Social media addiction and its association with sleep quality and anxiety: A school-based cross-sectional study from Nepal.

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Laxmi Pradhan, Prakash Adhikari, Kriti Shah, Sandesh Bhusal, Kamana Oli, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5783624/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 Excessive use of social media is linked with poor sleep quality and negative mental health outcomes. However, studies assessing the interplay of these three components among school children are exceedingly rare. This study aims to assess the levels of social media addiction, poor sleep quality, and anxiety among higher secondary school children, identify associated factors, and explore the correlations among these components. Methods This study was conducted among 418 higher secondary school students. Multivariable logistic regression at a significance level of 0.05 was employed to determine factors associated with social media addiction, poor sleep quality, and anxiety. Additionally, a correlation test was used to examine the associations between social media addiction, poor sleep quality, and anxiety. Results The prevalence rates of social media addiction, poor sleep quality, and anxiety were 33.5%, 64.4%, and 59.6%, respectively. Female students (aOR: 2.6; 95% CI: 1.6–4.1) and students from private schools (aOR: 3.7; 95% CI: 2.0-6.8) had greater odds of being addicted to social media. Students from the Brahmin/Chhetri ethnic group (aOR: 0.5; 95% CI: 0.3–0.9) had lower odds of experiencing poor sleep quality than the other groups did. Female students (aOR: 2.4; 95% CI: 1.6–3.6) were more likely to experience anxiety. Additionally, sleep quality and anxiety were weakly positively correlated with social media addiction. Conclusion Excessive social media use is associated with poor sleep quality and increased anxiety among Nepalese higher secondary students. Interventions such as face-to-face counseling, digital detox programs, and tailored approaches for high-risk groups are essential to address these issues and enhance their overall well-being. Clinical trial number: Not applicable Social media addiction Sleep quality Anxiety Students Nepal Figures Figure 1 Background Studies on social media have reported mixed findings regarding its impact on individual health. Although social networking can improve psychosocial well-being by increasing self-esteem and fostering a sense of belonging (1,2), excessive use is associated with mental illnesses such as sleep disturbances, anxiety, depression, mania, eating disorders, social isolation, insecurity, and fear of missing out (1,3). Additionally, bedtime use of social media can lead to cognitive arousal and suppress melatonin production, negatively impacting sleep quality (4,5). This can increase sleep onset latency, decrease sleep duration, and result in daytime sleepiness, lower work efficiency, depressed mood, and concentration problems, potentially leading to chronic diseases (1,6,7). Individuals emotionally involved in social media have a greater chance of developing anxiety and depression, as the inability to stay online and respond on social media can cause feelings of guilt, distress, and depressed mood (4). Social media users tend to compare their lives with those of others, leading to feelings of envy, depression, and reduced happiness (8). Conversely, anxious individuals have impaired sleep quality, resulting in greater bedtime use of social media, whereas depressed individuals are likely to be active on social media to increase their mood (4). The abovementioned evidence highlights the interplay between social media addiction, sleep quality, and anxiety symptoms. Studies from different parts of the world suggest a high prevalence of social media addiction (9,10), poor sleep quality (11) and anxiety (12) across different age groups worldwide, especially among students (12–14). Technological advancements and improved internet access have surged across Nepal, particularly during the COVID-19 pandemic era (15). In urban areas such as the Kathmandu Valley, internet access is now nearly ubiquitous. Access to the internet and mobile phones is very high in Nepal, with a total of 139.2% active cellular connections showing more cellular connections than the population does (15). The numbers are relatively high, especially in urban areas. Worldwide, 75% of young people aged 15–24 use the internet, with teenagers and adults primarily engaging in social media(1,16). Pathogenic internet use among adolescents is a rising social concern, and a greater proportion of students exhibit risky online behaviors such as arguing, cyber harassing or cyberstalking (17). In Nepal, sleep quality is very poor among high school students, with a prevalence of only 40.9% good sleep quality (18). Additionally, studies have suggested a high prevalence of anxiety among students at higher secondary levels (19). Overall, evidence on sleep quality, social media addiction, anxiety, and their interplay among higher secondary school students is limited in Nepal. Considering these gaps, this study focuses on assessing the proportion of higher secondary students who have social media addiction, poor sleep quality and anxiety and exploring their correlates. Materials and methods Study design, population and setting A cross-sectional study was conducted among higher secondary students of Suryabinayak Municipality, Bhaktapur, from 9 February 2024 to 10 March 2024. The Suryabinayak Municipality is located at the southeastern edge of Kathmandu Valley. It is a dense municipality where students from different parts of countries come to pursue higher education, which makes the population more inclusive. Sample size and sampling technique A list of all higher secondary schools in Suryabinayak Municipality was obtained from the education section of the municipality. From the six identified schools (five public, one private), three were randomly selected, ensuring the inclusion of the private school. Within these selected schools, classes 11 and 12 were randomly chosen. Students were then asked whether they used social media, and only those who did use social media were included in the study, while those who did not use social media were excluded. (Fig. 1 School selection process) The sample size for the study was calculated via the following formula for the cross-sectional survey (20). n = z 2 pq/d 2 where n = the sample size. z = reliability level (1.96) p = estimated proportion of students with anxiety = 0.556 (19) q = 1 –p = 1–0.556 = 0.444 d = maximum allowable error (0.05) The initial sample size was calculated to be 380. To account for a 15% nonresponse rate, the adjusted estimated sample size was adjusted to 437. Data collection tools and techniques Data were collected through paper-based self-administered questionnaires from 437 participants, 19 of whom were incomplete and were excluded from the final data analysis. Widely validated questionnaires with high internal consistency were used to measure the dependent variable. The Bergen Social Media Addiction Scale (BSMAS), Pittsburg Sleep Quality Index (PSQI), and Hospital Anxiety and Depression Scale (HADS) were used to measure social media addiction, sleep quality and anxiety, respectively. Measurements Social media addiction The Bergen Social Media Addiction Scale (BSMAS) was used to assess social media addiction among the participants. The BSMAS (Cronbach's alpha > 0.8) (21) consists of 6 items encompassing six core characteristics of addiction: salience, mood modification, tolerance, withdrawal, conflict, and relapse (21). The total score of the BSMAS ranges from 5–30, with each item ranging from 1 (very rarely) to 5 (very often). Individuals scoring 24 or more on the BSMAS were considered addicted to social media, whereas others were considered non addicted (21). Sleep quality The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality among the participants. The PSQI (Cronbach's alpha of 0.83) (22) consists of 19 items in seven domains: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication and daytime dysfunction over the last month. The score for the seven domains was assigned on a 0–3 scale, whereby 3 reflects the negative extreme on the Likert scale. Individuals with a score of 5 or more were categorized as having poor sleep quality, and individuals with a score of less than 5 were categorized as having good sleep quality (22). Anxiety Anxiety was measured via 7 items from the Hospital Anxiety and Depression Scale (HADS), and responses were given on a 4-point Likert scale (ranging from (23). The total anxiety score of the HADS-A