literature review social media addiction

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Aslib Journal of Information Management

ISSN : 2050-3806

Article publication date: 5 September 2023

As an unhealthy dependence on social media platforms, social media addiction (SMA) has become increasingly commonplace in the digital era. The purpose of this paper is to provide a general overview of SMA research and develop a theoretical model that explains how different types of factors contribute to SMA.

Design/methodology/approach

Considering the nascent nature of this research area, this study conducted a systematic review to synthesize the burgeoning literature examining influencing factors of SMA. Based on a comprehensive literature search and screening process, 84 articles were included in the final sample.

Analyses showed that antecedents of SMA can be classified into three conceptual levels: individual, environmental and platform. The authors further proposed a theoretical framework to explain the underlying mechanisms behind the relationships amongst different types of variables.

Originality/value

The contributions of this review are two-fold. First, it used a systematic and rigorous approach to summarize the empirical landscape of SMA research, providing theoretical insights and future research directions in this area. Second, the findings could help social media service providers and health professionals propose relevant intervention strategies to mitigate SMA.

Social media addiction
Influencing factors
Literature review
Theoretical framework
Addiction mechanism
Stimulus-organism-response framework

Acknowledgements

The authors are grateful to the editor and reviewers whose constructive comments have improved the quality of this manuscript considerably. This research was supported and funded by the following grants: National Social Science Foundation of China (21&ZD334) and the Science Fund for Creative Research Groups of NSFC (71921002).

Liang, M. , Duan, Q. , Liu, J. , Wang, X. and Zheng, H. (2023), "Influencing factors of social media addiction: a systematic review", Aslib Journal of Information Management , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/AJIM-10-2022-0476

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Systematic Review on Social Media Addiction: Bibliometric Analysis Application

16 Pages Posted: 19 Aug 2024 Publication Status: Under Review

Thanh Ngoc Dan Nguyen

Ho Chi Minh City Open University

Hao Yen Tran

Social media addiction has become a prevalent issue, affecting the psychological and social behaviors of individuals globally. This study systematically reviews 37 existing literature to identify key factors influencing social media addiction, its consequences on life satisfaction, and potential areas for future research. By employing bibliometric analysis, the study analyzes trends and gaps in research from 2014 to 2023, providing a comprehensive understanding of social media addiction and offering recommendations for further investigation.

Keywords: Social media addiction, life satisfaction, bibliometric analysis, well-being

Suggested Citation: Suggested Citation

Thanh Ngoc Dan Nguyen (Contact Author)

Ho chi minh city open university ( email ), do you have a job opening that you would like to promote on ssrn, paper statistics, related ejournals, data science, data analytics & informatics ejournal.

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A review of theories and models applied in studies of social media addiction and implications for future research

Affiliations.

1 School of Information, The University of Texas at Austin, USA. Electronic address: [email protected].
2 School of Information, The University of Texas at Austin, USA. Electronic address: [email protected].
PMID: 33268185
DOI: 10.1016/j.addbeh.2020.106699

With the increasing use of social media, the addictive use of this new technology also grows. Previous studies found that addictive social media use is associated with negative consequences such as reduced productivity, unhealthy social relationships, and reduced life-satisfaction. However, a holistic theoretical understanding of how social media addiction develops is still lacking, which impedes practical research that aims at designing educational and other intervention programs to prevent social media addiction. In this study, we reviewed 25 distinct theories/models that guided the research design of 55 empirical studies of social media addiction to identify theoretical perspectives and constructs that have been examined to explain the development of social media addiction. Limitations of the existing theoretical frameworks were identified, and future research areas are proposed.

Keywords: Facebook addiction; Internet addiction; Literature review; Problematic use; Social media addiction; Theoretical framework.

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Open access
Published: 28 August 2024

Academic self-discipline as a mediating variable in the relationship between social media addiction and academic achievement: mixed methodology

Özge Erduran Tekin ORCID: orcid.org/0000-0002-4052-1914 1

Humanities and Social Sciences Communications volume 11 , Article number: 1096 ( 2024 ) Cite this article

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Health humanities

This study examines the mediating role of academic self-discipline in the effect of university students’ social media addictions on academic achievement. The study sample consisted of 520 university students with a daily social media usage time of four hours or more, selected using the convenience sampling method. Data were collected from 36 cities in Turkey. Bergen Social Media Addiction Scale, Academic Self-discipline Scale, Personal Information Form, and Semi-structured Interview Form were used as data collection tools. The relationships between variables were analyzed using Pearson correlation analysis and regression analysis using Process Macro (model 4). In the regression analysis, mediation was tested with the Bootstrap technique. According to the analysis results, social media addiction predicts academic achievement. In addition, academic self-discipline has a partial mediating role in the relationship between social media addiction and academic achievement. As a result of the content analysis of the interviews, three themes were reached: “The Reasons for Social Media Addiction, The Effect of Social Media Addiction on Academic Achievement, and The Role of Academic Self-discipline in the Effect of Social Media Addiction on Academic Achievement.” The qualitative results obtained supported the quantitative results. Based on all these, suggestions were made based on increasing academic self-discipline to prevent social media addiction from affecting academic achievement.

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literature review social media addiction

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Bidirectional longitudinal associations of mental health with academic performance in adolescents: DADOS study

Introduction.

Excessive and misuse of social media is a crucial problem for the young age group, and social media addiction is quite common among university students (Chen and Peng, 2008 ; Ehrenberg et al. 2008 ; Kalaitzaki et al. 2020 ). When the reasons that push university students to use social media intensively are analyzed; the reasons such as communicating with others more easily, having fun, getting away from disturbing experiences and emotional situations and spending time are in the first place (Cohen et al. 2019 ; Özdemir, 2019 ; Zachos et al. 2018 ). Social media addiction has many negative consequences, including academic failure (Kaplan and Özdemir, 2023 ; Masood et al. 2020 ; Shi et al. 2020 ; Zhao, 2023 ). Problematic social media users are unable to control themselves, at this very point self-discipline may be important in preventing social media addiction (Li et al. 2010 ; Zahrai et al. 2022 ). According to research, self-discipline affects problematic internet use behaviors more than any other variable (Kim et al. 2007 ; Li et al. 2013 ). On the contrary, no study in the literature examines the mediating role of academic self-discipline, which represents the sustainability of self-discipline in academic subjects, in the relationship between social media addiction and academic achievement.

Relationship between social media addiction and academic achievement

Academic achievement is shaped by very comprehensive variables and is challenging to systematize in a specific model (Thomas and Maree, 2021 ; Whelan et al. 2020 ). However, the reflection of generally learned knowledge and skills in students’ examination performances is accepted as a critical indicator of academic achievement. Given that academic achievement significantly affects the student’s development in future processes, it is considered significant to examine what factors increase and decrease academic achievement (Shi and Qu, 2022 ).

It is important to examine the relationship between social media addiction, which is accepted as one of the problematic behaviors, and academic achievement (Zhao, 2023 ). Social media is an inclusive concept that describes the social networking sites and messaging applications that young people frequently use (Wartberg et al. 2020 ). Social media addiction, which is also accepted as an impulse control disorder, consists of problematic behaviors that manifest themselves as an individual’s irresistible desire for social media applications and loss of willpower, neglecting work, relationships, and daily routines due to intensive social media use (Andreassen and Pallesen, 2014 ; Young, 1996 ). Social media use has both positive and negative effects from an academic perspective. Social media can facilitate the exchange of information by connecting students and classrooms, provide a personalized learning environment, address different learning domains, and improve learning motivation (Arquero and Romero-Frı́as, 2013 ; Gazibara et al. 2020 ; Hrastinski, 2008 ; Kasperski and Blau, 2020 ). Therefore, the findings suggest that social media contributes to learning processes when used correctly (Jain et al. 2012 ). In addition, studies show that excessive and improper use of social media applications causes a decrease in academic achievement (Masood et al. 2020 ; Wu and Cheng, 2019 ). Social media negatively affects academic achievement because it distracts attention, causes procrastination, and reduces the time allocated to lessons by causing time loss (Junco, 2012 ; O’Keeffe et al. 2011 ). On the other hand, the self-control levels of individuals may be effective in preventing behaviors, such as spending a much longer time on social media applications than normal usage times and often not being aware of this situation and postponing daily tasks that need to be performed during this time (Diker and Taşdelen, 2017 ; Tutgun-Ünal and Deniz, 2015 ; Zahrai et al. 2022 ).

The mediating role of academic self-discipline

Behavioral theories try to explain the limitations of self-control, and the Uses and Gratifications Theory defines the lack of self-control as the inability to neglect smaller and momentarily pleasurable rewards to achieve larger goals (Katz et al. 1973 ). The conscious development and maintenance of self-control is defined as self-discipline (Bear, 2009 ). However, many disciplines use the concept of self-discipline by, it has also been expressed as self-regulation, self-control, self-motivation, and willpower. Duckworth and Seligman ( 2006 ) used the concepts of self-discipline and self-control interchangeably and defined self-discipline as a conscious and sustainable effort to suppress momentary desires to achieve planned goals. Therefore, it can be said that the concept of self-discipline, which refers to taking and maintaining responsibility, refers to the continuity in the ability of individuals to postpone their wants consciously and needs to achieve their long-term goals (Duckworth and Seligman, 2006 ). Academic self-discipline, which is the equivalent of self-discipline in the academic field, is defined as the ability to stay away from various stimuli by controlling oneself to achieve one’s academic goals, to focus one’s attention on the subject to be studied, and to maintain a certain working order in a planned manner (Pustika, 2020 ). By the definition, the scale used to measure academic self-discipline in this study has two sub-dimensions: Planned study and attention. Therefore, academic self-discipline was analyzed in this study, especially within the scope of these two dimensions.

