Resilience and Demographics as Predictors of Internet Addiction among Polytechnic Library Users in South-South, Nigeria

Resilience and Demographics as Predictors of Internet Addiction among Polytechnic Library Users in South-South, Nigeria

¹Godwin Oberhiri-Orumah, ²Esharenana E. Adomi (Prof.)

¹Federal Polytechnic library, Ekowe, Bayelsa State, Nigeria

²Department of Library and Information Science, Delta State University Abraka, Nigeria

DOI: https://dx.doi.org/10.47772/IJRISS.2024.8110008

Received: 08 August 2024; Accepted: 22 August 2024; Published: 27 November 2024

ABSTRACT

This study investigated resilience and demographics as predictors of internet addiction among polytechnic library users in South-South, Nigeria. The study adopted the correlational research design. The population for the study was 3,302 library users from which a sample size of 412 library users in five federal polytechnics using the multi-stage sampling technique was selected. The instrument used for data collection was the questionnaire. The results show that the extent of Internet addiction among polytechnic library users in South-South Nigeria is moderate. The study also found that the level of resilience among polytechnic library users in South-South Nigeria is to a very great extent. It also emerged that the relationship between resilience and Internet addiction among polytechnic library users in South-South Nigeria is strong. The study also found that the relationship between demographics and Internet addiction among polytechnic library users in South-South Nigeria is weak. The study also showed that resilience significantly predicts internet addiction among polytechnic library users. Based on the findings from the study, it was recommended that polytechnic management and library administrators in collaboration with the guidance and counselling unit should organise an awareness campaign for students on the consequences of internet addiction and develop initiatives and policies that promote a healthier internet use among student populations.

Keywords: Internet, Internet addiction, Library users, Resilience, Polytechnic students, Nigeria.

INTRODUCTION

Internet use has evolved into an inseparable routine of human life, and it has revolutionized the world with its infinite possibilities. Internet addiction can be defined as spending too much time on the Internet, accompanied by psychological overdependence on its use (Hsieh, 2019). Tertiary institution students are especially susceptible to developing a dependence on the Internet, more than most other segments of society. This was reported by Kandell, (2020) who identified numerous factors such as availability of time; ease of use; the psychological and developmental characteristics of young adulthood; limited or no parental supervision; an expectation of Internet/computer use covertly if not, as some courses are Internet-dependent, from assignments and projects to link with peers and mentors; the Internet offering a way of escape from exam anxiety. In general, Kuss (2013) reported that the main reason why youths are at particular risk of internet addiction is that they spend most of their time on online gaming and social applications like online social networking such as Twitter, Facebook, and telegrams. Campbell, (2021) described addiction as excessive thoughts about and desire to perform a behaviour, excessive time spent to plan and engage in the behaviour, and possibly recover from its effects (e.g. from hangovers), and less time spent on other activities. In general, at some point, negative consequences tend to ensue due to engaging in addictive behaviour (e.g.) physical discomfort, social disapproval, financial loss, or decreased self-esteem. Continuing to engage in addictive behaviour after suffering numerous negative consequences often has been a criterion of dependence on addictive behaviour (Goodman, 2021). Tiamiya et al. (2024) refer to internet addiction as excessive or compulsive use of the internet, usually incorporating social networking, gaming, and online shopping.

A person suffering from a substance use disorder is unable to concentrate on anything other than using these substances, even when they are aware of their other obligations. This is a result of the brain’s constant search for the chemical due to its dependence. Behaviour changes are also a characteristic of addiction. A person who regularly uses drugs or alcohol is likely to show signs of behavioural changes, including adjustments to their habits and personality. They might have lost interest in past activities they used to do with friends or family. Furthermore, growing tolerance to drugs which can be caused by a variety of drugs, including cocaine, opiates, and benzodiazepines is another factor for drug addiction. Withdrawal symptoms which is the last factor start when a person with an addiction and dependence could find it impossible to stop using the substance. This could be apparent when headaches, difficulty sleeping, pain in the muscles and bones, or other physical signs of illness appear.

At present, there are many uncertainties regarding the conceptualization of Internet addiction (IA) as a disorder, including Internet gaming disorder. However, most scholars describe IA as an impulse control disorder characterized by excessive or poorly controlled preoccupations, urges or behaviours regarding computer use and Internet access that lead to impairment or distress (Wang et al., 2019). The clinical application of IA may be supported by prior research that has demonstrated associations with a number of psychological impairments, such as low levels of well-being, self-esteem, and self-control (Mei et al., 2016); sleep problems; and depression, anxiety, stress, and loneliness (Ostovar et al., 2016). The technological revolution has increased Internet adoption worldwide, contributing to escalating Internet traffic per connection, as people move to higher-bandwidth broadband connections and the availability of several Internet applications (Pontes et al., 2015).

