The Mental Health and Social Media Use of Young Australians during the COVID-19 Pandemic
Abstract
:1. Introduction
2. Methods
2.1. Setting and Design
2.2. Participants and Procedure
2.3. Measures
2.3.1. Mental Health Measures
2.3.2. Social Media Measures
2.4. Data Analysis
2.5. Ethics and Safety
3. Results
3.1. Participants
3.2. Mental Health
3.3. Social Media Use—General
3.4. Associations between Social Media Use and DASS-21 Scores
3.5. Social Media Use for Support with Suicidal Thoughts or Self-Harm
4. Discussion
Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Shanahan, L.; Steinhoff, A.; Bechtiger, L.; Murray, A.L.; Nivette, A.; Hepp, U.; Ribeaud, D.; Eisner, M. Emotional distress in young adults during the COVID-19 pandemic: Evidence of risk and resilience from a longitudinal cohort study. Psychol. Med. 2020, 1–10. [Google Scholar] [CrossRef] [PubMed]
- Arora, T.; Grey, I.; Östlundh, L.; Lam, K.B.H.; Omar, O.M.; Arnone, D. The prevalence of psychological consequences of COVID-19: A systematic review and meta-analysis of observational studies. J. Health Psychol. 2020. [Google Scholar] [CrossRef] [PubMed]
- Wu, T.; Jia, X.; Shi, H.; Niu, J.; Yin, X.; Xie, J.; Wang, X. Prevalence of mental health problems during the COVID-19 pandemic: A systematic review and meta-analysis. J. Affect. Disord. 2020, 281, 91–98. [Google Scholar] [CrossRef]
- Nearchou, F.; Flinn, C.; Niland, R.; Subramaniam, S.S.; Hennessy, E. Exploring the Impact of COVID-19 on Mental Health Outcomes in Children and Adolescents: A Systematic Review. Int. J. Environ. Res. Public Health 2020, 17, 8479. [Google Scholar] [CrossRef]
- Liu, C.; Stevens, C.; Conrad, R.; Hahm, H. Evidence for elevated psychiatric distress, poor sleep, and quality of life concerns during the COVID-19 pandemic among U.S. young adults with suspected and reported psychiatric diagnoses. Psychiatry Res. 2020, 292, 113345. [Google Scholar] [CrossRef]
- Viner, R.M.; Russell, S.J.; Croker, H.; Packer, J.; Ward, J.; Stansfield, C.; Mytton, O.; Bonell, C.; Booy, R. School closure and management practices during coronavirus outbreaks including COVID-19: A rapid systematic review. Lancet Child Adolesc. Health 2020, 4, 397–404. [Google Scholar] [CrossRef]
- Kabátek, J. Jobless and Distressed: The Disproportionate Effects of Covid-19 on Young Australians; University of Melbourne: Melbourne, Australia, 2020. [Google Scholar]
- Lee, C.M.; Cadigan, J.M.; Rhew, I.C. Increases in Loneliness among Young Adults During the COVID-19 Pandemic and Association With Increases in Mental Health Problems. J. Adolesc. Health 2020, 67, 714–717. [Google Scholar] [CrossRef]
- World Health Organization. Global Status Report on Preventing Violence against Children; World Health Organization: Geneva, Switzerland, 2020.
