From Pandemic to Problematic: Social media use and its emerging patterns among university Students in Ethiopia

From Pandemic to Problematic: Social media use and its emerging patterns among university Students in Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article From Pandemic to Problematic: Social media use and its emerging patterns among university Students in Ethiopia Haileleul Mekonnen Tilinty This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7665108/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Social media use has become an essential aspect of student life worldwide. While it offers academic and social benefits, excessive use can develop into problematic social media use (PSMU). The COVID-19 pandemic accelerated dependent on digital platforms, raising concerns that patterns established during lockdown may persist in the post-pandemic era. Despite rapid growth of internet penetration in Ethiopia, limited evidence exists on the prevalence and usage patterns of PSMU among university students. Objective To determine the prevalence of PSMU among undergraduate students at Addis Ababa University and to describe their usage patterns. Methods A cross-sectional study was conducted among regular undergraduate students at Addis Ababa University’s main campus. Participants were selected using simple random sampling and data on social media engagement and problematic use were collected using a structured questionnaire incorporating a validated PSMU screening scale. Descriptive statistics were applied to estimate prevalence and summarize usage patterns. Chi-square tests were performed to assess associations between demographic characteristics and PSMU. Results The prevalence of PSMU was 17.1% (N = 54). Gender differences were significant, female students accounted for 64.8% of PSMU cases compared to 35.2% among males. PSMU was significantly higher among (3rd year of student and department of law students). The most commonly used platforms were telegram (97.8%) followed by TikTok (70.9%) and YouTube 127 (40.2%). Conclusion PSMU is prevalent among university students, affecting nearly one in five participants in post pandemic era. Gender, field of study, and academic year were associated with variations in PSMU, highlighting the need for targeted interventions. Universities in low-resource settings should prioritize digital literacy initiatives and preventive interventions. Keywords : Problematic social media use, behavioral addition, University students, Ethiopia Psychiatry Psychology Publishing/Media Problematic social media use behavioral addition University students Ethiopia Figures Figure 1 Figure 2 Introduction Problematic social media use refers to a pattern of social media engagement characterized by excessive use that leads to negative consequences in various aspects of an individual’s life such as daily functioning or mental health( 1 ). PSMU is often associated with symptoms similar to behavioral addictions, including preoccupation with social media, loss of control over use, and continued use despite negative outcomes ( 2 ). The COVID-19 pandemic significantly altered daily routines. Lockdowns, social distancing, and the transition to online learning led to heightened reliance on digital platforms( 3 – 5 ). Many students turned to social media not only for academic purposes but also for social connection and coping with isolation( 6 ). Evidence indicates that this surge increased internet dependency and raised the risk of developing or escalating PSMU( 7 , 8 ). University students around the world increasingly rely on social media for communication, entertainment, academic work, and staying informed( 9 , 10 ). While these platforms offer many benefits, uncontrolled or excessive use may lead to problematic social media use (PSMU)( 1 ). Understanding PSMU is especially important in low- and middle-income countries, where rapid growth in internet access and smartphone penetration may outpace awareness and regulation of healthy digital habits. Globally, studies have reported widely varying rates of PSMU among university students, depending on region, measurement tools, and sample characteristics. For example, a study in South Africa (Nelson Mandela University) found that about 38% of students exhibited signs of PSMU when assessed via the Bergen Social Media Addiction Scale (BSMAS)( 11 ). Meanwhile, in the Middle East and North Africa (MENA) region, a systematic review found PSMU prevalence generally around 22–24% among studied populations( 12 ). Among adolescents in 29 countries, the prevalence of problematic social media use ranged between approximately 5% and 15%, depending on country and definition( 13 ). In Ethiopia, few studies have focused specifically on PSMU among university undergraduate students. Related work has examined internet addiction broadly in university populations; a systematic review and meta-analysis in Ethiopia found that about 43.4% of university students had problematic internet use (PIU), with factors such as online gaming, depression, and substance use being associated ( 14 ). A more recent study in southern Ethiopia during the COVID-19 pandemic assessed problematic smartphone and social media use among undergraduates; it reported elevated levels of problematic usage correlated with depression, substance use, and urban residence( 15 ). The Bergen Social Media Addiction Scale (BSMAS) has been used and validated in various cultural settings and is considered a reliable tool to identify individuals at risk of problematic social media behaviors( 16 ). Evidence from 28 studies (N = 62,406) confirms its unidimensional structure, good internal consistency (Cronbach’s α = 0.83), and construct validity through associations with anxiety, depression, internet gaming disorder, and stress ( 17 ). Despite the growing presence of social media among Ethiopian university students, empirical evidence on the prevalence and usage patterns of PSMU in the post-pandemic era is scarce. Many studies in Ethiopia focus broadly on internet use without up-to-date data on social media behavior after COVID-19. Therefore, this study aims to determine the prevalence of problematic social media use among regular undergraduate students at Addis Ababa University main campus and examine patterns of social media engagement, including daily usage duration, preferred platforms, and primary purposes of use, in the post-pandemic era. Methods Study Design and Setting An institutional based cross-sectional study conducted at Addis Ababa University main campus (AAU), the largest and oldest public university in Ethiopia. The main campus hosts thousands of undergraduate students from diverse regions and academic disciplines, providing a representative setting for exploring student behaviors and mental health concerns. Study Population The source population consisted of 1837 regular undergraduate students enrolled at AAU main campus during the academic year 2024. Students across different academic years were eligible. Those who were seriously ill at the time of data collection or unable to provide informed consent were excluded. Sample Size and Sampling Procedure The sample size was determined using a single population proportion formula, considering prevalence of problematic social media use from previous studies (0.5), a 95% confidence level, and a margin of error of 5%. After adjusting for possible non-response, the final sample was set at 350. The total student population of 1837 was divided into strata based on the 16 departments and the four academic years (second, third, fourth, and fifth year). A proportional sample size was determined for each stratum, aiming to select a total of 350 students. After determining the distribution for each stratum, simple random sampling was applied within each subgroup. Data Collection Instrument A self-reported questionnaire was used to collect the data. The social networking usage scale was adopted to capture data on the function of social media utilization( 18 ). Frequency and forms of social media use were assessed by asking participants how often they use seven popular social media platforms in Ethiopia Facebook, Telegram, Twitter, Instagram, WhatsApp, YouTube, and TikTok each day. These seven platforms were identified based on the 2024 Digital Report of Ethiopia, Data Reportal website( 19 ). Participants indicated their usage by selecting one of the following options: not at all, less than 1 hour, less than 3 hours, less than 5 hours, or more than 5 hours. The presence of problematic social media use was evaluated using the Bergen Social Media Addiction Scale (BSMAS). The Bergen Social Media Addiction Scale (BSMAS) consists of six measures that assess the fundamental components of addiction (i.e., salience, mood modification, conflict, withdrawal, tolerance, and relapse). Each question is answered on a 5-point Likert scale resulting in a score ranging from 6 to 30. The BSMAS has been translated into several languages and has shown acceptable psychometric properties across studies ( 20 ). In this study Bergen Social Media Addiction Scale (BSMAS) was adopted to measure problematic social media use. Data Collection Procedure Data were collected by trained research assistants under the supervision of the principal investigator. Questionnaires were distributed in classrooms after obtaining informed consent. Students completed the survey anonymously to encourage honest responses. Completed questionnaires were checked for completeness and consistency on the spot. Data Analysis Data were entered and analyzed using SPSS version 28. All variables in this study were categorical, and a p-value < 0.05 was considered statistically significant. Descriptive Analysis Descriptive statistics were used to summarize participants’ sociodemographic characteristics, prevalence of