behavior, internet addiction manifests as a dependency on internet usage, leading to a progressive increase in the time spent online to achieve the same level of satisfaction or gratification [54, 47]. There are various types of IA, such as cybersex addiction, net compulsions, cyber-relational addiction, compulsive information seeking, and computer/gaming addiction [19, 25, 72].

Scholars, citing the American Psychological Association (APA), have indicated that internet addiction can manifest through several distinct characteristics. First, the user needs to progressively increase the amount of time spent online to derive the same sense of satisfaction. Second, if users are unable to access the internet, they experience unpleasant withdrawal symptoms such as anxiety, moodiness, and compulsive fantasizing about the internet, which are alleviated by resuming internet usage [2, 70]. Moreover, the user may turn to the internet as a coping mechanism for negative emotions such as guilt, anxiety, or depression. Additionally, a significant portion of the user’s time is dedicated to internet-related activities, such as researching internet vendors or reading internet-related literature. Furthermore, the user neglects other crucial aspects of life, including relationships, work, education, and leisure pursuits, in favor of spending time online. Finally, the user is willing to sacrifice relationships, employment, or other important facets of life to prioritize internet usage [39, 78].

According to Anderson et al. [3], the issue of internet addiction disorder holds particular significance for young people and young adults. Individuals within the age ranges of 12–19 years (adolescents) and 20–29 years (emerging adults) tend to engage with the internet more extensively than individuals in other age groups. Consequently, this heightened exposure and usage render them more susceptible to the risks associated with excessive and uncontrolled internet utilization.

The causes of internet addiction are elusive, and no singular factor is known to be a categorical cause. However, the adverse childhood experiences (ACE) theoretical model indicates that the inherent attributes of the internet itself contribute to the development of addictive behaviors. The ACE model identifies anonymity, convenience, and escapism as the key factors that facilitate internet addiction. Anonymity enables individuals to conceal their true identities and personal information online, granting them a sense of freedom to engage in activities without constraints. This anonymity also makes it challenging to regulate online behavior, potentially leading to excessive and uncontrolled internet usage. Convenience, while initially a beneficial aspect of the internet’s development, can also foster addiction and dependence, as individuals can perform various tasks, such as shopping or entertainment, without leaving their homes. Last, the virtual environment provided by the internet offers users a means of escaping and overcoming real-world difficulties or frustrations, enticing them to withdraw from reality and immerse themselves in the online realm [29, 73, 74].

The cognitive-behavioral model equally asserts that internet addiction is caused by proximal and distal factors [17]. Specific to the distal cause, the rapid advancement of internet technology serves as the initial stressor, potentially fostering maladaptive thought patterns. Situational cues are identified as moderators of this relationship. Additionally, certain psychological factors, such as depression, social anxiety, and substance dependence, may exacerbate maladaptive cognitions, leading to an increased propensity for pathological internet use behaviors. Specific to the proximal cause, the model proposes an interactive effect between maladaptive cognitions and the behavioral manifestations of pathological internet use. In essence, exposure to the internet can potentially trigger maladaptive thought patterns, and preexisting vulnerabilities can reinforce this relationship [6, 16]. In summary, the model suggests that as an individual’s level of adaptation to undesirable behaviors increases, he or she becomes more likely to exhibit pathological internet use, indicating a greater susceptibility to internet addiction. Internet addiction has several consequences for affected people, but no single treatment is adequate for its remediation.

Scholars have suggested clinical and psychological approaches for treating internet addiction [31, 33, 46, 67, 71, 75]. In addition to these procedures being helpful in controlling internet addiction, resilience is equally implicated in influencing the process of internet addiction. Resilience is well known to impede the development of problem behaviors in the human race. The extant literature has shown that resilience helps people deal with difficult situations in their lives [14, 26]. The concept of resilience encompasses a multifaceted and intricate set of characteristics, encompassing various aspects such as spatial, temporal, dynamic, and capacity-related dimensions, as well as potential outcomes [22]. By definition, resilience is generally defined as the ability of an individual to adapt to adversity, stress, or significant sources of stress such as family and relationship problems, health challenges, or workplace and financial difficulties [41, 53]. Empirically, resilience has been studied in various contexts, often emphasizing the capacity of individuals to maintain or regain mental health despite facing adversity [61]. As internet addiction is also a problem behavior, resilience has the potential to thwart its occurrence and vice versa [11, 23, 30]. As an internal source, resilience is defined as the qualities possessed by an individual in dealing with adversities and growing within adversities [45]. For instance, resilience exerts a direct influence on the propensity for internet addiction, and enhancing an individual’s resilience can serve as an effective strategy to mitigate problematic internet usage behaviors [8, 56].