ranges from 0–21. Anxiety was classified into three groups: normal (0–7), borderline (8–10) and abnormal (11–21) (23). Sociodemographic variables Sociodemographic factors included age in years, sex, ethnicity as per the Health Management Information System classification (Dalit, Janajati, Madhesi, Muslim, Brahmin/Chhetri and Other), religion (Hindu, Buddhist, Christian, Muslim and Other), family type (nuclear, joint and extended), academic grade (11 and 12), school type (private and community), father's and mother's education (cannot read and write, primary level, secondary level, higher secondary level, and university). Data management and analysis The data collected were entered and cleaned in MS Excel and exported to the Statistical Package for the Social Sciences (SPSS) version 25, where data coding and analysis were performed. Descriptive analysis was performed by calculating the number and percentage for categorical variables and the mean and standard deviation for continuous variables. The chi-square test was used to determine the associations between categorical independent variable socio-demographic characteristics and the categorical dependent variables social media addiction, poor sleep quality and anxiety. The variables with a p-value less than 0.1 during bivariate analysis were entered into the logistic regression analysis. Variables such as gender, family type, school type, father's education and mother's education had a p-value less than 0.1, and these variables were adjusted when multivariable logistic regression analysis was performed for social media addiction. Similarly, age, ethnicity and school type had a p-value less than 0.1, and these variables were adjusted when multivariable logistic regression analysis was performed for sleep quality. Likewise, sex, ethnicity and religion were adjusted while performing the multivariable logistic regression analysis for anxiety. The adjusted odds ratio was calculated at a 95% CI, and a p value less than 0.05 was considered statistically significant. A normality test revealed that the data were not normally distributed; Spearman's rank correlation analysis was therefore performed, and a p-value less than 0.05 was considered statistically significant. Results Socio-demographic characteristics Among 418 participants, 56.7% were males, and approximately half of the participants (51.7%) belonged to the Brahmin/Chhetri ethnic group. The mean age (± SD) of the participants was 17.2 ± 1.1 years. The majority of the participants (61.5%) belonged to a nuclear family. Over half of the participants were from community schools (58.9%) and from the eleventh grade (58.4%). Regarding parental education, 42.8% of the mothers and 25.3% of the fathers had no formal education. (Table 1 ) Table 1 Socio-demographic characteristics of the respondents (n = 418) Characteristics Frequency Percentage Age in years (Mean± SD: − 1 7.2 ± 1.1) 15–17 276 66.0 18–24 142 34.0 Gender Male 237 56.7 Female 181 43.3 Ethnicity Brahmin/Chhetri 216 51.7 Janajati 137 32.8 Dalit 29 6.9 Madhesi 16 3.8 Muslim 9 2.2 Others 11 2.6 Religion Hindu 361 86.4 Buddhist 36 8.6 Others 21 5.0 Family type Nuclear 257 61.5 Joint/Extended 161 38.5 Academic grade 11 244 58.4 12 174 41.6 Students by type of school Community 246 58.9 Private 172 41.1 Mother's education Illiterate 77 18.4 Informal education 102 24.4 Primary education 42 10 Secondary education 68 16.3 Higher secondary education 105 25.1 University level 24 5.7 Father's education Illiterate 44 10.5 Informal education 62 14.8 Primary education 59 14.1 Secondary education 80 19.1 Higher secondary education 72 17.2 University level 101 24.1 Social media addiction, sleep quality and anxiety One-third of the participants (33.5%) were addicted to social media. Similarly, 64.4% of the participants experienced symptoms of poor sleep quality, whereas 59.3% experienced symptoms of anxiety. (Table 2 ) Table 2 Social media addiction, sleep quality and anxiety among the respondents (n = 418) Characteristics Number Percentage Social media addiction No social media addiction (0–23) 278 66.5 Social media addiction (24–30) 140 33.5 Sleep quality Good sleep quality (0–4) 149 35.6 Poor sleep quality (5–21) 269 64.4 Anxiety Normal (0–7) 170 40.7 Borderline Anxiety (8–10) 100 23.9 Anxiety (11–21) 148 35.4 Factors associated with social media addiction, poor sleep quality and anxiety Female students (aOR: 2.6; 95% CI: 1.6–4.1) and students from private schools (aOR: 3.7; 95% CI: 2.0-6.8) had significantly greater odds of being addicted to social media. Conversely, students from the Brahmin/Chhetri ethnic group (aOR: 0.5; 95% CI: 0.3–0.9) had lower odds of experiencing poor sleep quality than others did. Additionally, female students (aOR: 2.4; 95% CI: 1.6–3.6) were more likely to experience anxiety. (Table 3 – 5 ) Table 3 Factors associated with social media addiction (n = 418) Variable Social media addiction (%) Unadjusted OR Adjusted OR Gender Female 70 (38.7) 1.5(1.0-2.3) 2.6(1.6–4.1)* Male 70 (29.5) Ref Ref Family type Nuclear 96(37.4) 1.6 (1.03–2.4)* 1.5(0.9–2.3) Joint/Extended 44(27.3) Ref Ref School type Private 83 (48.3) 3.1 (2.03–4.7)* 3.7(2.0 -6.8)* Community 57 (23.2) Ref Ref Mother's education Above secondary 60 (46.5) 2.3 (1.5–3.5)* 1.0(0.5–1.8) Secondary and below 80 (27.7) Ref Ref Father's education Above secondary 77 (44.5) 2.3 (1.5–3.5)* 1.3(0.7–2.3) Secondary and below 63 (25.7) Ref Ref * p-value less than 0.05 Table 4 Factors associated with poor sleep quality (n = 418) Variable Poor sleep quality (%) Unadjusted OR Adjusted OR Age 15–17 169 (61.2) 0.7 (0.4-1.0) 0.8(0.5–1.2) 18–24 100 (70.4) Ref Ref Ethnicity Brahmin/Chhetri 129 (59.7) 0.5 (0.2–0.8)* 0.5(0.3–0.9)* Janajati 90 (65.7) 0.6 (0.3–1.1)) 0.6(0.3–1.2) Others 50 (76.9) Ref Ref School type Private 100 (58.1) 0.6 (0.4–0.9)* 0.7(0.5–1.1) Public 169 (68.7) Ref Ref * p-value less than 0.05 Table 5 Factors associated with anxiety (n = 418) Variable Anxiety (%) Unadjusted OR Adjusted OR Gender Female 129 (71.3) 2.5 (1.6–3.7)* 2.4(1.6–3.6)* Male 119 (50.2) Ref Ref Ethnicity Brahmin/Chhetri 115 (53.2) 0.8 (0.4–1.3) 0.7(0.4–1.3) Janajati 94 (68.6) 1.5 (0.8–2.7) 1.1(0.6–2.1) Others 39 (60.0) Ref Ref Religion Hindu 207 (57.3) 0.5 (0.3-1.0)* 0.7(0.4–1.3) Non- Hindu 41 (71.9) Ref Ref * p-value less than 0.05 Correlations between social media addiction, sleep quality and anxiety . There was a weak positive correlation between social media addiction and the PSQI score (r s = 0.36, p value < 0.01), suggesting that higher levels of social media addiction are associated with poorer sleep quality. Similarly, there was a weak positive correlation between social media addiction and anxiety scores (r s = 0.38, p value < 0.01), indicating that higher levels of social media addiction are associated with higher levels of anxiety (24). (Table S1 ) Discussion The study revealed a high prevalence of social media addiction (33.5%), poor sleep quality (64.4%) and anxiety (59.3%) among higher secondary school children. This prevalence of social media addiction aligns with the prevalence of 31% among Asians, which was highlighted in a meta-analysis conducted by Cheng et al. across 32 nations (25). Additionally, a high prevalence of social media addiction was observed among secondary-level school children in Kathmandu, with a prevalence of 46%, which was measured via a different tool: the social media addiction scale (26). These results depict a problematic proportion of school children being addicted to social media. This may impact children’s academic performance (27); may cause difficulty sleeping; and may lead to personal, social and vocational problems among individuals (28). This highlights the urgency of addressing social media addiction problems among students. Studies have suggested that frequent face-to-face communication can break the cycle, leading to problematic use of social media and promoting psychological wellbeing (29). Female students and those from private schools were more likely to have social media addiction, which is consistent with the findings of other studies (30,31). Females tend to use social media for emotional support, social comparison, and connection, making them more susceptible to excessive use and addictive behaviors driven by social feedback and validation (32). Additionally, students from private schools were more likely to have social media addiction. This result aligns with findings from a study performed among high school students in India (33). Private school students, often from higher socioeconomic backgrounds, have greater access to personal devices, increasing their risk of social media addiction. Parental and school involvement, the