problematic social media use (PSMU), and patterns of social media engagement. Frequencies and percentages were calculated for all categorical variables, including sex, age group, year of study, department of study, daily social media use categories, preferred platforms, and purposes of use. The prevalence of PSMU was determined as the proportion of students meeting the cut-off on the Bergen Social Media Addiction Scale (BSMAS), with 95% confidence intervals (CI). Bivariate Analysis To examine associations between PSMU and demographic or social media usage variables: PSMU vs. Demographic Variables The Chi-square test was used to assess the association between PSMU and categorical demographic variables such as sex, year of study, faculty, and residence. Fisher’s exact test was applied when expected cell counts were less than 5. PSMU vs. Social Media Use Patterns Associations between PSMU and daily social media use categories (4 hours), preferred platforms, and purposes of use were assessed using the Chi-square test. Fisher’s exact test was used for tables with small expected frequencies. Data Management and Ethical Considerations Ethical approval was obtained from the Institutional Review Board of AAU, school of psychology. A letter was obtained from School of Psychology of Addis Ababa University. Then an official letter of support was submitted to the AAU registrar’s office and each department office of Addis Ababa University's main campus. Confidentiality was maintained at all levels of the study, and the collected information was kept in a secure place. Results Sociodemographic characteristics A total of three hundred sixteen (N = 316) regular undergraduate students from AAU main campus participated. Out of 350 participants from the initial determined sample size, ten ( 10 ) were not using any form of social media,14 participants refused to take part when they gave their consent and the remaining 10 participants had an incomplete response, leaving the final sample of 316 participants. From the participants, 22.8% (N = 72) were from the Department of Law, followed by 12.7% (N = 40) from the Department of Social Work, and 7.9% from the Department of Psychology. Table 1 shows the frequency and percentage of participating departments. More than half of the participants were male 57.3% (N = 181) and 42.7% (N = 135) were females. Figure 1 shows a pie chart of distribution of participants based on gender. The distribution of students across different years of study was 33.9% second year, 28.5% third year, 33.9% fourth year, and 3.8% fifth year. Figure 2 shows a bar chart of the level of study with respective percentages. Table 1 Department of Study of AAU Main Campus Regular Undergraduate Students Departments Frequency Percent Amharic Language 2 .6 Psychology 25 7.9 Journalism 23 7.3 Science and math 29 9.2 Social and language 22 7.0 Social work 40 12.7 Sociology 25 7.9 Special need 1 .3 Archaeology 1 .3 Education and planning 14 4.4 Foreign lang. 14 4.4 Geography 5 1.6 Law 72 22.8 Linguistic 1 .3 Oromo language 7 2.2 Political science 35 11.1 Total 316 100.0 Social Media Platforms From the social media platforms, telegram is mostly used 309(97.8%) followed by TikTok 224(70.9%) and YouTube 127(40.2%). Table 2 shows the frequency and percentage of social media platform usage. Table 2 Different Types of Social Media Platforms Social media platforms Frequency Percent 1. Telegram 309 97.8 2.Tiktok 224 70.9 3. YouTube 127 40.2 4. Instagram 70 22.2 5. Facebook 54 17.1 6. Twitter 43 13.6 7.Whatsupp 39 12.3 Purpose of Social Media Use From the participants, 99.2% (N = 314) use social media platforms to chat with friends, 98.3% (N = 311) use social media platforms to get updates on academic dates, 97.9% (N = 310) participant use social media for social networking, 97% (N = 307) participants use social media to watch movies and 20.5% (N = 65) use social media to watch pornography. Table 3 shows the frequency and percentage of social media use purpose among the participants. Table 3 Purpose of Social media use Social media function Frequency Percent 1. Utilizing social media for dating 290 93.8 2. To communicate with relatives 298 94 3.To chat with friends 314 99.2 4.For social networking 310 97.9 5.To consult lectures 305 96.3 6.To prepare for exams 124 39.1 7.To get updates on academic’s dates 311 98.3 8.To watch music videos 300 94.8 9.To watch movies 307 97.0 10. To watch pornography 65 20.5 11. To publish online content 269 85.1 Prevalence of Problematic Social Media Use As of now, there is no standard cutoff point for social media users to say it is problematic or not, but most of the researchers use a cutoff point of 19 and 24 based on the Bergen Social Media Addiction Scale ( 2 ). A study done in Hungary among a Large-Scale Nationally Representative Adolescent Sample tested different cut points to classify PSMU and a cut point of 19 gave a sensitivity of 83%, 99% specificity, 73% PPV, 99% NPV and 98% of accuracy, with this measurement they recommend nineteen ( 19 ) as an ideal cut point to classify as at risks of PSMU ( 2 ). In this study using a cutoff point of 19 on the Bergen social media addiction scale (BSMAS), 54 participants (17.1%) were classified as problematic social media users. Table 4 The Frequency and Percentage of Problematic Social Media Use. Social Media Use Score Frequency Percent% Non Problematic Social media Use 262 82.9% Problematic Social Media Use 54 17.1% The distribution of Problematic Social Media Use (PSMU) among different demographic factors reveals significant variation. Among the participants, 35.2%(N = 19) of the total male participants, exhibit signs of problematic social media use. In contrast, 64.8% (N = 35) of the total female participants, are affected by problematic social media use. The prevalence of problematic social media use varies significantly across different departments. The Law department has the highest number of PSMU cases, with 22.2% (N = 12) students affected. Following is the Social Work department with 13%(N = 7), Journalism, Science and Mathematics and Education & Planning departments, accounts 9.3% (N = 5). This distribution suggests that certain fields of study may be more susceptible to problematic social media use, possibly due to varying academic pressures or social environments. Considering the year of study, the 2nd-year students show a prevalence of 17 problematic social media use cases, which accounts for 31.5% of this group. The 3rd-year students have the highest number of cases, with 20 students affected, representing 37% of the total. In the category of 4th year and above, there are 17 PSMU cases, also making up 31.5% of the students in this category. This data indicates that PSMU is relatively evenly distributed across different years of study, though 3rd-year students exhibit a slightly higher tendency towards problematic use. Table 5 shows distribution of PSMU among different sociodemographic factors. Table 5 Distribution of Problematic Social Media Use Among Different Demographic Factors Demographic Factor Category PSMU Cases Percent of PSMU Cases Sex Male 19 35.2% Female 35 64.8% Department of Study Law 12 22.2% Social Work 7 13% Journalism 5 9.3% Science and Mathematics 5 9.3% Education & planning 5 9.3% Psychology 4 7.4% Year of Study 2nd Year 17 31.5% 3rd Year 20 37% 4th year and above 17 31.5% DISCUSSION This study found that 17.1% of the participants show problematic social media use (PSMU), as measured by the Bergen Social Media Addiction Scale (BSMAS). Although the rates vary, this prevalence is consistent with other studies conducted in different regions. For instance, a survey done in the U.S. among young adults found that 44% of the adults were using social media problematically, which is significantly higher than this finding( 21 ). A 2025 systematic review & meta-analysis on global prevalence of social media addiction among university students found a pooled global prevalence of 18.4% (95% CI: 14.7–22.6%) for social media addiction among university students which is similar with this study( 22 ). In contrast, a study done among Hungarian university students reported a problematic social media use prevalence of 4.5%, which is lower than this finding ( 2 ). The higher prevalence observed in this study could be due to the increasing accessibility of smartphones, the majority of university students' widespread use of social media, as well as the university's constant access to WIFI, both of which may contribute to increased rates of problematic usage. Due to a variety of methodological problems, including convenience sampling, focusing mostly on college students, and/or having small sample sizes, earlier research revealed a broad range of prevalence rates( 23 – 25 ). For example, 47% of Malaysian college students reported PSMU( 26 ). Additionally, the prevalence variation might also have resulted from the scale used to assess social media use, the cutoff point used to classify participants as problematic and non-problematic can also contribute to the significant difference among studies. The post-pandemic context appears to have amplified social media engagement. Lockdowns and the shift to online learning during COVID-19 likely normalized prolonged use, a trend that persists even after the return to in-person instruction. This observation supports previous research indicating that digital habits formed during the pandemic may persist and contribute to ongoing behavioral and mental health risks( 27 ). Gender and PSMU One of the findings in this study is the significant gender difference in problematic social media use. Female students were more affected (64.8%) than male students (35.2%), despite males being the majority in the sample. Some studies indicate that females are more vulnerable to excessive social networking use due to their stronger