Several studies have reported diverse findings on the relationship between resilience and internet addictive behaviors. For example, a systematic review of 19 studies involving 93,859 respondents revealed a statistically significant inverse correlation between resilience and internet addiction (r = -.27 (95% CI [−0.32, −0.22]), suggesting a negative relationship between the variables under investigation [24]. Similarly, the research conducted by Robertson et al. [48] demonstrated an inverse relationship between participants’ resilience levels and their propensity for internet addiction. Their findings indicated that individuals with higher resilience tended to exhibit lower degrees of problematic internet usage. Another study by Wu et al. [68] reinforced this finding, indicating that resilience can predict lower levels of internet addiction in adolescents. The study highlighted the importance of resilience in buffering against stressors that may lead to problematic internet use. Wu et al. emphasized that interventions aimed at enhancing resilience could be effective in preventing or reducing internet addiction [69]. Similarly, Latifian et al. [36] examined the role of resilience in predicting mental health outcomes, including internet addiction, among high school students in Tehran. Their findings confirmed that resilience is positively associated with better mental health and lower levels of internet addiction. The study emphasized that interventions aimed at improving academic resilience could significantly reduce the risk of internet addiction in adolescents, supporting the notion that resilience acts as a protective factor against various forms of maladaptive behaviours. Nam et al. [45] investigated the role of resilience in internet addiction among adolescents, finding that resilience acts as a buffer against the effects of vulnerability factors such as anxiety, depression, and impulsivity. The study demonstrated that higher levels of resilience are associated with lower levels of internet addiction. The researchers employed a moderated mediation model and found that resilience moderated the indirect effects of behavioural inhibition/activation systems (BIS/BAS) on internet addiction through clinical variables like depression and anxiety. Notably, the protective effects of resilience were more pronounced in female adolescents, indicating sex differences in how resilience influences internet addiction [45].

Furthermore, Jin et al. [27] carried out a cross-sectional study involving 326 students, employing self-report surveys to assess internet addiction, levels of depression, resilience, and sociodemographic information. The study revealed a positive association between internet addiction and depression, suggesting that individuals with higher levels of depression were more likely to exhibit problematic internet usage patterns. Conversely, the study revealed a negative correlation between internet addiction and resilience, indicating that individuals with higher resilience tended to display lower levels of internet addiction. Moreover, research conducted by Zhou et al. [78] revealed a significant relationship between resilience and internet addiction, with resilience emerging as a predictive factor for problematic internet usage. Their findings suggest that enhancing certain resilience-related attributes, such as fortitude, emotional regulation, and problem-solving abilities, could serve as an effective strategy to mitigate the propensity for addictive internet behaviors. Kutuk’s [34] research revealed a significant interplay among internet addiction, anxiety, and resilience. The study’s findings revealed that these variables exhibited noteworthy correlations with one another. Notably, resilience has emerged as a critical mediating factor in the relationship between internet addiction and anxiety levels, playing a pivotal role in shaping the dynamics between these two constructs [34].

Taken together, the studies revealed different findings, which could be attributed to several reasons. For example, the studies cited involved diverse samples, ranging from general populations to specific groups such as university students. The variations in sample characteristics, such as age, cultural background, and educational levels, may have contributed to the differing results. The relationship between resilience and IA could manifest differently across different populations. Resilience is a multidimensional construct, and different studies have operationalized and measured it in varying ways. Some studies have focused on specific aspects of resilience, such as emotional regulation or problem-solving abilities, while others have adopted a more comprehensive approach. The use of different resilience measures could lead to divergent findings.

Furthermore, the studies employed different research methodologies, including systematic reviews, cross-sectional surveys, and structural equation modeling approaches. The choice of research design and analytical technique can influence the nature and strength of the relationships observed between variables [35, 42]. These studies were conducted in different cultural contexts, so cultural norms, societal expectations, and environmental factors may play a role in shaping the relationship between resilience and internet addictive behaviors [63]. Resilience and its impact on internet usage patterns could vary across cultures [37, 63,64,65]. Some studies, such as Kutuk [34], have identified resilience as a mediating factor between internet addiction and anxiety levels. Other potential mediators or moderators, such as depression, social support, or coping strategies, may have been explored in different studies, leading to variations in the observed relationships [9, 49].

Even with these contrasting research outputs on IA, the situation remains fragmented, with a lack of consensus on the underlying predictors and mechanisms driving this phenomenon. Resilience, broadly defined as the ability to adapt positively to adversity or stress [58], has been identified as a potential protective factor against various psychological disorders and maladaptive behaviors [57, 62]. However, its role in mitigating internet addiction, particularly in diverse cultural contexts, remains underexplored. The importance of examining resilience within the context of IA stems from its dual nature: while resilience can serve as a protective factor, evidence also suggests that it may heighten susceptibility to certain maladaptive behaviors, depending on situational and cultural factors [10, 24]. Previous studies have demonstrated mixed findings, with some indicating a negative association between resilience and IA [24, 48], while others report no significant relationship [50, 76]. These inconsistencies highlight the need for further investigation into the mechanisms through which resilience influences IA and how these mechanisms may vary across cultural settings.

Theoretical models of resilience in relation to internet addiction

Several theoretical propositions underpin the essence of this study. For instance, resilience theory emphasizes individuals’ capacity to adapt positively to adversity, stress, or challenges [40]. It serves as a valuable framework for understanding how psychological resilience operates as a protective factor against maladaptive behaviours, including internet addiction [43]. Resilience theory explains how internal and external resources, such as self-efficacy and social support, enable individuals to cope effectively with stressors. This theory underpins the study’s exploration of resilience as a potential buffer against internet addiction, particularly in culturally distinct populations. For example, research suggests that resilience mitigates the impact of psychological stressors, such as anxiety and depression, on problematic internet use [45, 69].

