Analytical Text Example about Social Media – Social media or social network is one of several phenomena that began to emerge in the early 2000s. Most people who are able to connect to the internet today have social media account to get in touch with others online. However, there are also some bad impacts of social media, especially for teenager. That’s why this topic is often used by students to write an analytical text for their task. Teenagers play social media, via If you are looking for an analytical text about social media for your task, here is an example of analytical text that will be discussing the bad sides of social media for teenagers. Example of an Analytical Exposition Text about Social Media Social Media are Bad for Teenagers Social media or social network websites such as Twitter, Instagram, Facebook, Google Plus and many others have become one of the inescapable aspects of our modern life, especially for most teenagers. These websites are not just becoming a part of their world, but it’s indeed becoming their world. They spend their time more and more on social media. It happens because most of the teens now have their own smartphone. They can use it to connect to the internet and access social media freely. They are constantly posting and uploading status, pictures, and videos on social media. This hyper-connected habit to social media could lead to some bad effects for them. Firstly, most teens nowadays stay connected to the internet, accessing social media the whole time. They always check their social media account on the smartphone from the time they wake up in the morning till they back to sleep at night. This “always connected” habit is bad because it could make the risk they are getting bullied higher. These days, bullying doesn’t only happen in schools or on buses, but it also has spread over social media. It means, if a teen is getting bullied in real life, the bully will simply keep doing it online on social media. Secondly, based on the latest study, teenagers who engage with social media during the night could ruin their sleep pattern and it would lead to a higher risk of anxiety and depression. Teens who always online tended to feel that they have to available online 24 hours. It’s resulting anxiety if they didn’t respond or reply text or post immediately. It showed that teens are so emotionally devoted on social media that a fifth of secondary school students would stay awake at night just to make sure they don’t miss anything on social media. Lastly, Social media could decrease the real life social interaction because they are being more comfortable with their online friends. A separate study that was conducted by the National Citizen Service also found that most girls seek comfort on social media rather than talking their problem to their parents. The survey also suggested that girls are likely experiencing stress more often than boys about twice in a week. Social media websites are basically created to connect people around the world easily so they can interact and communicate with each other. However, the excessive use of social media could lead to some bad effects, especially for teenagers. As it has been mentioned above that social media could be a bullying media and make the chance of a teen is getting bullied higher, improve the risk of getting depressed and anxious, and reduce their social interaction in real life. Therefore, it obvious that social media are dangerous for teenagers’ health both emotionally and mentally. Well, that’s all about the example of analytical exposition about social media that discussing the bad effects of social media for teenagers. If you guys want to learn more about English, relating to text genre, grammar, or vocabulary, you can get more English lessons on the index page of ContohText.
aseparate study by the national citizen service found that, rather than talking to their parents, girls seek comfort on social media when they are worried. f social media such as facebook, twitter, instagram, and many others are basically created to connect everyone around the globe so they can interact and communicate each reiteration
Loading metrics Open Access Peer-reviewed Research Article Pinpin Zheng, Yingnan Jia, Hao Chen, Yimeng Mao, Suhong Chen, Yi Wang, Hua Fu, Junming Dai Mental health problems and social media exposure during COVID-19 outbreak Junling Gao, Pinpin Zheng, Yingnan Jia, Hao Chen, Yimeng Mao, Suhong Chen, Yi Wang, Hua Fu, Junming Dai x Published April 16, 2020 Figures AbstractHuge citizens expose to social media during a novel coronavirus disease COVID-19 outbroke in Wuhan, China. We assess the prevalence of mental health problems and examine their association with social media exposure. A cross-sectional study among Chinese citizens aged≥18 years old was conducted during Jan 31 to Feb 2, 2020. Online survey was used to do rapid assessment. Total of 4872 participants from 31 provinces and autonomous regions were involved in the current