preference for social interaction and emotional sharing online( 28 ). Conversely, other reports highlight higher prevalence among males, often linked to online gaming and pornography use ( 29 ). In the Ethiopian context, the relatively higher PSMU among females may reflect cultural dynamics where online communication compensates for offline social restrictions, or where social media becomes a primary means for academic and relational engagement. Academic Departments and PSMU Another important observation is the variation of PSMU across academic departments. Students from the Law department showed the highest prevalence (22.2%), followed by Social Work and Journalism. Previous literature indicates that students in disciplines with high workloads, competitive environments, or greater reliance on social connectedness are more prone to maladaptive social media use ( 30 ). The higher prevalence among Law students might therefore be explained by the demanding academic environment, stress management challenges, and possibly the use of social platforms as a coping strategy. This departmental variation highlights the need for targeted awareness and intervention programs within specific faculties. Year of Study and PSMU The distribution of problematic use across years of study was relatively even, though 3rd-year students reported the highest prevalence (37%). Transitional stressors, such as increased academic demands and identity formation processes, may explain this pattern. Previous studies have shown that middle years in higher education often coincide with elevated stress levels, academic pressure, and uncertainty about future careers, which may predispose students to maladaptive coping strategies including excessive social media use ( 31 ). Social Media Platforms and Purpose of Use Consistent with national trends, Telegram emerged as the most widely used platform (97.8%), followed by TikTok and YouTube. Telegram’s dominance reflects its accessibility, affordability, and centrality in academic communication in Ethiopia. TikTok’s high prevalence is particularly notable, aligning with global evidence that short-form video platforms are increasingly addictive among young populations ( 32 ).Regarding purpose of use, chatting with friends, accessing academic updates, and social networking were nearly universal. Interestingly, a small but meaningful proportion (20.5%) of participants reported using social media for pornography, a finding that resonates with global concerns about risky online behaviors and their potential psychological consequences. Implications The observed prevalence of PSMU (17.1%) raises concerns for university administrators, mental health professionals, and policymakers. Excessive social media use has been linked to sleep disturbances, reduced academic performance, anxiety, and depression( 28 ). Given that nearly one in five students are at risk, interventions are urgently required. These may include digital literacy campaigns, peer support groups, counseling services, and integration of psychoeducation into university curricula. Furthermore, gender- and department-specific interventions may be more effective, recognizing the unique vulnerabilities identified in this study. Limitations This study has several limitations. First, the cross-sectional design precludes causal inferences between social media use and problematic patterns. Second, reliance on self-reported measures may be subject to recall bias and social desirability bias. Third, the study focused on a single university, limiting generalizability to other Ethiopian contexts. Nevertheless, the use of a validated measurement tool (BSMAS) and the inclusion of a relatively large sample size strengthen the validity of the findings. Conclusion Problematic social media use is prevalent among undergraduate students at Addis Ababa University, with post-pandemic behavioral shifts contributing to sustained high engagement. Students spend significant time on platforms such as Telegram, TikTok and YouTube primarily for entertainment, academic purposes, and social connection. The findings not only align with global patterns but also reveals on unique contextual dynamics in Ethiopia. There is a clear need for preventive strategies and interventions to address this emerging mental health and academic challenge. Abbreviations AAU Addis Ababa University AOR Adjusted Odds Ratio BSMAS Bergen’s Social Media Addiction Scale CI Confidence Interval EDPM Education and Planning Management NPV Negative Predictive Value PPV Positive Predictive Value PSMU Problematic social media use SPSS Software Program for Social Science USA United States of America Declarations Author Contributions Statement Haileleul Mekonnen Tilinty: Led the research, including the study design, data collection, data analysis, manuscript drafting, and revision. Managed research coordination and ensured overall quality and integrity of the research. Ethics approval and consent to participate The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the (8) of 1975, as revised in 2013. All procedures involving human subjects were approved by the scientific committee of Addis Ababa University, School of Psychology. All participants provided written informed consent before taking part in the survey. Participants were fully informed about the purpose of the study, the procedures involved, and any potential risks or benefits. Participation was entirely voluntary, and participants were assured that their responses would remain confidential and used solely for research purposes. Consent for publication Not applicable Authorship I have read the journal policies on author responsibilities and submit this manuscript in accordance with those policies. Third Party Material All of the material is owned by the authors and/or no permissions are required. Dual Publication The results/data/figures in this manuscript have not been published elsewhere, nor are they under consideration by another publisher. Availability of data and materials The data and materials used in this study are available upon reasonable request. Due to privacy concerns and institutional policies, the data cannot be made publicly accessible. Interested parties may contact [email protected] to request access to the data and materials. Competing interests The author declare that they have no competing interests. Clinical trial number Not applicable. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not for profit sectors. All expenses related to the study, including data collection, analysis, and manuscript preparation, were self-funded. Acknowledgement Not applicable References Andreassen C, Pallesen S. Social Network Site Addiction - An Overview. Curr Pharm Des. 2014 June 31;20(25):4053–61. Bányai F, Zsila Á, Király O, Maraz A, Elekes Z, Griffiths MD, et al. Problematic Social Media Use: Results from a Large-Scale Nationally Representative Adolescent Sample. Jiménez-Murcia S, editor. PLOS ONE. 2017 Jan 9;12(1):e0169839. Iivari N, Sharma S, Ventä-Olkkonen L. Digital transformation of everyday life – How COVID-19 pandemic transformed the basic education of the young generation and why information management research should care? Int J Inf Manag. 2020 Dec;55:102183. Liu Q, Mo S. Is Social Distancing Law the New Normal? Forced Shift to Media Online Learning and Its Effectiveness: A Moderating Role of Student Engagement During the Pandemic of COVID-19. Front Psychol. 2022 June 17;13:923996. Parker K, Uddin R, Ridgers ND, Brown H, Veitch J, Salmon J, et al. The Use of Digital Platforms for Adults’ and Adolescents’ Physical Activity During the COVID-19 Pandemic (Our Life at Home): Survey Study. J Med Internet Res. 2021 Feb 1;23(2):e23389. Ghanayem LK, Shannon H, Khodr L, McQuaid RJ, Hellemans KGC. Lonely and scrolling during the COVID-19 pandemic: understanding the problematic social media use and mental health link among university students. Front Psychiatry. 2024 Jan 31;15:1247807. Casale S, Akbari M, Seydavi M, Bocci Benucci S, Fioravanti G. Has the prevalence of problematic social media use increased over the past seven years and since the start of the COVID-19 pandemic? A meta-analysis of the studies published since the development of the Bergen social media addiction scale. Addict Behav. 2023 Dec;147:107838. Ozturk FO, Ayaz-Alkaya S. Internet addiction and psychosocial problems among adolescents during the COVID-19 pandemic: A cross-sectional study. Arch Psychiatr Nurs. 2021 Dec;35(6):595–601. Legaree BA. Considering the changing face of social media in higher education. Yeoman K, editor. FEMS Microbiol Lett. 2015 Aug;362(16):fnv128. Chowdhury EK. Examining the benefits and drawbacks of social media usage on academic performance: a study among university students in Bangladesh. J Res Innov Teach Learn [Internet]. 2024 Feb 8 [cited 2025 Sept 14]; Available from: https://www.emerald.com/insight/content/doi/10.1108/JRIT-07-2023-0097/full/html Mostert N. Exploring the prevalence of problematic smartphone use and problematic social media use amongst students at a South African University. Soc Sci Humanit Open. 2025;12:101778. Abbouyi S, Bouazza S, El Kinany S, El Rhazi K, Zarrouq B. Depression and anxiety and its association with problematic social media use in the MENA region: a systematic review. Egypt J Neurol Psychiatry Neurosurg. 2024 Feb 1;60(1):15. Boer M, Van Den Eijnden RJJM, Boniel-Nissim M, Wong SL, Inchley JC, Badura P, et al. Adolescents’ Intense and Problematic Social Media Use and Their Well-Being in 29 Countries. J Adolesc Health. 2020 June;66(6):S89–99. Atalay YA. Prevalence of internet addiction and associated factors among university students in Ethiopia: systematic review and meta-analysis. Front Digit Health. 