Resilience, defined by Bloesch et al. (2015), involves the dynamic response of individuals or systems to changes and disturbances while maintaining function, structure, and feedback mechanisms. Shanava and Gergauli (2022) associate resilience with the ability to adapt and confront stress or trauma, emphasizing its multidimensional nature influenced by context, age, gender, culture, and life experiences. As a personal trait, resilience plays a vital role in preserving psychological well-being and self-efficacy amid adversity (Venkitaraman & Kosuru, 2023). Resilient individuals effectively manage stress, mitigating negative outcomes like anxiety and depression (Li, 2010). VanBreda (2018) introduces four patterns associated with resilience: dispositional, relational, situational, and philosophical, each emphasizing different factors contributing to resilience. Resilience, therefore, distinguishes individuals who can cope effectively with challenges from those who struggle, endure prolonged negative effects, and find it challenging to recover from setbacks (Boring, 2018; Hatipoğlu, 2018).

Certain demographic factors are also associated with IA, such as higher school grades, poor academic performance higher family income, and lower level of parental attachment (Tsitsika, 2016). Some researchers have reported that lower social class and younger generations belonging to the lower income group are more susceptible to becoming addicted to the Internet (Kotrotsiou et al, 2016). Demographic characteristics, including socioeconomic status, gender, age, and income, thus, play a vital role in internet addiction. The studies on the impact of gender are mixed. Some researchers found that males are more susceptible to Internet addiction. For example, Bisen and Deshpande (2020) found that male students use smartphones more frequently than females. Some researchers reported that males and females exhibit different behavioural patterns concerning internet addiction. Hence, it is more likely that there would be gender differences in the outcomes such as stress, and burnout (Liang et al., 2016). It is also interesting to note that males use the Internet for pleasure rather than for searching information when compared to females. How they spend time on the Internet results in internet addiction differs according to gender. A recent study showed that some online users were becoming addicted to the Internet in the same way that others became addicted to drugs, alcohol, or gambling, which resulted in academic failure, reduced work performance, and even marital discord and separation (Zenebe, et al. 2021). Various types of online activities, such as online gaming, social networking, online gambling, online shopping, virtual sex, and information overload, are related to internet addiction (Wu et al. 2015).

The Internet could play a significant role in the lives of polytechnic students as its use can complement the resources and services of the library and enhance their learning and academic performance when used with restraint, especially for academic purposes. Despite the benefits, students can derive from the Internet when used in moderation, studies have shown that most library users of polytechnics indulge in the use of the Internet on their smartphones while in the library reading, which is similar to most addictive disorders (Wu et al. 2015; Fabio & Stracuzzi, 2022). The fact that smartphones are portable makes the risks more insidious and pervasive. Although Internet addiction is reported to be associated with various personal, social and psychological factors in the literature, this study has been conducted to investigate the influence of resilience and demographics on Internet addiction among Polytechnic library users in South-South, Nigeria. To achieve this, the following research questions are formulated to guide the study:

Research Questions

RQ1. What is the extent of internet addiction among the polytechnic library users in South-South, Nigeria?
RQ2. What is the extent of resilience among the polytechnic library users in South-South, Nigeria?
RQ3. What is the relationship between resilience and internet addiction among polytechnic library users in South-South, Nigeria?
RQ4. What is the joint relationship between demographics (gender, age, level of study) and Internet addiction among polytechnic library users in South-South, Nigeria?

Hypothesis

Resilience will not significantly predict internet addiction among polytechnic library users in South-South, Nigeria.

LITERATURE REVIEW

Internet Addiction among Polytechnic Library Users

Internet addiction usually refers to persistent and recurrent maladaptive behaviour, causing distress and significant functional impairments (Kumar & Mondal, 2018). Internet addiction is concerned with overuse or excessive use of the Internet, and some researchers call it Internet addiction disorder (Feng et al., 2019). It is also named “problematic Internet use”, “pathological Internet use”, or “compulsive Internet use” (Kumar & Mondal, 2018). The healthy way of using it is to accomplish a planned objective within a reasonable period with no behavioural or intellectual distress. Some individuals succeed in limiting their Internet use, whereas others cannot regulate themselves (Diomidous, et al., 2016). Misuse of the Internet has become a health concern worldwide and is growing swiftly and steadily. The field of Internet addiction (internet addiction) has experienced significant debates over the years. At present, there are many uncertainties regarding the conceptualization of internet addiction as a disorder, including Internet gaming disorder (Wang, et al. 2019). However, most scholars describe internet addiction as an impulse control disorder characterized by excessive or poorly controlled preoccupations, urges, or behaviours regarding computer use and Internet access that lead to impairment or distress (Tao, et al., 2021). Excessive use of the Internet also affects the academic achievements of students. Students are more to the addicted Internet and are more involved in it than their studies, and hence they have poor academic performance (Frangos, et al., 2022).