- Pereda, N.; Díaz-Faes, D.A. Family violence against children in the wake of COVID-19 pandemic: A review of current perspectives and risk factors. Child Adolesc. Psychiatry Ment. Health 2020, 14, 1–7. [Google Scholar] [CrossRef]
- Glowacz, F.; Schmits, E. Psychological distress during the COVID-19 lockdown: The young adults most at risk. Psychiatry Res. 2020, 293, 113486. [Google Scholar] [CrossRef]
- Jia, R.; Ayling, K.; Chalder, T.; Massey, A.; Broadbent, E.; Morling, J.R.; Coupland, C.; Vedhara, K. Young people, mental health and COVID-19 infection: The canaries we put in the coal mine. Public Health 2020, 189, 158–161. [Google Scholar] [CrossRef]
- Thorisdottir, I.E.; Asgeirsdottir, B.B.; Kristjansson, A.L.; Valdimarsdottir, H.B.; Tolgyes, E.M.J.; Sigfusson, J.; Allegrante, J.P.; Sigfusdottir, I.D.; Halldorsdottir, T. Depressive symptoms, mental wellbeing, and substance use among adolescents before and during the COVID-19 pandemic in Iceland: A longitudinal, population-based study. Lancet Psychiatry 2021, 8, 663–672. [Google Scholar] [CrossRef]
- Balachandran, A.K.; Alagarsamy, S.; Mehrolia, S. Suicide among children during Covid-19 pandemic: An alarming social issue. Asian J. Psychiatry 2020, 54, 102420. [Google Scholar] [CrossRef] [PubMed]
- Tanaka, T.; Okamoto, S. Increase in suicide following an initial decline during the COVID-19 pandemic in Japan. Nat. Hum. Behav. 2021, 5, 229–238. [Google Scholar] [CrossRef] [PubMed]
- Ueda, M.; Nordström, R.; Matsubayashi, T. Suicide and mental health during the covid-19 pandemic in Japan. Public Health 2021. [Google Scholar] [CrossRef]
- Dubé, J.P.; Smith, M.M.; Sherry, S.B.; Hewitt, P.L.; Stewart, S.H. Suicide behaviors during the COVID-19 pandemic: A meta-analysis of 54 studies. Psychiatry Res. 2021, 301, 113998. [Google Scholar] [CrossRef]
- Lustig, S.; Koenig, J.; Resch, F.; Kaess, M. Help-seeking duration in adolescents with suicidal behavior and non-suicidal self-injury. J. Psychiatr. Res. 2021, 140, 60–67. [Google Scholar] [CrossRef] [PubMed]
- Carr, M.J.; Steeg, S.; Webb, R.T.; Kapur, N.; Chew-Graham, A.C.; Abel, K.M.; Hope, H.; Pierce, M.; Ashcroft, D.M. Effects of the COVID-19 pandemic on primary care-recorded mental illness and self-harm episodes in the UK: A population-based cohort study. Lancet Public Health 2021, 6, e124–e135. [Google Scholar] [CrossRef]
- Robinson, J.; Rodrigues, M.; Fisher, S.; Bailey, E.; Herrman, H. Social media and suicide prevention: Findings from a stakeholder survey. Shanghai Arch. Psychiatry 2015, 27, 27–35. [Google Scholar] [CrossRef]
- Schultz, A.; Parikh, J. Keeping Our Services Stable and Reliable During the Covid-19 Outbreak. Available online: https://about.fb.com/news/2020/03/keeping-our-apps-stable-during-covid-19/ (accessed on 13 May 2021).