2024 Sept 11;6:1373735. Mengistu N, Habtamu E, Kassaw C, Madoro D, Molla W, Wudneh A, et al. Problematic smartphone and social media use among undergraduate students during the COVID-19 pandemic: In the case of southern Ethiopia universities. Zou D, editor. PLOS ONE. 2023 Jan 25;18(1):e0280724. Zarate D, Hobson BA, March E, Griffiths MD, Stavropoulos V. Psychometric properties of the Bergen Social Media Addiction Scale: An analysis using item response theory. Addict Behav Rep. 2023 June;17:100473. Bottaro R, Griffiths MD, Faraci P. Meta-analysis of Reliability and Validity of the Bergen Social Media Addiction Scale (BSMAS). Int J Ment Health Addict [Internet]. 2025 Mar 8 [cited 2025 Sept 14]; Available from: https://link.springer.com/10.1007/s11469-025-01461-x Gupta S, Bashir L. Social Networking Usage Questionnaire: Development and Validation in an Indian Higher Education Context. Turk Online J Distance Educ. 2018 Oct 18;214–27. Digital 2024: Ethiopia — DataReportal – Global Digital Insights [Internet]. [cited 2025 Sept 14]. Available from: https://datareportal.com/reports/digital-2024-ethiopia Andreassen CS, Torsheim T, Brunborg GS, Pallesen S. Development of a Facebook Addiction Scale. Psychol Rep. 2012 Apr;110(2):501–17. Shensa A, Escobar-Viera CG, Sidani JE, Bowman ND, Marshal MP, Primack BA. Problematic social media use and depressive symptoms among U.S. young adults: A nationally-representative study. Soc Sci Med. 2017 June;182:150–7. Salari N, Zarei H, Hosseinian-Far A, Rasoulpoor S, Shohaimi S, Mohammadi M. The global prevalence of social media addiction among university students: a systematic review and meta-analysis. J Public Health. 2025 Jan;33(1):223–36. Wilson K, Fornasier S, White KM. Psychological Predictors of Young Adults’ Use of Social Networking Sites. Cyberpsychology Behav Soc Netw. 2010 Apr;13(2):173–7. Wolniczak I, Cáceres-DelAguila JA, Palma-Ardiles G, Arroyo KJ, Solís-Visscher R, Paredes-Yauri S, et al. Association between Facebook Dependence and Poor Sleep Quality: A Study in a Sample of Undergraduate Students in Peru. Schuelke M, editor. PLoS ONE. 2013 Mar 12;8(3):e59087. Cheng C, Lau Y ching, Chan L, Luk JW. Prevalence of social media addiction across 32 nations: Meta-analysis with subgroup analysis of classification schemes and cultural values. Addict Behav. 2021 June;117:106845. Univeristi Teknologi Malaysia. He is also with Department of Computer, Damavand Branch, Islamic Azad University, Damavand, Iran, Jafarkarimi H, Sim ATH, the Department of Information Systems, Universiti Teknologi Malaysia, Malaysia, Saadatdoost R, the Department of Computer and Information Technology, Parand Branch, Islamic Azad University, Parand, Iran, et al. Facebook Addiction among Malaysian Students. Int J Inf Educ Technol. 2016;6(6):465–9. Haucke M, Liu S, Heinzel S. The Persistence of the Impact of COVID-19–Related Distress, Mood Inertia, and Loneliness on Mental Health During a Postlockdown Period in Germany: An Ecological Momentary Assessment Study. JMIR Ment Health. 2021 Aug 26;8(8):e29419. Andreassen CS. Online Social Network Site Addiction: A Comprehensive Review. Curr Addict Rep. 2015 June;2(2):175–84. Kuss D, Griffiths M. Social Networking Sites and Addiction: Ten Lessons Learned. Int J Environ Res Public Health. 2017 Mar 17;14(3):311. Müller KW, Dreier M, Beutel ME, Duven E, Giralt S, Wölfling K. A hidden type of internet addiction? Intense and addictive use of social networking sites in adolescents. Comput Hum Behav. 2016 Feb;55:172–7. Elhai JD, Levine JC, Dvorak RD, Hall BJ. Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use. Comput Hum Behav. 2016 Oct;63:509–16. Montag C, Yang H, Elhai JD. On the Psychology of TikTok Use: A First Glimpse From Empirical Findings. Front Public Health. 2021 Mar 16;9:641673. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Tilinty","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0002-5767-4105","institution":"Addis Ababa university","correspondingAuthor":true,"prefix":"","firstName":"Haileleul","middleName":"Mekonnen","lastName":"Tilinty","suffix":""}],"badges":[],"createdAt":"2025-09-20 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08:29:15","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101008,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7665108/v1/2fd70cbd9b2355ec6acefbaf.html"},{"id":91966682,"identity":"858dcab1-9b37-4a4a-90e1-03c8cf8d3fb7","added_by":"auto","created_at":"2025-09-23 08:29:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49049,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eA Pie Chart of Distribution of Participants Based on Gender.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7665108/v1/b27637455ad389e06f94a6e0.png"},{"id":91966680,"identity":"89f5d8f1-87f9-46c5-b89b-2a675f75258d","added_by":"auto","created_at":"2025-09-23 08:29:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35568,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eBar chart of level of study\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7665108/v1/0982a307668908226af32b7f.png"},{"id":91968563,"identity":"3a2f7ce3-97e7-45d3-b9ae-8597116ed556","added_by":"auto","created_at":"2025-09-23 08:45:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":975821,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7665108/v1/bf9251a2-a6ed-49a8-9695-ed4f8cb4aa42.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eFrom Pandemic to Problematic: Social media use and its emerging patterns among university Students in Ethiopia\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProblematic social media use refers to a pattern of social media engagement characterized by excessive use that leads to negative consequences in various aspects of an individual\u0026rsquo;s life such as daily functioning or mental health(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). PSMU is often associated with symptoms similar to behavioral addictions, including preoccupation with social media, loss of control over use, and continued use despite negative outcomes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe COVID-19 pandemic significantly altered daily routines. Lockdowns, social distancing, and the transition to online learning led to heightened reliance on digital platforms(\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Many students turned to social media not only for academic purposes but also for social connection and coping with isolation(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Evidence indicates that this surge increased internet dependency and raised the risk of developing or escalating PSMU(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUniversity students around the world increasingly rely on social media for communication, entertainment, academic work, and staying informed(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). While these platforms offer many benefits, uncontrolled or excessive use may lead to problematic social media use (PSMU)(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Understanding PSMU is especially important in low- and middle-income countries, where rapid growth in internet access and smartphone penetration may outpace awareness and regulation of healthy digital habits.\u003c/p\u003e\u003cp\u003eGlobally, studies have reported widely varying rates of PSMU among university students, depending on region, measurement tools, and sample characteristics. For example, a study in South Africa (Nelson Mandela University) found that about 38% of students exhibited signs of PSMU when assessed via the Bergen Social Media Addiction Scale (BSMAS)(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Meanwhile, in the Middle East and North Africa (MENA) region, a systematic review found PSMU prevalence generally around 22\u0026ndash;24% among studied populations(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Among adolescents in 29 countries, the prevalence of problematic social media use ranged between approximately 5% and 15%, depending on country and definition(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn Ethiopia, few studies have focused specifically on PSMU among university undergraduate students. Related work has examined internet addiction broadly in university populations; a systematic review and meta-analysis in Ethiopia found that about 43.4% of university students had problematic internet use (PIU), with factors such as online gaming, depression, and substance use being associated (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). A more recent study in southern Ethiopia during the COVID-19 pandemic assessed problematic smartphone and social media use among undergraduates; it reported elevated levels of problematic usage correlated with depression, substance use, and urban residence(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Bergen Social Media Addiction Scale (BSMAS) has been used and validated in various cultural settings and is considered a reliable tool to identify individuals at risk of problematic social media behaviors(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Evidence from 28 studies (N\u0026thinsp;=\u0026thinsp;62,406) confirms its unidimensional structure, good internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.83), and construct validity through associations with anxiety, depression, internet gaming disorder, and stress (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite the growing presence of social media among Ethiopian university students, empirical evidence on the prevalence and usage patterns of PSMU in the post-pandemic era is scarce. Many studies in Ethiopia focus broadly on internet use without up-to-date data on social media behavior after COVID-19.\u003c/p\u003e\u003cp\u003eTherefore, this study aims to determine the prevalence of problematic social media use among regular undergraduate students at Addis Ababa University main campus and examine patterns of social media engagement, including daily usage duration, preferred platforms, and primary purposes of use, in the post-pandemic era.