study. Besides demographics and social media exposure SME, depression was assessed by The Chinese version of WHO-Five Well-Being Index WHO-5 and anxiety was assessed by Chinese version of generalized anxiety disorder scale GAD-7. multivariable logistic regressions were used to identify associations between social media exposure with mental health problems after controlling for covariates. The prevalence of depression, anxiety and combination of depression and anxiety CDA was 95%CI 95%CI and 95%CI during COVID-19 outbroke in Wuhan, China. More than 80% 95%CI of participants reported frequently exposed to social media. After controlling for covariates, frequently SME was positively associated with high odds of anxiety OR = 95%CI and CDA OR = 95%CI compared with less SME. Our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health problems, especially depression and anxiety among general population and combating with “infodemic” while combating during public health emergency. Citation Gao J, Zheng P, Jia Y, Chen H, Mao Y, Chen S, et al. 2020 Mental health problems and social media exposure during COVID-19 outbreak. PLoS ONE 154 e0231924. Kenji Hashimoto, Chiba Daigaku, JAPANReceived March 4, 2020; Accepted April 4, 2020; Published April 16, 2020Copyright © 2020 Gao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are Availability All relevant data are within the manuscript and its Supporting Information Junling Gao was funded by National key R&D Program of China grant no. 2018YFC2002000 & 2018YFC2002001 and National Natural Science Foundation of China grant no. 71573048. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the interests The authors have declared that no competing interests exist. IntroductionA public health emergency of international concern-novel coronavirus disease COVID-19 outbroke[1] in Wuhan, China on 31 December 2019, which has been spread to 24 countries outside of China and infected 37,558 patients globally 37,251 in China by 9 February 2020[2]. The outbreak of COVID-19 in China has caused mental health problems among the public in China[3] and Japan[4] and medical workers in Wuhan[5]. The National Health Commission has released guideline for local authorities to promote psychological crisis intervention for patients, medical personnel, people under medical observation and civilians during the COVID-19 outbreak[6]. However, what type of mental disorders are prevalent and how they distribute among population are not know. So, a rapid assessment of outbreak-associated mental disorders for both civilians and health care workers, is needed[7]. The official departments strive to improve the public’s awareness of prevention and intervention strategies by providing daily updates about surveillance and active cases on websites and social media[3]. Besides, many self-media and netizens also release and transfer related information on social media, such as WeChat and Weibo. Social media may lead to misinformation overload[8,9], which in turn may cause mental health problems. WHO pointed out that identifying the underlying drivers of fear, anxiety and stigma that fuel misinformation and rumour, particularly through social media[10]. Previous studies indicated that indirect exposure to mass trauma through the media can increase the initial rates of post-traumatic stress disorder PTSD symptoms[11]. A previous study also shown social media exposure may positively related to forming risk perceptions during the MERS outbreak in South Korea[12]. But there was no study to examine the association between social media exposure and mental health problems. So, the current study aims to describes the prevalence and distribution of two major mental disorders-anxiety and depression among Chinese population [13], and examine their associations with social media exposure by rapid assessment during COVID-19 outbreak. Materials and methods Design and participants This cross-sectional study was online conducted during Jan 31 to Feb 2, 2020. Chinese citizens aged≥18 years old were invited to participate online survey though Wenjuanxing platform In total, 5,851 participants took part in the survey. After removing the participants without completed questionnaires, 4872 participants from 31 provinces and autonomous regions were involved in the current study. A written consent in the first section of online survey was given to all participants before filling the questionnaire. This study has been approved by the Institutional Review Board of Fudan University, School of Public HealthIRB2020-01-0800. Measurements Mental health to a previous study two major mental disorders-depression and anxiety [13] were assessed in the current study. Depression was assessed by The Chinese version of WHO-Five Well-Being Index WHO-5[14], which consists of five positively worded items that reflect the presence or absence of well-being rather than depressive symptomatology. Participants are asked to report the presence of these positive