Bélanger et al. [2424 Belanger RE, Akre C, Berchtold A, Michaud PA. A U-shaped association between intensity of Internet use and adolescent health. Pediatrics. 2011;127(2):e330-e335. doi: 10.1542/peds.2010-1235 https://doi.org/10.1542/peds.2010-1235...
] |
Switzerland, 2002 |
CSS |
7211, 3905/3306 |
17.91±2.11 |
CU; 0, 0-<1, 1-≤2, >2 |
DTS. Cutoff: NR |
Age; academic track; socioeconomic status; chronic condition; PA |
Cao et al. [2525 Cao H, Qian Q, Weng T, Yuan C, Sun Y, Wang H, Tao F. Screen time, physical activity and mental health among urban adolescents in China. Prev Med. 2011;53(4-5):316-320. doi: 10.1016/j.ypmed.2011.09.002 https://doi.org/10.1016/j.ypmed.2011.09....
] |
China, 2010 |
CSS |
5003, 2606/2397 |
13.2±1.0 |
ST (TV/CU); <2, >2 |
DSRSC. Cutoff : 15 |
Gender, grade, family type, perceived socioeconomic status, BMI, fruit and vegetable intake, and fizzy drinks intake |
Cao et al. [2626 Cao R, Gao T, Hu Y, Qin Z, Ren H, Liang L, Li C, Mei S. Clustering of lifestyle factors and the relationship with depressive symptoms among adolescents in Northeastern China. J Affect Disord. 2020;274:704-710. doi: 10.1016/j.jad.2020.05.064 https://doi.org/10.1016/j.jad.2020.05.06...
] |
China, 2018 |
CSS |
4178, 1946/2232 |
14.25±1.77 |
ST (TV/VG/CU/MP); <2, >2 |
CES-D. Cutoff: 16 |
Gender, age, living in school dormitory accommodation, school type and perceived socioeconomic status |
Casiano[1616 Liu M, Wu L, Yao S. Dose–response association of screen time-based sedentary behaviour in children and adolescents and depression: a meta-analysis of observational studies. Br J Sports Med. 2016;50(20):1252-1258. doi: 10.1136/bjsports-2015-095084 https://doi.org/10.1136/bjsports-2015-09...
] |
Canada, 2000-2001 |
CSS |
9137, 4544/4593 |
12-19 |
TV, VG, CU; 0, <1/7, <1/3, 0.4-0.7, 0.8-1.4, 1.5-2, 2-3, ≥3 |
CIDI short form. Cutoff: 0.90 |
Household income; gender |
da Costa, et al. [2727 da Costa BGG, Chaput JP, Lopes MVV, Malheiros LEA, Silva KS. Movement behaviors and their association with depressive symptoms in Brazilian adolescents: A cross-sectional study. J Sport Health Sci. 2020. doi: 10.1016/j.jshs.2020.08.003 https://doi.org/10.1016/j.jshs.2020.08.0...
] |
Brazil, 2019 |
CSS |
610, 295/315 |
16.33±1.4 |
TV, VG, MP; <2, 2-4, ≥4 |
CES-D. Cutoff: 20 |
Sex, age, weight status, and socioeconomic status |
Godinho, et al. [2828 Godinho J, Araujo J, Barros H, Ramos E. Characteristics associated with media use in early adolescence. Cad Saude Publica. 2014;30(3):587-598. doi: https://doi.org/10.1590/0102-311X00100313 https://doi.org/10.1590/0102-311X0010031...
] |
Portugal, 2003-2004 |
CSS |
1680, 796/884 |
13 |
ST (≤2, 2-3, >3); TV (≤1, 1-2, >2); CU (≤2, >2) |
BDI-II. Cutoff: 13 |
Living with both parents, Parents’ age, Type of school, Repeated school year, Sleep duration, Ever smoke, Frequency of PA, BMI |
Grøntved et al. [2929 Grontved A, Singhammer J, Froberg K, Møller NS, Pan A, Pfeiffer KA, Kristensen PL. A prospective study of screen time in adolescence and depression symptoms in young adulthood. Prev Med. 2015;81:108-113. doi: 10.1016/j.ypmed.2015.08.009 https://doi.org/10.1016/j.ypmed.2015.08....
] |
Denmark, 2009-2010 |
PCS |
435, 203/232 |
15.6±0.4 |
ST, TV (0-1, 1-3, >3); CU (0-1, 1-3) |
MDI scale. Cutoff: 20 |
Age, BMI and CRF, follow-up time, sex, parental education level, parentalmarital status, smoking status, and alcohol intake in adolescence |
Hoare et al. [3030 Hoare E, Millar L, Fuller-Tyszkiewicz M, Skouteris H, Nichols M, Jacka F, Swinburn B, Chikwendu C, Allender S. Associations between obesogenic risk and depressive symptomatology in Australian adolescents: a cross-sectional study. J Epidemiol Community Health. 2014;68(8):767-772. doi: 10.1136/jech-2013-203562 https://doi.org/10.1136/jech-2013-203562...