Likewise, the cognitive-behavioural model [17] plays an important role in addictive behaviours. The the cognitive-behavioural model posits that internet addiction arises from maladaptive cognitions and behaviours, which are influenced by both proximal (e.g., thought patterns) and distal (e.g., environmental triggers) factors. This model highlights the role of resilience as a moderating factor in the development of pathological internet use. For instance, resilience may counteract maladaptive thought patterns, such as escapism or compulsive internet use, which are central to this model. Studies have demonstrated that higher resilience levels are associated with reduced susceptibility to maladaptive cognitions, suggesting that resilience may indirectly lower the risk of internet addiction [24, 56].

Furthermore, the Adverse Childhood Experiences (ACE) model contributes adequately to the essence of this study. For example, the Adverse Childhood Experiences (ACE) model explains how early life adversities, such as trauma or neglect, can increase vulnerability to addictive behaviours, including internet addiction [20, 21]. This model identifies key factors like anonymity, escapism, and convenience, which the internet offers, as triggers for addictive tendencies. Resilience, in this context, serves as a critical mediator, helping individuals overcome the negative effects of adverse experiences. Research has shown that individuals with higher resilience are better equipped to cope with the emotional and psychological consequences of ACEs, thereby reducing their likelihood of engaging in addictive behaviours [12, 30].

With respect to culture, resilience and internet addictive behaviours, the cross-cultural psychology highlights how cultural norms, values, and social structures influence psychological constructs like resilience and behaviours such as internet addiction [51]. This framework is essential for understanding the differences in how resilience operates across diverse cultural contexts, such as Ghana and Saudi Arabia. For instance, while Ghanaian youth may rely on peer networks and community support, Saudi youth might be influenced by family structures and societal expectations. Cultural variations in resilience and internet addiction are critical for developing hypotheses that account for socio-cultural nuances [64, 77]. This is supported by the stress-diathesis model, which posits that individual vulnerabilities interact with environmental stressors to produce maladaptive outcomes, such as internet addiction [44]. Resilience acts as a protective factor, mitigating the impact of these stressors. This theoretical lens supports the hypothesis that resilience reduces the risk of internet addiction by buffering against stress-inducing factors like academic pressures or social isolation, which are common among tertiary students [78, 34].

The current study

Internet addiction, characterized by excessive and uncontrolled use of the internet, has emerged as a significant mental health concern, particularly among young people and young adults [77]. It has been associated with various negative outcomes, including poor academic performance, social isolation, and mental health issues [7, 32, 60]. While numerous studies have explored the relationship between internet addiction and different psychological factors [78], the role of resilience as a potential predictor has received relatively less attention, particularly in cross-cultural contexts.

Resilience, defined as the ability to adapt positively and cope effectively with adversity or stress [58], has been found to play a protective role against various psychological disorders and maladaptive behaviors [57, 62]. However, the relationship between resilience and internet addictive behaviors remains unclear, with some studies suggesting a negative association [24], while others reporting no significant relationship [50, 76]. Furthermore, the mechanisms through which resilience influences internet addictive behaviors and the potential moderating effects of cultural factors remain unexplored [10, 38]. This study, therefore, aimed to investigate the role of resilience as a predictor of internet addictive behaviors among Ghanaian and Saudi individuals utilizing a structural equation modeling approach. The selection of Ghanaian and Saudi samples for this study reflects their distinct cultural settings, offering an opportunity to examine the interplay between resilience and internet addiction (IA) in diverse socio-cultural contexts. Ghanaian youth may face challenges such as socio-economic pressures, peer influence, and limited technological supervision, while Saudi youth might encounter academic stress, societal restrictions, and social isolation. These contextual differences shape how resilience manifests and operates as a protective or risk factor against IA. Research has shown that cultural attitudes towards mental health, societal expectations, and access to resources significantly influence resilience and its effectiveness in mitigating IA. Furthermore, while high internet usage is prevalent in both countries, the underlying risk factors and motivations differ, highlighting the need for culturally informed approaches to understanding resilience in relation to IA.

This study aims to fill critical gaps in the literature by exploring resilience as a predictor of IA in these culturally distinct populations, addressing the limited research on its cross-cultural dimensions. By using a structural equation modeling (SEM) approach, the study seeks to uncover mechanisms through which resilience interacts with IA and to identify cultural variations in this relationship. Integrating Ghanaian and Saudi samples provides a nuanced understanding of how resilience functions across diverse cultural landscapes. The findings can inform tailored interventions, such as resilience-building programs and digital well-being initiatives, aimed at reducing IA in culturally sensitive ways. This cross-cultural perspective not only advances theoretical understanding but also offers practical solutions for mitigating IA among tertiary students in different socio-cultural settings. Drawing on the empirical and theoretical perspectives, the study explored how resilience predicts internet addiction. To achieve the study’s aim, the following questions and hypotheses were tested:

  1. 1.

