Contributing Factors in Adolescents’ Mental Well-Being—The Role of Socioeconomic Status, Social Support, and Health Behavior
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Data Collection
2.2.1. Socioeconomic and Demographic Data
2.2.2. Social Support
2.2.3. Health Behavior
2.2.4. Mental Well-Being
2.3. Data Analysis
3. Results
3.1. Result of the Factor Analysis
3.2. Determinants of Mental Well-Being
4. Discussion
Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Before Imputation | After Imputation | ||||
---|---|---|---|---|---|
N (%) | Mean (±SD) | N (%) | Mean (±SD) | ||
Age (missing: 0.91%) | 15.28 (1.70) | 15.28 (1.70) | |||
Gender of students (missing: 0%) | Male | 997 (60.76%) | 997 (60.76%) | ||
Female | 644 (39.24%) | 644 (39.24%) | |||
Educational attainment of father (missing: 5.12%) | Not known | 181 (11.62%) | 189 (11.52%) | ||
Primary school or less | 60 (3.85%) | 75 (4.57%) | |||
Vocational school | 434 (27.87%) | 459 (27.97%) | |||
Secondary school/high school | 375 (24.08%) | 397 (24.19%) | |||
University/college | 507 (32.56%) | 521 (31.75%) | |||
Educational attainment of mother (missing: 5.79%) | Not known | 131 (8.47%) | 132 (8.04%) | ||
Primary school or less | 60 (3.88%) | 74 (4.51%) | |||
Vocational school | 214 (13.84%) | 244 (14.87%) | |||
Secondary school/high school | 515 (33.31%) | 544 (33.15%) | |||
University/college | 626 (40.49%) | 647 (39.43%) | |||
Family affluence (missing: 1.77%) | Low | 645 (43.58%) | 715 (43.57%) | ||
Medium | 656 (44.32%) | 725 (44.18%) | |||
High | 179 (12.09%) | 201 (12.25%) | |||
Subjective perception of family wealth (missing: 1.77%) | Not well-off | 63 (3.91%) | 63 (3.84%) | ||
Average | 918 (56.95%) | 933 (56.86%) | |||
Well-off | 631 (39.14%) | 645 (39.31%) | |||
Residence (missing: 0.24%) | Debrecen | 1012 (61.82%) | 1015 (61.85%) | ||
Other surrounding settlements | 625 (38.18%) | 626 (38.15%) | |||
Type of school (missing: 0.61%) | Primary school | 358 (21.95%) | 358 (21.82%) | ||
Vocational school | 62 (3.80%) | 66 (4.02%) | |||
Secondary school | 516 (31.64%) | 518 (31.57%) | |||
High school | 695 (42.61%) | 699 (42.60%) | |||
Life satisfaction (missing: 6.46%) | 7.42 (1.94) | 7.39 (1.92) | |||
Depression scale (missing: 13.16%) | 2.12 (2.44) | 2.11 (2.40) | |||
Psychosomatic symptoms (missing: 8.78%) | 21.17 (7.77) | 21.17 (7.57) |
Median (Interquartile Range) | Factors | Communalities | |||||||
---|---|---|---|---|---|---|---|---|---|
Unhealthy Food Consumption | Screen Time | Physical Activity | Social Support | Using the Computer Not for Playing | Breakfast Consumption and Family Meals | Healthy Food Consumption | |||
Frequency of salty snacks consumption | 3 (2) | 0.812 | 0.122 | −0.024 | 0.012 | 0.034 | 0.113 | 0.005 | 0.688 |
Frequency of sugar-containing soft drinks consumption | 3 (3) | 0.778 | 0.137 | −0.063 | 0.081 | 0.037 | −0.070 | −0.092 | 0.649 |
Frequency of fast-foods consumption | 2 (1) | 0.731 | 0.124 | 0.092 | −0.008 | 0.081 | 0.007 | 0.016 | 0.565 |
Frequency of sweets consumption | 4 (2) | 0.685 | −0.024 | −0.065 | −0.013 | −0.040 | 0.154 | 0.129 | 0.516 |
Frequency of energy drinks consumption | 1 (1) | 0.558 | 0.144 | 0.058 | −0.080 | 0.190 | −0.206 | −0.048 | 0.422 |
Playing on the computer on weekdays | 3 (3) | 0.167 | 0.816 | 0.025 | −0.033 | −0.020 | 0.051 | −0.061 | 0.703 |