feelings in the last 2 weeks on a 6-point scale ranging from all of the time 5 points to at no time 0 points. A summed score below 13 indicates depression[14]. Anxiety was assessed by Chinese version of generalized anxiety disorder scale GAD-7[15,16], which consists 7 symptoms. Participants were asked how often they were bothered by each symptom during the last 2 weeks. Response options were “not at all,” “several days,” “more than half the days,” and “nearly every day,” scored as 0, 1, 2, and 3, respectively. A score of 10 or greater represents a reasonable cut point for identifying cases of anxiety[15,16]S1 Table. Social media exposure SME.Social media exposure was measured by asking how often respondents during the past week were exposed to news and information about COVID-19 on social media, such as Sina weibo, Zhihu, Douban, WeChat and etc S1 Table. Response options were “never”, “once in a while”, “sometimes”, “often” and “very often”. Because of less proportion of “never”, so we recoded social media exposure into “less” “never” and “once in a while”, “sometimes” and “frequently” “often” and “very often”. following covariates were included in this study gender, age 10-year categories, educational level junior high school, senior high school, college and master and higher, marital status recoded into married and other [including unmarried, divorced, and widowed], self-rated health categorized as excellent, very good and good or low, occupationstudents/retired, health care worker and others, citiesWuhan and others, areaurban and rural. Statistical analyses The χ2 /trend tests were used to determine the prevalence of depression, anxiety and combination of depression and anxiety by categorical variables including social media exposure and covariates. Logistic regression analyses were used to explain the association between the prevalence of depression, anxiety and combination of depression and anxiety and SME after controlling for covariates. We estimated the adjusted ORs and their 95% confidence intervals CIs of independent variables for frailty. The STATA version program StataCorp LP., College Station, TX, USA was used to carry out all analyses. Results Social media exposure Of all 4827 participants, the mean age of was years ranged 18–85, the proportion of “less”, “sometimes”, and “frequently” of SME was and As shown in Table 1, more than 60% of them were women, and most were aged 21–30 years. Many participants had achieved a college education, more than half of them were married. Only of them were health care workers and were from Hubei province, and were from urban area. Most of them reported “excellent” or “very good” health. Univariate analyses found that the proportion of frequently SME among men 95%CI was lower than among women 95%CI the proportion of frequently SME among youngers aged -30 years was higher than among elders aged 41- years. Participants with low education middle school and high school had lower proportion of frequently SME than who with high education college and master. Participants who are students or retired had higher proportion of frequently SME. The proportion of SME was not different between participants from Hubei province and others, however, participants from rural area reported higher proportion of frequently SME than who from urban area. Participants who were excellent health had higher proportion of frequently SME than others. Depression and SME The prevalence of depression was 95%CI As shown Fig 1, Multivariate analyses found that the adjusted odds of depression were greater among who age 21–30 years OR = 95%CI and 31–40 years OR = 95%CI compared with who aged ≤20 years, and lower among those with college OR = 95%CI and master OR = 95%CI education than those with middle school. Participants from Hubei province had no higher adjusted odds than those from other province OR = 95%CI but those from rural area had lower adjusted odds OR = 95%CI than those from urban area. The decrease of self-rated health significantly accompanied the increased odds of depression. About the focus of this study, higher frequency of SME was insignificantly positively associated with the adjusted odds of depression after controlling for all covariates. Anxiety and SME The prevalence of anxiety was 95%CI As shown Fig 2, Multivariate analyses found that that the adjusted odds of depression were greater among those aged 31–40 years OR = 95%CI compared with those aged -20 years, and lower among those with college OR = 95%CI and master OR = 95%CI education than those with middle school. The adjusted odds of depression among unmarried participants OR = 95%CI was lower than among married ones. Participants from other provinces had no higher adjusted odds OR = 95%CI than those from Hubei province. The adjusted odds of depression were greater among those with good/general/poor SRH OR = 95%CI compared with those with excellent SRH. About the focus of this study, frequently SME can increase the adjusted