    What are the prevalence rates of internet addiction among tertiary students in Ghana and Saudi Arabia?

  2. 2.

    What are the levels of resilience among tertiary students in Ghana and Saudi Arabia?

  3. 3.

    H1: Students’ resilience (composite) will predict their addictive internet behaviors (dimensions).

  4. 4.

    H1: Students’ resilience (composite) will predict their internet addictive behaviors (composite).

The hypotheses were derived from the following conceptual model in Fig. 1:

Fig. 1
figure 1

Hypothesized conceptual model

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According to this model, it is assumed that a composite score of resilience could predict dimensions and the composite of internet addiction.

Methods and participant selection

This study employed a cross-sectional survey design, with data collected between (September 2023 to March, 2024). A convenience sampling method was utilized to recruit participants, primarily due to the accessibility of university students across Ghana and Saudi Arabia. This approach allowed for efficient recruitment while ensuring a diverse sample within the constraints of time and resources. The sample comprised 738 participants, including 258 (male = 138, female = 120) Saudi university students and 480 (male = 252, female = 228) Ghanaian university students. Participants were recruited from various faculties and departments within selected universities in both countries, ensuring representation across academic disciplines and contexts.

To calculate the sample size, the study used G*Power analysis with a confidence level of 95% and a margin of error of 5%, ensuring statistical reliability and power for structural equation modeling (SEM). Recruitment was conducted online through platforms like Qualtrics and Google Forms to maximize accessibility and convenience for participants. Measures to reduce common method bias included guaranteeing participant anonymity, counterbalancing the order of survey items, and utilizing different response scales to minimize potential response biases. Demographic variables, including age, gender, academic year, and field of study, were collected to ensure the sample’s diversity. Participants ranged in age from 18 to 38 years, representing a typical university demographic. Gender distribution was balanced, enabling the exploration of gender-based differences in resilience and internet addictive behaviors.

Measures

The study used the Resilience Scale (RS) [66] and the Internet Addiction Test (IAT) [52] (Appendix A) to measure resilience and internet addiction, respectively. The RS, a 25-item scale rated on a 7-point Likert scale, provided a composite score of resilience, with higher scores indicating greater resilience. The IAT, a 20-item 4-point Likert scale, assessed internet addiction across four dimensions: lack of control (5 items, α = 0.789), social withdrawal and emotional conflict (7 items, α = 0.819), time management issues (5 items, α = 0.901), and responsibility (3 items, α = 0.868). The composite Cronbach’s alpha for the IAT was 0.918, reflecting strong internal consistency. To accommodate the linguistic diversity of the samples, the RS and IAT were translated into Arabic for the Saudi participants and maintained in English for the Ghanaian participants. A rigorous translation and back-translation process was employed to ensure semantic equivalence and preserve item meaning across languages. The psychometric properties of the translated scales were assessed, confirming reliability and validity within both cultural contexts. The Cronbach’s alpha for the RS was 0.871, indicating high reliability in both samples. To mitigate cultural bias, the translation process included expert reviews and pilot testing in both countries. This ensured the instruments were culturally sensitive and relevant for both populations, enhancing the reliability and generalizability of the findings.

To ensure that the scales meet scientific requirement, a confirmatory factor analysis was performed. In this, the evaluation of the Internet Addiction Scale’s model fit indices demonstrates acceptable levels of goodness-of-fit, indicating that the scale is well-suited for measuring the construct. The Standardized Root Mean Square Residual (SRMR) is reported at 0.017, well within the acceptable range of ≤ 0.09, signifying minimal residual discrepancies between observed and predicted values. The Root Mean Square Error of Approximation (RMSEA) stands at 0.062, which falls within the acceptable range of 0.05 to 0.10, indicating a reasonable approximation of the model to the population. The Goodness-of-Fit Index (GFI) is 0.94, exceeding the threshold of ≥ 0.90, suggesting a strong model fit. Similarly, the Adjusted Goodness-of-Fit Index (AGFI) is 0.86, surpassing the acceptable benchmark of ≥ 0.80, and the Comparative Fit Index (CFI) is 0.91, also above the recommended threshold of ≥ 0.80, further validating the scale’s suitability for assessing internet addiction. These indices collectively confirm the robustness of the scale’s structure and measurement properties.

Again, the evaluation of the Resilience Scale’s fit indices suggests that the model demonstrates an acceptable fit to the data, suitable for measuring resilience. The Root Mean Square Residual (RMR) is reported at 0.064, falling well within the acceptable threshold of ≤ 0.09, indicating minimal residual discrepancies. The Root Mean Square Error of Approximation (RMSEA) is 0.072, which lies within the acceptable range of 0.05 to 0.10, showing a reasonable approximation to the population model. The Goodness-of-Fit Index (GFI) is 0.90, meeting the minimum criterion of ≥ 0.90, signifying a good overall model fit. The Adjusted Goodness-of-Fit Index (AGFI) is 0.87, exceeding the acceptable threshold of ≥ 0.80, further supporting the model’s adequacy. Lastly, the Comparative Fit Index (CFI) is 0.89, close to the recommended threshold of ≥ 0.80, indicating a satisfactory comparative fit. Collectively, these indices validate the Resilience Scale’s structure and its appropriateness for assessing resilience.