Concentration is the ability to maintain one’s attention despite being bored, tired, or other negative emotional states by focusing sufficiently on the subject one is working on (Taylor et al. 2002 ). Considering that one of the dimensions of academic self-discipline is concentration, it is assumed that increased academic self-discipline may be effective in academic achievement. Planning is another dimension considered in terms of academic self-discipline (Cao and Cao, 2004 ). When considered within the scope of self-discipline theory, planning also includes perseverance and self-motivation and provides convenience in achieving individual goals and fulfilling tasks (Shi and Qu, 2022 ). Students can achieve their goals for better performance (Malte et al. 2009 ). In a study, it was observed that there was no significant difference between students with high and low academic achievement in terms of self-discipline. However, there were differences in various dimensions of time management, including planning (Fang and Wang, 2003 ). Unlike self-discipline, it can be meaningful to examine academic self-discipline in the axis of planning and attention separately and examine the relationship between academic self-discipline and academic achievement in depth through both quantitative and qualitative data to make more concrete suggestions to increase academic achievement.

The present study

Self-discipline, which consists of three dimensions: concentration, impulse control, and delayed gratification, allows one to consider the possible advantages and disadvantages of the action before taking the action. Thus, it helps the person to stay away from risky behaviors and postpone immediate pleasures by being patient for long-term gains (Taylor et al. 2002 ). Therefore, self-discipline is recognized as one of the main factors affecting students’ academic achievement (Liang et al. 2020 ; Van Endert, 2021 ). Students with insufficient self-discipline face academic failure (Tominey and McClelland, 2011 ). Although studies have shown a relationship between self-discipline and academic achievement (Duckworth et al. 2019 ), it is still unclear how self-control and self-discipline affect academic achievement (Shi and Qu, 2022 ). In addition, it requires self-discipline to focus on academic tasks by moving away from harmful internet or social media use that causes time loss (Mbaluka, 2017 ). Self-discipline is important in controlling behavioral addiction types, such as social media addiction. In addition, considering that self-discipline significantly affects academic achievement (Duckworth and Carlson, 2013 ; Zhao and Kuo, 2015 ), it suggests that high academic self-discipline may have a protective role in the negative effects of impulse behavior disorders, such as social media addiction, on academic achievement. Although there are studies examining the relationship between self-control, self-discipline, and social media addiction (Koç et al. 2023 ; Sağar, 2021 ; Zahrai et al. 2022 ), there is no study investigating the mediating role of academic self-discipline in the relationship between social media addiction and academic achievement with a mixed method. Based on all these, this study aimed to examine the mediating role of academic self-discipline in the relationship between university students’ social media addictions and their academic achievement. The quantitative and qualitative sub-objectives created within the scope of this purpose are as follows.

Quantitative sub-objectives:

-Is there a significant relationship between social media addiction, academic achievement, and academic self-discipline in university students?

Is there a mediating role of academic self-discipline in the effect of social media addiction on academic achievement in university students?

Qualitative sub-objectives:

What are the common themes related to university students’ experiences of social media addiction, academic achievement, and academic self-discipline?

How do academic self-discipline experiences mediate the relationship between university students’ social media addictions and academic achievement?

This study was designed as an exploratory sequential mixed design. With mixed methods, a weak or missing aspect of one of the quantitative and qualitative methods can be covered by the strengths of the other (Creswell and Plano Clark, 2018 ). The calculated regression coefficients guide the examination of the relationship between social media addiction and academic achievement and the mediating role of academic self-discipline. However, to better understand the effect of social media addiction on academic achievement and make academic self-discipline-based intervention suggestions, a mixed-method approach was used in this study, considering that it is critical to collect data from students through their opinions.

Participants

The sample of this study consisted of 520 university senior students ranging from 22 to 27 ( \(\bar{x}\) = 24.43; Sd = 1.49) studying in various departments (Psychology, Law, Engineering, and Teaching) at state universities in Turkey in the 2023–2024 academic year. Data were collected from 36 cities in Turkey. Considering the ease of accessing the data, the convenience sampling method was preferred. In the convenience sampling method, due to the limitations in terms of the labor force and time, the sample is selected from easily accessible and applicable units (Büyüköztürk et al. 2014 ). Firstly, data were collected from 873 students through Google Forms. Then, the analyses continued with the data obtained from 520 people who stated that their daily social media usage time was four hours or more. It was aimed to provide more reliable information about the effect of social media addiction on the academic achievement of the 520 students, 299 (57.5%) were female, and 221 (42.5%) were male. Of the participants, 307 (57.9%) defined their socioeconomic level as low, 135 (26%) defined their socioeconomic level as medium, and 84 (16.2%) defined their socioeconomic level as high. The students wrote the transcript grade median, which consisted of the calculation of the end-of-term grades of the courses they had taken until the last year. To obtain more comprehensive information about their academic achievements throughout their university life, the sample consisted of final-year university students. In this context, 182 (35%) of the students who participated in the study had general weighted grade point averages between 1.00 and 2.00, 179 (34.4%) between 2.00 and 3.00, and 159 (30.6%) between 3.00 and 4.00.

In the qualitative phase of this study, 20 volunteer students were selected by purposive sampling method from the students who participated in the quantitative data collection phase. To ensure maximum diversity, male and female students studying in different departments were selected and interviews were conducted with students with high levels of social media addiction to obtain in-depth information. In this context, nine of the students aged between 22 and 25 were male and 11 were female. Three of them were law students, four were teachers, four were psychology students and nine were final-year students studying in various engineering departments.

Data collection tools

Bergen Social Media Addiction Scale developed by Andreassen et al. ( 2016 ) was adapted to Turkish culture by Demirci ( 2019 ). The scale was constructed to fulfill the basic addiction criteria of mental preoccupation, mood change, tolerance, withdrawal, conflict, and failed quit attempts. The scale, graded on a five-point Likert scale, consists of six items. The scores that can be obtained from the scale vary between 6 and 30. In the adaptation study, the Cronbach’s alpha internal consistency coefficient of the scale was calculated as 0.83 and the test-retest reliability coefficient was calculated as 0.83. The suitability of the scale for use in this study was examined by reliability analysis, and exploratory factor analysis was applied. In this context, the KMO value was found to be 0.89 and the Barlett Sphericity test p < 0.000, and it was accepted that the data set was suitable for factor analysis. The unidimensional structure of the scale (explaining 64% of the total variance) was also confirmed in this data set. The fact that the factor loadings of the scale ranged from 0.77 to 0.85 indicates that the items of the scale are compatible with the structure in which it is located. In addition, the Cronbach’s alpha reliability coefficient of the scale was calculated as 0.89 in this study. Based on all these, it can be said that it is appropriate to use the scale within the scope of this study. Some of the items that make up the Bergen Social Media Addiction Scale are as follows:

Have you felt the urge to use social media more and more?

Has using social media too much negatively affected your work/studies?

Would you be uncomfortable or distressed if you were banned from using social media?

The Academic Self-discipline Scale was developed by Şal ( 2022 ) to measure the academic self-discipline levels of university students and adapted to Turkish culture by Erduran Tekin and Şal ( 2023 ). The scale, which consists of eighteen items, has two sub-dimensions “planned work” and “attention.” The scale is scored on a five-point Likert scale and items 6, 7, and 16 are evaluated as reverse. While the scores obtained from the scale vary between 18 and 90, an increase in the scores means an increase in academic self-discipline. In the adaptation study, the structure consisting of two sub-dimensions was confirmed, and the goodness of fit indices of the model indicated an acceptable fit. In the adaptation study, Cronbach’s alpha coefficient of the Academic Self-discipline Scale was calculated as 0.86. The suitability of the scale for use in this study was examined by reliability analysis, and exploratory factor analysis was applied. In this context, the KMO value was found to be 0.87 and the Barlett Sphericity test p < 0.000, and the data set was accepted as suitable for factor analysis. The two-dimensional structure of the scale (explaining 40% of the total variance) was also confirmed in this data set. The factor loadings of the scale ranged from 0.39 to 0.74, indicating that the items belonging to the scale are compatible with the structure in which it is located. In addition, the Cronbach’s alpha reliability coefficient of the scale was calculated as 0.85 in this study. Based on all these, it can be said that it is appropriate to use the scale within the scope of this study. Some of the items that make up the Academic Self-discipline Scale are as follows:

I have my schedule where I plan my study time.

I organize my study environment so that there are no distractions.

If I have planned to study, I can refuse to hang out with my best friend.”

The participants were asked to fill out the Personal Information Form. The form includes sections for age, gender, city of residence, and graduation grades. The academic achievements of the participants were examined based on the General Weighted Grade Point Average (GPA) written on the last semester’s transcript from the undergraduate program they studied. Those with GPAs between 1.00 and 2.00 were considered low academic achievers (2.00 was considered low academic achievement), and those with GPAs between 2.01 and 3.00 were considered medium academic achievers (3.00 was considered medium academic achievement). Those with GPAs between 3.01 and 4.00 were considered high academic achievers.