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Setting\u003c/h2\u003e\u003cp\u003eAn institutional based cross-sectional study conducted at Addis Ababa University main campus (AAU), the largest and oldest public university in Ethiopia. The main campus hosts thousands of undergraduate students from diverse regions and academic disciplines, providing a representative setting for exploring student behaviors and mental health concerns.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eThe source population consisted of 1837 regular undergraduate students enrolled at AAU main campus during the academic year 2024. Students across different academic years were eligible. Those who were seriously ill at the time of data collection or unable to provide informed consent were excluded.\u003c/p\u003e\n\u003ch3\u003eSample Size and Sampling Procedure\u003c/h3\u003e\n\u003cp\u003eThe sample size was determined using a single population proportion formula, considering prevalence of problematic social media use from previous studies (0.5), a 95% confidence level, and a margin of error of 5%. After adjusting for possible non-response, the final sample was set at 350.\u003c/p\u003e\u003cp\u003eThe total student population of 1837 was divided into strata based on the 16 departments and the four academic years (second, third, fourth, and fifth year). A proportional sample size was determined for each stratum, aiming to select a total of 350 students. After determining the distribution for each stratum, simple random sampling was applied within each subgroup.\u003c/p\u003e\n\u003ch3\u003eData Collection Instrument\u003c/h3\u003e\n\u003cp\u003eA self-reported questionnaire was used to collect the data. The social networking usage scale was adopted to capture data on the function of social media utilization(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFrequency and forms of social media use were assessed by asking participants how often they use seven popular social media platforms in Ethiopia Facebook, Telegram, Twitter, Instagram, WhatsApp, YouTube, and TikTok each day. These seven platforms were identified based on the 2024 Digital Report of Ethiopia, Data Reportal website(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Participants indicated their usage by selecting one of the following options: not at all, less than 1 hour, less than 3 hours, less than 5 hours, or more than 5 hours.\u003c/p\u003e\u003cp\u003eThe presence of problematic social media use was evaluated using the Bergen Social Media Addiction Scale (BSMAS). The Bergen Social Media Addiction Scale (BSMAS) consists of six measures that assess the fundamental components of addiction (i.e., salience, mood modification, conflict, withdrawal, tolerance, and relapse). Each question is answered on a 5-point Likert scale resulting in a score ranging from 6 to 30. The BSMAS has been translated into several languages and has shown acceptable psychometric properties across studies (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In this study Bergen Social Media Addiction Scale (BSMAS) was adopted to measure problematic social media use.\u003c/p\u003e\n\u003ch3\u003eData Collection Procedure\u003c/h3\u003e\n\u003cp\u003eData were collected by trained research assistants under the supervision of the principal investigator. Questionnaires were distributed in classrooms after obtaining informed consent. Students completed the survey anonymously to encourage honest responses. Completed questionnaires were checked for completeness and consistency on the spot.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eData were entered and analyzed using SPSS version 28. All variables in this study were categorical, and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003eDescriptive Analysis\u003c/p\u003e\u003cp\u003eDescriptive statistics were used to summarize participants\u0026rsquo; sociodemographic characteristics, prevalence of problematic social media use (PSMU), and patterns of social media engagement.\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eFrequencies and percentages were calculated for all categorical variables, including sex, age group, year of study, department of study, daily social media use categories, preferred platforms, and purposes of use.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThe prevalence of PSMU was determined as the proportion of students meeting the cut-off on the Bergen Social Media Addiction Scale (BSMAS), with 95% confidence intervals (CI).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eBivariate Analysis\u003c/p\u003e\u003cp\u003eTo examine associations between PSMU and demographic or social media usage variables:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003ePSMU vs. Demographic Variables\u003cul type=\"circle\"\u003e\n \u003cli\u003eThe Chi-square test was used to assess the association between PSMU and categorical demographic variables such as sex, year of study, faculty, and residence.\u003c/li\u003e\n \u003cli\u003eFisher\u0026rsquo;s exact test was applied when expected cell counts were less than 5.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003ePSMU vs. Social Media Use Patterns\u003cul type=\"circle\"\u003e\n \u003cli\u003eAssociations between PSMU and daily social media use categories (\u0026lt;2 hours, 2\u0026ndash;4 hours, \u0026gt;4 hours), preferred platforms, and purposes of use were assessed using the Chi-square test.\u003c/li\u003e\n \u003cli\u003eFisher\u0026rsquo;s exact test was used for tables with small expected frequencies.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n\u003c/ol\u003e\u003c/div\u003e\n\u003ch3\u003eData Management and Ethical Considerations\u003c/h3\u003e\n\u003cp\u003eEthical approval was obtained from the Institutional Review Board of AAU, school of psychology. A letter was obtained from School of Psychology of Addis Ababa University. Then an official letter of support was submitted to the AAU registrar\u0026rsquo;s office and each department office of Addis Ababa University's main campus. Confidentiality was maintained at all levels of the study, and the collected information was kept in a secure place.\u003c/p\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSociodemographic characteristics\u003c/h2\u003e\u003cp\u003eA total of three hundred sixteen (N\u0026thinsp;=\u0026thinsp;316) regular undergraduate students from AAU main campus participated. Out of 350 participants from the initial determined sample size, ten (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) were not using any form of social media,14 participants refused to take part when they gave their consent and the remaining 10 participants had an incomplete response, leaving the final sample of 316 participants.\u003c/p\u003e\u003cp\u003eFrom the participants, 22.8% (N\u0026thinsp;=\u0026thinsp;72) were from the Department of Law, followed by 12.7% (N\u0026thinsp;=\u0026thinsp;40) from the Department of Social Work, and 7.9% from the Department of Psychology. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the frequency and percentage of participating departments.\u003c/p\u003e\u003cp\u003eMore than half of the participants were male 57.3% (N\u0026thinsp;=\u0026thinsp;181) and 42.7% (N\u0026thinsp;=\u0026thinsp;135) were females. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows a pie chart of distribution of participants based on gender.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe distribution of students across different years of study was 33.9% second year, 28.5% third year, 33.9% fourth year, and 3.8% fifth year. Figure\u0026nbsp;2 shows a bar chart of the level of study with respective percentages.\u003c/p\u003e\u003cp\u003e\u003cem\u003eTable 1 Department of Study of AAU Main Campus Regular Undergraduate Students\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepartments\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAmharic Language\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePsychology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eJournalism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eScience and math\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e9.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSocial and language\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSocial work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e12.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSociology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSpecial need\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eArchaeology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eEducation and planning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e4.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eForeign lang.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e4.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eGeography\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLaw\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e22.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLinguistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eOromo language\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePolitical science\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eSocial Media Platforms\u003c/h2\u003e\u003cp\u003eFrom the social media platforms, telegram is mostly used 309(97.8%) followed by TikTok 224(70.9%) and YouTube 127(40.2%). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the frequency and percentage of social media platform usage.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eDifferent Types of Social Media Platforms\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial media platforms\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1. Telegram\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e97.