Statistical analysis

The data were analyzed using structural equation modeling (SEM) in IBM AMOS. SEM was chosen due to its capacity to evaluate complex relationships between latent and observed variables, providing a robust framework for hypothesis testing. The analysis focused on two primary objectives: [1] assessing the predictive role of resilience on the dimensions of internet addiction and [2] examining the overall predictive relationship between resilience and the composite of internet addiction. Prior to analysis, several measures were implemented to ensure data quality and compliance with SEM assumptions. With regards to multicollinearity, all the variables were mean-centered following recommendations in the literature [15, 59]. In terms of common method bias, the Harman’s single-factor test was conducted to confirm that a single factor did not account for the majority of variance, ensuring the validity of the measures. The model fitness (Appendix B) was evaluated using standard indices, including the Chi-square/df ratio, comparative fit index (CFI), GFI, AGFI, RMR, and root mean square error of approximation (RMSEA). The p-value threshold for statistical significance was set at < 0.05. Missing data were minimal (< 5%) and handled using expectation-maximization (EM) methods to avoid bias in the results. Descriptive statistics were computed to summarize participant demographics and variable distributions.

Results

Research question one

What are the prevalence rates of internet addiction among tertiary students in Ghana and Saudi Arabia?

The study examined the prevalence of internet addictive behaviors among a sample of 738 participants from Ghana and Saudi Arabia, categorizing them into three groups: average users, overusers, and internet addicts. Table 1 presents the results.

Table 1 Prevalence of internet addiction
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The results in Table 1 indicated that the majority (73.1%) of participants fell into the overuser category, suggesting a widespread trend of potentially excessive internet usage among tertiary education students. This finding underscores the growing challenge of managing internet usage, particularly in environments where digital technologies are integral to academic and social life. While 13.8% of participants were identified as average users, maintaining moderate and healthy internet habits, 13.1% of the sample met the criteria for internet addiction. These individuals exhibited compulsive or addictive internet use patterns, which could lead to adverse consequences such as academic underperformance, social isolation, and mental health challenges. A comparative analysis of the findings across the two cultural contexts revealed nuanced differences. In Ghana, internet overuse was often linked to peer pressure, limited supervision, and the increasing integration of digital tools in educational settings. Conversely, in Saudi Arabia, internet addiction was more frequently associated with academic stress, societal restrictions, and social isolation, which may drive individuals to rely on the internet as a coping mechanism. These variations highlight the influence of cultural and environmental factors on internet usage behaviors and suggest the need for context-specific interventions.

Research question two

What is the level of resilience among Ghanaian and Saudi Arabian students?

Table 2 Level of resilience among students
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Table 2 presents the resilience levels of 738 tertiary education students from Ghana and Saudi Arabia, categorized into low, moderate, and high resilience groups. The findings indicate that the largest proportion of students (35.6%, n = 263) demonstrated low resilience, suggesting significant challenges in coping with adversity and stress. Another 35.0% (n = 258) exhibited moderate resilience, reflecting an average ability to adapt to stressors. The smallest group (29.4%, n = 217) displayed high resilience, characterized by strong adaptive capacities and effective coping strategies. A comparative analysis of resilience levels between the Ghanaian and Saudi Arabian samples highlights notable differences influenced by cultural, environmental, and societal factors. Ghanaian students were more likely to exhibit low resilience, potentially reflecting socio-economic challenges, limited access to mental health resources, and a lack of systemic support in educational institutions. Conversely, Saudi students, while facing strict societal norms and academic stress, showed a relatively higher proportion of moderate to high resilience levels, possibly due to stronger familial support systems and culturally embedded coping mechanisms. These findings underscore the need to address context-specific barriers to resilience. In Ghana, interventions could focus on strengthening institutional and community support systems, fostering emotional regulation, and providing access to resilience-building programs. In Saudi Arabia, targeted strategies to alleviate academic stress and promote adaptive coping mechanisms could further enhance resilience among tertiary students.

  • H1: Students’ resilience (composite) will predict their addictive internet behaviors (dimensions).

According to the hypothesis, it was expected that students’ resilience abilities, represented by a composite measure, would predict the occurrence of internet addictive behaviours across various dimensions. Table 3 presents the results.

Table 3 Composite of resilience for predicting IAT dimensions
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The results of the structural equation modeling (SEM) analysis, as summarized in Table 3, provide critical insights into the relationship between resilience and various dimensions of internet addictive behaviours. Four key dimensions of internet addiction—lack of control, social withdrawal and emotional conflict, concealing problematic behaviour, and time management issues—were analysed in relation to the resilience composite variable.

The analysis revealed a statistically significant positive relationship between resilience and lack of control in internet use (β = 0.124, SE = 0.047, C.R. = 2.740, p = .006). This finding suggests that students with higher resilience levels are modestly more likely to exhibit difficulties in regulating their internet usage. While resilience is typically associated with adaptive behaviours, this result indicates a potential paradox where high resilience may occasionally contribute to persistence in maladaptive habits, such as excessive internet use.