In the qualitative dimension of the study, semi-structured interview forms created by the researcher in this study were used. These forms were prepared based on the findings obtained by analyzing the quantitative data and researching the literature. After the forms were examined by two expert lecturers, a pilot application was carried out with a student on the comprehensibility of the questions, and the final version was given after the necessary corrections. While one of the most basic ways to ensure validity in qualitative research is the accuracy and detailed reporting of the categories and interpretations obtained, reliability is to minimize the difference in the interpretation of data by different experts (Büyüköztürk et al. 2014 ; Yıldırım and Şimşek, 2019 ). Thus, two academic members who were experts in their fields were consulted during the data interpretation process. The questions in the interview form are as follows:

What are the things that cause you to spend a lot of time on social media tools during the day?

How do you think spending too much time on social media tools affects your academic achievement?

Do you have academic self-discipline? How do you evaluate yourself?

Do you work in a planned way? How do you think working in a planned way affects academic achievement?

Do you ever get distracted while studying because of social media tools? If yes, what measures do you take to prevent social media tools from distracting you while studying?

What do you think you need to improve your academic achievement?

What should happen so that social media does not affect your academic achievement?

Data collection

Considering the ease of access to the data in the present study, the data were collected online using Google Forms. All ethical rules required by scientific research were followed in data collection. Ethics committee approval dated 23.01.2024 and numbered E-35592990-050.01.04-3222142 was obtained from the National Defense University Scientific Research and Publication Ethics Board for the study.

To examine the suitability of the data for parametric tests, kurtosis, skewness, and Z score analyses were performed (Schumacker and Tomek, 2013 ). Multivariate outliers in the data set were analyzed by calculating the Mahalanobis distance. Skewness and kurtosis values were re-analyzed and presented in Table 1 , and it was assumed that the data were normally distributed. In addition to descriptive analyses in which values, such as arithmetic mean and standard deviation, were calculated, ANOVA and t -test analyses were used to determine differences, and correlation analysis was used to determine the relationships between variables. The presence of multicollinearity, one of the prerequisites for regression analysis, was examined through variance inflation factors (VIF) and tolerance values (TV) of the variables in the model. If VIF ≥ 10 and TV ≤ 0.10, the multicollinearity problem is mentioned and the VIF values of the variables in this model are 2.23, and TV values are 0.45, and there is no multicollinearity problem. In this study, the mediating role of academic self-discipline in the relationship between social media addiction and academic achievement was analyzed with the regression of the Bootstrapping Technique (Hayes, 2017 ). Analyses were conducted with SPSS 26 PROCESS programs.

The “content analysis” method was preferred when analyzing qualitative data. With content analysis, the data obtained are conceptualized and organized in a way to be understood, and themes are created (Yıldırım and Şimşek, 2019 ). Content analysis aims to collect similar data collected through interviews under certain themes and to put these themes into a regular format. Firstly, the data obtained from 20 interviews were transferred to the computer environment in writing. A total of 62 pages of data were obtained from the interviews. Twenty interview data were recorded with student codes (e.g., P1, P2, P3, P4, and P5). Then, these organized data were regularised with MAXQDA 2020 software. For the analysis, the data were read repeatedly and analyzed within the scope of the research questions. The themes obtained were coded by two more academicians except the researcher. The coding reliability percentage was calculated using the formula “Agreement/(Agreement + Disagreement)” suggested by Miles and Huberman ( 1994 ). Coding reliability above 80% (Miles and Huberman, 1994 ), the lowest recommended percentage of agreement, was achieved, and the reliability was calculated as 90%. In cases where consensus could not be reached on the codes, participant confirmation was used to build consensus and increase reliability. The data obtained were given systematically according to the research questions in the findings section and supported with direct quotations to increase credibility.

Pearson analysis

Within the scope of the first sub-objective of this study, the skewness and kurtosis values of the social media addiction, academic achievement, and academic self-discipline scale scores and the correlation analysis results examining the relationships between the variables are presented in Table 1 .

Considering the data obtained from this study, it can be said that the skewness and kurtosis values are in the range of +−2 and the data have a normal distribution (George and Mallery, 2019 ). As a result of the analyses, it was seen that the social media addiction scores ( \(\overline{{\boldsymbol{x}}}\) = 15.67) of the data constituting the study group were above the average. Considering the relationship between the variables of this study, as seen in Table 1 , there was a negative and highly significant relationship between social media addiction and academic achievement ( r = −0.63, p < 0.01) and a negative and highly significant relationship between social media addiction and academic self-discipline ( r = −0.74, p < 0.01). When the relationship between academic achievement and academic self-discipline was analyzed, it was seen that there was a positive and highly significant relationship ( r = 0.60, p < 0.01). The findings suggest that as social media addiction increases, academic achievement and academic self-discipline decrease, and as academic self-discipline increases, academic achievement increases.

Results of mediation analysis

Within the scope of the second sub-objective of this study, the mediating role of academic self-discipline in the effect of social media addiction on academic achievement was analyzed using the Regression-based Bootstrapping Technique. In the analyses, 1000 bootstrap sampling was used and the estimates were evaluated at 95% confidence intervals reflecting the results adjusted for bias error. The model used for the mediation role was designed according to Model 4 proposed by Hayes ( 2017 ) in the presence of one independent, one dependent, and one mediator variable. The model is shown in Fig. 1 , and the analysis results of the mediation of academic self-discipline in the effect of social media addiction on academic achievement are presented in Table 2 :

Social media addiction predicts academic achievement through academic self-discipline [ R 2 = 0.44; F (2-519) = 203.530; p < 0.001].

As shown in Fig. 1 , social media addiction directly predicted academic self-discipline negatively ( a = −0.74; p < 0.001). Likewise, it was seen that academic self-discipline directly predicted academic achievement positively ( b = 0.29; p < 0.001). In addition, social media addiction directly predicted academic achievement negatively ( c = −0.63; p < 0.001). When academic self-discipline, the mediating variable, was included in the model, it was observed that this effect was c 1 = −0.42 and the value was still significant.

There was a partial mediation effect since the coefficient resulting from the inclusion of mediator variables in the model was still a significant coefficient and 95% confidence intervals (CI) for the significance of the indirect effects of partial mediation determined in the model are given in Table 2 .

It was understood that the partial mediation model was significant [ F (2-519) = 203.530, p < 0.001]. Social media addiction and academic self-discipline explained 44% of the variance in academic achievement (Table 2 ). In the mediation analysis using the bootstrapping technique, for the hypothesis of this study to be confirmed, the 95% confidence interval (CI) values obtained from the analysis should not contain a zero (0) value to support the research hypothesis (Gürbüz, 2019 ). The mediating role of academic self-discipline in the effect of social media addiction on academic achievement was significant (Bootstrap Coefficient = −0.22, 95% CI [−0.31; −0.14]), and these confidence intervals did not include any zero (0) point.

Qualitative analysis results

Table 3 lists the codes formed as a result of question-based analyses of the data collected from semi-structured interviews with students.

The codes obtained as a result of the analysis of semi-structured interviews conducted to examine the mediating role of academic self-discipline in the effect of university students’ social media addictions on their academic achievement are brought together in three themes and presented in Table 4 .

The quotations related to the most frequently repeated codes explaining the “Reasons for social media addiction” which constitutes Theme 1, are given below:

Desire to receive news “ When I don’t use social media tools, such as Twitter and Instagram, I miss the current news. There is a new event every minute in our country and I see many things on those platforms that I cannot see on television. Therefore, I find myself constantly looking at Twitter and Instagram (P4).”

Entertainment and relaxation “ Life is already hard and boring. At the moment, if you want to do something outside, everything is expensive. Even going to a cinema is incredibly costly for a student. In this case, social media applications are the place where there is content that relaxes, entertains, and makes you laugh at a cheap price (P17).”

Communicating with others “ Social media tools are as much a part of our body as our hands and feet. Instagram is the main way I communicate with other people, my friends, my date. For example, I always check Instagram to see what stories he has posted . (P9).”

The quotations related to the most frequently repeated codes explaining “The effect of social media addiction on academic achievement”, which constitutes Theme 2, are given below:

Loss of time “ I sit at my desk to study, and then a notification comes. I pick up my phone, thinking I’ll check it for a minute, but that’s not the case. I find myself constantly scrolling through posts and watching meaningless videos. This creates an incredible waste of time. I realize that hours have passed, but I haven’t studied at all because I was looking at Instagram or Twitter (P20).”

Inability to pay attention to the lessons, “ My mind stays on social media tools and I can’t concentrate on my lessons. I’m always looking at who went where and what story they shared. Then I started to envy people’s virtual happiness even though I knew it was not real. I can’t concentrate on my lessons thinking about all these things (P11).”

Inability to work regularly “ I am preparing a full study plan, I start, and I say I will take a 10 min break. In the meantime, I look at social media applications, 10 min has become 40 min. I say it’s okay and start over, but it’s the same again. Even if I work regularly one day, I cannot work regularly the next day. This cycle repeats itself (P1).”