Zamzuri, et al (2021) studied the Internet Addiction among Youth in one of the public universities in Semarang, Indonesia. The purpose of the study is to determine the level of Internet addiction among students in Indonesia. The study adopted a descriptive survey method. A questionnaire was used to collect data from 164 youths using a random sampling technique. The results show that social influence and coordination are seen as factors that determine the influence of Internet addiction among the youth. The study concluded that awareness among the public, especially parents and educators, has to be created with regard to the risks of Internet addiction and strategies to limit Internet use. Olawade, et al (2020) studied Internet Addiction among University Students during the Covid-19 Lockdown: Case Study of Institutions in Nigeria. The results revealed that the majority of the students were categorized as normal internet users (45%), 42% as mildly addicted, and 13% as moderately addicted. None of the students were severely addicted.

With the availability and mobility of new media, Internet addiction has emerged as a potential problem in young people which refers to excessive computer use that interferes with their daily life. The Internet is used to facilitate research and to seek information for interpersonal communication and business transactions. On the other hand, it can be used by some to indulge in pornography, excessive gaming, chatting for long hours, and even gambling (Kumar & Mondal, 2018). Mathew and Krishnan (2020) reported that internet addiction can reduce the young generation’s productivity and cause cognitive dysfunction, poor academic performance, and physical, mental, and behavioural disturbances. Mathew and Krishnan added that internet addiction can reduce the young generation’s productivity and cause cognitive dysfunction, poor academic performance, and physical, mental, and behavioural disturbances. Oo, Soe, & Oo, (2021) conducted a study on Internet usage and Internet addiction among medical students in universities in Myanmar and found that more than 60 per cent of the students used to engage in several activities excessively such as emailing (17%), gaming (50%), watching movies (90%), social media (93%), chatting (78%), and studies (63%). Bello et al. (2024) conducted a study to determine the prevalence of internet addiction among undergraduate health sciences students at Usmanu Danfodiyo University in Sokoto, Nigeria. This was a cross-sectional study, using a multistage sampling technique. The Young Internet Addiction Test was used to obtain the data, which was analysed using the Statistical Package for Social Sciences (SPSS) version 23.0 for Windows. A total of 294 students were interviewed, with a mean age and standard deviation of 24±2.9 years, and a male-to-female ratio of 2.3:1. Approximately, 42% of the students had mild internet addiction, and 13% had moderate internet addiction. A significant association was found between the severity of internet addiction and time spent on the internet per day.

Internet addiction can reduce the young generation’s productivity and cause cognitive dysfunction, poor academic performance, and physical, mental, and behavioural disturbances (Mathew & Krishnan, 2020). Hassan, et al (2020) Internet addiction among young adults in Bangladesh revealed that the overall prevalence of Internet addiction was 27.1%. The study also found that the Internet addiction rate was 28.6% in the subgroup 19–24 years and 23.5% among 25–35 years old. Therefore, it is imperative to estimate internet addiction’s magnitude among polytechnic students to obtain accurate data to develop different strategies and programmes to intervene in this problem. Balasubramanian and Parayitam (2023) studied the consequences of Internet addiction among university students in India and found that time spent on the Internet every day is positively related to internet addiction and internet addiction is positively related to time spent on networking, video streaming, short video apps, educational apps, chat apps, online shopping apps, money involved apps, etc. The study by Raveendran, et al (2021) on Internet addiction among students of the medical college in North Kerala revealed that the prevalence of Internet addiction was 59%.113 (49.8%) students were average online users (mild addiction), 19 (8.4%) students were experiencing occasional and frequent problems (moderate addiction) and 2 (0.8%) severely addicted students most of the study population initiated Internet use between the ages of 16 -18 years, 89 (39%).

Resilience among the Polytechnic Library Users

Resilience has been suggested as a protective factor against various psychopathologies, including Internet addiction (Kim, et al, 2014). Kirby and Fraser (2020) define resilience as the achievement of positive outcomes despite risk. VanBreda (2018) defined resilience as “the personal qualities that enable one to thrive in the face of adversity. The definition describes a resilient person as being able to achieve positive outcomes despite challenges. When individuals encounter a stressful situation, they can give up, recover but to a diminished capacity, recover to baseline, or recover and thrive beyond the baseline to cope with the stress (Steinhardt & Dolbier, 2008). That is, a resilient individual can deal with stress and successfully reduce negative psychological outcomes, such as anxiety and depression and the effects of vulnerability can be buffered by high levels of resilience (Kim, et al. 2014).