- Pew Research Center. Teens, Social Media & Technology; Pew Research Center: Washington, DC, USA, 2018. [Google Scholar]
- Naslund, J.A.; Bondre, A.; Torous, J.; Aschbrenner, K.A. Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice. J. Technol. Behav. Sci. 2020, 5, 245–257. [Google Scholar] [CrossRef] [Green Version]
- Robinson, J.; Cox, G.; Bailey, E.; Hetrick, S.; Rodrigues, M.; Fisher, S.; Herrman, H. Social media and suicide prevention: A systematic review. Early Interv. Psychiatry 2015, 10, 103–121. [Google Scholar] [CrossRef]
- Lovibond, S.H.; Lovibond, P.F. Manual for the Depression Anxiety Stress Scales; Psychology Foundation: Sydney, Australia, 1995. [Google Scholar]
- Shaw, T.; Campbell, M.; Runions, K.; Zubrick, S. Properties of the DASS-21 in an Australian Community Adolescent Population. J. Clin. Psychol. 2016, 73, 879–892. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Szabó, M. The short version of the Depression Anxiety Stress Scales (DASS-21): Factor structure in a young adolescent sample. J. Adolesc. 2010, 33, 1–8. [Google Scholar] [CrossRef]
- Hawke, L.D.; Hayes, E.; Darnay, K.; Henderson, J. Mental health among transgender and gender diverse youth: An exploration of effects during the COVID-19 pandemic. Psychol. Sex. Orientat. Gend. Divers. 2021, 8, 180–187. [Google Scholar] [CrossRef]
- Xiong, J.; Lipsitz, O.; Nasri, F.; Lui, L.M.W.; Gill, H.; Phan, L.; Chen-Li, D.; Iacobucci, M.; Ho, R.; Majeed, A.; et al. Impact of COVID-19 pandemic on mental health in the general population: A systematic review. J. Affect. Disord. 2020, 277, 55–64. [Google Scholar] [CrossRef] [PubMed]
- Vindegaard, N.; Benros, M.E. COVID-19 pandemic and mental health consequences: Systematic review of the current evidence. Brain Behav. Immun. 2020, 89, 531–542. [Google Scholar] [CrossRef] [PubMed]
- Evans, S.; Alkan, E.; Bhangoo, J.K.; Tenenbaum, H.; Ng-Knight, T. Effects of the COVID-19 lockdown on mental health, wellbeing, sleep, and alcohol use in a UK student sample. Psychiatry Res. 2021, 298, 113819. [Google Scholar] [CrossRef] [PubMed]
- Tamarit, A.; de la Barrera, U.; Mónaco, E.; Schoeps, K.; Castilla, I.M. Psychological impact of covid-19 pandemic in spanish adolescents: Risk and protective factors of emotional symptoms. Rev. Psicol. Clín Niños Adolesc. 2020, 7, 73–80. [Google Scholar]
- Kornilaki, E.N. The psychological effect of COVID-19 quarantine on Greek young adults: Risk factors and the protective role of daily routine and altruism. Int. J. Psychol. 2021. [Google Scholar] [CrossRef]
- Australian Institute of Health and Welfare. Australia’s Health 2016; AIHW: Canberra, Australia, 2016.
- Pan, K.-Y.; Kok, A.A.L.; Eikelenboom, M.; Horsfall, M.; Jörg, F.; Luteijn, R.A.; Rhebergen, D.; van Oppen, P.; Giltay, E.J.; Penninx, B.W.J.H. The mental health impact of the COVID-19 pandemic on people with and without depressive, anxiety, or obsessive-compulsive disorders: A longitudinal study of three Dutch case-control cohorts. Lancet Psychiatry 2021, 8, 121–129. [Google Scholar] [CrossRef]
- Scharkow, M. The Accuracy of Self-Reported Internet Use—A Validation Study Using Client Log Data. Commun. Methods Meas. 2016, 10, 13–27. [Google Scholar] [CrossRef]
- Ernala, S.K.; Burke, M.; Leavitt, A.; Ellison, N.B. How well do people report time spent on facebook? An evaluation of established survey questions with recommendations. In In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA, 25–30 April 2020; Association for Computing Machinery: New York, NY, USA, 2020; pp. 1–14. [Google Scholar]
- Barthorpe, A.; Winstone, L.; Mars, B.; Moran, P. Is social media screen time really associated with poor adolescent mental health? A time use diary study. J. Affect. Disord. 2020, 274, 864–870. [Google Scholar] [CrossRef]