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2.Tiktok\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3. YouTube\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4. Instagram\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5. Facebook\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6. Twitter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.Whatsupp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003ePurpose of Social Media Use\u003c/h2\u003e\u003cp\u003eFrom the participants, 99.2% (N\u0026thinsp;=\u0026thinsp;314) use social media platforms to chat with friends, 98.3% (N\u0026thinsp;=\u0026thinsp;311) use social media platforms to get updates on academic dates, 97.9% (N\u0026thinsp;=\u0026thinsp;310) participant use social media for social networking, 97% (N\u0026thinsp;=\u0026thinsp;307) participants use social media to watch movies and 20.5% (N\u0026thinsp;=\u0026thinsp;65) use social media to watch pornography. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the frequency and percentage of social media use purpose among the participants.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003ePurpose of Social media use\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial media function\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1. Utilizing social media for dating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e290\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2. To communicate with relatives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3.To chat with friends\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4.For social networking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e97.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.To consult lectures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6.To prepare for exams\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.To get updates on academic\u0026rsquo;s dates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e311\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8.To watch music videos\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9.To watch movies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e97.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10. To watch pornography\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11. To publish online content\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e269\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003ePrevalence of Problematic Social Media Use\u003c/h2\u003e\u003cp\u003eAs of now, there is no standard cutoff point for social media users to say it is problematic or not, but most of the researchers use a cutoff point of 19 and 24 based on the Bergen Social Media Addiction Scale (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). A study done in Hungary among a Large-Scale Nationally Representative Adolescent Sample tested different cut points to classify PSMU and a cut point of 19 gave a sensitivity of 83%, 99% specificity, 73% PPV, 99% NPV and 98% of accuracy, with this measurement they recommend nineteen (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) as an ideal cut point to classify as at risks of PSMU (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study using a cutoff point of 19 on the Bergen social media addiction scale (BSMAS), 54 participants (17.1%) were classified as problematic social media users.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eThe Frequency and Percentage of Problematic Social Media Use.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Media Use Score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercent%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon Problematic Social media Use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProblematic Social Media Use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe distribution of Problematic Social Media Use (PSMU) among different demographic factors reveals significant variation. Among the participants, 35.2%(N\u0026thinsp;=\u0026thinsp;19) of the total male participants, exhibit signs of problematic social media use. In contrast, 64.8% (N\u0026thinsp;=\u0026thinsp;35) of the total female participants, are affected by problematic social media use.\u003c/p\u003e\u003cp\u003eThe prevalence of problematic social media use varies significantly across different departments. The Law department has the highest number of PSMU cases, with 22.2% (N\u0026thinsp;=\u0026thinsp;12) students affected. Following is the Social Work department with 13%(N\u0026thinsp;=\u0026thinsp;7), Journalism, Science and Mathematics and Education \u0026amp; Planning departments, accounts 9.3% (N\u0026thinsp;=\u0026thinsp;5). This distribution suggests that certain fields of study may be more susceptible to problematic social media use, possibly due to varying academic pressures or social environments.\u003c/p\u003e\u003cp\u003eConsidering the year of study, the 2nd-year students show a prevalence of 17 problematic social media use cases, which accounts for 31.5% of this group. The 3rd-year students have the highest number of cases, with 20 students affected, representing 37% of the total. In the category of 4th year and above, there are 17 PSMU cases, also making up 31.5% of the students in this category. This data indicates that PSMU is relatively evenly distributed across different years of study, though 3rd-year students exhibit a slightly higher tendency towards problematic use. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows distribution of PSMU among different sociodemographic factors.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eDistribution of Problematic Social Media Use Among Different Demographic Factors\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic Factor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePSMU Cases\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent of PSMU Cases\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64.8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepartment of Study\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLaw\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSocial Work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJournalism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScience and Mathematics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation \u0026amp; planning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePsychology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear of Study\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2nd Year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3rd Year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4th year and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study found that 17.1% of the participants show problematic social media use (PSMU), as measured by the Bergen Social Media Addiction Scale (BSMAS). Although the rates vary, this prevalence is consistent with other studies conducted in different regions. For instance, a survey done in the U.S. among young adults found that 44% of the adults were using social media problematically, which is significantly higher than this finding(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). A 2025 systematic review \u0026amp; meta-analysis on global prevalence of social media addiction among university students found a pooled global prevalence of 18.4% (95% CI: 14.7\u0026ndash;22.6%) for social media addiction among university students which is similar with this study(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn contrast, a study done among Hungarian university students reported a problematic social media use prevalence of 4.5%, which is lower than this finding (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe higher prevalence observed in this study could be due to the increasing accessibility of smartphones, the majority of university students' widespread use of social media, as well as the university's constant access to WIFI, both of which may contribute to increased rates of problematic usage.\u003c/p\u003e\u003cp\u003eDue to a variety of methodological problems, including convenience sampling, focusing mostly on college students, and/or having small sample sizes, earlier research revealed a broad range of prevalence rates(\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). For example, 47% of Malaysian college students reported PSMU(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAdditionally, the prevalence variation might also have resulted from the scale used to assess social media use, the cutoff point used to classify participants as problematic and non-problematic can also contribute to the significant difference among studies.\u003c/p\u003e\u003cp\u003eThe post-pandemic context appears to have amplified social media engagement. Lockdowns and the shift to online learning during COVID-19 likely normalized prolonged use, a trend that persists even after the return to in-person instruction. This observation supports previous research indicating that digital habits formed during the pandemic may persist and contribute to ongoing behavioral and mental health risks(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eGender and PSMU\u003c/h2\u003e\u003cp\u003eOne of the findings in this study is the significant gender difference in problematic social media use. Female students were more affected (64.8%) than male students (35.2%), despite males being the majority in the sample. Some studies indicate that females are more vulnerable to excessive social networking use due to their stronger preference for social interaction and emotional sharing online(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Conversely, other reports highlight higher prevalence among males, often linked to online gaming and pornography use (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In the Ethiopian context, the relatively higher PSMU among females may reflect cultural dynamics where online communication compensates for offline social restrictions, or where social media becomes a primary means for academic and relational engagement.