A stronger positive relationship was observed between resilience and social withdrawal and emotional conflict (β = 0.174, SE = 0.057, C.R. = 3.860, p < .001). This indicates that students with higher resilience levels are more likely to experience social withdrawal and emotional challenges related to their internet use. This finding suggests that resilience, while beneficial in many contexts, may amplify emotional and social complexities for students who rely on the internet as a coping mechanism.

The relationship between resilience and concealing problematic internet behaviours was the most pronounced among the four dimensions (β = 0.292, SE = 0.051, C.R. = 6.652, p < .001). This strong positive association implies that students with higher resilience levels are significantly more likely to hide their problematic internet use and associated responsibilities. This behaviour could stem from the ability to manage external appearances effectively, a trait often linked with resilience, while simultaneously struggling to address underlying issues.

Finally, resilience was positively associated with time management issues related to internet use (β = 0.130, SE = 0.029, C.R. = 2.880, p = .004). This suggests that students with higher resilience levels are more likely to experience challenges in balancing their time effectively, potentially due to their tendency to persevere with internet-related activities despite their impact on daily responsibilities.

The results highlight a complex and somewhat counterintuitive relationship between resilience and internet addiction. While resilience is generally associated with positive outcomes, this study suggests that higher resilience levels may also predispose students to certain dimensions of internet addictive behaviours. This could be due to the persistence and coping mechanisms inherent in resilience, which may inadvertently reinforce maladaptive internet use patterns.

These findings underscore the need for nuanced interventions that address both the strengths and vulnerabilities associated with resilience. Programs aimed at fostering resilience should incorporate strategies to ensure that these traits are channelled toward adaptive behaviours rather than reinforcing problematic internet use. For example, incorporating time management training and emotional regulation techniques into resilience-building programs could mitigate the observed tendencies toward social withdrawal, time mismanagement, and concealment of internet-related issues.

In terms of policy and practice, educational institutions should consider integrating digital literacy and well-being initiatives alongside resilience training. These programs could help students develop healthier internet usage habits, enhance their emotional awareness, and balance their academic and personal responsibilities more effectively. Moreover, this study’s findings contribute to the broader understanding of how psychological traits, such as resilience, interact with behavioural tendencies, emphasizing the importance of tailoring interventions to address these intricate relationships. The results are buttressed by the structural model in Fig. 2.

Fig. 2
figure 2

Composite resilience predicting the IAT dimensions

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  • H1: Students’ resilience (composite) will predict their internet addictive behaviors (composite)

The aim of the hypothesis was that students’ resilience (composite) would predict their internet addictive behaviors (composite). The results of the structural equation modeling (SEM) analysis presented in Table 4 provide significant support for this relationship.

Table 4 Composite of resilience for predicting the IAT
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The SEM results presented in Table 4 reveal a strong positive relationship between the resilience composite variable and the Internet Addiction Test (IAT) composite variable. The standardized estimate for this relationship was β = 0.794 (SE = 0.156, CR = 5.103, p < .001), indicating that higher levels of resilience are significantly associated with an increased likelihood of exhibiting internet addictive behaviours.

This finding suggests a complex dynamic in which resilience, typically regarded as a protective factor, may paradoxically contribute to higher internet addictive tendencies in certain contexts. This strong positive association could reflect how individuals with higher resilience persistently engage with the internet, potentially as a mechanism for coping with stressors or meeting social and academic demands. For example, resilient students may demonstrate a capacity to manage adversity but might channel this persistence into maladaptive internet use, reinforcing addictive behaviours.

These results highlight the need to consider the dual nature of resilience in the context of internet addiction. While resilience can enable individuals to adapt to challenges and overcome adversity, its interaction with digital environments may lead to excessive engagement with internet-related activities. This finding underscores the importance of tailoring interventions that leverage the positive aspects of resilience while mitigating its potential contribution to maladaptive internet behaviours.

Practical implications include the development of targeted resilience-building programs that incorporate strategies for healthy internet use. For instance, resilience training should include components such as time management, emotional regulation, and critical reflection on digital habits to prevent the persistence of problematic behaviours. Educational institutions can also adopt digital well-being initiatives that encourage balanced internet usage and integrate mental health support services to address underlying stressors driving internet addiction.

This finding also contributes to the theoretical understanding of resilience as a multidimensional construct. It challenges traditional assumptions that resilience is exclusively protective, demonstrating that its effects can vary depending on the behavioural context and external influences, such as digital environments. Further research is needed to explore these dynamics across diverse cultural settings to refine our understanding of resilience’s role in internet addiction. Figure 3 shows the findings.

Fig. 3
figure 3

Composites of the resilience predictions from the IAT

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Discussion

This study explored the relationship between resilience and internet addictive behaviors (IA) among tertiary education students in Ghana and Saudi Arabia, highlighting both the prevalence of IA and the nuanced role of resilience. The findings revealed low resilience levels among a substantial portion of the sample, suggesting significant vulnerability to stressors and challenges. Low resilience, often linked to difficulties in managing adversity, may predispose students to maladaptive coping mechanisms, including excessive internet use [8, 56]. This relationship was evident across both Ghanaian and Saudi samples, underscoring the importance of addressing resilience within the broader context of IA interventions.

