Table 4.
Summary of the included studies.
| ID | Author and Year | Title | Country | Study design | Duration | Data collection | N | Sampling | Males | Age | Theory |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Arend et al. (37) | Increased screen use on days with increased perceived COVID-19-related confinements - a day level ecological momentary assessment study | Germany, Austria | L | 14 days | online | 102 | R | 18.6% | 25.5 | – |
| 2 | Ellis et al. (40) | Physically isolated but socially connected: psychological adjustment and stress among adolescents during the intial COVID-19 crisis | Canada | C | online | 1,054 | C | 21.9% | 16.68 | – | |
| 3 | Li et al. (41) | The impact of COVID-19 on the loves and mental health of Australian adolescents | Australia | C | online | 760 | C | 19% | 14.8 | – | |
| 4 | Liu et al. (42) | COVID-19 information overload and generation Z's social media discontinuance intention during the pandemic lockdown | United Kingdom | C | online | 322 | C | 38.80% | 18-25 | Stimulus-organism-response (S-O-R) model | |
| 5 | Zhao et al. (43) | COVID-19 stress and addictive social media use (SMU): mediating role of active use and social median flow | China | C | online | 512 | C | 37.5% | 22.12 | Addictive social media use, Theory of basic psychological needs | |
| 6 | Arslan et al. (44) | Coronavirus Anxiety and Psychological Asjustment in College Students: Exploring the Role of College Belongingness and Social media Addiction | Turkey | C | online | 315 | C | 23% | 21.65 | – | |
| 7 | Zhen et al. (45) | College students coping with COVID-19: stress-buffering effects of self-discolsure on social media and parental support | United States | C | online | 215 | C | 21% | 20.5 | Stressful life events, Social penetration theory | |
| 8 | Dong et al. (46) | Internet Addiction and Related Psychological Factors Among Children and Adolescents in China During the Coronavirus Disease 2019 (COVID-19) Epidemic | China | C | online | 2,050 | C | 52% | 12.34 | – | |
| 9 | Vall-Roqué et al. (47) | The impact of COVID-19 lockdown on social network sites use, body image disturbance and self-esteem among adolescent and young women | Spain | C | online | 1,620 | C | 0% | 14-24 | – | |
| 10 | Sheoran et al. (48) | Prevalence of psychological distress among adolescents in relation to internet addiction during COVID-19 times | India | C | online | 300 | C | 50% | 15.57 | – | |
| 11 | Hong et al. (49) | Social media exposure and college students' mental health during the outbreak of covid-19: the emdiating role of rumination and the moderating role of mindfulness | China | C | online | 439 | C | 58.10% | 20.37 | Health belief model, Integrated model of ruminative response style, Diathesis-stress model | |
| 12 | Magson et al. (38) | Risk and protective factors for prospective changes in adoelscent mental health during the COVID-19 pandemic | Australia | L | 12 months | online | 248 | C | 50% | 14.4 | – |
| 13 | Li et al. (50) | Mental health among college students during the COVID-19 pandemic in China: a 2-wave longitudinal survey | China | L | 2.5 months | online | T1: 164 101; T2: 68 658 | C | 37.40% | college year (freshman, sophomore, junior, senior, and graduate) | – |
| 14 | Chambonn -iere et al. (51) |
Effect of the covid-19 lockdown on physical activity and sedentary behvaiors in french children and adolescents: new results from the ONAPS national survey | France | C | online | 6,491 | C | 38.80% | 6-17 | – | |
| 15 | Islam et al. (52) | Problematic internet use among yound and adult population in Bangladesh: Correlates with lifestyle and online activities during the COVID-19 pandemic | Bangladesh | C | online | 13,525 | C | 61.30% | 23.7 | – | |