odds OR = 95%CI of anxiety compared with less SME after controlling for all covariates. Combination of depression and anxiety and SME The prevalence of combination of depression and anxiety CDA was 95%CI As shown Fig 3, Multivariate analyses found that that the adjusted odds of depression were greater among those aged 31–40 years OR = 95%CI compared with those aged -20 years, and lower among those with college OR = 95%CI and master OR = 95%CI education than those with middle school. The adjusted odds of depression among unmarried participants OR = 95%CI was lower than among married ones. The adjusted odds of depression were greater among those with good/general/poor SRH OR = 95%CI compared with those with excellent SRH. About the focus of this study, frequently SME can increase the adjusted odds OR = 95%CI of CDA compared with less SEM after controlling for all covariates. DiscussionThe latest national sample indicated the prevalence of any disorder excluding dementia, anxiety disorders and depressive disorders was 95%CI 95%CI and 95%CI in China[13]. Comparing with this national data, the current cross-sectional study found that much higher prevalence of depression 95%CI anxiety 95%CI and CDA 95%CI during COVID-19 outbroke in Wuhan, China. These findings are consistent with the previous studies’ that exposing public health emergency can cause public mental health problems, such as Wenchuan and Lushan earthquakes[17], 2014 Ebola Outbreak[7,18], and SARS[19]. Social media is one of main channels updating the COVID-19 information[3]. This study also found that of participants frequently expose them to social media, and frequently SME associated high odds of anxiety and CDA, which is consistent with previous studies [11]. there may be two reasons explaining the association between frequently SME and mental health. During COVID-19 outbreak, disinformation and false reports about the COVID-19 have bombarded social media and stoked unfounded fears among many netizens[20], which may confuse people and harm people’s mental health[9]. Besides, many citizens expressed their negative feelings, such as fear, worry, nervous, anxiety et al. on social media, which are contagious social network[21,22]. So, WHO’s infodemics’ team is working hand in glove with countries’ communications department to deliver information to a broader public audience[23]. Finally, we also found that SME was not different between participants from Hubei province and others, but the formers faced higher odds of anxiety. It indicated that participants from Hubei province- the infectious focus directly expose to public health emergency, and may suffer more mental health problemes[17,19]. Compared with the control measures taken by other cities, Wuhan have sealed off the city from all outside contact to stop the spread of the COVID-19. As the prevention and control measures called new standard by WHO[24], the lockdown of Wuhan is a very effective way to interrupt the transmission of the virus, however, the strictest measures in Wuhan might lead to more serious mental health problems of local people. Some potential limitations should be noted in this study. First, this is a cross-sectional study, so it is difficult to accurately elucidate causal relationships between SME and mental health. Additional longitudinal studies, such as cohort studies or nested case-control studies, are essential in the future. Although large sample, the survey was conducted online, which is suitable for rapid assessment, so some respondent bias, such as few elder citizens’ participation, may have affected the results. Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors. ConclusionsIn conclusion, our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health among general population while combating with COVID-19. Fortunately, The China government have provided mental health services by varied channel including hotline, online consultation, online course and outpatient consultation[6], but more attention should be paid to depression and anxiety. The next implication is to combat with “infodemic” by monitoring and filtering out false information and promoting accurate information though cross-section collaborations. Supporting information References1. WHO. WHO Director-General's statement on IHR Emergency Committee on Novel Coronavirus 2019-nCoV. accessed Feb 9, 2020 2. WHO. Novel Coronavirus2019-nCoV Situation Report–20. accessed Feb 9, 2020 3. Bao Y, Sun Y, Meng S, Shi J, Lu L. 2019-nCoV epidemic address mental health care to empower society. The Lancet. Feb 07,2020. DOI View Article Google Scholar 4. Shigemura J, Ursano RJ, Morganstein JC, Kurosawa M, Benedek DM. Public responses to the novel 2019 coronavirus 2019-nCoV in Japan mental health consequences and target populations. Psychiatry Clin Neurosci. Feb 08, 2020. pmid32034840 View Article PubMed/NCBI Google Scholar 5. Kang L, Li Y, Hu S, et al. The mental health of medical workers in Wuhan, China dealing with the 2019 