promotion of face-to-face communication, digital detox programs, and mindfulness practices can help reduce this dependence (34). Online group guidance programs are also effective in addressing social media addiction (35). Approximately two-thirds of the students experienced poor sleep quality, similar to the 59.1% prevalence reported among higher secondary students in Kathmandu Valley (18). Students from across the country often migrate to cities for advanced education, particularly at the higher secondary level and beyond. The challenges of independent living in unfamiliar environments, coupled with academic pressures and increased responsibilities, may adversely impact sleep duration and quality. Our study revealed a weak positive correlation between sleep quality and social media addiction, which is consistent with the findings of a systematic review and meta-analysis by Li Ying et al. (36). Cognitive‒behavioral theory suggests that individuals' thoughts and feelings can influence their actions, and vice versa. Consequently, social media addiction may impact emotions and cognitions, ultimately contributing to poor sleep quality (37). Additionally, we observed a significant association between ethnicity and sleep quality, with Brahmin/Chhetri students exhibiting lower odds of poor sleep quality than other groups did. This disparity might be attributed to the disproportionate challenges faced by ethnic minority groups, such as Dalit, Madhesi, and Muslim students, who may experience higher levels of discrimination and stress, negatively affecting their sleep. Nevertheless, further research is warranted to explore the potential influence of socioeconomic factors, living conditions, and specific ethnic and cultural elements on this relationship. A total of three out of five (59.3%) students in our study experienced anxiety. Similarly, a high prevalence of anxiety was observed among higher secondary students in Kathmandu Valley (19). High anxiety among higher secondary students may stem from transitioning to a new academic setting, living independently, and lacking family support. In Nepal, many families discourage open discussions, leading adolescents to internalize their problems. Coupled with academic pressure, relationship issues, and emotional changes, this isolation can significantly heighten anxiety (38). Compared with males, females presented greater odds of experiencing anxiety symptoms, which is consistent with previous research conducted among different groups of students (19,38). This disparity may be attributed to several factors. Women are more likely to encounter traumatic events such as sexual trauma, gender discrimination, domestic violence, and relationship stressors and tend to ruminate on these experiences more frequently than men (39). Gender-based differences in upbringing and socialization can also influence anxiety patterns. From childhood, boys are often encouraged to confront fears, leading to increased exposure and reduced fear responses, whereas girls may be discouraged from expressing fear (39). Additionally, men are more likely to underreport anxiety symptoms than women (39). Biological factors may also contribute to sex differences in anxiety, with women being more sensitive to the stress hormone corticotropin-releasing factor (40). Given these factors, tailored interventions and coping mechanisms are essential for addressing anxiety among students, particularly females. A weak positive correlation was observed between social media addiction and anxiety, which aligns with findings from a systematic review and meta-analysis by Li Ying et al. (36). Constant exposure to idealized online personas can foster feelings of inadequacy and anxiety among students (41). Moreover, excessive social media use often reduces face-to-face interactions, hindering the development of essential social skills and contributing to social anxiety. The risk of cyberbullying and online harassment further exacerbates anxiety levels in this population (42). The diverse features and content available on social media platforms may also influence students' anxiety levels. Strengths and Limitations This study employed widely accepted tools to measure social media addiction, sleep quality, and anxiety. This study contributes to the limited body of literature exploring the complex relationships among social media addiction, sleep quality, and anxiety. Our study has several limitations worth noting. Incorporating variables such as wealth quintile, access to gadgets, and internet facilities at home could have provided a deeper understanding of the topic, which this study did not address. In addition, the use of subjective measurements may have introduced respondent bias. However, efforts were made to mitigate this by clearly explaining the study objectives to the students. Conclusion This study revealed high rates of social media addiction, poor sleep quality, and anxiety among higher secondary school students. A weak positive correlation between these factors was also identified. These findings underscore the need for targeted interventions, particularly for female and private school students. Strategies such as parental involvement, face-to-face interaction promotion, and school-based digital detox programs could help reduce social media addiction. Special attention should be given to girls, who are more susceptible to anxiety. Addressing social media addiction may also improve sleep quality and overall mental health. Abbreviations AOR: Adjusted Odds Ratio, BSMAS: Bergen Social Media Addiction Scale, CI: Confidence Interval, COVID: Coronavirus disease, HADS: Hospital Anxiety and Depression Scale, MS: Microsoft, PSQI: Pittsburg Sleep Quality Index, SPSS: Statistical Package for the Social Sciences and SD: Standard Deviation Declarations Acknowledgment We would like to thank all the students and school staff for their cooperation during data collection. We are also grateful to Suryabinayak Municipality for granting us permission to conduct the study. Authors’ contributions LP and AKS conceived and designed the study. LP and KO conducted the survey, while LP and PA performed the analysis. LP drafted the initial manuscript, which was subsequently revised with input from all authors. AKS supervised the study. All authors have reviewed, approved, and endorsed the final version of the manuscript. Funding None Data availability The data is in the supplementary file. Ethics approval and consent to participate The work was done in accordance to the Helsinki Declaration of Research Ethics. Ethical approval was obtained from the Institutional Review Board of the Institute of Medicine (Reference number: 379(6-11) E2/080/081). Administrative approval for conducting the study was obtained from Suryabinayak municipality (Ref: 080/81/914) and from the school administration of the respective schools. Written informed consent was obtained from the students before data collection to ensure their willingness to participate, and no identifiers were listed in the questionnaire to make it anonymous and confidential. Parental consent was obtained from students who were under the age of 18 years. Consent for publication Not applicable Competing interests Authors have no competing interest associated with this paper. References Singh R, Arya S, Chadha B. Relationship between Social Media, Poor Sleep Quality and Anxiety. Webology. 2021;18(3):1151–63. Best P, Manktelow R, Taylor B. Online communication, social media and adolescent wellbeing: A systematic narrative review. Child Youth Serv Rev. 2014 Jun;41:27–36. Xiao W, Peng J, Liao S. Exploring the Associations between Social Media Addiction and Depression: Attentional Bias as a Mediator and Socio-Emotional Competence as a Moderator. Int J Environ Res Public Health. 2022;19(20). 