Robertson et al. (2018) found that resilience predicted Internet addiction negatively significantly. Zhou, et al. (2021) found a negative correlation between Internet addiction and resilience. Resilience decreases negative psychological effects that are commonly accompanied by Internet addiction (Choi, et al 2014). Studies have reported a clear distinction concerning resilience-related factors between genders (Frydenberg& Lewis, 2020). In general, girls tend to show higher scores in resilience along with constructive coping strategies, such as seeking social support and problem-solving, whereas boys showed higher scores in avoidant coping (Choi, et al, 2014). Moreover, only in girls, resilience had a negative association with the possibility of Internet addiction. Resilience is important because the students can face, overcome, and be strengthened amid Internet addiction. Resilience has a direct influence on Internet addiction, and improving student’s resilience can be an effective way to reduce Internet addiction behaviour.

Resilience contributes to an easy temperament that promotes positive responses from others, self-esteem, self-efficacy, independence, self-reliance and environmental opportunities (Kirby & Fraser, 2020). Block (2021) posits that as a result of this adaptive flexibility, individuals with higher levels of resilience are more likely to experience positive affect, have higher levels of self-confidence, and display better psychological adjustment than individuals with low levels of resilience. A positive outcome for students with high resilience levels is likely to also exhibit academic resilience and sustain high levels of achievement, motivation and performance despite stressful conditions that place them at risk of doing poorly in school. Conversely, students who lack resilience tend to have a hard time adjusting to stressors, do not enjoy class, participate less in class, and have lower self-esteem than students with high resilience (Block, 2021). Lee et al (2016) only in girls, resilience had a negative association with the possibility of Internet addiction and moderated the relationship between depression and Internet addiction. Resilience has a direct influence on Internet addiction, and improving an individual’s resilience can be an effective way to reduce Internet addiction behaviour (Li, et al. 2022). Previous studies have suggested that Internet addicts have special personality traits. Resilience has been found to influence Internet addiction indirectly, impacting the pathology through stress, perceived class climate, and alienation (Li, et al. 2022). Taken together, these studies show that resilience, peer relationships, depression, and Internet addiction are related variables. When facing stressful situations, resilient individuals may rely on self-efficacy and emotional regulation strategy, resulting in a more positive emotional state.

Zhou, et al. (2021) studied the relationship between resilience and Internet addiction and found that peer relationship was a mediator for the relationship between resilience and Internet addiction. Peer relationships were responsible for almost 50.0 per cent of the resilience related to Internet addiction, which indicated that resilience moderates Internet addiction severity mainly through peer relationships. The study also found that depression mediated the relationship between resilience and Internet addiction with an effect size of 15.60 percent. The study recommended that parents and teachers of young adults should help foster their Internet resilience and other related abilities in two key ways to buffer them against Internet addiction. The study by Robertson et al. (2018) on ‘Resilience a protective factor of Internet addiction’ found that overall, the higher the level of the participants’ resilience, the lower the level of their Internet addiction. The study concluded that using the Internet and playing online games are both used as coping mechanisms for stress, but not Facebook. That resilience could help cope with online game addiction but does not have a mechanism to cope with Facebook addiction perhaps because users use online games and Facebook for different purposes and needs. Savulich et al., (2023) identified key characteristics associated with resilience:(a) positive adaptation in response to adversity, (b) facing challenges head-on rather than despairing or distracting, (c) reliance on psychological mechanisms for coping, including cognitive and emotional coping abilities, (d) the corpus callosum, especially the anterior body, as a key neural substrate of resilience., (e) extraversion, (f) openness to experience, (g) self-efficacy, and agreeability, (h) face fear or being able to leave one’s comfort zone, (i) feeling that one has a mission or meaning in life, and (j) being open to challenges. After reviewing these lists of qualities of resilient individuals, it appears most of these qualities are centred on social competence.