novel coronavirus. The Lancet Psychiatry. Feb 05, 2020. accessed Feb 11, 2020 View Article Google Scholar 6. National Health Commission of the People’s Republic of China. Guideline for psychological crisis intervention during 2019-nCoV. accessed Feb 10, 2020 7. Shultz JM, Baingana F, Neria Y. The 2014 Ebola Outbreak and Mental Health Current Status and Recommended Response. JAMA 2015; 3136 567–8. pmid25532102 View Article PubMed/NCBI Google Scholar 8. Bontcheva K, Gorrell G, Wessels B. Social Media and Information Overload Survey Results. arXiv e-prints, 2013. accessed June 01, 2013. View Article Google Scholar 9. Florian Roth, Brönnimann G. Focal Report 8 Risk Analysis Using the Internet for Public Risk Communication. accessed Feb 12, 2020 10. WHO. COVID 2019 PHEIC Global research and innovation forum towards a research roadmap. accessed Feb 14, 2020 11. Neria Y, Sullivan GM. Understanding the mental health effects of indirect exposure to mass trauma through the media. JAMA 2011; 30612 1374–5. pmid21903818 View Article PubMed/NCBI Google Scholar 12. Choi D-H, Yoo W, Noh G-Y, Park K. The impact of social media on risk perceptions during the MERS outbreak in South Korea. Computers in Human Behavior 2017; 72 422–31. View Article Google Scholar 13. Huang Y, Wang Y, Wang H, et al. Prevalence of mental disorders in China a cross-sectional epidemiological study. Lancet Psychiatry 2019; 63 211–24. pmid30792114 View Article PubMed/NCBI Google Scholar 14. WHO Collaborating Centre in Mental Health. Chinese version of the WHO-Five Well-Being Index. accessed Feb 10, 2020 15. Spitzer RL, Kroenke K, Williams JB, Lowe B. A brief measure for assessing generalized anxiety disorder the GAD-7. Archives of internal medicine 2006; 16610 1092–7. pmid16717171 View Article PubMed/NCBI Google Scholar 16. Xu WF PY, Chen BQ. Assessment of Anxiety and Depression by Self-rating Scales of GAD-7 and PHQ-9 in Cardiovascular Outpatients. World Latest Medicine Information Electronic Version, 2018, 181612–14. in Chinese View Article Google Scholar 17. Xie Z, Xu J, Wu Z. Mental health problems among survivors in hard-hit areas of the Wenchuan and Lushan earthquakes. J Ment Health 2017; 261 43–9. pmid28084103 View Article PubMed/NCBI Google Scholar 18. Ji D, Ji YJ, Duan XZ, et al. Prevalence of psychological symptoms among Ebola survivors and healthcare workers during the 2014–2015 Ebola outbreak in Sierra Leone a cross-sectional study. Oncotarget 2017; 88 12784–91. pmid28061463 View Article PubMed/NCBI Google Scholar 19. Mak IW, Chu CM, Pan PC, Yiu MG, Chan VL. Long-term psychiatric morbidities among SARS survivors. Gen Hosp Psychiatry 2009; 314 318–26. pmid19555791 View Article PubMed/NCBI Google Scholar 20. Xinhua. Bat soup, biolab, crazy numbers … Misinformation "infodemic" on novel coronavirus exposed. accessed Feb 15, 2020 21. Kramer AD, Guillory JE, Hancock JT. Experimental evidence of massive-scale emotional contagion through social networks. Proc Natl Acad Sci U S A 2014; 11124 8788–90. pmid24889601 View Article PubMed/NCBI Google Scholar 22. Niederkrotenthaler T, Stack S, Till B, et al. Association of Increased Youth Suicides in the United States With the Release of 13 Reasons Why. JAMA Psychiatry 2019; 769 933–40. View Article Google Scholar 23. WHO. Director-General’s remarks at the media briefing on 2019 novel coronavirus on 8 February 2020. accessed Feb 15, 2020 24. WHO. Emergencies Coronavirus EC Meeting. accessed Feb 15, 2020
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However too much exposure of social media can also be bad especially for teenagers. As it mentioned above, social media could become media for bullying, risk them of anxiety and depression, and risk their real-life social interaction. Therefore, social media are dangerous for teenagers' health both mentally and emotionally. Terjemah:
Firstly students can use internet for searching a lot of information that related with material in their school. They can learn by themselves how to overcome their homework using internet. Internet provides a lot of free media learning that students can easy to access it. Secondly, an online education provides students with the convenience of
Althoughsocial media can be used in a positive way, negative effects such as a lack of social skills cyber bullying and outweigh the positive. A negative effect of social media is that it interferes with the development and nature of one's social interactions. People often say that they know someone but in reality, they only know their social
Kitasudah belajar contoh explanation text yang kebanyakan tentang gejala alam. Kali ini adalah contoh explanation text about social phenomena.Teks explanation mamang bisa bertema alam dan juga sosial. Sebagaimana disebutkan dalam pengertian teks explanation, jenis teks ini berfungsi untuk mejelaskan bagaimana dan kenapa suatu gejala alam dan sosial itu terjadi.
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exposition text about social media