Playing on the computer on weekends | 4 (4) | 0.113 | 0.811 | −0.005 | −0.025 | −0.042 | 0.080 | −0.129 | 0.696 |
Watching TV and videos on weekdays | 3 (2) | 0.129 | 0.676 | −0.088 | −0.016 | 0.290 | −0.107 | 0.074 | 0.583 |
Watching TV and videos on weekends | 5 (3) | 0.081 | 0.628 | −0.118 | −0.046 | 0.319 | −0.183 | 0.044 | 0.555 |
Frequency of vigorous physical activity | 6 (2) | 0.023 | −0.056 | 0.861 | 0.070 | −0.031 | 0.025 | 0.116 | 0.765 |
Weekly hours of vigorous physical activity | 4 (3) | −0.050 | −0.059 | 0.839 | 0.069 | −0.024 | 0.005 | 0.040 | 0.718 |
Moderate-to-vigorous physical activity | 5 (3) | 0.023 | −0.009 | 0.791 | −0.004 | 0.028 | 0.139 | 0.107 | 0.657 |
Perceived social support from family | 26 (5) | −0.003 | 0.006 | 0.010 | 0.834 | −0.049 | 0.222 | 0.034 | 0.748 |
Quality of family communication | 17 (3) | −0.050 | 0.040 | 0.051 | 0.806 | −0.080 | 0.200 | 0.069 | 0.708 |
Perceived social support from friends (peer support) | 26 (5) | 0.050 | −0.149 | 0.081 | 0.665 | 0.139 | −0.153 | 0.079 | 0.522 |
Using the computer not for playing on weekdays | 4 (3) | 0.133 | 0.159 | −0.012 | −0.001 | 0.881 | −0.064 | −0.019 | 0.824 |
Using the computer not for playing on weekends | 5 (4) | 0.069 | 0.122 | 0.000 | 0.016 | 0.894 | −0.056 | −0.013 | 0.823 |
Breakfast with the parents | 3 (2) | 0.088 | −0.035 | 0.039 | 0.200 | −0.030 | 0.794 | 0.114 | 0.695 |
Breakfast consumption on weekdays | 5 (5) | −0.036 | −0.024 | 0.117 | −0.120 | −0.085 | 0.685 | −0.025 | 0.508 |
Evening meal with the parents | 4 (3) | 0.020 | −0.013 | 0.009 | 0.326 | −0.026 | 0.658 | 0.218 | 0.588 |
Frequency of vegetables consumption | 4 (2) | −0.038 | −0.020 | 0.098 | 0.087 | 0.003 | 0.092 | 0.887 | 0.814 |
Frequency of fruit consumption | 4 (2) | 0.060 | −0.068 | 0.173 | 0.093 | −0.027 | 0.129 | 0.858 | 0.799 |
Eigenvalue | 3.765 | 3.048 | 1.967 | 1.808 | 1.548 | 1.330 | 1.080 | ||
Explained variance (%) | 17.114 | 13.856 | 8.941 | 8.218 | 7.036 | 6.046 | 4.909 | ||
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Kaiser–Meyer–Olkin Measure of Sampling Adequacy (KMO): 0.716; Bartlett’s Test of Sphericity: p < 0.001; total variance explained: 66.12%. |
References
- World Health Organization. Adolescent Mental Health: Mapping Actions of Nongovernmental Organizations and Other International Development Organizations. Available online: https://apps.who.int/iris/bitstream/handle/10665/44875/9789241503648_eng.pdf;jsessionid=2E6F176D74F28C01798AA5F8F7468A01?sequence=1 (accessed on 8 September 2020).
- Belfer, M.L. Child and Adolescent Mental Disorders: The Magnitude of the Problem across the Globe. J. Child Psychol. Psychiatry 2008, 49, 226–236. [Google Scholar] [CrossRef]
- Patel, V.; Flisher, A.J.; Hetrick, S.; McGorry, P. Mental Health of Young People: A Global Public-Health Challenge. Lancet 2007, 369, 1302–1313. [Google Scholar] [CrossRef]
- World Health Organization. Investing in Children: The European Child and Adolescent Health Strategy 2015–2020 Regional Committee for Europe 64th Session; WHO Regional Office for Europe: Copenhagen, Denmark, 2014; Available online: https://www.euro.who.int/__data/assets/pdf_file/0010/253729/64wd12e_InvestCAHstrategy_140440.pdf?ua= (accessed on 8 September 2020).