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eAcademic Departments and PSMU\u003c/h2\u003e\u003cp\u003eAnother important observation is the variation of PSMU across academic departments. Students from the Law department showed the highest prevalence (22.2%), followed by Social Work and Journalism. Previous literature indicates that students in disciplines with high workloads, competitive environments, or greater reliance on social connectedness are more prone to maladaptive social media use (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The higher prevalence among Law students might therefore be explained by the demanding academic environment, stress management challenges, and possibly the use of social platforms as a coping strategy. This departmental variation highlights the need for targeted awareness and intervention programs within specific faculties.\u003c/p\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003eYear of Study and PSMU\u003c/h2\u003e\u003cp\u003eThe distribution of problematic use across years of study was relatively even, though 3rd-year students reported the highest prevalence (37%). Transitional stressors, such as increased academic demands and identity formation processes, may explain this pattern. Previous studies have shown that middle years in higher education often coincide with elevated stress levels, academic pressure, and uncertainty about future careers, which may predispose students to maladaptive coping strategies including excessive social media use (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eSocial Media Platforms and Purpose of Use\u003c/h2\u003e\u003cp\u003eConsistent with national trends, Telegram emerged as the most widely used platform (97.8%), followed by TikTok and YouTube. Telegram\u0026rsquo;s dominance reflects its accessibility, affordability, and centrality in academic communication in Ethiopia. TikTok\u0026rsquo;s high prevalence is particularly notable, aligning with global evidence that short-form video platforms are increasingly addictive among young populations (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).Regarding purpose of use, chatting with friends, accessing academic updates, and social networking were nearly universal. Interestingly, a small but meaningful proportion (20.5%) of participants reported using social media for pornography, a finding that resonates with global concerns about risky online behaviors and their potential psychological consequences.\u003c/p\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003eImplications\u003c/h2\u003e\u003cp\u003eThe observed prevalence of PSMU (17.1%) raises concerns for university administrators, mental health professionals, and policymakers. Excessive social media use has been linked to sleep disturbances, reduced academic performance, anxiety, and depression(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Given that nearly one in five students are at risk, interventions are urgently required. These may include digital literacy campaigns, peer support groups, counseling services, and integration of psychoeducation into university curricula. Furthermore, gender- and department-specific interventions may be more effective, recognizing the unique vulnerabilities identified in this study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study has several limitations. First, the cross-sectional design precludes causal inferences between social media use and problematic patterns. Second, reliance on self-reported measures may be subject to recall bias and social desirability bias. Third, the study focused on a single university, limiting generalizability to other Ethiopian contexts. Nevertheless, the use of a validated measurement tool (BSMAS) and the inclusion of a relatively large sample size strengthen the validity of the findings.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eProblematic social media use is prevalent among undergraduate students at Addis Ababa University, with post-pandemic behavioral shifts contributing to sustained high engagement. Students spend significant time on platforms such as Telegram, TikTok and YouTube primarily for entertainment, academic purposes, and social connection. The findings not only align with global patterns but also reveals on unique contextual dynamics in Ethiopia. There is a clear need for preventive strategies and interventions to address this emerging mental health and academic challenge.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eAAU\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAddis Ababa University\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eAOR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eBSMAS\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBergen\u0026rsquo;s Social Media Addiction Scale\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eEDPM\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEducation and Planning Management\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eNPV\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNegative Predictive Value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ePPV\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePositive Predictive Value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ePSMU\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProblematic social media use\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eSPSS\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSoftware Program for Social Science\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eUSA\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHaileleul Mekonnen Tilinty: Led the research, including the study design, data collection, data analysis, manuscript drafting, and revision. Managed research coordination and ensured overall quality and integrity of the research. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the\u0026nbsp;\u003c/em\u003e\u003ca href=\"https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/\"\u003e\u003cem\u003e(8)\u003c/em\u003e\u003c/a\u003e\u003cem\u003e\u0026nbsp;of 1975, as revised in 2013. All procedures involving human subjects were approved by\u0026nbsp;\u003c/em\u003ethe scientific committee of Addis Ababa University, School of Psychology.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll participants provided written informed consent before taking part in the survey. Participants were fully informed about the purpose of the study, the procedures involved, and any potential risks or benefits. Participation was entirely voluntary, and participants were assured that their responses would remain confidential and used solely for research purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI have read the journal policies on author responsibilities and submit this manuscript in accordance with those policies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThird Party Material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll of the material is owned by the authors and/or no permissions are required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDual Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results/data/figures in this manuscript have not been published elsewhere, nor are they under consideration by another publisher.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data and materials used in this study are available upon reasonable request. Due to privacy concerns and institutional policies, the data cannot be made publicly accessible. Interested parties may contact [email protected] to request access to the data and materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not for profit sectors. All expenses related to the study, including data collection, analysis, and manuscript preparation, were self-funded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAndreassen C, Pallesen S. Social Network Site Addiction - An Overview. Curr Pharm Des. 2014 June 31;20(25):4053\u0026ndash;61. \u003c/li\u003e\n\u003cli\u003eB\u0026aacute;nyai F, Zsila \u0026Aacute;, Kir\u0026aacute;ly O, Maraz A, Elekes Z, Griffiths MD, et al. Problematic Social Media Use: Results from a Large-Scale Nationally Representative Adolescent Sample. Jim\u0026eacute;nez-Murcia S, editor. PLOS ONE. 2017 Jan 9;12(1):e0169839. \u003c/li\u003e\n\u003cli\u003eIivari N, Sharma S, Vent\u0026auml;-Olkkonen L. Digital transformation of everyday life \u0026ndash; How COVID-19 pandemic transformed the basic education of the young generation and why information management research should care? Int J Inf Manag. 2020 Dec;55:102183. \u003c/li\u003e\n\u003cli\u003eLiu Q, Mo S. Is Social Distancing Law the New Normal? Forced Shift to Media Online Learning and Its Effectiveness: A Moderating Role of Student Engagement During the Pandemic of COVID-19. Front Psychol. 2022 June 17;13:923996. \u003c/li\u003e\n\u003cli\u003eParker K, Uddin R, Ridgers ND, Brown H, Veitch J, Salmon J, et al. The Use of Digital Platforms for Adults\u0026rsquo; and Adolescents\u0026rsquo; Physical Activity During the COVID-19 Pandemic (Our Life at Home): Survey Study. J Med Internet Res. 2021 Feb 1;23(2):e23389. \u003c/li\u003e\n\u003cli\u003eGhanayem LK, Shannon H, Khodr L, McQuaid RJ, Hellemans KGC. Lonely and scrolling during the COVID-19 pandemic: understanding the problematic social media use and mental health link among university students. Front Psychiatry. 