The high prevalence of IA among participants further emphasizes the urgency of mitigating its adverse effects. Internet addiction, characterized by uncontrollable internet use at the expense of other life responsibilities, presents risks to students’ academic performance, social relationships, and psychological well-being [39, 78]. The findings demonstrated that IA manifests across various dimensions, including lack of control, social withdrawal, concealing problematic behaviors, and time management issues. These behaviors resonate with the theoretical foundations provided by the ACE model, which highlights anonymity, convenience, and escapism as key contributors to internet dependency [29], and the cognitive-behavioral model, which identifies maladaptive cognitions and situational cues as reinforcers of pathological internet use [17].

A comparative analysis between Ghanaian and Saudi students revealed nuanced cultural and contextual differences influencing the resilience-IA relationship. In Ghana, low resilience levels were more prevalent, potentially reflecting socio-economic pressures, limited mental health resources, and a lack of structured digital literacy programs. These factors may exacerbate the tendency for internet overuse as a means of coping with life challenges. In contrast, Saudi students exhibited relatively higher resilience levels, yet they also showed a significant association between resilience and IA, driven by academic stress, societal restrictions, and social isolation. The distinct contexts underline the importance of culturally tailored interventions that address the unique drivers of IA in each population. For instance, Ghanaian interventions could focus on improving access to mental health services, fostering community-based support systems, and integrating resilience-building programs with digital literacy education. In Saudi Arabia, strategies might emphasize reducing academic stress, promoting social connectedness, and equipping students with adaptive coping mechanisms to balance internet use with real-world responsibilities. These comparative insights provide a broader understanding of how cultural, societal, and environmental factors shape the resilience-IA dynamic.

Resilience, while generally considered a protective factor against maladaptive behaviors, can in some contexts facilitate internet use as a coping mechanism to manage stress, loneliness, or academic pressure. For instance, students with high resilience may use the internet adaptively for problem-solving, connecting with support networks, or engaging in academic enrichment, inadvertently increasing their time online. Over time, this heightened engagement could transition into habitual or addictive patterns, particularly if alternative coping mechanisms or offline resources are limited. Environmental factors further complicate this relationship. In cultures where internet access is highly valued for education and social interaction, resilient individuals may lean on technology to navigate challenges efficiently. However, if these environments lack sufficient regulation or alternative recreational activities, the boundary between productive and addictive internet use may blur. Additionally, in collectivist societies like Ghana, where community support is integral to resilience, the internet may become a surrogate for social interaction in contexts where physical community engagement is constrained. Conversely, in Saudi Arabia, societal and family pressures may drive resilient individuals to seek refuge online, leveraging digital spaces as a means of autonomy or stress relief.

Again, the observed relationships between resilience and internet addictive behaviors (IA) are shaped significantly by the cultural contexts of Ghana and Saudi Arabia. In Ghana, resilience-building practices often draw heavily from communal and peer networks, reflecting the collectivist orientation of Ghanaian society. This cultural backdrop emphasizes community-based support, which can either mitigate or exacerbate internet addiction depending on the availability and quality of social resources. Conversely, Saudi Arabian cultural practices highlight the influence of family structures and religious values, which often promote resilience through structured guidance and adherence to societal norms. However, these same structures can also contribute to increased stress and reliance on the internet as a coping mechanism in the face of academic and social pressures. Furthermore, societal attitudes toward internet use differ, with Ghanaian students often associating high internet use with social connectivity and educational advancement, whereas Saudi students may use the internet to navigate academic stress and societal restrictions. Recognizing these cultural variations is critical for tailoring interventions to enhance resilience while mitigating IA, ensuring that approaches are contextually relevant and culturally sensitive.

Conclusion

This study sheds light on the relationship between resilience levels and internet addictive behaviors among tertiary education students in Ghana and Saudi Arabia. The findings revealed a trend toward low resilience levels among the majority of respondents, indicating vulnerability among students to various stressors and challenges. This vulnerability is compounded by the high prevalence rate of internet addictive behaviors observed among the student population. The correlation between low resilience and difficulties in managing stress and adversity underscores the need for targeted interventions aimed at enhancing resilience and promoting healthy coping mechanisms among students. However, the study’s findings also highlight the complexity of this issue, as higher levels of resilience were found to be associated with increased susceptibility to various aspects of internet addiction. This suggests that resilience, which is typically considered a positive trait, may also serve as a risk factor for the development or exacerbation of IA.

Recommendations

The study findings reveal the dangers of low resilience in the midst of ever-increasing problems associated with excessive internet usage among students. Again, while resilience is typically considered a protective factor, our findings suggest that under certain conditions, high resilience may be linked to increased internet addiction. Therefore, we recommend the following to be done in institutions of higher education for tertiary students in both Ghana and Saudi Arabia:

  1. 1.

    Universities in both countries should ensure that resilience-building programmes do not only focus on strengthening students’ ability to cope with adversity but also include education on the potential risks of over-relying on certain coping mechanisms, such as excessive internet use. Students should be made aware that resilience involves not only bouncing back from challenges but also making healthy choices in how they manage stress.