According to Dipali et al. (2023), resilience and internet addiction have been studied in relation to undergraduate college students. The relationship between academic resilience and internet addiction among undergraduate students was explored, and it was found that there was no significant relationship between the two factors. In another study, Touloupis et al. (2022) investigated internet addiction among psychology students, as well as the role of resilience and perceived economic hardship in the manifestation of the phenomenon. The study involved 252 students (233 women, 19 men) from Aristotle University of Thessaloniki. They completed a self-report questionnaire, which included a short version of a scale on resilience (The Connor-Davidson Resilience Scale – CD-RISC), a scale on perceived economic hardship (Economic Hardship Questionnaire), and a scale on Internet Addiction (Internet Addiction Test). The results showed that students of Psychology, regardless of their academic year, make above-average/normal and excessive/addictive internet use displaying indicative behaviours (e.g., uncontrollable internet use, neglect of social life). Jacob, (2020) investigated the difference in the locus of control and resilience with respect to different levels of internet addiction as well as their impact on internet addiction among emerging adults. It assessed Internet Addiction levels, investigated the association between internet addiction, locus of control, and resilience, and analysed gender differences. Internet addiction test by Young, Locus of Control (LOC-Scale) Scale. The study found a significant relationship between internet addiction, locus of control, and resilience. There was a significant gender difference in Internet Addiction, indicating that gender plays a role in the development and severity of Internet Addiction. The study also revealed a significant difference in Resilience among different levels of Internet Addiction, suggesting that individuals with higher levels of Internet Addiction may have lower levels of Resilience.

Terwase and Ibaishwa (2014), examined resilience, shyness, and loneliness as predictors of internet addiction among university undergraduate students in Benue State, Nigeria. Resilience negatively predicted internet addiction among university undergraduate students in Benue State. Shyness and loneliness positively predicted internet addiction among university undergraduate students in Benue State. The emotional aspect of loneliness negatively predicted internet addiction, while the social aspect of loneliness positively predicted internet addiction. The multiple regression analysis showed that resilience, shyness, loneliness, emotional loneliness, and social loneliness jointly had a significant influence on internet addiction among undergraduate students. From the literature reviewed, resilience has been considered a protective factor against Internet addiction. Tas (2019) studied the association between depression, anxiety, stress, social support, resilience, and internet addiction. One of the purposes of the study is to test whether social support and resilience have a significant effect on predicting Internet addiction in university students. A relational screening model was used in this study. The study was conducted on 347 students studying in a private university and a state university in Turkey. The sample was chosen randomly from different departments during the 2018‐2019 Academic Year. The study found that a significant negative association was found between Internet addiction and social support and resilience. A significant positive association was found between social support and resilience. The study concluded that when the negative correlation between social support and resilience is taken into consideration, it can be said that increased social support can prevent Internet addiction and also increase individuals’ resilience. Increased resilience will be effective in decreasing internet addiction. The study therefore suggests that health personnel working on Internet addiction can include psycho‐education programs to decrease individuals’ depression and anxiety levels and to increase their resilience and social support levels.

Demographics and Internet Addiction among Library Users

In a recently conducted study on a sample of 3380 first-year undergraduate students in China, the researchers reported that males showed higher scores of internet addiction when compared to females (Shan et al., 2021). Similar gender differences were noted among university students in the Slovak Republic (Rigelsky, et al. 2021) as the study found that males tend to spend more time on the Internet for pleasure and search for information, whereas females prefer using the Internet for social networking.

In a study by Ozkan and Ozkan (2023), demographic factors have been found to be associated with internet addiction. Male gender, adolescent age group, separation of parents, high income, and being a student are identified as risk factors for gaming addiction. In Brazil, Terroso et al. (2022) investigated associations among Internet addiction, demographic, and cognitive variables, such as impulsivity, aggression, and depressive and/or anxiety symptoms. In this study, 1,485 young adults (67.9% women) were assessed using four psychological instruments. It was found that 19.1% of the participants presented moderate or severe internet addiction, with men having a higher prevalence (45.0%).

METHODOLOGY

The correlational research design was adopted to execute this study. The descriptive correlational research design research aims to provide static pictures of phenomena and also establish the relationship between different variables (Ivy, 2022). The correlational research design does not involve the manipulation of variables. This design is considered appropriate because it enabled the researcher to explore the relationship among boredom, resilience, sensation seeking and demographics as predictors of internet addiction among polytechnic library users in South-South, Nigeria. It enables the prediction of the changes in the dependent variables based on the value of the independent variables (Obasuyi, 2020). The population of this study is 3,302 registered library users of the federal polytechnics in South-South, Nigeria. These Polytechnics include Federal Polytechnic Ukana, Akwa-Ibom State, Federal Polytechnic Ekowe, Bayelsa State, Federal Polytechnic, Ugep, Cross River State, Auchi Polytechnic, Auchi, Edo State, and Federal Polytechnic of Oil and Gas, Bonny, Rivers State.

A breakdown of the population by institution is in Table 1.

Table 1: Population of the study

Source: Registered Library Users 2021/2022 in five Polytechnics.

Sample size

The sample size for this study is 412 library users in federal polytechnics in South-south, Nigeria. To select the sample size for the study, the researcher adopted the multi-stage sampling technique. In the first stage, the cluster sampling technique was used to select respondents from the different polytechnics who are registered library users. Subsequently, the proportional sampling technique was utilized to allocate a sample size for each stratum following its proportion to the total population. This approach ensures the representativeness of the sample across the entire population. Following this, the simple random technique was applied to randomly select samples from each stratum.