- Tsitsika, A.K.; Tzavela, E.C.; Janikian, M.; Ólafsson, K.; Iordache, A.; Schoenmakers, T.M.; Tzavara, C.; Richardson, C. Online Social Networking in Adolescence: Patterns of Use in Six European Countries and Links With Psychosocial Functioning. J. Adolesc. Health 2014, 55, 141–147. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rae, J.R.; Lonborg, S.D. Do motivations for using facebook moderate the association between facebook use and psychological well-being? Front. Psychol. 2015, 6, 771. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Seabrook, E.M.; Kern, M.L.; Rickard, N.S. Social networking sites, depression, and anxiety: A systematic review. JMIR Ment. Health 2016, 3, e50. [Google Scholar] [CrossRef] [PubMed]
- Liu, H.; Liu, W.; Yoganathan, V.; Osburg, V.S. COVID-19 information overload and generation Z’s social media discontinuance intention during the pandemic lockdown. Technol. Forecast Soc. Chang. 2021, 166, 120600. [Google Scholar] [CrossRef]
- LGBTIQ + Health Australia. Snapshot of Mental Health and Suicide Prevention Statistics for LGBTIQ+ People; LGBTIQ + Health Australia: Sydney, Australia, 2021. [Google Scholar]
- Cerel, J.; Tucker, R.R.; Aboussouan, A.; Snow, A. Suicide exposure in transgender and gender diverse adults. J. Affect. Disord. 2020, 278, 165–171. [Google Scholar] [CrossRef] [PubMed]
- Lenhart, A.; Madden, M. Social Networking Websites and Teens; Pew Research Center: Washington, DC, USA, 2007. [Google Scholar]
- Anderson, M.; Jiang, J. Teens’ Social Media Habits and Experiences; Pew Research Center: Washington, DC, USA, 2018. [Google Scholar]
- Australian Psychological Society. Digital Me: A Survey Exploring the Effect of Social Media and Digital Technology on Australians’ Wellbeing; Australian Psychological Society: Melbourne, Australia, 2017. [Google Scholar]
- Khasawneh, A.; Madathil, K.C.; Dixon, E.; Wiśniewski, P.; Zinzow, H.; Roth, R. Examining the Self-Harm and Suicide Contagion Effects of the Blue Whale Challenge on YouTube and Twitter: Qualitative Study. JMIR Ment. Health 2020, 7, e15973. [Google Scholar] [CrossRef]
- Brown, R.C.; Fischer, T.; Goldwich, D.A.; Plener, P.L. “I just finally wanted to belong somewhere”—Qualitative analysis of experiences with posting pictures of self-injury on instagram. Front Psychiatry 2020, 11, 274. [Google Scholar] [CrossRef] [Green Version]
- Lavis, A.; Winter, R. #Online harms or benefits? An ethnographic analysis of the positives and negatives of peer-support around self-harm on social media. J. Child Psychol. Psychiatry 2020, 61, 842–854. [Google Scholar] [CrossRef]
- Swedo, E.A.; Beauregard, J.L.; de Fijter, S.; Werhan, L.; Norris, K.; Montgomery, M.P.; Rose, E.B.; David-Ferdon, C.; Massetti, G.M.; Hillis, S.D.; et al. Associations Between Social Media and Suicidal Behaviors During a Youth Suicide Cluster in Ohio. J. Adolesc. Health 2021, 68, 308–316. [Google Scholar] [CrossRef]
- La Sala, L.; Teh, Z.; Lamblin, M.; Rajaram, G.; Rice, S.; Hill, N.T.M.; Thorn, P.; Krysinska, K.; Robinson, J. Can a social media intervention improve online communication about suicide? A feasibility study examining the acceptability and potential impact of the #chatsafe campaign. PLoS ONE 2021, 16, e0253278. [Google Scholar] [CrossRef]
- Thorn, P.; Hill, N.T.; Lamblin, M.; Teh, Z.; Battersby-Coulter, R.; Rice, S.; Bendall, S.; Gibson, K.L.; Finlay, S.M.; Blandon, R.; et al. Developing a Suicide Prevention Social Media Campaign With Young People (The #Chatsafe Project): Co-Design Approach. JMIR Ment. Health 2020, 7, e17520. [Google Scholar] [CrossRef] [PubMed]
- Robinson, J.; Hill, N.T.M.; Thorn, P.; Battersby-Coulter, R.; Teh, Z.; Reavley, N.; Pirkis, J.; Lamblin, M.; Rice, S.; Skehan, J. The #chatsafe project Developing guidelines to help young people communicate safely about suicide on social media: A Delphi study. PLoS ONE 2018, 13, e0206584. [Google Scholar] [CrossRef] [Green Version]
- Australian Institute of Health and Welfare. Ambulance Attendances: Suicidal and Self-Harm Behaviours; AIHW: Canberra, Australia, 2021.