] |
Australia, 2012 |
CSS |
800, 360/440 |
13.1±0.6 |
ST (TV/VG/CU); ≤2, >2 |
SMFQ. Cutoff: 10. |
Age, PA, weight status, fruit and vegetable, sweet drink, takeaway food consumption over a month period, parents’ level of education, and school |
Hoare, et al. [3131 Hoare E, Milton K, Foster C, Allender S. Depression, psychological distress and Internet use among community-based Australian adolescents: a cross-sectional study. BMC Public Health. 2017;17(1):365. doi: 10.1186/s12889-017-4272-1 https://doi.org/10.1186/s12889-017-4272-...
] |
Australia, 2013-2014 |
CSS |
2967, 1530/1437 |
14.6±2.0 |
IU; ≤2, 2-6, ≥7 |
DISC-IV. Cutoff: NR |
Age, relative level of socio-economic disadvantage and BMI |
Hong et al. [3232 Hong X, Li J, Xu F, Tse LA, Liang Y, Wang Z, Tak-sun Yu I, Griffiths S. Physical activity inversely associated with the presence of depression among urban adolescents in regional China. BMC Public Health. 2009;9:148. doi: 10.1186/1471-2458-9-148 https://doi.org/10.1186/1471-2458-9-148...
] |
China, 2004 |
CSS |
2444, 1180/1264 |
13.85±1.04 |
TV; Low, middle, high |
CDI. Cut-off: 20 |
Age; gender; school grade; BMI; study time; sleep time; smoking; alcohol; unintentional injuries; parents’ education, parents’ job; family structure |
Hrafnkelsdottir et al. [3333 Hrafnkelsdottir SM, Brychta RJ, Rognvaldsdottir V, Gestsdottir S, Chen KY, Johannsson E, Guðmundsdottir SL, Arngrimsson SA. Less screen time and more frequent vigorous physical activity is associated with lower risk of reporting negative mental health symptoms among Icelandic adolescents. PLoS One. 2018;13(4):e0196286. doi: 10.1371/journal.pone.0196286 https://doi.org/10.1371/journal.pone.019...
] |
Iceland, 2015 |
CSS |
244, 100/144 |
15.8±0.3 |
ST (CG,TV, IU, CU) <5.3, ≥5.3 |
SCL-90. Cut-off: 30 |
Sex, body fat percentage and maternal education |
Kim et al. [3434 Kim JY. The nonlinear association between Internet using time for non-educational purposes and adolescent health. J Prev Med Public Health. 2012;45(1):37-46. doi: 10.3961/jpmph.2012.45.1.37 https://doi.org/10.3961/jpmph.2012.45.1....
] |
Korea, 2009 |
CSS |
75066, 39612/35454 |
12-18 |
CU; 0, 0-<1, 1-≤2, >2 |
Self-reported |
Age, residing region, type of school, subjective academic performance status, subjective economic status, presence of parents, family lives together and sedentary behavior in weeks and weekend |
Kremer et al. [3535 Kremer P, Elshaug C, Leslie E, Toumbourou JW, Patton GC, Williams J. Physical activity, leisure-time screen use and depression among children and young adolescents. J Sci Med Sport. 2014;17(2):183-187. doi: 10.1016/j.jsams.2013.03.012 https://doi.org/10.1016/j.jsams.2013.03....
] |
Australia, 2006 |
CSS |
8029, 3852/4177 |
11.5±0.8 |
ST (TV/VG/CU): <2, ≥2 |
SMFQ. Cut-off: ≥8 |
Location and area- socioeconomic status |
Lee et al. [3636 Lee HH, Sung JH, Lee JY, Lee JE. Differences by Sex in Association of Mental Health With Video Gaming or Other Nonacademic Computer Use Among US Adolescents. Prev Chronic Dis. 2017;14:E117. doi: 10.5888/pcd14.170151 https://doi.org/10.5888/pcd14.170151...
] |
USA, 2015 |
CSS |
15624, 8015/7609 |
High school students |
VG; 0, <1, 1, 2, 3, 4, ≥5 |
Self-reported |
Crude |
Leung et al. [3737 Leung CY, Torres R. Sleep duration does not mediate the association between screen time and adolescent depression and anxiety: findings from the 2018 National Survey of Children's Health. Sleep Med. 2021;81:227-234. doi: 10.1016/j.sleep.2021.02.031 https://doi.org/10.1016/j.sleep.2021.02....
] |
USA, 2018 |
CSS |
10794, 5710/5084 |
13-17 |
TV; <1, 1, 2, 3, ≥4 |
Doctor or health professional |
Sex, age, poverty level, insurance type, parent education, language spoken at home, race/ethnicity, household generation, family structure, comorbid conditions, and emotional/behavior medications |
Lim et al. [3838 Lim CH, Kim EJ, Kim JH, Lee JS, Lee Y, Park HE. The correlation of depression with Internet use and body image in Korean adolescents. Korean J Pediatr. 2017;60(1):17-23. doi: 10.3345/kjp.2017.60.1.17 https://doi.org/10.3345/kjp.2017.60.1.17...