The quotations related to the most frequently repeated codes explaining Theme 3, “The role of academic self-discipline in the effect of social media addiction on academic achievement” are given below:

To be disciplined “ As long as I am disciplined and can control myself, I can stay away from social media tools. Of course, one of the biggest benefits of this is my academic achievement . As I continue to control myself, use social media tools less, and stay away from them while studying, my attention and interest in the lesson increases. I can be more successful (P17).”

To focus on lessons “ Social media tools are a very serious stimulant. At least while studying, it is very useful to take the phone out of the room, and if the computer is open, it is very useful to keep only the file being studied open without opening different tabs. As usage is limited, study time remains. In this case, it allows us to focus more on the lessons and not pay attention to unnecessary stimuli (P13).”

Adhering to the work plan “ When I work more regularly, when I do not pay attention to other things even for a short time during the study and, I can follow my study program prepared for me, this makes me more successful (P6).”

This study aimed to examine the mediating role of academic self-discipline in the relationship between social media addiction and the academic achievement of university students in Turkey. In this context, the first sub-objective of the present research is to examine the relationship between social media addiction, academic achievement, and academic self-discipline. There is a significant negative relationship between social media addiction and academic achievement. When the relationship between academic self-discipline and academic achievement is analyzed, there is a significant positive relationship. Accordingly, as social media addiction increases, academic achievement and academic self-discipline decrease, and as academic self-discipline increases, academic achievement increases. The results obtained from this study are consistent with studies showing that social media addiction negatively affects academic achievement (Kaplan and Özdemir, 2023 ; Masood et al. 2020 ; Shi et al. 2020 ; Zhao, 2023 ).

The second sub-objective of this study is to examine the mediating role of academic self-discipline in the relationship between university students’ social media addictions and academic achievement. It was found that social media addiction and academic self-discipline explained 44% of the variance in academic achievement. The mediating role of academic self-discipline in the effect of social media addiction on academic achievement was significant. To determine the appropriate preventive and intervention mental health services that can be offered to university students, it is important to examine the variables that may mediate the relationship between social media addiction and academic achievement when the studies conducted in the literature are examined, seen that self-control and self-discipline are related to student’s academic achievement (Duckworth and Carlson, 2013 ; Liang et al. 2020 ; Mbaluka, 2017 ; van Endert, 2021 ; Zhao and Kuo, 2015 ). The themes obtained within the scope of the third and fourth sub-objectives of the research provide information about the causes of social media addiction, how social media addiction affects academic achievement, and what is the mediating role of academic self-discipline in this effect. When the literature is examined, similar to the results obtained from this study, social media addiction negatively affects academic achievement (Zhao, 2023 ), self-discipline significantly predicts academic achievement positively (Lin, 2021 ), and there are negative relationships between self-control and problematic social media use (Wu et al. 2013 ). Ning and Inan ( 2023 ) examined the mediating role of self-control in the effect of social media addiction on academic success. They concluded that self-control has a mediating role in the relationship between social media addiction and academic success, similar to the results obtained from this study. In another study conducted by Putri et al. ( 2022 ) with university students, it was concluded that high self-discipline reduces social media use. According to the same study, although there is no direct relationship between social media use and academic success, academic success is associated with higher self-control (Putri et al. 2022 ). According to Lindner et al. ( 2017 ), students with high self-control show higher attention skills, are more motivated to fulfill their responsibilities, and have higher academic achievement. In a study examining the mediating role of self-discipline in the relationship between cognitive ability and academic success, it was concluded that the mediating role of self-discipline is significant, and planning is a moderating variable in this relationship (Shi and Qu, 2022 ).

According to the qualitative analysis results, university students exhibit social media addiction behaviors for various reasons such as entertainment, relaxation, receiving news, communicating with others, and habit. These results are consistent with other studies in the literature (Cohen et al. 2019 ; Özdemir, 2019 ; Zachos et al. 2018 ). As a result of the interviews, social media use causes a waste of time, prevents students from devoting themselves to lessons and regular study, and increases their reluctance to study. They have difficulty controlling themselves in terms of social media use, which can be considered the negative effects of social media. According to the students, for social media addiction not to affect academic achievement, they should work in a planned manner, use time effectively, remove distracting stimuli from the environment while studying, pay attention to the lessons, continue their study activities in a disciplined manner, improve their self-control, and follow their study plans continuously. These results support other studies emphasizing the impact of attention, planned study, and time management on academic success (Cao and Cao, 2004 ; Shi and Qu, 2022 ; Taylor et al. 2002 ). Based on all these, although the results obtained from this study are consistent with the literature, more studies are needed examining the relationship between social media addiction and academic achievement. On the other hand, no mixed methodology with study has been found that addresses the mediating role of academic self-discipline in the relationship between social media addiction and academic success, and it is assumed that this study will make a significant contribution to the relevant literature. Additionally, this study encourages further examination of the protective role of the academic self-discipline variable in reducing social media addiction and increasing academic achievement.

Conclusion and suggestions

According to the results of this study, while social media addiction reduces academic achievement, academic self-discipline can prevent social media addiction from reducing academic achievement. Thus, it is recommended that academic self-discipline-based psychoeducation practices be implemented to reduce social media addiction among university students and increase their academic achievement. The obtained qualitative results allow us to understand the mediating role of academic self-discipline in this relationship in more detail. Given the themes, it is recommended that preventive guidance activities that can improve academic self-discipline, especially planned work, and attention, should be implemented more by both educators and school psychologists working in universities. Helping students create a structured study plan, providing regular guidance to help them implement this plan, teaching attention exercises and various memory exercises, and giving behavioral assignments to develop self-discipline are examples of these activities. When the themes explaining the reasons that lead students to use the internet are examined, the creation of other entertainment and recreation areas that can replace social media can contribute to distancing university students from social media. On the other hand, more quantitative and qualitative studies are needed in the literature to examine the relationship between social media addiction and academic achievement in terms of different variables.

Limitations

This study is limited to the quantitative and qualitative data obtained from students who continue to study as seniors in the 2023–2024 academic year at public universities in Turkey. Although there is no mixed methodology with studies examining the relationship between social media addiction and academic achievement variables with academic self-discipline, a very limited number of studies have examined the relationship with self-discipline. This study was supported by studies on self-control and self-regulation, which are used by some researchers instead of the concept of self-discipline. To prevent conceptual confusion and reveal the mediating role of academic self-discipline, such a path was followed, which some researchers may consider a limitation.

Data availability

The data generated and/or analyzed during the present study are available from the corresponding author upon reasonable request. The data cannot be directly placed in a public repository due to limited permissions obtained from the participants. However, the corresponding author is willing to share anonymized data with interested researchers upon request.

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Erduran Tekin, Ö. Academic self-discipline as a mediating variable in the relationship between social media addiction and academic achievement: mixed methodology. Humanit Soc Sci Commun 11 , 1096 (2024). https://doi.org/10.1057/s41599-024-03633-x

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Video Game Addiction in Young People (8–18 Years Old) after the COVID-19 Pandemic: The Grey Area of Addiction and the Phenomenon of “Gaming Non-Pathological Abuse (GNPA)”

Domenico piccininno.

1 Department of Forensic Criminology, Forensic Science Academy (FSA), 84083 Castel San Giorgio, Italy; moc.liamg@572onniniccipocinemod

Giulio Perrotta

2 Istituto per lo Studio delle Psicoterapie (ISP), 00185 Rome, Italy

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The data were received and stored by Giovanni Della Porta.

Introduction: In the literature, video game addiction in youths is correlated with dysfunctional symptoms of anxiety, emotional disorders, and mood disorders, and the pandemic period of 2020–2022 has favored the aggravation of this behavioral addiction. Therefore, we identified the need to analyze this phenomenon with an emphasis on the risks and correlates related to deviance and maladjustment from a prospective perspective, seeking to understand the impact of the individual variables examined. Aim: To demonstrate whether the condition of “gaming non-pathological abuse” (GNPA) promotes psychopathological features of clinical interest, in the absence of a diagnosis of “gaming disorder” (GD). Materials and methods: A search performed on PubMed and administration of an ad hoc sociological questionnaire were used to investigate individual variables of criminological interest in a representative population sample (531 males/females, 8–18 years old, M: 14.4, SD: 2.5). Results: Statistical analysis showed that after the pandemic period, digital video game addiction was reinforced, feeding psychopathological traits consistent with anxiety, emotional disorders, and mood disorders. Variables correlated with impulsive, aggressive, and violent behavior related to age, gender, socio-environmental and economic background, and the severity of digital video game addiction. Conclusions: In the youth population (8–18 years), “gaming non-pathological abuse” (GNPA) is related to aggressive, impulsive and violent behaviors that foster phenomena of social maladjustment and deviance, especially in individuals living in disadvantaged or otherwise complex socio-economic and family contexts. Looking forward, the study of structural and functional personality profiles is essential in order to anticipate and reduce the future risk of psychopathological and criminal behavior.