- Altman, D.G.; Royston, P. The cost of dichotomising continuous variables. BMJ 2006, 332, 1080. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Characteristic | Response | n (%) |
---|---|---|
Age, M (SD) | 21.1 (3.0) | |
Gender | Male | 20.8 (77) |
Female | 70.4 (261) | |
Transgender | 0.3 (1) | |
Non-binary | 4.1 (15) | |
Other | 1.1 (4) | |
Unsure | 1.9 (7) | |
Prefer not to say | 0.5 (2) | |
Indigenous status | Aboriginal | 2.2 (8) |
Torres Strait Islander | 0 (0) | |
Both | 0 (0) | |
Prefer not to say | 0.8 (3) | |
Neither | 97.0 (356) | |
State | Victoria | 68.0 (249) |
New South Wales | 11.5 (42) | |
Tasmania | 6.0 (22) | |
Queensland | 5.7 (21) | |
Western Australia | 3.0 (11) | |
South Australia | 2.7 (10) | |
Australian Capital Territory | 2.7 (10) | |
Northern Territory | 0.3 (1) | |
Area of residence * | Major City | 59.5 (217) |
Inner regional | 21.4 (78) | |
Outer regional | 10.7 (39) | |
Remote | 3.8 (14) | |
Unsure | 4.7 (17) | |
Education and employment ** | Full-time student | 58.2 (216) |
Part-time student | 11.3 (42) | |
Full-time employed | 17.3 (64) | |
Part-time employed | 34.0 (126) | |
Unpaid worker as parent or carer | 1.6 (6) | |
Unemployed Seeking work Seeking study Seeking both | 13.7 (51) 43.1 (22) 3.9 (2) 27.5 (14) |
Gender | Age % (n) | ||||||||
---|---|---|---|---|---|---|---|---|---|
Characteristic | Male % (n) | Female % (n) | Gender- Diverse % (n) | Test Statistic | p Value | Younger % (n) | Older % (n) | Test Statistic | p Value |
Previous mental health diagnosis | 23.919 | 0.000 | 6.781 | 0.011 | |||||
Yes | 31.2 (24) | 55.3 (140) | 81.5 (22) | 44.6 (75) | 58.4 (111) | ||||
No | 68.8 (52) | 44.7 (113) | 18.5 (5) | 55.4 (93) | 41.6 (79) | ||||
Perceived impact of COVID-19 | NA * | 0.009 | 2.887 | 0.256 | |||||
Positive | 8.0 (6) | 5.5 (14) | 0 | 9 (5.2) | 11 (6.0) | ||||
Negative | 74.7 (56) | 87.8 (224) | 100.0 (27) | 146 (83.9) | 162 (88.0) | ||||
Neutral | 17.3 (13) | 6.7 (17) | 0 | 19 (10.9) | 11 (6.0) | ||||
Hours of daily social media use | NA * | 0.005 | 12.139 | 0.007 | |||||
0–2 | 42.5 (31) | 25.7 (65) | 14.3 (4) | 21.6 (37) | 34.8 (64) | ||||
3–4 | 43.8 (32) | 47.8 (121) | 39.3 (11) | 46.8 (80) | 45.7 (84) | ||||
5–7 | 9.6 (7) | 16.6 (42) | 21.4 (6) | 17.5 (30) | 13.6 (25) | ||||
7+ | 4.1 (3) | 9.9 (25) | 25.0 (7) | 14.0 (24) | 6.0 (11) | ||||
Used social media to support self | 31.716 | 0.000 | 5.593 | 0.019 | |||||
Yes | 22.1 (15) | 34.8 (87) | 82.1 (23) | 42.4 (70) | 30.2 (55) | ||||