] |
Korea, 2008 |
CSS |
920, 633/287 |
15-17 |
IU; 0-1, 1-3, >3 |
CES-D. Cutoff: 24 |
Sex, age, PA, BMI, Perception on body image, Figure satisfaction |
Liu et al. [3939 Liu J, Liu CX, Wu T, Li B, Jia C, Liu X. Prolonged mobile phone use is associated with depressive symptoms in Chinese adolescents. J Affect Disord. 2019;259:128-134. doi: 10.1016/j.jad.2019.08.017 https://doi.org/10.1016/j.jad.2019.08.01...
] |
China, 2015 |
CSS |
11831, 5813/6018 |
15.0±1.5 |
MP; <1, 1-2, ≥2 (weekday)/<2, 2-<4, 4-<5, ≥5 (weekend) |
CES-D. Cut-off:>90th percentile |
Age, gender, chronic disease, smoking, alcohol use, school, family factors, weekday sleep duration, and insomnia |
Mridha et al. [1818 Mridha MK, Hossain MM, Ali Khan MS, Hanif AAM, Hasan M, Mitra D, Hossaine M, Ullah MA, Sarker SK, Rahman SM, Bulbul MI, Shamim AA. Prevalence and associated factors of depression among adolescent boys and girls in Bangladesh: findings from a nationwide survey. BMJ Open. 2021;11(1):e038954. doi:10.1136/bmjopen-2020-038954 https://doi.org/10.1136/bmjopen-2020-038...
] |
Bangladesh, 2018-2019 |
CSS |
9569, 4761/4808 |
10-19 |
TV; 0, 0-<1, 1-≤2, >2 |
PHQ-9. Cut-off: ≥5 |
Age, residence, educational status, maternal/paternal education and occupation, religion, household size, household member, tobacco use, Fruits and vegetables intake, Processed food intake, Consumption of fortified oil, Consumption of iodised salt, PA, Weight. |
Primack et al. [2222 Primack Brian A., Brandi Swanier, Anna M. Georgiopoulos, Land SR, Fine MJ. Association between media use in adolescence and depression in young adulthood: a longitudinal study. Arch Gen Psychiatry. 2009;66(2):181-188. doi: 10.1001/archgenpsychiatry.2008.532 https://doi.org/10.1001/archgenpsychiatr...
] |
USA, 1994-2002 |
PCS |
4142, 2145/1967 |
Grade 7-12 |
TV, CG; hours per day |
CES-D; Cut-off: 24 (F), 22 (M). |
Baseline CES-D score; age; gender; race/ethnicity; socioeconomic status; ever married; educational achievement of at least graduation from high school |
Twenge et al. [1717 Twenge JM, Farley E. Not all screen time is created equal: associations with mental health vary by activity and gender. Soc Psychiatry Psychiatr Epidemiol. 2021;56(2):207-217. doi: 10.1007/s00127-020-01906-9 https://doi.org/10.1007/s00127-020-01906...
] |
UK, 2015 |
CSS |
11427, 5720/5707 |
13.77±0.45 |
TV, CG, IU; <1, 1-<2, 2-<5, ≥5 |
SMFQ. Cut-off: 12. |
Age, family income, natural father present, ethnicity, the age the primary caregiver left formal education, primary caregiver’s employment, number of siblings in household, longstanding illness, and the primary caregiver’s vocabulary word score |
Wang et al. [2323 Jin W, Rong Y, Danlin L, Hong N, Wang C, Wan Y, Xu S, Tao F, Zhang S. Association of health literacy and screen time with depressive symptoms among middle school students. J Hygiene Res. 2019;48(5):765-771.] |
China, 2017 |
CSS |
1062, 576/486 |
15.38±1.74 |
ST (TV/VG/CU); ≤2, >2 |
SDS. Cutoff: 0.6 |
Grade, health status, family economic situation |
Xu et al. [4040 Xu H, Guo J, Wan Y, Zhang S, Yang R, Xu H, Ding P, Tao F. Association Between Screen Time, Fast Foods, Sugar-Sweetened Beverages and Depressive Symptoms in Chinese Adolescents. Front Psychiatry. 2020;11:458. doi: 10.3389/fpsyt.2020.00458 https://doi.org/10.3389/fpsyt.2020.00458...
] |
China, 2017-2018 |
CSS |
14500, 7347/7153 |
14.9±1.8 |
ST (TV/CU/MP); 0, <1, 1-2, 2-3, 3-4, 4-5, >5 |
CDI. Cut-off: 19. |
Age, Grade, Residence, The only child in the family, Boarding school, Father/mother's education level, Self-perceived socioeconomic status, The number of close friend |