1. Introduction

Video game use has constantly increased among children and adolescents, having uncertain consequences for their health [ 1 ]. Video game addiction or gaming disorder (GD) is defined as the constant and repetitive use of the Internet to play frequently with different players, potentially leading to negative consequences in many aspects of life. In clinical settings, addiction to video game use for recreational purposes is considered a psychopathology only if the behavioral pattern of persistent and recurrent video game use leads to significant impairment of daily functioning or psychological distress. It is diagnosed according to the Diagnostic Statistical Manual of Mental Disorders (DSM5-TR) criteria, Section 3 , wherein over a period of 12 months at least, five criteria are enough confirm GD, with concerns resulting from gaming (cognitive salience), withdrawal symptoms when gaming is not possible, tolerance (need to increase gaming time), failure in attempts to control/reduce use, loss of interest in other hobbies or activities (behavioral salience), overuse despite acknowledging the existence of a problem, lies about time spent playing, video games use to sedate/regulate/reduce an unpleasant emotional experience, loss or impairment of relevant interpersonal relationships, and impairment of school or work performance [ 2 , 3 ]. As recent technological development has allowed easy access to gaming on many devices, video game addiction has become a serious public health problem with increasing prevalence [ 4 ]. The non-pathological abuse of video games for recreational activity (“gaming non-pathological abuse”, or GNPA), which does not meet the diagnostic criteria of the DSM-5-TR, is not yet considered in the scientific literature, although it may be a potential cause of psychological distress for the subject [ 5 , 6 , 7 ].

With the advent of the global COVID-19 pandemic, social isolation and fear of viral contagion resulted in profound changes in social relationships among people [ 8 ], generating or fueling the psychopathological symptoms of anxiety, emotional distress, low mood [ 9 , 10 , 11 ], and psychosis [ 12 ] in those affected by internet gaming disorder and video game addiction. It also fostered deviant and criminal conduct, such as cyberbullying [ 13 ] and other behavioral addictions [ 2 , 6 , 7 , 14 , 15 , 16 , 17 , 18 , 19 ] that promote isolation, aggression, and deviant and criminal behavior and suicide risk [ 6 , 7 , 20 , 21 , 22 ] and also influence cognitive and behavioral performance [ 23 ]; thus, all of the above are clinically relevant conditions worthy of psychotherapeutic [ 24 ] and pharmacological evaluation and treatment [ 25 , 26 ].

Recent systematic review and meta-analysis studies have shown and confirmed that the prolonged effects of the recreational use of video games determine an increase in anxiety (phobias, fixations, panic and sleep disorders), emotional (aggression and impulsivity) and mood (manic and depressive) symptoms, and risk of suicidal ideations [ 27 , 28 , 29 , 30 ]. Additionally, from a neurobiological point of view, recent studies have shown that the reckless use of certain types of games, violent ones in particular, can impact brain circuits by leading to their structural and functional modification of the cognitive performance of attentional, control–rational, and visuospatial skills and reward processing [ 31 , 32 ]. However, contrary studies also emerge from the literature, praising the cognitive, motivational, emotional, and social benefits of the playful activity of using video games [ 33 , 34 , 35 ] in terms of the cognitive behavioral approach to therapy [ 36 ] and cognitive and psychopathological assessment [ 37 , 38 , 39 , 40 ], thus leading to confusion between the outcomes of published research.

The purpose of the present study is to analyze the impact of the post-COVID-19-pandemic period on the youth population (8–18 years old) who use video games for recreational purposes, in the absence of a psychopathological diagnosis of “Gaming Disorder” (GD) but with an attenuated condition that the literature does not take into consideration (i.e., “gaming non-pathological abuse”, or GNPA) and then correlate the data obtained from the administration of a questionnaire survey to assess the severity of dependency using the variables of age gender; socio-environmental and economic background; and impulsive, aggressive, and violent behaviors, if present. In the absence of a GD diagnosis according to DSM-5-TR criteria, the aim was to demonstrate that such a condition is still worthy of socio-clinical intervention because it can generate potential psychological distress.

2. Materials and Methods

2.1. materials and methods.

From January 1991 to June 2024, we actively searched PubMed for systematic reviews, meta-analyses, clinical trials, and randomized controlled trials using “Addiction AND Video games”, selecting 257 eligible results, 35 of which were included by removing duplicate content, irrelevant items, and absence of search items. To get a broader and more complete overview of the topic, 6 more references were added (from elsewhere and not the Pubmed platform, being materials from the academic literature), for a total of 41 results. Simple reviews, opinion contributions, or publications in popular volumes were excluded as redundant or not relevant to this work. An artificial intelligence program was not used for the automatic selection of results, but the tools and services offered by the PubMed platform were used. The search was not limited to English and Italian language papers ( Figure 1 ).

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Object name is epidemiologia-05-00035-g001.jpg

PRISMA flow diagram template. Adapted from Page M.J. et al. [ 41 ].

The use of the literature was necessary to construct the introduction section of this study and to understand the usefulness of delving into the topic of “gaming non-pathological abuse” (GNPA), which is still not discussed in the literature because it is not considered clinically relevant.

Having identified the criteria for selecting the population, various meetings in educational institutions were arranged to raise awareness among students and ask for their participation, subject to prior signing of informed consent and data processing, signed by parents or by students over 18. Having indicated the link to fill out the specially prepared Sociological Questionnaire (with 50 items, analyzing the variables listed in Table 1 , with single yes/no, multiple, or open-ended responses), the students (independently or helped by a familiar adult) logged on to complete it. The present research work was carried out from January 2023 to June 2024. All participants were guaranteed anonymity and the ethical requirements of the Declaration of Helsinki were met. Since this research was not funded by anyone, it is free of conflicts of interest.

List of selected variables, specifying type and description.

N	Variable	Type_Variable	Type_Answer	Description
1	Age	Generic	Continued: 8–18 years old	Variable related to age
2	Gender	Generic	Dichotomous_Yes/No	Variable related to gender
3	Cluster	Generic	Dichotomous_Yes/No	Variable related to membership in the clinical group (daily recreational use of video games, more than 60 min) or control group (daily recreational use of video games, less than or equal to 60 min), including non-continuous
4	Time spent per day on recreational activities such as video games	Clinic	Continued_1–12 h	Variable related to the specific daily time (expressed in h/hour) spent on video game playing activity
5	Night game	Clinic	Dichotomous_Yes/No	Variable related to the time spent playing video game during nighttime hours that are usually devoted to sleep and rest
6	Solo game	Clinic	Dichotomous_Yes/No	Variable related (most of the time) to the performance of the video game as a playful activity in solitude rather than in company or sharing
7	Time taken away from study	Clinic	Dichotomous_Yes/No	Variable related to the time taken away from studying in favor of video games
8	Time taken away from friends	Clinic	Dichotomous_Yes/No	Variable related to the time taken away from friends in favor of video games
9	Time taken away from going out	Clinic	Dichotomous_Yes/No	Variable related to the time taken away from going out in public and attending events in favor of videogames
10	Time taken away from personal hygiene	Clinic	Dichotomous_Yes/No	Variable related to the time taken away from personal hygiene in favor of videogames
11	Time taken away from eating	Clinic	Dichotomous_Yes/No	Variable related to the time taken away from eating in favor of video games
12	Reason for addiction: absence of friends	Clinic	Dichotomous_Yes/No	Variable related to the reason for time spent on video game playing activity (absence of friends)
13	Reason for addiction: reduced interest in the outdoors	Clinic	Dichotomous_Yes/No	Variable related to the reason that justifies the time devoted to the video game playing activity (reduced interest in spending time outdoors, in public, or on group activities)
14	Reason justifying addiction: poor school performance	Clinic	Dichotomous_Yes/No	Variable related to the reason that justifies the time spent on video game playing activity (poor school performance)
15	Reason justifying addiction: emotional and family difficulties	Clinic	Dichotomous_Yes/No	Variable related to the reason for time spent on video games playing activity (emotional and family difficulties)
16	Alterations in life conduction as a result of video game-like activity	Clinic	Dichotomous_Yes/No	Variable related to the perceived negative effect on one’s lifestyle, resulting from the performance of playful activities with video games
17	Reinforcement of video game addiction in the pandemic	Clinic	Dichotomous_Yes/No	Variable related to the perceived temporal increase in playful activities with video games during and after the pandemic period
18	Use of lies	Clinic	Dichotomous_Yes/No	Variable related to telling lies during and after playing video games (e.g., to continuing to play or not taking specific responsibility)
19	Anger	Clinic	Dichotomous_Yes/No	Variable related to the expression of anger during and after the performance of playful activities with video games (e.g., to continuing playing or not taking specific responsibility)
20	Aggressiveness	Clinic	Dichotomous_Yes/No	Variable related to the display of aggressivity during and after the performance of playful activities with video games (e.g., continuing playing or not taking specific responsibility)
21	Subjective perception of benefits of using video games	Clinic	Dichotomous_Yes/No	Variable related to the subjective perception of possible benefits from performing playful activities with video games
22	Preferred game setting (violence)	Clinic	Dichotomous_Yes/No	Variable related to the preference for a certain video game types (violent type/non-violent type)
23	Use of video games in online mode	Clinic	Dichotomous_Yes/No	Variable related to the prevalence or not of using video games in on-line or off-line mode
24	Online encounters with individuals younger than the recommended age	Clinic	Dichotomous_Yes/No	Variable related to online meetings with individuals younger than the recommended age (e.g., 18 years old for violent games)
25	Witnessing others of deviant or criminal conduct	Clinic	Dichotomous_Yes/No	Variable related to having witnessed online deviant or criminal conduct by other users
26	Simulation or implementation of deviant or criminal conduct	Clinic	Dichotomous_Yes/No	Variable related to having witnessed or simulated online deviant or criminal conduct seen in video games

Data from the questionnaires were tabulated in an Excel database, and statistical analysis was performed using SPSS software, version 27. Descriptive analyses of categorical and continuous variables and an exploratory analysis were conducted to identify potential associated factors; Chi-square tests were performed at a 5% significance level to identify the associated dependent and independent variables. An exploratory bivariate and multivariate analysis was then conducted to determine the value of the selected variables. Multivariate logistic regression analysis was performed with a 95% confidence interval based on the variables selected from the bivariate model with a significance level of up to 20%. Variables with collinearity (≥5.0) were excluded to improve the predictive value of the multivariate analysis.