  2. 2.

    While resilience can help manage stress, it should be balanced with activities that promote physical and mental well-being, such as exercise, social interactions, and hobbies that do not involve internet use. This approach can help prevent the overuse of the internet as a sole coping mechanism.

  3. 3.

    Educational institutions should implement digital literacy programmes that teach students about the risks associated with excessive internet use, even among those with high resilience. These programs should emphasize the importance of setting boundaries and recognizing the signs of internet addiction.

  4. 4.

    Encourage students to actively monitor their online activities and set limits on their internet usage. Tools and apps that track screen time can be promoted to help students balance their time spent online with offline activities.

  5. 5.

    Universities in both countries should ensure that students have access to counselling services where they can discuss their internet use and resilience levels. Counsellors should be trained to recognize when resilience might be contributing to unhealthy internet behaviours and provide appropriate interventions.

  6. 6.

    It is important for universities to recognise that the cultural context in both Ghana and Saudi Arabia can influence how resilience and internet use are perceived and managed. Such interventions should be culturally sensitive, acknowledging the different societal norms, family dynamics, and educational pressures that might affect students in each country.

Limitations of the study

  1. 1.

    The study utilized a convenience sampling method to recruit participants from specific universities in Ghana and Saudi Arabia. While this approach was effective in accessing a diverse group of tertiary students, it limits the generalizability of the findings to the broader population. The sample may not adequately represent the full spectrum of tertiary education students in both countries, as it excludes individuals from other educational institutions and non-student populations. Future research should consider employing probability sampling techniques (e.g., stratified random sampling) or including participants from a wider range of universities and regions to enhance the representativeness of the findings and provide a more comprehensive understanding of resilience and internet addiction across diverse contexts.

  2. 2.

    Although the study included participants from two culturally distinct contexts, Ghana and Saudi Arabia, it did not fully explore the influence of unmeasured cultural variables. Factors such as societal attitudes towards mental health, community support structures, religious beliefs, and differing levels of technological access may have affected the observed relationships between resilience and internet addiction. These cultural dimensions are critical for understanding how resilience operates and how internet addiction manifests in different environments. Future studies should incorporate qualitative methods or additional cultural measures to better capture these nuances and provide a deeper understanding of the cultural underpinnings of resilience and internet addiction.

  3. 3.

    The study relied on self-report instruments to assess resilience and internet addiction, which, while widely validated, are subject to inherent limitations. Respondents may have been influenced by biases such as social desirability, recall inaccuracies, or misrepresentation of their behaviors. These biases could impact the reliability of the data and the validity of the findings. To mitigate this limitation in future research, multi-method approaches could be employed, such as incorporating objective measures (e.g., internet usage logs), observer reports, or triangulation with qualitative interviews to enhance the accuracy and depth of the data.

  4. 4.

    The study’s exclusive focus on university students may narrow the applicability of the findings to other age groups or educational levels. Resilience and internet addiction dynamics may differ significantly among younger adolescents, working professionals, or other populations. Expanding future research to include diverse demographic groups would enhance the scope of understanding and allow for broader applications of the findings.

Suggestion for further research

The results of the present study, which included data from two different contexts (Ghana and Saudi Arabia), suggest a potentially universal pattern in the relationship between resilience levels and internet addictive behaviours. However, further research from diverse contexts is necessary to substantiate this conclusion.

Data availability

The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to the potential inclusion of sensitive information about individuals or entities. Confidentiality agreements or privacy regulations prevent public disclosure.

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Acknowledgements

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Funding

This work was supported through the Annual Funding track by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [GrantA193].

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  1. King Faisal University, Al-Hofuf, Saudi Arabia

    Mazen Omar Almulla, Abdulaziz Mohammed Alismail & Abdullah Ahmed Almulla

  2. University of Education, Winneba, Ghana

    Inuusah Mahama

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All the authors on this paper contributed their quota to its success. IM conceptualized study, wrote the background, and performed the analysis. MOA collected the data wrote the methodology and implications. AMA interpreted the results and offered the discussions. AAA wrote the implications and structured the references. Together, MOA, AMA, and AAA applied for and received a grant to facilitate the process of the paper.

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Correspondence to Mazen Omar Almulla.

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This research project received ethical clearance from one institutional review board in Ghana. The University Research Ethics Committee at the University of Education, Winneba approved and provided clearance with the reference number UREC-UEW/24/007. The researchers adhered to established guidelines for studies involving human participants. All protocols were designed to protect participants’ rights and welfare. The aforementioned ethics committee carefully reviewed and approved the study methodology, ensuring compliance with ethical standards in educational research. This approval process demonstrates the researchers’ commitment to conducting ethically sound and scientifically valid research.

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Almulla, M.O., Alismail, A.M., Mahama, I. et al. Resilience as a predictor of internet addictive behaviours: a study among Ghanaian and Saudi samples using structural equation modelling approach. BMC Psychol 13, 77 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40359-025-02383-y

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40359-025-02383-y

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BMC Psychology

ISSN: 2050-7283

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