- Whiteford, H.A.; Degenhardt, L.; Rehm, J.; Baxter, A.J.; Ferrari, A.J.; Erskine, H.E.; Charlson, F.J.; Norman, R.E.; Flaxman, A.D.; Johns, N.; et al. Global Burden of Disease Attributable to Mental and Substance Use Disorders: Findings from the Global Burden of Disease Study 2010. Lancet 2013, 382, 1575–1586. [Google Scholar] [CrossRef]
- HBSC International Coordinating Centre Child & Adolescent Health Research Unit. Health Behaviour in School-Aged Children (HBSC) 2014: Terms of Reference. Available online: http://www.hbsc.org/about/HBSCToR.pdf (accessed on 8 September 2020).
- Inchley, J.; Currie, D.; Young, T.; Samdal, O.; Torsheim, T.; Augustson, L.; Mathison, F.; Aleman-Diaz, A.; Molcho, M.; Weber, M.B. (Eds.) Growing up Unequal: Gender and Socioeconomic Differences in Young People’s Health and Well-Being. Health Behaviour in School-Aged Children (HBSC) Study: International Report from the 2013/2014 Survey; World Health Organization Regional Office for Europe: Copenhagen, Denmark, 2016. [Google Scholar]
- Németh, Á.; Költő, A. Health Behaviour in School-Aged Children (HBSC): A WHO-Collaborative Cross-National Study. National Report 2014; National Institute for Health Promotion: Budapest, Hungary, 2016.
- Patton, G.C.; Sawyer, S.M.; Santelli, J.S.; Ross, D.A.; Afifi, R.; Allen, N.B.; Arora, M.; Azzopardi, P.; Baldwin, W.; Bonell, C.; et al. Our Future: A Lancet Commission on Adolescent Health and Wellbeing. Lancet 2016, 387, 2423–2478. [Google Scholar] [CrossRef]
- World Health Organization. Mental Health: New Understanding, New Hope; The World Health Report; 2001. Available online: https://www.who.int/whr/2001/en/whr01_en.pdf?ua=1 (accessed on 8 September 2020).
- Klanšček, H.J.; Žiberna, J.; Korošec, A.; Zurc, J.; Albreht, T. Mental Health Inequalities in Slovenian 15-Year-Old Adolescents Explained by Personal Social Position and Family Socioeconomic Status. Int. J. Equity Health 2014, 13, 26. [Google Scholar] [CrossRef]
- Quon, E.C.; McGrath, J.J. Subjective Socioeconomic Status and Adolescent Health: A Meta-Analysis. Health Psychol. Off. J. Div. Health Psychol. Am. Psychol. Assoc. 2014. [Google Scholar] [CrossRef]
- Sweeting, H.; Hunt, K. Adolescent Socio-Economic and School-Based Social Status, Health and Well-Being. Soc. Sci. Med. 2014, 121, 39–47. [Google Scholar] [CrossRef]
- Viner, R.M.; Ozer, E.M.; Denny, S.; Marmot, M.; Resnick, M.; Fatusi, A.; Currie, C. Adolescence and the Social Determinants of Health. Lancet 2012, 379, 1641–1652. [Google Scholar] [CrossRef]
- Currie, C.; Zanotti, C.; Morgan, A.; Currie, D.; de Looze, M.H.; Roberts, C.; Samdal, O.; Otto, R.F.; Smith, V.B. Social Determinants of Health and Well-Being among Young People. In Health Behaviour in School-Aged Children (HBSC) Study: International Report from the 2009/2010 Survey; World Health Organization Regional Office for Europe: Copenhagen, Denmark, 2012. [Google Scholar]
- World Health Organization. Social Cohesion for Mental Well-Being among Adolescents. 2007. Available online: http://www.euro.who.int/__data/assets/pdf_file/0005/84623/E91921.pdf (accessed on 8 September 2020).
- World Health Organization. Risks to Mental Health: An Overview of Vulnerabilities and Risk Factors. 2012. Available online: http://www.who.int/mental_health/mhgap/risks_to_mental_health_EN_27_08_12.pdf (accessed on 8 September 2020).