2.2. Setting and Participants

The clinical population of the study consists of children and adolescents aged 8 to 18 years, either exposed or not to COVID-19 infection, who attended elementary, middle and high schools over three years, from 2020 to 2022. Inclusion criteria are related to the participant’s age at the time of enrollment to the present study, declaration of video game use for leisure (for at least 1 h a day), absence of GD diagnosis according to DSM-5-TR criteria, good health, Italian nationality, defined sexual gender (male/female), and informed consent and data processing, personally signed if 18 years old or signed by parents/guardian if a minor. Exclusion criteria relate to age under 8 years or over 18 years at the time of enrollment in the present study, declaration of non-use of video games for leisure or in any case for a daily use of less than 1 h, presence of one or more pathological conditions both physically and mentally certified, foreign nationality, undefined sexual gender (transgender), and absence, incorrect or withdrawal of informed consent and data processing. The control population of the study consists of children and adolescents aged 8–18 years, exposed or not to COVID-19 infection, who were attending elementary, middle and high schools over three years (2020–2022). Inclusion criteria are related to the participant’s age at the time of enrollment to the present study, declaration of video game use for leisure for less than 1 h, absence of GD diagnosis according to DSM-5-TR criteria, good health, Italian nationality, defined sexual gender (male/female), and informed consent and data processing signed personally if 18 years or by parents or legal representatives if under age. Exclusion criteria include participants of less than 8 years or older than 18 years at the time of enrollment in this study, declaration of video game use for leisure or more than 1 h per day, presence of one or more pathological certified conditions, both physical and mental, foreign nationality, undefined sexual gender (transgender), and absence, erroneousness or withdrawal of informed consent and data processing.

The schools were selected randomly but considering geographical calibration to cover all territorial areas of the country (Italy) for an equal sample distribution. In total, 9 schools participated in the study: 3 from northern Italy, 3 in central Italy, and 3 in southern Italy. We identified the sample size with the minimum n through a statistic calculation of the total interviewable students and daily use of video games for recreational purposes, determining a power of 80% and a significance level of 95%, with a design error of 5%. Therefore, a minimum required sample of at least 520 school-age children was identified. The drop-out rate was 0/531 (0.0%).

3.1. Descriptive Statistics

The selected clinical population group (participants who reported daily playful activity using video games for over 60 min) is made up of 271 participants (clinical patients), ambisexual, aged 8–18 years (M: 14.3, SD: 2.5), while the control group (participants who reported daily playful activity using video games for a maximum of 60 min) is made up of 260 participants, ambisexual, aged 8–18 years (M: 14.5, SD: 2.5). The total population consists of 531 participants, ambisexual, aged 8–18 years (M: 14.4, SD: 2.5) ( Table 2 ).

Population group ( n _%).

Clinical Group
Age_y_Range	Male_ (%)	Female_ (%)	Total_ (%)
8–12	36 (29.7%)	46 (30.7%)	82 (30.2%)
13–18	85 (70.3%)	104 (69.3%)	189 (69.8%)
	121 (44.6%)	150 (55.3%)	(100%)

	(%)	(%)	(%)
8–12	53 (30.4%)	19 (22.1%)	72 (27.7%)
13–18	121 (69.6%)	67 (77.9%)	188 (72.3%)
	174 (66.9%)	86 (33.1%)	(100%)

	(%)	(%)	(%)
8–12	89 (30.2%)	65 (27.5%)	154 (29.0%)
13–18	206 (59.8%)	171 (72.5%)	377 (71.0%)
	295 (55.5%)	236 (45.5%)	(100%)

Statistical findings regarding the variables of clinical interest are shown in Table 3 .

Variables of clinical interest—statistical findings.

N_Variable	Nomenclature	H/n_Case			% Total
N_Variable	Nomenclature	H_Time	N_Case_Total	N_Case_Clinic
4	Time spent per day on recreational activities such as video games	1	271	11	51.0
		2	85	85	16.0
		3	84	84	15.8
		4	33	33	6.2
		5	13	13	2.4
		6	12	12	2.3
		7	5	5	0.9
		8	8	8	1.5
		9	6	6	1.1
		10	4	4	0.8
		11	3	3	0.6
		12	7	7	1.3

5	Night game_yes	219		219	41.2
6	Solo game_yes	162		162	30.5
7	Time taken away from study_yes	56		56	10.5
8	Time taken away from friends_yes	169		169	31.8
9	Time has taken away from going out_yes	35		35	6.6
10	Time taken away from personal hygiene_yes	45		45	8.5
11	Time has taken away from eating_yes	305		271	57.3
12	Reason for addiction: absence of friends_yes	138		138	25.9
13	Reason for addiction: reduced interest in the outdoors_yes	56		56	10.5
14	Reason justifying addiction: poor school performance_yes	33		33	6.2
15	Reason justifying addiction: emotional and family difficulties_yes	443		271	83.3
16	Alterations in life conduction as a result of video game-like activity	286		271	53.8
17	Reinforcement of video game addiction in pandemic_yes	326		271	61.3
18	Use of lies_yes	229		229	43.0
19	Anger_yes	234		234	44.0
20	Aggressiveness_yes	266		266	50.1
21	Subjective perception of benefits from using video games_yes	341		271	64.1
22	Preferred game setting (violence) _yes	449		271	84.4
23	Use of video games in online mode_yes	396		271	74.4
24	Online encounters with individuals younger than the recommended age_yes	417		271	78.4
25	Witnessing others of deviant or criminal conduct_yes	417		271	78.4
26	Simulation or implementation of deviant or criminal conduct_yes	417		271	78.4

3.2. T-Test for Independent Samples

We performed a T-test for the selected clinical variables using independent samples, designating “3” as the dependent variable; significant results emerged, as shown in Table 4 .

T-test for independent variables (dependent variable: #3).

N_Variable	Nomenclature	F	t	gl
1	Age	2.152	−0.904	529	0.366
2	Gender	25.347	−5.288	529
4	Time spent per day on recreational activities such as video games	294.708	−19.234	529
5	Night-game_yes	58.634	−7.759	529
6	Solo-game_yes	5.012	1.115	529	0.265
7	Time taken away from study_yes	42.740	3.293	529
8	Time taken away from friends_yes	2.797	0.834	529	0.405
9	Time has taken away from going out_yes	9.290	−1.538	529	0.125
10	Time taken away from personal hygiene_yes	8.520	1.448	529	0.148
11	Time has taken away from eating_yes	3.595	0.945	529	0.345
12	Reason for addiction: absence of friends_yes	0.089	0.149	529	0.882
13	Reason for addiction: reduced interest in the outdoors_yes	4.603	−1.074	529	0.283
14	Reason justifying addiction: poor school performance_yes	1.873	0.683	529	0.495
15	Reason justifying addiction: emotional and family difficulties_yes	2.415	0.775	529	0.439
16	Alterations in life conduction as a result of video game-like activity	4.558	−1.063	529	0.288
17	Reinforcement of video game addiction in pandemic_yes	8.169	−2.350	529
18	Use of lies_yes	27.039	−2.843	529
19	Anger_yes	13.131	−2.174	529
20	Aggressiveness_yes	11.240	−2.089	529
21	Subjective perception of benefits from using video games_yes	0.022	−1.521	529	0.129
22	Preferred game setting (violence) _yes	3.951	−0.998	529	0.319
23	Use of video games in online mode_yes	13.675	−1.829	529	0.068
24	Online encounters with individuals younger than the recommended age_yes	1.061	−0.515	529	0.607
25	Witnessing others of deviant or criminal conduct_yes	12.486	−1.753	529	0.080
#26	Simulation or implementation of deviant or criminal conduct_yes	12.486	−1.753	529	0.080

3.3. Statistical Trends

The variables of clinical interest are grouped into 6 groups: (a) “time management” group (4, 5, 6); (b) “loss of time” group (7, 8, 9, 10, 11); (c) “reason for addiction” group (12, 13, 14, 15); (d) “subjective perception” group (16, 17, 21, 22); (e) “deviant and criminal conduct” group (18, 19, 20, 26); and the (f) “online mode” group (23, 24, 25). From the analysis of the data, upon carrying out the frequency assessment, a constant and directly proportional trend emerged between the duration of hourly playing time (or gaming time) and variables 16, 18, 19, 20, 21, and 26 ( Figure 2 ).