No | 77.9 (53) | 65.2 (163) | 17.9 (5) | 57.6 (95) | 69.8 (127) | ||||
Used social media to support others | 6.939 | 0.031 | 3.231 | 0.083 | |||||
Yes | 41.8 (28) | 50.6 (124) | 71.4 (30) | 55.6 (90) | 45.8 (82) | ||||
No | 58.2 (39) | 49.4 (121) | 28.6 (8) | 44.4 (72) | 54.2 (97) |
DASS-21 Subscale | M (SD) | Normal | Mild | Moderate | Severe | Extremely Severe |
---|---|---|---|---|---|---|
Depression | 19.2 (12.1) | 23.2 (86) | 14.3 (53) | 20.8 (77) | 13.5 (50) | 28.3 (105) |
Anxiety | 13.5 (9.8) | 29.4 (109) | 15.9 (59) | 13.7 (51) | 14.0 (52) | 27.0 (100) |
Stress | 19.4 (10.1) | 37.2 (138) | 12.7 (47) | 19.7 (73) | 18.9 (70) | 11.6 (43) |
Variables | Depression | Anxiety | Stress | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
M | SD | F | df | p | η2 | M | SD | F | df | p | η2 | M | SD | F * | df | p | η2 | |
Gender | 9.315 | 2, 364 | 0.000 | 0.049 | 7.270 | 2, 364 | 0.001 | 0.038 | 12.252 | 2, 70 | 0.000 | 0.060 | ||||||
Male | 17.0 | 12.6 | 11.2 | 10.0 | 15.9 | 10.7 | ||||||||||||
Female | 19.0 | 11.7 | 13.5 | 9.4 | 19.7 | 9.7 | ||||||||||||
Gender-diverse | 27.9 | 10.7 | 19.2 | 10.3 | 26.1 | 8.8 | ||||||||||||
Age | 2.026 | 1, 369 | 0.155 | - | 5.489 | 1, 369 | 0.020 | 0.015 | 0.324 | 1, 369 | 0.569 | - | ||||||
Younger | 20.2 | 12.1 | 14.7 | 9.4 | 19.7 | 9.7 | ||||||||||||
Older | 18.4 | 12.1 | 12.4 | 10.0 | 19.1 | 10.7 | ||||||||||||
MH diagnosis | 33.028 | 1, 356 | 0.000 | 0.085 | 49.034 | 1, 356 | 0.000 | 0.121 | 54.326 | 1, 354 | 0.000 | 0.132 | ||||||
Yes | 22.5 | 12.0 | 16.6 | 9.8 | 22.9 | 9.6 | ||||||||||||
No | 15.5 | 11.1 | 9.8 | 8.6 | 15.5 | 9.5 | ||||||||||||
Daily SM use | 7.081 | 3, 351 | 0.000 | 0.057 | 6.069 | 3, 351 | 0.000 | 0.049 | 5.785 | 3, 115 | 0.001 | 0.043 | ||||||
0–2 h | 16.3 | 11.8 | 11.0 | 10.1 | 17.3 | 11.3 | ||||||||||||
3–4 h | 19.5 | 12.0 | 13.6 | 9.1 | 19.4 | 9.4 | ||||||||||||
5–7 h | 19.8 | 11.8 | 14.1 | 9.2 | 20.8 | 9.9 | ||||||||||||
>7 h | 26.9 | 11.3 | 18.9 | 10.2 | 24.8 | 8.6 |
Social Media Platform | Daily | Weekly | Occasionally | Never |
---|---|---|---|---|
70.8 (255) | 13.9 (50) | 8.3 (30) | 6.9 (25) | |
69.8 (251) | 13.3 (48) | 10.6 (38) | 6.4 (23) | |
Snapchat | 46.7 (168) | 12.7 (45) | 18.9 (68) | 21.7 (78) |
YouTube | 45.6 (164) | 33.6 (121) | 14.7 (53) | 6.1 (22) |
Tik Tok | 25.3 (91) | 16.7 (60) | 23.9 (86) | 34.2 (123) |
17.2 (62) | 12.2 (44) | 36.4 (131) | 34.2 (123) | |
13.6 (49) | 12.8 (46) | 43.6 (157) | 30.0 (108) | |
11.2 (40) | 11.2 (40) | 43.3 (156) | 34.4 (124) | |
Interactive online games | 8.6 (31) | 6.9 (25) | 27.2 (98) | 57.2 (206) |