The research instrument used for data collection in this study was a questionnaire. The adapted questionnaire was based on a scholarly validated instrument: The Resilience Scale (RS), developed by Connor-Davidson (2003), and Internet Addiction Scale (IAS), developed by Young (1995). However, their items were modified to reflect the present study. A five-point ranking scale ranging from “very great extent”, “Great extent”, “Moderate extent”, “Small extent” and “No extent” was adopted in this study. The questionnaire was divided into two parts. Part one was on demographics data, made up of four items which comprised, the name of the institution, gender, age and level of study. The demographics were used to answer research questions four and test hypotheses two. Part two of the questionnaire is made up of two sections. Section A, which was on the extent of boredom among polytechnic library users in South-South Nigeria was used to answer research questions one and test hypotheses one. Section B, which was on the extent of Internet Addiction among Polytechnic Library Users in South-South Nigeria, was used to answer research question two. The researcher, assisted by a research assistant in each of the polytechnic libraries being studied, distributed the questionnaire to the respondents. The administered questionnaires were collected from the respondents on the same day upon completion.

Data analysis

The data obtained from the administration of the questionnaire were analysed using frequency and percentage for the demographics section of the questionnaire. Mean and standard deviation were used to analyse data generated from research questions one and two. While, Pearson’s Product Moment Correlation Coefficient (PPMCC) was used to analyse data in research questions three to establish the relationship between two variables. Hypotheses 1 was tested with Linear Regression.

RESULTS

A total of 412 copies of the questionnaire were distributed and 410 (99%) copies were returned. The response rate of 99% is considered adequate for the study. Of the total 410 participants, 136 (33.2%) were from Auchi Polytechnic, 78 (19%) from Federal Polytechnic, Ugep, 76 (18.5%) from Federal Polytechnic, Ukana, 67 (16.3%) from Federal Polytechnic, Ekowe, and 53 (12.9%) from Federal Polytechnic of Oil and Gas, Bonny. It can be concluded that the majority of participants in the study are from Auchi Polytechnic. The majority of polytechnic library users are at the HND Two level, with 116 (28.3%) students, followed by 103 (25.1%) at the HND One level, 96 (23.4%) at the ND Two level, and 95 (23.2%) at the ND One level. This suggests a concentration of library usage among students in their HND two levels. There are 194 (47.3%) females and 216 (52.7%) males, indicating that the majority of library users are male. The distribution of library users by age is as follows: 140 (34.1%) fall within the 21-23 age bracket, 102 (24.9%) within 24-26, 85 (20.7%) within 18-20, 59 (14.4%) aged 27 and above, and 24 (5.9%) between 15-17 years old.

Therefore, it can be concluded that the majority of library users belong to the 21-23 age group.

Research Question 1: What is the extent of Internet addiction among polytechnic library users?

The data in Table 2: are used to answer this question.

Table 2: The Extent of Internet Addiction among the Polytechnic Library Users

Table 2: reveals a grand mean of 3.09 (Std. = 0.93), surpassing the criterion mean of 3.00. Consequently, it shows that the extent of Internet addiction among polytechnic library users in South-South Nigeria is moderate.

Research Question 2: What is the extent of resilience among the polytechnic library users?

The data in Table 3 are used to answer this question.

Table 3: The Extent of Resilience among Library Users

Table 3 indicates a grand mean of 4.02 (Std. = 0.54), exceeding the criterion mean of 3.00. This shows that the level of resilience among polytechnic library users in South-South Nigeria is to a very great extent.

Research Question 3: What is the relationship between resilience and Internet addiction among polytechnic library users?

The data in Table 4 are used to answer this question.

Table 4: Relationship between Resilience and Internet Addiction

Based on the data from Table 4, the Pearson correlation coefficient (r = .261) indicates a positive correlation. With a significant value (Sig.2-tailed) of .000 (p < 0.05), it shows that the relationship between resilience and Internet addiction among polytechnic library users in South-South Nigeria is strong.

Research Question 4: What is the joint relationship between demographics (gender, age and level of study) and Internet addiction among polytechnic library users in South-South Nigeria?

The data in Table 5 are used to answer this question.

Table 5: Joint Relationship between Demographics (gender, age and level of study) and Internet Addiction

Based on the data from Table 5, the Pearson correlation coefficient (r = -.035) indicates a negative correlation. With a significant value (Sig.2-tailed) of .484 (p > 0.05), it shows that the relationship between demographics and Internet addiction among polytechnic library users in South-South Nigeria is weak.

Testing of the Hypotheses

Hypothesis 1: Resilience will not significantly predict Internet addiction among polytechnic library users.