| 16 | Parker et al. (53) | The use of digital platforms for adult's and adolescents' physical activity during the COVID-19 pandemic (our life at home): survey study | Australia | C | online | 963 | R | 28.90% | 16.2 | – | |
| 17 | Dragun et al. (54) | Have lifestyle habits and psychilogical well-being changed among adolescents and medical students due to COVID-19 lockdown in Croatia? | Croatia | C | offline/online | T1: 1326; T2: 531 | C | 40% | 18 | – | |
| 18 | Fumagalli et al. (36) | Centennials, FOMO, and loneliness: an investigation of the impact of social networking and messaging/VoIP apps usage during the initial stage of the coronavirus pandemic | Italy, Argentina, United Kingdom | L | 1 month | online | 334 | C | 30.20% | 21.5 | Evolutionay theory of loneliness |
| 19 | Magis-Weinberg et al. (55) | Positive and Negative Online Experiences and Loneliness in Peruvian Adolescents During the COVID-19 Lockdown | Latin America | L | 3 months | online | 735 | C | 38.80% | 13.25 | – |
| 20 | Rens et al. (56) | Mental distress and its contributing factors among young people during the first wave of COVID-19: a belgian survey study | Belgium | C | online | 2,008 | R | 21.91% | 22.27 | – | |
| 21 | Xiao et al. (57) | Physical activity, screen time and mood disturbance among chinese adolescents during COVID-19 | China | C | online | 1,680 | C | 51.30% | 7-12 | – | |
| 22 | Nomura et al. (58) | Cross-sectional survey of depressive symptoms and suicide-related ideation at a japanese national unviersity during the COVID-19 stay-home order | Japan | C | online | 2,449 | C | 58% | 20 | – | |
| 23 | Hudimova et al. (59) | The impact of social media on young web user's psychological well-being during the COVID-19 pandemic progression | Ukraine | C | online | 254 | C | NA | 16-21 | – | |
| 24 | Cauberghe et al. (60) | How adolescents use social media to cope with feelings of loneliness and anxiety during COVID-19 lockdown | Belgio | C | online | 2,165 | C | 34.4% | 15.51 | Mood management theory | |
| 25 | Pigaiani et al. (61) | Adolescent lifestyle behaviors, coping strategies and subjective wellbeing during the COVID-19 pandemic: an online student survey | Italy | C | online | 306 | C | 72.90% | 18.1 | – | |
| 26 | Islam et al. (52) | Problematic Smartphone and Social Media Use Among Bangladeshi College and University Students Amid COVID-19: The Role of Psychological Well-Being and Pandemic Related Factors | Bangladesh | C | Online | 5,511 | C | 58.90% | 21.2 (1.7) | – | |
| 27 | Chen et al. (62) | Internet-Related Behaviors and Psychological Distress Among Schoolchildren During the COVID-19 School Hiatus | China | C | Online | 2,026 | C | 50.10% | 10.71 (1.07) | Interaction of Person- Affect-Cognition-Execution (I-PACE) model | |
| 28 | Fung et al. (63) | Problematic Use of Internet-Related Activities and Perceived Weight Stigma in Schoolchildren: A Longitudinal Study Across Different Epidemic Periods of COVID-19 in China | China | L | 6 months | Online | T1: 550; T2: 543; T3: 489 | C | 51% | 11.60 (.74) | Components model of addiction |
| 29 | Hayran et al. (64) | Well-Being and Fear of Missing Out (FOMO) on Digital Content in the Time of COVID-19: A Correlational Analysis among University Students | Europe | C | online | 178 | C | 62 | 21.35 (1.82) | – | |
| 30 | Siste et al. (65) | Implications of COVID-19 and Lockdown on Internet Addiction Among Adolescents: Data From a Developing Country | Indonesia | C | online | 2,932 | C | 21,3% | 17.38 (2.24) | – |
Study design (C, correlational; L, longitudinal): Duration If longitudinal duration in months (between first and last wave); N, analytical sample size; Sampling (Type of sampling procedure) (R, random; C, convenient; other, specify); Age (Mean, Standard deviation or Range, if Longitudinal, M and SD at T1 are reported).