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Object name is epidemiologia-05-00035-g002.jpg

Graph of growth curves between the variable representing the daily duration of gaming time and the tendency to lie, feel anger, show aggression, perceive benefits from gaming activity, and engage in deviant and criminal behavior. The X-axis shows all study participants according to an increasing scale of severity (concerning the number of hours devoted to playful activity with video games; the more hours devoted, the more severe the need to use video games as an addictive tool), while the Y-axis shows hours of video game use. The subjects in the clinical group are in blue, while the subjects in the control group are in red.

3.4. Binary Correlations

A binary correlation between the generic and clinical variables was performed, detecting a range of significance values concentrated in all subgroups of interest ( Table 5 ).

Binary correlations between clinical variables. R: correlation coefficient; p : significance.

N	Variable	Age (1)		Gender (2)		Cluster (3)
N	Variable	R		R		R
4	Time spent per day on recreational activities such as video games	0.151		0.210		0.934
5	Night game_yes	0.102		0.103		0.320
6	Solo game_yes	0.117		0.122		0.048	0.265
7	Time taken away from study_yes	0.043	0.317	−0.016	0.705	0.142
8	Time taken away from friends_yes	0.168		−0.007	0.874	0.036	0.405
9	Time has taken away from going out_yes	−0.048	0.268	0.009	0.835	−0.067	0.125
10	Time taken away from personal hygiene_yes	−0.060	0.167	−0.022	0.612	0.063	0.148
11	Time has taken away from eating_yes	0.044	0.309	−0.014	0.754	0.041	0.345
12	Reason for addiction: absence of friends_yes	0.171		0.085		0.006	0.882
13	Reason for addiction: reduced interest in the outdoors_yes	0.180		−0.075	0.085	−0.047	0.283
14	Reason justifying addiction: poor school performance_yes	0.092		0.048	0.270	0.030	0.495
15	Reason justifying addiction: emotional and family difficulties_yes	0.093		0.099		0.034	0.439
16	Alterations in life conduction as a result of video game-like activity	−0.015	0.731	0.025	0.568	−0.046	0.288
17	Reinforcement of video game addiction in pandemic_yes	0.198		−0.010	0.816	0.102
18	Use of lies_yes	0.575		0.089		0.123
19	Anger_yes	0.054	0.218	0.033	0.445	0.094
20	Aggressiveness_yes	0.055	0.206	0.027	0.532	0.090
21	Subjective perception of benefits from using video games_yes	0.087		0.123		−0.066	0.129
22	Preferred game setting (violence) _yes	0.035	0.418	−0.047	0.285	−0.043	0.319
23	Use of video games in online mode_yes	−0.031	0.477	0.199		−0.079	0.068
24	Online encounters with individuals younger than the recommended age_yes	0.082	0.060	0.014	0.756	−0.022	0.607
25	Witnessing others of deviant or criminal conduct_yes	0.233		0.045	0.301	−0.076	0.080
26	Simulation or implementation of deviant or criminal conduct_yes	0.263		0.045	0.301	−0.076	0.080

4. Discussion

The analyzed data from the selected population sample allowed for detailed descriptive analysis and correlations between variables. In particular, from the overall data obtained, it is possible to make the following claims:

The variable for the daily hourly duration of video game play activity (4) is inversely proportional to the number of participants in the present study; within 12 h, 440/531 (82.9%) subjects play for less than 3 h per day, and as the daily hours increase, the number of participants decreases. The 1 h cut-off was determined based on the scientific literature referenced herein, which considers video game use of less than 60 min as non-pathological.
In the clinical subgroup “time management” (4, 5, 6), variable 5 is represented by 6/10 of the overall sample, demonstrating that the participants frequently use some evening and nighttime hours, which are normally devoted to sleep activity, to play. These data are consistent with the result of variable 7, which is represented by only 10% of the research population. Variable 6 accounts for just under 1/3 of the sample, showing that more than 2/3 of the video game activity is a game shared with other people, consistent with variable 23 of online gaming, which is represented by almost 4/5 of the total population sample.
In the “loss of time” clinical subgroup (7, 8, 9, 10, 11), the variable most represented is #11, showing that time spent on gaming absorbs that to be spent on food and eating in almost 6/10 of the samples. This is followed by variable 8, with almost 1/3, showing that video game play activity is closely related to age ( p < 0.001).
In the clinical subgroup “reason for addiction” (12, 13, 14, 15), variables indicating school and family difficulties (15) and the absence of friends (12) are more represented, by more than 8/10 for the former and a little more than 1/4 for the latter. This confirms that the ludic activity of video games can be considered an “emotional refuge” for pre-adolescents and adolescents.
In the clinical subgroup “subjective perception” (16, 17, 21, 22), more than 50% of the population sample states that they perceive alterations in the normal conduct of life due to video games (variable 16), as the time devoted to gaming must be taken away from other activities; however, this finding must be compared with the outcome of variable 21, which confirms the positive perceptions of the participants in more than 6/10 of the total population sample: these data must be read with caution, as a positively perceived state does not necessarily correspond to an actual state of well-being, as evidenced by the variables of the deviant and criminal conduct clinical subgroup. Therefore, this apparent state of well-being is likely linked to the reward circuit arising from video game use, which is known to be involved during these activities.
Variable 17 confirms that the pandemic period exacerbated video game addiction, both during and after the conclusion of the pandemic, in both cases for more than 6/10 of the total population sample. This variable correlated with both age (R = 0.198, p < 0.001) and longer duration of video game use (R = 0.102, p = 0.019) but also with time taken away from study (R = 0.139, p = 0.001), time takenn away from friends (R = −0.198, p < 0.001), use of lies (R = 0.130, p = 0.003), anger (R = 0.197, p < 0.001), aggression (R = 0.199, p < 0.001), and preference for video games with violent themes (R = 0.155, p < 0.001).
In the “deviant and criminal conduct” clinical subgroup (18, 19, 20, 26), 40–50% of participants reported feeling anger and aggression and using lying as a strategy for not taking responsibility.
A worrying result emerges from variable 22, in which more than 8/10 of the sample population prefers video games with violent and/or aggressive contents, as if the individual tends to sublimate unconscious destructive energy through gaming or as if the more one releases emotional and nervous tension while playing video games, the greater the urge to continue, thus reinforcing a confirmatory pattern. The latter interpretation would seem to be confirmed by the bivariate correlation analysis between this variable and variables 12 (R = 0.123, p = 0. 005), 15 (R = 0.111, p = 0.010), 16 (R = 0.115, p = 0.008), 17 (R = 0.155, p < 0.001), 18 (R = 0.089, p = 0.041), 19 (R = 0.651, p < 0.001), and 20 (R = 0.640, p < 0.001).
Finally, in the clinical subgroup “online mode”, alarming data emerge from pre-adolescent and adolescent subjects who play online video games without parental control, who find themselves pulled into a virtual reality where almost 8/10 of the research sample experience inappropriate contact with adults, and the youngest play violent games, resulting in direct and indirect participation in deviant and criminal conduct.
Frequent use beyond 2 h a day of playful activity with violent-type video games increases aggressive, violent, and manipulative behavior through lying, facilitating the process of imitating deviant and criminal behavior in real life. Age is directly correlated with deviant and criminal conduct, both of others (R = 0.233, p < 0.001) and one’s own (R = 0.266, p < 0.001), while the greater the use of video games for recreational purposes in terms of time, the more frequent the presence of manipulative (R = 0.123, p = 0.005), angry (R = 0.094, p = 0.030), and aggressive (R = 0.090, p = 0.037) behaviors.

The value of the new nosographic category “gaming non-pathological abuse” (GNPA), in our opinion, has the same clinical importance as the better-known “gaming disorder” (GD) because in this study, we have shown that in the absence of positivity for at least five criteria, subjects who nevertheless use video games for recreational purposes for more than 1 h per day present a marked increase in values related to aggressive, manipulative and angry conduct, and these underlie deviant and/or criminal attitudes in developmental age. The absence of positivity for at least five criteria does not characterize the diagnosis of GD but is certainly worthy of clinical evaluation if the temporal use of the ludic tool is more than 1 h per day, regardless of gender and mode of use, so that we might prevent or intervene promptly in attitudes that may already be deviant or criminal (or become so if reinforced).

Limitations, Implications for Clinical Practice, and Prospects

A set of variables of socio-criminological and clinical nature were used in the present study, but they do not entirely represent the phenomenon, because it was not possible to perform a regression and thus obtain statistically significant values. However, thanks to the good results obtained, we can reflect upon the need to organize a larger population sample and a set of variables that also include health data, outcomes of test admini-stration, and the reconstruction of personality profiles. This study must be considered the first piece of a larger research work that hopefully can be more broadly developed as new means are attained, including economic ones. Lastly, the survey instrument used is not clinical but socio-criminological, as the goal of this research was not to diagnose the selected population sample but to understand the direct and indirect consequences of video game overuse. For this reason, a questionnaire with survey functions was used rather than a standardized and validated test.

5. Conclusions

A large sample of the youth population (8–18 years old) was studied to demonstrate whether addictive behaviors in the use of video games for leisure, which fail to meet the diagnostic criteria for Gaming Disorder (GD), are worthy of investigation as a potential threat to the subject’s psychological stability. The study shows that “gaming non-pathological abuse” (GNPA), understood as an attenuated form of GD that has fewer than five diagnostic criteria required for nosographic diagnosis, is also related to aggressive, impulsive, and violent behaviors that foster phenomena of social maladjustment and deviance, especially in individuals living in already disadvantaged and/or complex socio-economic and family contexts. The assessment of socio-environmental, family and personal variables—such as childhood trauma, poverty, degrading social context, and highly deviant or criminal friendships—together with the study of structural and functional personality profiles is essential in investigating this phenomenon from a clinical point of view, in the absence of a GD diagnosis, to anticipate and/or reduce the future risk of psychopathological and criminal behavior.