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Pradhan","email":"data:image/png;base64,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","orcid":"","institution":"Institute of Medicine, Tribhuvan University","correspondingAuthor":true,"prefix":"","firstName":"Laxmi","middleName":"","lastName":"Pradhan","suffix":""},{"id":401502976,"identity":"b06dcc1e-26e5-463d-8465-ed5fe78d2d3b","order_by":1,"name":"Prakash Adhikari","email":"","orcid":"","institution":"Institute of Medicine, Tribhuvan University","correspondingAuthor":false,"prefix":"","firstName":"Prakash","middleName":"","lastName":"Adhikari","suffix":""},{"id":401502977,"identity":"8180ea14-6529-4ec9-b6c6-db581ae66f86","order_by":2,"name":"Kriti Shah","email":"","orcid":"","institution":"KIST Medical College","correspondingAuthor":false,"prefix":"","firstName":"Kriti","middleName":"","lastName":"Shah","suffix":""},{"id":401502978,"identity":"7661defe-c160-4578-9471-0165a9b01a82","order_by":3,"name":"Sandesh Bhusal","email":"","orcid":"","institution":"University of Connecticut","correspondingAuthor":false,"prefix":"","firstName":"Sandesh","middleName":"","lastName":"Bhusal","suffix":""},{"id":401502979,"identity":"3e87bf09-af07-4729-9f6f-3e3e976edfbf","order_by":4,"name":"Kamana Oli","email":"","orcid":"","institution":"Institute of Medicine, Tribhuvan University","correspondingAuthor":false,"prefix":"","firstName":"Kamana","middleName":"","lastName":"Oli","suffix":""},{"id":401502980,"identity":"5bbb15e9-2385-46eb-8c6f-b425da6ac36f","order_by":5,"name":"Pratik Khanal","email":"","orcid":"","institution":"University of Bergen","correspondingAuthor":false,"prefix":"","firstName":"Pratik","middleName":"","lastName":"Khanal","suffix":""},{"id":401502981,"identity":"c7202dfa-fe5e-403f-8e1f-df26e7fd5660","order_by":6,"name":"Anil Kumar Singh","email":"","orcid":"","institution":"Institute of Medicine, Tribhuvan University","correspondingAuthor":false,"prefix":"","firstName":"Anil","middleName":"Kumar","lastName":"Singh","suffix":""}],"badges":[],"createdAt":"2025-01-07 18:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5783624/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5783624/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73939861,"identity":"8121263b-ee36-4235-9ca3-87930b7c2eed","added_by":"auto","created_at":"2025-01-16 07:47:54","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":76220,"visible":true,"origin":"","legend":"\u003cp\u003eSchool selection process\u003c/p\u003e","description":"","filename":"Fig1SchoolSelectionProcess.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5783624/v1/f1ac68975a09e415b4b0b452.jpg"},{"id":73941556,"identity":"6adbcfdf-806a-47b4-b824-2158d479bab6","added_by":"auto","created_at":"2025-01-16 08:03:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1179381,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5783624/v1/6c0e570a-5946-489d-8899-90fb10661036.pdf"},{"id":73939860,"identity":"ea3d40a5-5040-48b7-a954-6d05af599ce4","added_by":"auto","created_at":"2025-01-16 07:47:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13475,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryDataS1Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5783624/v1/b18fed2c7fab3f9630b7ad8c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eSocial media addiction and its association with sleep quality and anxiety: A school-based cross-sectional study from Nepal.\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eStudies on social media have reported mixed findings regarding its impact on individual health. Although social networking can improve psychosocial well-being by increasing self-esteem and fostering a sense of belonging (1,2), excessive use is associated with mental illnesses such as sleep disturbances, anxiety, depression, mania, eating disorders, social isolation, insecurity, and fear of missing out (1,3). Additionally, bedtime use of social media can lead to cognitive arousal and suppress melatonin production, negatively impacting sleep quality (4,5). This can increase sleep onset latency, decrease sleep duration, and result in daytime sleepiness, lower work efficiency, depressed mood, and concentration problems, potentially leading to chronic diseases (1,6,7).\u003c/p\u003e \u003cp\u003eIndividuals emotionally involved in social media have a greater chance of developing anxiety and depression, as the inability to stay online and respond on social media can cause feelings of guilt, distress, and depressed mood (4). Social media users tend to compare their lives with those of others, leading to feelings of envy, depression, and reduced happiness (8). Conversely, anxious individuals have impaired sleep quality, resulting in greater bedtime use of social media, whereas depressed individuals are likely to be active on social media to increase their mood (4).\u003c/p\u003e \u003cp\u003eThe abovementioned evidence highlights the interplay between social media addiction, sleep quality, and anxiety symptoms. Studies from different parts of the world suggest a high prevalence of social media addiction (9,10), poor sleep quality (11) and anxiety (12) across different age groups worldwide, especially among students (12\u0026ndash;14).\u003c/p\u003e \u003cp\u003eTechnological advancements and improved internet access have surged across Nepal, particularly during the COVID-19 pandemic era (15). In urban areas such as the Kathmandu Valley, internet access is now nearly ubiquitous. Access to the internet and mobile phones is very high in Nepal, with a total of 139.2% active cellular connections showing more cellular connections than the population does (15). The numbers are relatively high, especially in urban areas. Worldwide, 75% of young people aged 15\u0026ndash;24 use the internet, with teenagers and adults primarily engaging in social media(1,16). Pathogenic internet use among adolescents is a rising social concern, and a greater proportion of students exhibit risky online behaviors such as arguing, cyber harassing or cyberstalking (17).\u003c/p\u003e \u003cp\u003eIn Nepal, sleep quality is very poor among high school students, with a prevalence of only 40.9% good sleep quality (18). Additionally, studies have suggested a high prevalence of anxiety among students at higher secondary levels (19). Overall, evidence on sleep quality, social media addiction, anxiety, and their interplay among higher secondary school students is limited in Nepal. Considering these gaps, this study focuses on assessing the proportion of higher secondary students who have social media addiction, poor sleep quality and anxiety and exploring their correlates.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, population and setting\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted among higher secondary students of Suryabinayak Municipality, Bhaktapur, from 9 February 2024 to 10 March 2024. The Suryabinayak Municipality is located at the southeastern edge of Kathmandu Valley. It is a dense municipality where students from different parts of countries come to pursue higher education, which makes the population more inclusive.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample size and sampling technique\u003c/h3\u003e\n\u003cp\u003eA list of all higher secondary schools in Suryabinayak Municipality was obtained from the education section of the municipality. From the six identified schools (five public, one private), three were randomly selected, ensuring the inclusion of the private school. Within these selected schools, classes 11 and 12 were randomly chosen. Students were then asked whether they used social media, and only those who did use social media were included in the study, while those who did not use social media were excluded. (Fig.\u0026nbsp;1 School selection process)\u003c/p\u003e \u003cp\u003eThe sample size for the study was calculated via the following formula for the cross-sectional survey (20).\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;z\u003csup\u003e2\u003c/sup\u003epq/d\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ewhere n\u0026thinsp;=\u0026thinsp;the sample size.\u003c/p\u003e \u003cp\u003ez\u0026thinsp;=\u0026thinsp;reliability level (1.96)\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;estimated proportion of students with anxiety\u0026thinsp;=\u0026thinsp;0.556 (19)\u003c/p\u003e \u003cp\u003eq\u0026thinsp;=\u0026thinsp;1 \u0026ndash;p\u0026thinsp;=\u0026thinsp;1\u0026ndash;0.556\u0026thinsp;=\u0026thinsp;0.444\u003c/p\u003e \u003cp\u003ed\u0026thinsp;=\u0026thinsp;maximum allowable error (0.05)\u003c/p\u003e \u003cp\u003eThe initial sample size was calculated to be 380. To account for a 15% nonresponse rate, the adjusted estimated sample size was adjusted to 437.\u003c/p\u003e\n\u003ch3\u003eData collection tools and techniques\u003c/h3\u003e\n\u003cp\u003eData were collected through paper-based self-administered questionnaires from 437 participants, 19 of whom were incomplete and were excluded from the final data analysis. Widely validated questionnaires with high internal consistency were used to measure the dependent variable. The Bergen Social Media Addiction Scale (BSMAS), Pittsburg Sleep Quality Index (PSQI), and Hospital Anxiety and Depression Scale (HADS) were used to measure social media addiction, sleep quality and anxiety, respectively.