The data in Tables 6 – 8 provide the answer to this hypothesis

Table 6: Model Summary Table of Relationship between Resilience and Internet Addiction

Table 7: ANOVA Summary Table of Relationship between Resilience and Internet Addiction

Table 8: Coefficient Summary Table of Relationship between Resilience and Internet Addiction

The tables 6 – 8 provide the R (.261) and R-squared (.068) values. The R-value (R = .261) indicates a weak positive correlation between resilience and internet addiction. The R-squared value (R-squared = .068) indicates that approximately 7% of the variance in internet addiction can be explained by resilience. The ANOVA table suggests that the regression model predicts the dependent variable, internet addiction, significantly well (F(1,409) = 29.719, p < 0.000, which is less than 0.05), indicating that the overall regression model is statistically significant and provides a good fit for the data. Furthermore, the Coefficients table provides important information for predicting internet addiction from resilience. The coefficient (β = .000) indicates that resilience contributes statistically significantly to the model, supporting its role in predicting internet addiction. Therefore, the null hypothesis is rejected, suggesting that resilience significantly predicts internet addiction among polytechnic library users.

DISCUSSION OF FINDINGS

Extent of Internet Addiction among Polytechnic Library Users

Finding from the study in table 2 revealed that the extent of Internet addiction among polytechnic library users in the South-South Nigeria is moderate. It was revealed that more than half of the respondents do agreed that they stay online longer than they intended, prefer the excitement of the internet to intimacy with your classmates, people around them complain about the amount of time they spend online, check their email before something else that they need to do, find themselves anticipating when they will go online again, lose sleep due to late-night log-ins, people around them complain about the amount of time they spend online, fear that life without the internet would be boring, empty, or joyless, and feel preoccupied with the internet when offline, or fantasize about being online. The above finding from the study corroborated the finding of Mathew and Krishnan (2020) who reported that internet addiction can reduce the young generation’s productivity and cause cognitive dysfunction, poor academic performance, and physical, mental, and behavioral disturbances.

In a contrary vein, the finding of this study contracted Mariavinifa, Govindarajan, and Felix (2021) study on the prevalence and associated factors of Internet addiction among college students using smartphones in Tamil Nadu and found that out of the five hundred students, 38.8 % are normal users, 37% are mild addicts, 21% are moderate addicts, 3.2% are severe addicts. The author therefore reported that the overall prevalence of Internet addiction was 61.2% and that the degree of Internet addiction was significantly associated with age, time spent daily on the Internet, and using the Internet for social media, online communications, and playing online games. Mariavinifa, et al. (2021) concluded that the prevalence of Internet addiction is high among university students.

Extent of Resilience among the Polytechnic Library Users

The finding of the study from Table 3 revealed that the extent of resilience among library users in South-South Nigeria is very great. It was observed that most of the respondents agreed that they are able to adapt to change, believe that sometimes fate or God can help, deal with whatever comes their way, put in their best effort no matter what, believed that when things look hopeless, they don’t give up, and that they work to attain their goals. This finding agrees with Robertson, Yan, and Rapoza (2018) who found that, overall, the higher the level of the participants’ resilience, the lower the level of their Internet addiction. A positive outcome for students with high resilience levels is likely to also exhibit academic resilience and sustain high levels of achievement, motivation and performance despite stressful conditions that place them at risk of doing poorly in school. Conversely, students who lack resilience tend to have a hard time adjusting to stress or, do not enjoy class, participate less in class, and have lower self-esteem than students with high resilience (Block, 2021). The finding of this study on the other hand contradicted the finding of Tas, (2019) studied the association between depression, anxiety, stress, social support, resilience, and Internet addiction and found that there is a significant negative association between Internet addiction and social support and resilience. A significant positive association was found between social support and resilience.

Relationship between resilience and Internet addiction among polytechnic library users

The finding of the study from Table 4 revealed that there exists strong relationship between resilience and internet addiction among polytechnic library users in South –South Nigeria. This indicated that resilience has a direct influence on Internet addiction, and improving an individual’s resilience can be an effective way to reduce Internet addiction. This finding is in conformity with Li, et al. (2022) which reported that resilience has a direct influence on internet addiction. Li, et al. (2022) suggested that Internet addicts have special personality traits. Resilience has been found to influence Internet addiction indirectly, impacting the pathology through stress, perceived class climate, and alienation. In the same vein, the findings also corroborated the findings of Zhou, et al. (2021) study which showed that peer relationship was a mediator for the relationship between resilience and Internet addiction. Peer relationships were responsible for almost 50.0 percent of the resilience related to Internet addiction, which indicated that resilience moderates Internet addiction severity mainly through peer relationships.