Acknowledgments

We thank Roberta Ballarin for her contribution during the drafting of the sociological questionnaire, administered to the population sample by Domenico Piccininno, to investigate individual variables.

Funding Statement

This study received no external funding.

Author Contributions

D.P. is the study originator and material executor. G.P. authored the manuscript and performed the statistical analysis. D.P. received and stored the research data, and G.P is the creator of "Gaming Non-Pathological Abuse" (GNPA). All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

All participants were assured of compliance with the ethical requirements of the Charter of Human Rights, the Declaration of Helsinki in its most up-to-date version, the Oviedo Convention, the guidelines of the National Bioethics Committee, the standards of “Good Clinical Practice” (GCP) in its most recent version, the national and international codes of ethics of reference, as well as the fundamental principles of state law and international laws according to the updated guidelines on observational studies and clinical trials. According to Legislative Decree No. 52/2019 and Law No. 3/2018, this research does not require the prior approval of an Ethics Committee in the implementation of Regulation (EU) no. 536/2014. In compliance with Regulation (EU) 2017/745, the Declaration of Helsinki, and the Oviedo Convention, the scientific research contained in the manuscript (a) does not involve new or already on-the-market drugs or medical devices; (b) does not involve the administration of a new or already on-the-market drug or medical device; (c) is not for commercial purposes; (d) is not sponsored or funded; (e) involved participants that signed informed consent and data processing, in compliance with applicable national and EU regulations; (f) refers to non-interventional but observational-comparative diagnostic topics, for validation of the newly proposed questionnaire; and (g) featured a population sample that was collected at a date before the start of this study and is part of a private, non-public database.

Informed Consent Statement

The subjects recruited gave regular informed consent, thus remaining completely anonymous.

Data Availability Statement

Conflicts of interest.

The authors declare no conflicts of interest.

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IMAGES

Essay on Social Media Addiction
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(PDF) SOCIAL MEDIA ADDICTION AND YOUNG PEOPLE: A SYSTEMATIC REVIEW OF
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COMMENTS

Research trends in social media addiction and problematic social media
The present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013-2022. Bibliometric analysis was conducted on 501 articles that were extracted from the Scopus database using the keywords social media addiction and problematic social media use. ... Although the ...
Social Media Addiction and Young People: a Systematic Review of Literature
social media addiction is negatively associated, in which the. higher the addiction in social media, the lower the young. people's academic performance (Hou et al., 2019). This i s. because ...
(PDF) Social Media Addiction: A Systematic Review ...
In this study, we use the cognitive-behavioral model of pathological use and conduct a systematic review of social media addiction literature from 2008-2019. Based on the review of 132 papers, we ...
Social Media Addiction
A review of the literature indicates that the most common usage of social media is the management of social relationships and that persons driven by the need to form new relationships on social media were prone to addiction (Ahmed & Vaghefi, 2021).
Social Media Use and Its Connection to Mental Health: A Systematic Review
Abstract. Social media are responsible for aggravating mental health problems. This systematic study summarizes the effects of social network usage on mental health. Fifty papers were shortlisted from google scholar databases, and after the application of various inclusion and exclusion criteria, 16 papers were chosen and all papers were ...
Social Media Addiction: A Systematic Review through Cognitive-Behavior
Despite the abundance of research published on social media addiction, this literature is fragm ented, and there is no synthesis of the drivers and outcomes of this behavior. In this study, we use the cognitive-behavioral model of pathological use and conduct a systematic review of social media addiction literature from 2008- 2019.
Social Media Addiction
The chapter concludes by offering a summary of the most important concepts in the literature review associated with social media addiction. Download chapter PDF. Keywords. Pathological internet use ... Social media addiction: Its impact, mediation, and intervention. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 13(1 ...
Influencing factors of social media addiction: a systematic review
Originality/value. The contributions of this review are two-fold. First, it used a systematic and rigorous approach to summarize the empirical landscape of SMA research, providing theoretical insights and future research directions in this area. Second, the findings could help social media service providers and health professionals propose ...
Systematic Review on Social Media Addiction: Bibliometric ...
Abstract. Social media addiction has become a prevalent issue, affecting the psychological and social behaviors of individuals globally. This study systematically reviews 37 existing literature to identify key factors influencing social media addiction, its consequences on life satisfaction, and potential areas for future research.
Review Social media use and its impact on adolescent mental health: An
Literature reviews on how social media use affects adolescent mental health have accumulated at an unprecedented rate of late. Yet, a higher-level integration of the evidence is still lacking. We fill this gap with an up-to-date umbrella review, a review of reviews published between 2019 and mid-2021. Our search yielded 25 reviews: seven meta ...
Addiction to Social Media and Attachment Styles: A Systematic
Web-based communication via social networking sites (SNSs) is growing fast among adolescents and adults and some research suggests that excessive SNS use can become an addiction among a small minority of individuals. There is a growing body of research that has examined the impact of attachment styles and its influence on internet addiction (more generally) and social media addiction (more ...
Social Media Use and Mental Health and Well-Being Among Adolescents
The current paper presents a scoping review of the published literature in the research field of social media use and its association with mental health and well-being among adolescents. ... Bergen Social Media Addiction Scale is a commonly used questionnaire amongst the included studies (Hanprathet et al., 2015; Banyai et al., ...
A review of theories and models applied in studies of social media
With the increasing use of social media, the addictive use of this new technology also grows. Previous studies found that addictive social media use is associated with negative consequences such as reduced productivity, unhealthy social relationships, and reduced life-satisfaction. However, a holist …
A review of theories and models applied in studies of social media
To align with the majority of the literature, we used social media addiction (SMA) or addictive social media use (in a non-clinical sense) in the remainder of this review, with a recognition of the controversies associated with the term. Exceptions were made when it is more precise to use the other terms (e.g., when referring to prior literature).
Academic self-discipline as a mediating variable in the ...
When the literature is examined, similar to the results obtained from this study, social media addiction negatively affects academic achievement (Zhao, 2023), self-discipline significantly ...
Addiction to social media and attachment styles: A systematic
Web-based communication via social networking sites (SNSs) is growing fast among adolescents and adults and some research suggests that excessive SNS use can become an addiction among a small minority of individuals. There is a growing body of research that has examined the impact of attachment styles and its influence on internet addiction (more generally) and social media addiction (more ...
Research trends in social media addiction and problematic social media
Global dispersion of social networking sites in relation to social media addiction or social media problematic use. peak was reached in 2021 with 195 publications. Analyzing
Online Social Networking and Addiction—A Review of the Psychological
The aim of this literature review was to present an overview of the emergent empirical research relating to usage of and addiction to social networks on the Internet. Initially, SNSs were defined as virtual communities offering their members the possibility to make use of their inherent Web 2.0 features, namely networking and sharing media content.
Frontiers
After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use of social media, the authors obtained a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books and 1 conference review.
Social media use, social anxiety, and loneliness: A systematic review
"Internet addiction" was an early term used to describe dependency on or inability ... PsycINFO and PubMed databases were explored to identify studies in this literature review prior to May 2020. ... it may be important to consider whether there may be cultural differences in the motivations for using social media. As part of this review ...
PDF Addiction to Social Media and Attachment Styles: A Systematic
Consequently, the present study systematically reviewed the evidence concerning internet/social media addiction and attachment style. A total of 32 papers published between 2000 and 2018 met the inclusion criteria following searches in the following databases: Scopus, Web of Science, PubMed, ProQuest, and Google Scholar.
A systematic review: the influence of social media on depression
Social media. The term 'social media' refers to the various internet-based networks that enable users to interact with others, verbally and visually (Carr & Hayes, Citation 2015).According to the Pew Research Centre (Citation 2015), at least 92% of teenagers are active on social media.Lenhart, Smith, Anderson, Duggan, and Perrin (Citation 2015) identified the 13-17 age group as ...
Research trends in social media addiction and problematic social media
A systematic review by Khan and Khan (20) has pointed out that social media addiction has a negative impact on users' mental health. For example, social media addiction can lead to stress levels rise, loneliness, and sadness (54). Anxiety is another common mental health problem associated with social media addiction.
Causes and Consequences of Social Media Addiction -Literature Review
It was identified that some of the causes of social media. addiction were early exposure to technology, underlying. mental health issues, peer pressure, design features, and the. user interface of ...
The impact of social media use types and social media addiction on
Literature review and hypothesis development2.1. Social media use and addiction. The term addiction is mainly related to alcohol, ... Social media addiction means that college students spend a lot of time on social media and ignore people and things around them, which affect their physical and mental health, ...
Video Game Addiction in Young People (8-18 Years Old) after the COVID
1. Introduction. Video game use has constantly increased among children and adolescents, having uncertain consequences for their health [].Video game addiction or gaming disorder (GD) is defined as the constant and repetitive use of the Internet to play frequently with different players, potentially leading to negative consequences in many aspects of life.