\u003c/p\u003e\n\u003ch3\u003eMeasurements\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSocial media addiction\u003c/h2\u003e \u003cp\u003eThe Bergen Social Media Addiction Scale (BSMAS) was used to assess social media addiction among the participants. The BSMAS (Cronbach's alpha\u0026thinsp;\u0026gt;\u0026thinsp;0.8) (21) consists of 6 items encompassing six core characteristics of addiction: salience, mood modification, tolerance, withdrawal, conflict, and relapse (21). The total score of the BSMAS ranges from 5\u0026ndash;30, with each item ranging from 1 (very rarely) to 5 (very often). Individuals scoring 24 or more on the BSMAS were considered addicted to social media, whereas others were considered non addicted (21).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSleep quality\u003c/h2\u003e \u003cp\u003eThe Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality among the participants. The PSQI (Cronbach's alpha of 0.83) (22) consists of 19 items in seven domains: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication and daytime dysfunction over the last month. The score for the seven domains was assigned on a 0\u0026ndash;3 scale, whereby 3 reflects the negative extreme on the Likert scale. Individuals with a score of 5 or more were categorized as having poor sleep quality, and individuals with a score of less than 5 were categorized as having good sleep quality (22).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnxiety\u003c/h3\u003e\n\u003cp\u003eAnxiety was measured via 7 items from the Hospital Anxiety and Depression Scale (HADS), and responses were given on a 4-point Likert scale (ranging from (23). The total anxiety score of the HADS-A ranges from 0\u0026ndash;21. Anxiety was classified into three groups: normal (0\u0026ndash;7), borderline (8\u0026ndash;10) and abnormal (11\u0026ndash;21) (23).\u003c/p\u003e\n\u003ch3\u003eSociodemographic variables\u003c/h3\u003e\n\u003cp\u003eSociodemographic factors included age in years, sex, ethnicity as per the Health Management Information System classification (Dalit, Janajati, Madhesi, Muslim, Brahmin/Chhetri and Other), religion (Hindu, Buddhist, Christian, Muslim and Other), family type (nuclear, joint and extended), academic grade (11 and 12), school type (private and community), father's and mother's education (cannot read and write, primary level, secondary level, higher secondary level, and university).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData management and analysis\u003c/h2\u003e \u003cp\u003eThe data collected were entered and cleaned in MS Excel and exported to the Statistical Package for the Social Sciences (SPSS) version 25, where data coding and analysis were performed.\u003c/p\u003e \u003cp\u003eDescriptive analysis was performed by calculating the number and percentage for categorical variables and the mean and standard deviation for continuous variables. The chi-square test was used to determine the associations between categorical independent variable socio-demographic characteristics and the categorical dependent variables social media addiction, poor sleep quality and anxiety. The variables with a p-value less than 0.1 during bivariate analysis were entered into the logistic regression analysis. Variables such as gender, family type, school type, father's education and mother's education had a p-value less than 0.1, and these variables were adjusted when multivariable logistic regression analysis was performed for social media addiction. Similarly, age, ethnicity and school type had a p-value less than 0.1, and these variables were adjusted when multivariable logistic regression analysis was performed for sleep quality. Likewise, sex, ethnicity and religion were adjusted while performing the multivariable logistic regression analysis for anxiety. The adjusted odds ratio was calculated at a 95% CI, and a p value less than 0.05 was considered statistically significant. A normality test revealed that the data were not normally distributed; Spearman's rank correlation analysis was therefore performed, and a p-value less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic characteristics\u003c/h2\u003e \u003cp\u003eAmong 418 participants, 56.7% were males, and approximately half of the participants (51.7%) belonged to the Brahmin/Chhetri ethnic group. The mean age (\u0026plusmn; SD) of the participants was 17.2 \u0026plusmn; 1.1 years. The majority of the participants (61.5%) belonged to a nuclear family. Over half of the participants were from community schools (58.9%) and from the eleventh grade (58.4%). Regarding parental education, 42.8% of the mothers and 25.3% of the fathers had no formal education. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the respondents (n\u0026thinsp;=\u0026thinsp;418)\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\u003eCharacteristics\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\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge in years (Mean\u0026plusmn; SD: \u0026minus;\u0026thinsp;1\u003c/b\u003e7.2 \u0026plusmn; 1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrahmin/Chhetri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJanajati\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDalit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMadhesi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuddhist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNuclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJoint/Extended\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcademic grade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStudents by type of school\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher secondary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFather's education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher secondary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.1\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=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSocial media addiction, sleep quality and anxiety\u003c/h2\u003e \u003cp\u003eOne-third of the participants (33.5%) were addicted to social media. Similarly, 64.4% of the participants experienced symptoms of poor sleep quality, whereas 59.3% experienced symptoms of anxiety. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\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\u003eSocial media addiction, sleep quality and anxiety among the respondents (n\u0026thinsp;=\u0026thinsp;418)\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\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSocial media addiction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo social media addiction (0\u0026ndash;23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial media addiction (24\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep quality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood sleep quality (0\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor sleep quality (5\u0026ndash;21)\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\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnxiety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (0\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBorderline Anxiety (8\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety (11\u0026ndash;21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.4\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\u003eFactors associated with social media addiction, poor sleep quality and anxiety\u003c/h2\u003e \u003cp\u003eFemale students (aOR: 2.6; 95% CI: 1.6\u0026ndash;4.1) and students from private schools (aOR: 3.7; 95% CI: 2.0-6.8) had significantly greater odds of being addicted to social media. Conversely, students from the Brahmin/Chhetri ethnic group (aOR: 0.5; 95% CI: 0.3\u0026ndash;0.9) had lower odds of experiencing poor sleep quality than others did. Additionally, female students (aOR: 2.4; 95% CI: 1.6\u0026ndash;3.6) were more likely to experience anxiety. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\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\u003eFactors associated with social media addiction (n\u0026thinsp;=\u0026thinsp;418)\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial media addiction (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnadjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (38.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5(1.0-2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.6(1.6\u0026ndash;4.1)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNuclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96(37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6 (1.03\u0026ndash;2.4)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5(0.9\u0026ndash;2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJoint/Extended\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44(27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSchool type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (48.