4.4 (16) | 12.5 (45) | 46.1 (166) | 36.9 (133) | |
Tumblr | 4.2 (15) | 9.1 (33) | 40.3 (145) | 46.4 (167) |
3.9 (14) | 14.6 (52) | 46.4 (167) | 35.3 (127) | |
0.9 (3) | 0.6 (2) | 43.9 (158) | 54.7 (197) | |
Other | 3.3 (12) | 2.7 (10) | 23.1 (83) | 70. 8 (255) |
All platforms (N = 363) | 96.1 (349) | 1.9 (7) | 1.2 (4) | 0.8 (3) |
Variable | Supporting Self (N = 125) | Supporting Others (N = 172) | |
---|---|---|---|
Platform used | YouTube | 52.0 (65) | 8.1 (14) |
47.2 (59) | 39.5 (68) | ||
40.8 (51) | 61.0 (105) | ||
Tumblr | 24.0 (30) | 13.4 (23) | |
Snapchat | 22.4 (28) | 8.1 (14) | |
13.6 (17) | 8.7 (15) | ||
Tik Tok | 13.6 (17) | 4.1 (7) | |
16.8 (20) | 4.1 (7) | ||
9.6 (12) | 0.6 (1) | ||
0.8 (1) | 4.1 (7) | ||
0 | 0.6 (1) | ||
Confidence | Not at all confident | 13.6 (17) | 11.0 (19) |
Slightly confident | 19.2 (24) | 32.6 (56) | |
Somewhat confident | 26.4 (33) | 23.3 (40) | |
Fairly Confident | 24.0 (30) | 23.8 (41) | |
Completely confident | 9.6 (12) | 5.8 (10) | |
No response | 7.2 (9) | 4.7 (8) | |
Outcome | Felt much better | 12.8 (16) | 17.4 (30) |
Felt a bit better | 55.2 (69) | 33.1 (57) | |
Did not feel better or worse | 20.0 (25) | 20.9 (36) | |
Felt a bit worse | 4.0 (5) | 16.3 (28) | |
Felt much worse | 0.8 (1) | 6.4 (11) | |
Felt suicidal | 0.8 (1) | 2.3 (4) | |
No response | 6.4 (8) | 4.7 (8) |
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Bailey, E.; Boland, A.; Bell, I.; Nicholas, J.; La Sala, L.; Robinson, J. The Mental Health and Social Media Use of Young Australians during the COVID-19 Pandemic. Int. J. Environ. Res. Public Health 2022, 19, 1077. https://doi.org/10.3390/ijerph19031077
Bailey E, Boland A, Bell I, Nicholas J, La Sala L, Robinson J. The Mental Health and Social Media Use of Young Australians during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health. 2022; 19(3):1077. https://doi.org/10.3390/ijerph19031077
Chicago/Turabian StyleBailey, Eleanor, Alexandra Boland, Imogen Bell, Jennifer Nicholas, Louise La Sala, and Jo Robinson. 2022. "The Mental Health and Social Media Use of Young Australians during the COVID-19 Pandemic" International Journal of Environmental Research and Public Health 19, no. 3: 1077. https://doi.org/10.3390/ijerph19031077
APA StyleBailey, E., Boland, A., Bell, I., Nicholas, J., La Sala, L., & Robinson, J. (2022). The Mental Health and Social Media Use of Young Australians during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health, 19(3), 1077. https://doi.org/10.3390/ijerph19031077