2024 Jan 31;15:1247807. \u003c/li\u003e\n\u003cli\u003eCasale S, Akbari M, Seydavi M, Bocci Benucci S, Fioravanti G. Has the prevalence of problematic social media use increased over the past seven years and since the start of the COVID-19 pandemic? A meta-analysis of the studies published since the development of the Bergen social media addiction scale. Addict Behav. 2023 Dec;147:107838. \u003c/li\u003e\n\u003cli\u003eOzturk FO, Ayaz-Alkaya S. Internet addiction and psychosocial problems among adolescents during the COVID-19 pandemic: A cross-sectional study. Arch Psychiatr Nurs. 2021 Dec;35(6):595\u0026ndash;601. \u003c/li\u003e\n\u003cli\u003eLegaree BA. Considering the changing face of social media in higher education. Yeoman K, editor. FEMS Microbiol Lett. 2015 Aug;362(16):fnv128. \u003c/li\u003e\n\u003cli\u003eChowdhury EK. Examining the benefits and drawbacks of social media usage on academic performance: a study among university students in Bangladesh. J Res Innov Teach Learn [Internet]. 2024 Feb 8 [cited 2025 Sept 14]; Available from: https://www.emerald.com/insight/content/doi/10.1108/JRIT-07-2023-0097/full/html\u003c/li\u003e\n\u003cli\u003eMostert N. Exploring the prevalence of problematic smartphone use and problematic social media use amongst students at a South African University. Soc Sci Humanit Open. 2025;12:101778. \u003c/li\u003e\n\u003cli\u003eAbbouyi S, Bouazza S, El Kinany S, El Rhazi K, Zarrouq B. Depression and anxiety and its association with problematic social media use in the MENA region: a systematic review. Egypt J Neurol Psychiatry Neurosurg. 2024 Feb 1;60(1):15. \u003c/li\u003e\n\u003cli\u003eBoer M, Van Den Eijnden RJJM, Boniel-Nissim M, Wong SL, Inchley JC, Badura P, et al. Adolescents\u0026rsquo; Intense and Problematic Social Media Use and Their Well-Being in 29 Countries. J Adolesc Health. 2020 June;66(6):S89\u0026ndash;99. \u003c/li\u003e\n\u003cli\u003eAtalay YA. Prevalence of internet addiction and associated factors among university students in Ethiopia: systematic review and meta-analysis. Front Digit Health. 2024 Sept 11;6:1373735. \u003c/li\u003e\n\u003cli\u003eMengistu N, Habtamu E, Kassaw C, Madoro D, Molla W, Wudneh A, et al. Problematic smartphone and social media use among undergraduate students during the COVID-19 pandemic: In the case of southern Ethiopia universities. Zou D, editor. PLOS ONE. 2023 Jan 25;18(1):e0280724. \u003c/li\u003e\n\u003cli\u003eZarate D, Hobson BA, March E, Griffiths MD, Stavropoulos V. Psychometric properties of the Bergen Social Media Addiction Scale: An analysis using item response theory. Addict Behav Rep. 2023 June;17:100473. \u003c/li\u003e\n\u003cli\u003eBottaro R, Griffiths MD, Faraci P. Meta-analysis of Reliability and Validity of the Bergen Social Media Addiction Scale (BSMAS). Int J Ment Health Addict [Internet]. 2025 Mar 8 [cited 2025 Sept 14]; Available from: https://link.springer.com/10.1007/s11469-025-01461-x\u003c/li\u003e\n\u003cli\u003eGupta S, Bashir L. Social Networking Usage Questionnaire: Development and Validation in an Indian Higher Education Context. Turk Online J Distance Educ. 2018 Oct 18;214\u0026ndash;27. \u003c/li\u003e\n\u003cli\u003eDigital 2024: Ethiopia \u0026mdash; DataReportal \u0026ndash; Global Digital Insights [Internet]. [cited 2025 Sept 14]. Available from: https://datareportal.com/reports/digital-2024-ethiopia\u003c/li\u003e\n\u003cli\u003eAndreassen CS, Torsheim T, Brunborg GS, Pallesen S. Development of a Facebook Addiction Scale. Psychol Rep. 2012 Apr;110(2):501\u0026ndash;17. \u003c/li\u003e\n\u003cli\u003eShensa A, Escobar-Viera CG, Sidani JE, Bowman ND, Marshal MP, Primack BA. Problematic social media use and depressive symptoms among U.S. young adults: A nationally-representative study. Soc Sci Med. 2017 June;182:150\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eSalari N, Zarei H, Hosseinian-Far A, Rasoulpoor S, Shohaimi S, Mohammadi M. The global prevalence of social media addiction among university students: a systematic review and meta-analysis. J Public Health. 2025 Jan;33(1):223\u0026ndash;36. \u003c/li\u003e\n\u003cli\u003eWilson K, Fornasier S, White KM. Psychological Predictors of Young Adults\u0026rsquo; Use of Social Networking Sites. Cyberpsychology Behav Soc Netw. 2010 Apr;13(2):173\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eWolniczak I, C\u0026aacute;ceres-DelAguila JA, Palma-Ardiles G, Arroyo KJ, Sol\u0026iacute;s-Visscher R, Paredes-Yauri S, et al. Association between Facebook Dependence and Poor Sleep Quality: A Study in a Sample of Undergraduate Students in Peru. Schuelke M, editor. PLoS ONE. 2013 Mar 12;8(3):e59087. \u003c/li\u003e\n\u003cli\u003eCheng C, Lau Y ching, Chan L, Luk JW. Prevalence of social media addiction across 32 nations: Meta-analysis with subgroup analysis of classification schemes and cultural values. Addict Behav. 2021 June;117:106845. \u003c/li\u003e\n\u003cli\u003eUniveristi Teknologi Malaysia. He is also with Department of Computer, Damavand Branch, Islamic Azad University, Damavand, Iran, Jafarkarimi H, Sim ATH, the Department of Information Systems, Universiti Teknologi Malaysia, Malaysia, Saadatdoost R, the Department of Computer and Information Technology, Parand Branch, Islamic Azad University, Parand, Iran, et al. Facebook Addiction among Malaysian Students. Int J Inf Educ Technol. 2016;6(6):465\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eHaucke M, Liu S, Heinzel S. The Persistence of the Impact of COVID-19\u0026ndash;Related Distress, Mood Inertia, and Loneliness on Mental Health During a Postlockdown Period in Germany: An Ecological Momentary Assessment Study. JMIR Ment Health. 2021 Aug 26;8(8):e29419. \u003c/li\u003e\n\u003cli\u003eAndreassen CS. Online Social Network Site Addiction: A Comprehensive Review. Curr Addict Rep. 2015 June;2(2):175\u0026ndash;84. \u003c/li\u003e\n\u003cli\u003eKuss D, Griffiths M. Social Networking Sites and Addiction: Ten Lessons Learned. Int J Environ Res Public Health. 2017 Mar 17;14(3):311. \u003c/li\u003e\n\u003cli\u003eM\u0026uuml;ller KW, Dreier M, Beutel ME, Duven E, Giralt S, W\u0026ouml;lfling K. A hidden type of internet addiction? Intense and addictive use of social networking sites in adolescents. Comput Hum Behav. 2016 Feb;55:172\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eElhai JD, Levine JC, Dvorak RD, Hall BJ. Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use. Comput Hum Behav. 2016 Oct;63:509\u0026ndash;16. \u003c/li\u003e\n\u003cli\u003eMontag C, Yang H, Elhai JD. On the Psychology of TikTok Use: A First Glimpse From Empirical Findings. Front Public Health. 2021 Mar 16;9:641673. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Problematic social media use, behavioral addition, University students, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-7665108/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7665108/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eSocial media use has become an essential aspect of student life worldwide. While it offers academic and social benefits, excessive use can develop into problematic social media use (PSMU). The COVID-19 pandemic accelerated dependent on digital platforms, raising concerns that patterns established during lockdown may persist in the post-pandemic era. Despite rapid growth of internet penetration in Ethiopia, limited evidence exists on the prevalence and usage patterns of PSMU among university students.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo determine the prevalence of PSMU among undergraduate students at Addis Ababa University and to describe their usage patterns.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional study was conducted among regular undergraduate students at Addis Ababa University\u0026rsquo;s main campus. Participants were selected using simple random sampling and data on social media engagement and problematic use were collected using a structured questionnaire incorporating a validated PSMU screening scale. Descriptive statistics were applied to estimate prevalence and summarize usage patterns. Chi-square tests were performed to assess associations between demographic characteristics and PSMU.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe prevalence of PSMU was 17.1% (N\u0026thinsp;=\u0026thinsp;54). Gender differences were significant, female students accounted for 64.8% of PSMU cases compared to 35.2% among males. PSMU was significantly higher among (3rd year of student and department of law students). The most commonly used platforms were telegram (97.8%) followed by TikTok (70.9%) and YouTube 127 (40.2%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003ePSMU is prevalent among university students, affecting nearly one in five participants in post pandemic era. Gender, field of study, and academic year were associated with variations in PSMU, highlighting the need for targeted interventions. Universities in low-resource settings should prioritize digital literacy initiatives and preventive interventions. \u003cb\u003eKeywords\u003c/b\u003e: Problematic social media use, behavioral addition, University students, Ethiopia\u003c/p\u003e","manuscriptTitle":"From Pandemic to Problematic: Social media use and its emerging patterns among university Students in Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 08:29:11","doi":"10.21203/rs.3.rs-7665108/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5cbcea9b-3294-47c8-86bc-38dbe9ecb452","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55058038,"name":"Psychiatry"},{"id":55058039,"name":"Psychology"},{"id":55058040,"name":"Publishing/Media"}],"tags":[],"updatedAt":"2025-09-23T08:29:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 08:29:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7665108","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7665108","identity":"rs-7665108","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}