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1 (2.03\u0026ndash;4.7)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3.7(2.0 -6.8)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (46.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3 (1.5\u0026ndash;3.5)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0(0.5\u0026ndash;1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFather's education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (44.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3 (1.5\u0026ndash;3.5)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3(0.7\u0026ndash;2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e* p-value less than 0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \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\u003eFactors associated with poor sleep quality (n\u0026thinsp;=\u0026thinsp;418)\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor sleep quality (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnadjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (61.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7 (0.4-1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8(0.5\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (70.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrahmin/Chhetri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (59.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (0.2\u0026ndash;0.8)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.5(0.3\u0026ndash;0.9)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJanajati\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (65.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 (0.3\u0026ndash;1.1))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6(0.3\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSchool type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (58.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 (0.4\u0026ndash;0.9)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7(0.5\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (68.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e* p-value less than 0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \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\u003eFactors associated with anxiety (n\u0026thinsp;=\u0026thinsp;418)\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnxiety (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnadjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (71.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5 (1.6\u0026ndash;3.7)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.4(1.6\u0026ndash;3.6)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119 (50.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrahmin/Chhetri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (53.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.4\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7(0.4\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJanajati\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (68.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (0.8\u0026ndash;2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1(0.6\u0026ndash;2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207 (57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (0.3-1.0)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7(0.4\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon- Hindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (71.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e* p-value less than 0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCorrelations between social media addiction, sleep quality and anxiety\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThere was a weak positive correlation between social media addiction and the PSQI score (r\u003csub\u003es\u003c/sub\u003e = 0.36, p value\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting that higher levels of social media addiction are associated with poorer sleep quality. Similarly, there was a weak positive correlation between social media addiction and anxiety scores (r\u003csub\u003es\u003c/sub\u003e = 0.38, p value\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating that higher levels of social media addiction are associated with higher levels of anxiety (24). (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study revealed a high prevalence of social media addiction (33.5%), poor sleep quality (64.4%) and anxiety (59.3%) among higher secondary school children.\u003c/p\u003e \u003cp\u003eThis prevalence of social media addiction aligns with the prevalence of 31% among Asians, which was highlighted in a meta-analysis conducted by Cheng et al. across 32 nations (25). Additionally, a high prevalence of social media addiction was observed among secondary-level school children in Kathmandu, with a prevalence of 46%, which was measured via a different tool: the social media addiction scale (26). These results depict a problematic proportion of school children being addicted to social media. This may impact children\u0026rsquo;s academic performance (27); may cause difficulty sleeping; and may lead to personal, social and vocational problems among individuals (28). This highlights the urgency of addressing social media addiction problems among students. Studies have suggested that frequent face-to-face communication can break the cycle, leading to problematic use of social media and promoting psychological wellbeing (29).\u003c/p\u003e \u003cp\u003eFemale students and those from private schools were more likely to have social media addiction, which is consistent with the findings of other studies (30,31). Females tend to use social media for emotional support, social comparison, and connection, making them more susceptible to excessive use and addictive behaviors driven by social feedback and validation (32). Additionally, students from private schools were more likely to have social media addiction. This result aligns with findings from a study performed among high school students in India (33). Private school students, often from higher socioeconomic backgrounds, have greater access to personal devices, increasing their risk of social media addiction. Parental and school involvement, the promotion of face-to-face communication, digital detox programs, and mindfulness practices can help reduce this dependence (34). Online group guidance programs are also effective in addressing social media addiction (35).\u003c/p\u003e \u003cp\u003eApproximately two-thirds of the students experienced poor sleep quality, similar to the 59.1% prevalence reported among higher secondary students in Kathmandu Valley (18). Students from across the country often migrate to cities for advanced education, particularly at the higher secondary level and beyond. The challenges of independent living in unfamiliar environments, coupled with academic pressures and increased responsibilities, may adversely impact sleep duration and quality.\u003c/p\u003e \u003cp\u003eOur study revealed a weak positive correlation between sleep quality and social media addiction, which is consistent with the findings of a systematic review and meta-analysis by Li Ying et al. (36). Cognitive‒behavioral theory suggests that individuals' thoughts and feelings can influence their actions, and vice versa. Consequently, social media addiction may impact emotions and cognitions, ultimately contributing to poor sleep quality (37). Additionally, we observed a significant association between ethnicity and sleep quality, with Brahmin/Chhetri students exhibiting lower odds of poor sleep quality than other groups did. This disparity might be attributed to the disproportionate challenges faced by ethnic minority groups, such as Dalit, Madhesi, and Muslim students, who may experience higher levels of discrimination and stress, negatively affecting their sleep. Nevertheless, further research is warranted to explore the potential influence of socioeconomic factors, living conditions, and specific ethnic and cultural elements on this relationship.\u003c/p\u003e \u003cp\u003eA total of three out of five (59.3%) students in our study experienced anxiety. Similarly, a high prevalence of anxiety was observed among higher secondary students in Kathmandu Valley (19). High anxiety among higher secondary students may stem from transitioning to a new academic setting, living independently, and lacking family support. In Nepal, many families discourage open discussions, leading adolescents to internalize their problems. Coupled with academic pressure, relationship issues, and emotional changes, this isolation can significantly heighten anxiety (38).