The finding of the study further supported the findings of Robertson et al. (2018) on ‘Resilience a protective factor of Internet addiction’ which indicated that people who have higher resilience tend to have lower levels of Internet addiction and that the more time spent on online gaming and use of social media apps, the higher the addiction levels tend to be. Also, this finding reaffirmed Jacob (2020) findings on the difference in the Locus of Control and Resilience with respect to different levels of Internet Addiction as well as their impact on Internet Addiction among emerging adults, and found that there is a significant relationship between Internet Addiction, Locus of Control, and Resilience.

Relationship between demographics (gender, age and level of study) and Internet addiction among polytechnic library users

The findings of the study in Table 5 indicated that there is weak relationship between demographics and Internet addiction among polytechnic library users in South-South Nigeria. The finding of the study supported Shan et al. (2021) finding using a sample of 3380 first-year undergraduate students in China and reported that males showed higher scores of internet addiction when compared to females. Similar gender differences were noted among university students in the Slovak Republic (Rigelsky et al., 2021) as the study found that males tend to spend more time on the Internet for pleasure and search for information, whereas, females prefer using the Internet for social networking. The finding of the study also confirmed Sulaiman et al. (2016) who explored the role of demographics (e.g., age, gender, and occupational position) in relation to Internet addiction and demonstrated that no significant differences in terms of Internet addiction between the genders. However, significant differences were found in Internet addiction depending on age and occupational position. Ozkan and Ozkan (2023) in their study also revealed that demographic factors have association with internet addiction. Similarly, in a study conducted in Brazil by Terroso et al. (2022) on the associations among Internet addiction, demographic, and cognitive variables, such as impulsivity, aggression, and depressive and/or anxiety symptoms showed that 19.1% of the participants presented moderate or severe internet addiction, with men having a higher prevalence (45.0%). Khubchandani et al. (2021) also discovered that internet addiction was more prevalent among males, young adults, and those with higher education levels.

Prediction between Resilience and Internet addiction among polytechnic library users in South-South, Nigeria

The finding of the study in hypothesis 1, Tables 6-8 showed that resilience significantly predicts internet addiction among polytechnic library users. It indicated a weak positive association between resilience and internet addiction. With the coefficient (β = .000), it shows that resilience contributes statistically significant to the model, supporting its role in predicting internet addiction among polytechnic library users in South-South, Nigeria. This finding is consistent with Tas, (2019) in one hand revealed that there is a significant positive association between social support and resilience. The finding of the study on the other hand disagrees with Tas, (2019) which indicated that there is a significant negative association between Internet addiction and social support and resilience. The result of the study also disagrees with Robertson, Yan, and Rapoza (2018) who found that, the higher the level of the participants’ resilience, the lower the level of their Internet addiction. Robertson, Yan and Rapoza (2018) found that resilience predicts internet addiction significantly.

CONCLUSION

Various variables in academic institutions determine the extent to which library users utilize the Internet. However, resilience and demographics are some of the different variables that determine the extent of internet usage and addiction among students (library users). The findings of this study underscore the intricate interplay between resilience demographics, and internet addiction among polytechnic library users. By investigating these predictors, there is a deeper understanding of the complex psychological factors driving excessive internet addiction. The results clearly show resilience as a great predictor towards internet addiction attracting library users towards compulsive internet use. From the findings of the study, it can be concluded that resilience apart from demographics of library users predict internet addiction among library users in federal polytechnics in South-South, Nigeria. Thus, resilience significantly have strong relationship and predict internet addiction among the polytechnic library users but demographics has a weak relationship with internet addiction and hence, do not significantly predict internet addiction among the federal polytechnic library users in South-South, Nigeria.

RECOMMENDATIONS

Based on the findings of the study, the following recommendations were made.

1. To decrease the level of resilience that contributes to internet addiction, school counsellors and polytechnic management should promote and support students in cultivating effective coping mechanisms to handle stress, boredom, and other factors that may result in excessive internet usage.” Possible strategies may involve practices such as mindfulness meditation, indulging in physical exercise, or pursuing hobbies and occupations that offer a sense of satisfaction and tranquillity.
2. Library administrators and polytechnic administration should educate and encourage library users to actively work towards minimising internet addiction and enhancing their general well-being by setting reasonable and achievable goals.
3. Polytechnic management and library administrators can encourage library customers to engage in a variety of activities and hobbies that offer various forms of stimulation and excitement. This can help prevent the development of resilience and reduce the risk of internet addiction. This could include activities that engage them mentally, physically, socially, and creatively.
4. There should be a collaborative approach, educational institutions, parents and non-governmental organizations, to raise awareness about the risks of internet addiction among student populations.

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