\u003c/p\u003e \u003cp\u003eCompared with males, females presented greater odds of experiencing anxiety symptoms, which is consistent with previous research conducted among different groups of students (19,38). This disparity may be attributed to several factors. Women are more likely to encounter traumatic events such as sexual trauma, gender discrimination, domestic violence, and relationship stressors and tend to ruminate on these experiences more frequently than men (39). Gender-based differences in upbringing and socialization can also influence anxiety patterns. From childhood, boys are often encouraged to confront fears, leading to increased exposure and reduced fear responses, whereas girls may be discouraged from expressing fear (39). Additionally, men are more likely to underreport anxiety symptoms than women (39). Biological factors may also contribute to sex differences in anxiety, with women being more sensitive to the stress hormone corticotropin-releasing factor (40). Given these factors, tailored interventions and coping mechanisms are essential for addressing anxiety among students, particularly females.\u003c/p\u003e \u003cp\u003eA weak positive correlation was observed between social media addiction and anxiety, which aligns with findings from a systematic review and meta-analysis by Li Ying et al. (36). Constant exposure to idealized online personas can foster feelings of inadequacy and anxiety among students (41). Moreover, excessive social media use often reduces face-to-face interactions, hindering the development of essential social skills and contributing to social anxiety. The risk of cyberbullying and online harassment further exacerbates anxiety levels in this population (42). The diverse features and content available on social media platforms may also influence students' anxiety levels.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study employed widely accepted tools to measure social media addiction, sleep quality, and anxiety. This study contributes to the limited body of literature exploring the complex relationships among social media addiction, sleep quality, and anxiety.\u003c/p\u003e \u003cp\u003eOur study has several limitations worth noting. Incorporating variables such as wealth quintile, access to gadgets, and internet facilities at home could have provided a deeper understanding of the topic, which this study did not address. In addition, the use of subjective measurements may have introduced respondent bias. However, efforts were made to mitigate this by clearly explaining the study objectives to the students.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed high rates of social media addiction, poor sleep quality, and anxiety among higher secondary school students. A weak positive correlation between these factors was also identified. These findings underscore the need for targeted interventions, particularly for female and private school students. Strategies such as parental involvement, face-to-face interaction promotion, and school-based digital detox programs could help reduce social media addiction. Special attention should be given to girls, who are more susceptible to anxiety. Addressing social media addiction may also improve sleep quality and overall mental health.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAOR: Adjusted Odds Ratio, BSMAS: Bergen Social Media Addiction Scale, CI: Confidence Interval, COVID: Coronavirus disease, HADS: Hospital Anxiety and Depression Scale, MS: Microsoft, PSQI: Pittsburg Sleep Quality Index, SPSS: Statistical Package for the Social Sciences and SD: Standard Deviation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the students and school staff for their cooperation during data collection. We are also grateful to Suryabinayak Municipality for granting us permission to conduct the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLP and AKS conceived and designed the study. LP and KO conducted the survey, while LP and PA performed the analysis. LP drafted the initial manuscript, which was subsequently revised with input from all authors. AKS supervised the study. All authors have reviewed, approved, and endorsed the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data is in the supplementary file.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was done in accordance to the Helsinki Declaration of Research Ethics. Ethical approval was obtained from the Institutional Review Board of the Institute of Medicine (Reference number: 379(6-11) E2/080/081). Administrative approval for conducting the study was obtained from Suryabinayak municipality (Ref: 080/81/914) and from the school administration of the respective schools. Written informed consent was obtained from the students before data collection to ensure their willingness to participate, and no identifiers were listed in the questionnaire to make it anonymous and confidential. Parental consent was obtained from students who were under the age of 18 years.\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\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors have no competing interest associated with this paper.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSingh R, Arya S, Chadha B. Relationship between Social Media, Poor Sleep Quality and Anxiety. Webology. 2021;18(3):1151\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eBest P, Manktelow R, Taylor B. Online communication, social media and adolescent wellbeing: A systematic narrative review. Child Youth Serv Rev. 2014 Jun;41:27\u0026ndash;36.\u003c/li\u003e\n\u003cli\u003eXiao W, Peng J, Liao S. Exploring the Associations between Social Media Addiction and Depression: Attentional Bias as a Mediator and Socio-Emotional Competence as a Moderator. Int J Environ Res Public Health. 2022;19(20).\u003c/li\u003e\n\u003cli\u003eWoods HC, Scott H. #Sleepyteens: Social media use in adolescence is associated with poor sleep quality, anxiety, depression and low self-esteem. J Adolesc. 2016;51(June):41\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eAdams SK, Kisler TS. Sleep quality as a mediator between technology-related sleep quality, depression, and anxiety. Cyberpsychology, Behav Soc Netw. 2013;16(1):25\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eAlonzo R, Hussain J, Stranges S, Anderson KK. Interplay between social media use, sleep quality, and mental health in youth: A systematic review. Sleep Med Rev. 2021 Apr;56:101414.\u003c/li\u003e\n\u003cli\u003eHale L, Kirschen GW, Lebourgeois MK, Gradisar M, Garrison MM, Montgomery-downs H, et al. Youth screen media habits and sleep : sleep-friendly screen-behavior recommendations for clinicians , educators , and parents Corresponding Author : Lauren Hale , PhD Professor of Family , Population , and Preventive Medicine Program in Public Health Ston. 2018;1\u0026ndash;36.\u003c/li\u003e\n\u003cli\u003eCain J. It\u0026rsquo;s time to confront student mental health issues associated with smartphones and social media. Am J Pharm Educ. 2018;82(7):738\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eBhandari PM, Neupane D, Rijal S, Thapa K, Mishra SR, Poudyal AK. Sleep quality, internet addiction and depressive symptoms among undergraduate students in Nepal. BMC Psychiatry. 2017;17(1):1\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eSchmickler JM, Blaschke S, Robbins R, Mess F. Determinants of Sleep Quality: A Cross-Sectional Study in University Students. Int J Environ Res Public Health. 2023;20(3).\u003c/li\u003e\n\u003cli\u003eGhrouz AK, Noohu MM, Dilshad Manzar M, Warren Spence D, BaHammam AS, Pandi-Perumal SR. Physical activity and sleep quality in relation to mental health among college students. Sleep Breath. 2019;23(2):627\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eMeeks K, Peak AS, Dreihaus A. Depression, anxiety, and stress among students, faculty, and staff. J Am Coll Heal. 2023;71(2):348\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eJiang XL, Zheng XY, Yang J, Ye CP, Chen YY, Zhang ZG, et al. A systematic review of studies on the prevalence of Insomnia in university students. Public Health. 2015 Dec;129(12):1579\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003ePaudel K, Adhikari TB, Khanal P, Bhatta R, Paudel R, Bhusal S, et al. Sleep quality and its correlates among undergraduate medical students in Nepal: A cross-sectional study. PLOS Glob Public Heal. 2022;2(2):1\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eData Portal [Internet]. 2023. Digital 2023: Nepal \u0026mdash; DataReportal \u0026ndash; Global Digital Insights.\u003c/li\u003e\n\u003cli\u003eInternational Telecommunication Union [Internet]. 2022. Facts and Figures 2022.\u003c/li\u003e\n\u003cli\u003eYamada M, Sekine M, Tatsuse T, Asaka Y. Prevalence and associated factors of pathological internet use and online risky behaviors among japanese elementary school children. J Epidemiol. 2021;31(10):537\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eKhadka R, Bista S, Baskota S, Poudel L, Gurung M. Sleep Quality among College Students in Kathmandu Valley, Nepal. Nepal Med J. 2019;2(2):1\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eKarki A, Thapa B, Pradhan PMS, Basel P. Depression, anxiety and stress among high school students: A cross-sectional study in an urban municipality of Kathmandu, Nepal. PLOS Glob Public Heal. 2022;2(5):e0000516.\u003c/li\u003e\n\u003cli\u003eCharan J, Biswas T. How to calculate sample size for different study designs in medical research? Indian J Psychol Med. 2013;35(2):121\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eCopez-Lonzoy A, Vallejos-Flores M, Capa-Luque W, Salas-Blas E, Montero Doig AM, Dias PC, et al. Adaptation of the Bergen Social Media Addiction Scale (BSMAS) in Spanish. Acta Psychol (Amst). 2023;241.\u003c/li\u003e\n\u003cli\u003eSmyth C. The Pittsburgh Sleep Quality Index (PSQI). Director. 2000;8(1):28\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eSkapinakis P. Hospital Anxiety and Depression Scale (HADS). Encycl Qual Life Well-Being Res. 2014;(D):2930\u0026ndash;3.\u003c/li\u003e\n\u003cli\u003eMukaka MM. Statistics corner: A guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2012;24(3):69\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eCecilia Cheng, Yan-ching Lau, Linus Chan JWL. Prevalence of social media addiction across 32 nations: Meta-analysis with subgroup analysis of classification schemes and cultural values. 2020;\u003c/li\u003e\n\u003cli\u003ePaudel A, Chhetri M. Association Between Social Media and Psychological Effects Among Adolescents: A School Based Cross-Sectional Study in Kathmandu City of Nepal. Res Sq. 2021;1\u0026ndash;17.\u003c/li\u003e\n\u003cli\u003eChaudhury P, Tripathy HK. A study on impact of smartphone addiction on academic performance. Int J Eng Technol. 2018;7(2):50\u0026ndash;3.\u003c/li\u003e\n\u003cli\u003eWegmann E, Stodt B, Brand M. Addictive use of social networking sites can be explained by the interaction of internet use expectancies, internet literacy, and psychopathological symptoms. J Behav Addict. 2015;4(3):155\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eKim JH, Seo M, David P. Alleviating depression only to become problematic mobile phone users: Can face-to-face communication be the antidote? Comput Human Behav. 2015 Oct;51(PA):440\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eVieira YP, Viero V dos SF, Saes-Silva E, da Silva PA, da Silva LS, de Oliveira Saes M, et al. Excessive use of social media by high school students in southern Brazil. Rev Paul Pediatr. 2022;40:1\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eWartberg L, Kriston L, Thomasius R. Internet gaming disorder and problematic social media use in a representative sample of German adolescents: Prevalence estimates, comorbid depressive symptoms and related psychosocial aspects. Comput Human Behav. 2020;103(April 2019):31\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eDam VAT, Dao NG, Nguyen DC, Vu TMT, Boyer L, Auquier P, et al. Quality of life and mental health of adolescents: Relationships with social media addiction, Fear of Missing out, and stress associated with neglect and negative reactions by online peers. PLoS One. 2023;18(6 June):1\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eMasthi NRR, Pruthvi S, Mallekavu P. a Comparative Study on Social Media Addiction Between Public and Private High School Students of Urban Bengaluru, India. ASEAN J Psychiatry. 2017;18(2):0\u0026ndash;0.\u003c/li\u003e\n\u003cli\u003eChang H, Meng X, Li Y, Liu J, Yuan W, Ni J, et al. The effect of mindfulness on social media addiction among Chinese college students: A serial mediation model. Front Psychiatry. 2023;14(March).\u003c/li\u003e\n\u003cli\u003eSamudraa R, Nur Wangid M. The Effectiveness of Online Group Guidance in Reducing Social Media Addiction of High School Students. Int J Multicult Multireligious Underst. 2023;10(10):1.\u003c/li\u003e\n\u003cli\u003eLi Y, Li G, Liu L, Wu H. Correlations between mobile phone addiction and anxiety, depression, impulsivity, and poor sleep quality among college students: A systematic review and meta-analysis. J Behav Addict. 2020;9(3):551\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eGao WJ, Hu Y, Ji JL, Liu XQ. Relationship between depression, smartphone addiction, and sleep among Chinese engineering students during the COVID-19 pandemic. World J Psychiatry. 2023;13(6):361\u0026ndash;75.\u003c/li\u003e\n\u003cli\u003eAryal N, Rajbhandari A. Social media use and anxiety levels among school adolescents : a cross- \u0026shy; sectional study in Kathmandu , Nepal. 2024;1\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eDorti M. C. Examining Sex and gender differences in Anxiety Disorder. Intech. 2015;11:13.\u003c/li\u003e\n\u003cli\u003eAnxiety \u0026amp; Depression Association of America [Internet]. 2021. Facts | Anxiety and Depression Association of America, ADAA.\u003c/li\u003e\n\u003cli\u003eShafer L. Harvard Graduate School of Education. 2017. Social Media and Teen Anxiety | Harvard Graduate School of Education.\u003c/li\u003e\n\u003cli\u003eCommission CHR. Cyberbullying , human rights and bystanders. Aust Hum Right Commision. 2012;1\u0026ndash;6.\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":"Social media addiction, Sleep quality, Anxiety, Students, Nepal","lastPublishedDoi":"10.21203/rs.3.rs-5783624/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5783624/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eExcessive use of social media is linked with poor sleep quality and negative mental health outcomes. However, studies assessing the interplay of these three components among school children are exceedingly rare. This study aims to assess the levels of social media addiction, poor sleep quality, and anxiety among higher secondary school children, identify associated factors, and explore the correlations among these components.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study was conducted among 418 higher secondary school students. Multivariable logistic regression at a significance level of 0.05 was employed to determine factors associated with social media addiction, poor sleep quality, and anxiety. Additionally, a correlation test was used to examine the associations between social media addiction, poor sleep quality, and anxiety.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence rates of social media addiction, poor sleep quality, and anxiety were 33.5%, 64.4%, and 59.6%, respectively. Female students (aOR: 2.6; 95% CI: 1.6\u0026ndash;4.1) and students from private schools (aOR: 3.7; 95% CI: 2.0-6.8) had greater odds of being addicted to social media. Students from the Brahmin/Chhetri ethnic group (aOR: 0.5; 95% CI: 0.3\u0026ndash;0.9) had lower odds of experiencing poor sleep quality than the other groups did. Female students (aOR: 2.4; 95% CI: 1.6\u0026ndash;3.6) were more likely to experience anxiety. Additionally, sleep quality and anxiety were weakly positively correlated with social media addiction.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eExcessive social media use is associated with poor sleep quality and increased anxiety among Nepalese higher secondary students. Interventions such as face-to-face counseling, digital detox programs, and tailored approaches for high-risk groups are essential to address these issues and enhance their overall well-being.\u003c/p\u003e\u003ch2\u003eClinical trial number:\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e","manuscriptTitle":"Social media addiction and its association with sleep quality and anxiety: A school-based cross-sectional study from Nepal.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-16 07:47:47","doi":"10.21203/rs.3.rs-5783624/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":"0f7d26e7-042c-4f7b-99e6-ca0b5c6bca57","owner":[],"postedDate":"January 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-16T07:47:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-16 07:47:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5783624","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5783624","identity":"rs-5783624","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}