- Brookie, K.L.; Best, G.I.; Conner, T.S. Intake of Raw Fruits and Vegetables Is Associated With Better Mental Health Than Intake of Processed Fruits and Vegetables. Front Psychol 2018, 9, 487. [Google Scholar] [CrossRef]
- Iannotti, R.J.; Janssen, I.; Haug, E.; Kololo, H.; Annaheim, B.; Borraccino, A.; the HBSC Physical Activity Focus Group. Interrelationships of Adolescent Physical Activity, Screen-Based Sedentary Behaviour, and Social and Psychological Health. Int. J. Public Health 2009, 54, 191–198. [Google Scholar] [CrossRef]
- Vancampfort, D.; Stubbs, B.; Firth, J.; Van Damme, T.; Koyanagi, A. Sedentary Behavior and Depressive Symptoms among 67,077 Adolescents Aged 12–15 Years from 30 Low- and Middle-Income Countries. Int. J. Behav. Nutr. Phys. Act. 2018, 15, 73. [Google Scholar] [CrossRef]
- Bíró, É.; Dezső, D.; Sándor, J.; Ádány, R. Inequalities in Hungarian Adolescents’ Health, Health Behaviour and Well-Being, Based upon the Results of a Cross-Sectional Survey at Settlement Level, Using the Health Behaviour in School-Aged Children Questionnaire. Child. Youth Serv. Rev. 2018, 90, 15–20. [Google Scholar] [CrossRef]
- Currie, C.; Inchley, J.; Molcho, M.; Lenzi, M.; Veselska, Z.; Wild, F. Health Behaviour in School-Aged Children (HBSC) Study Protocol: Background, Methodology and Mandatory Items for the 2013/14 Survey; CAHRU: Andrews, UK, 2014. [Google Scholar]
- Kovacs, M. The Children’s Depression, Inventory (CDI). Psychopharmacol. Bull. 1985, 21, 995–998. [Google Scholar]
- StataCorp. Stata Statistical Software: Release 12; StataCorp LP: College Station, TX, USA, 2011. [Google Scholar]
- Cavallo, F.; Zambon, A.; Borraccino, A.; Raven-Sieberer, U.; Torsheim, T.; Lemma, P.; the HBSC Positive Health Group. Girls Growing through Adolescence Have a Higher Risk of Poor Health. Qual. Life Res. 2006, 15, 1577–1585. [Google Scholar] [CrossRef]
- Silva, S.A.; Silva, S.U.; Ronca, D.B.; Gonçalves, V.S.S.; Dutra, E.S.; Carvalho, K.M.B. Common Mental Disorders Prevalence in Adolescents: A Systematic Review and Meta-Analyses. PLoS ONE 2020, 15, e0232007. [Google Scholar] [CrossRef]
- Landstedt, E.; Asplund, K.; Gillander Gådin, K. Understanding Adolescent Mental Health: The Influence of Social Processes, Doing Gender and Gendered Power Relations. Sociol. Health Illn. 2009, 31, 962–978. [Google Scholar] [CrossRef]
- Grant, N.; Wardle, J.; Steptoe, A. The Relationship Between Life Satisfaction and Health Behavior: A Cross-Cultural Analysis of Young Adults. Int. J. Behav. Med. 2009, 16, 259–268. [Google Scholar] [CrossRef]
- Hong, S.A.; Peltzer, K. Dietary Behaviour, Psychological Well-Being and Mental Distress among Adolescents in Korea. Child Adolesc. Psychiatry Ment. Health 2017, 11, 56. [Google Scholar] [CrossRef]
- Bell, S.L.; Audrey, S.; Gunnell, D.; Cooper, A.; Campbell, R. The Relationship between Physical Activity, Mental Wellbeing and Symptoms of Mental Health Disorder in Adolescents: A Cohort Study. Int. J. Behav. Nutr. Phys. Act. 2019, 16, 138. [Google Scholar] [CrossRef]
- Ho, F.K.W.; Louie, L.H.T.; Chow, C.B.; Wong, W.H.S.; Ip, P. Physical Activity Improves Mental Health through Resilience in Hong Kong Chinese Adolescents. BMC Pediatr. 2015, 15, 48. [Google Scholar] [CrossRef]
- Brindova, D.; Veselska, Z.D.; Klein, D.; Hamrik, Z.; Sigmundova, D.; van Dijk, J.P.; Reijneveld, S.A.; Geckova, A.M. Is the Association between Screen-Based Behaviour and Health Complaints among Adolescents Moderated by Physical Activity? Int. J. Public Health 2015, 60, 139–145. [Google Scholar] [CrossRef]
- Hoare, E.; Milton, K.; Foster, C.; Allender, S. The Associations between Sedentary Behaviour and Mental Health among Adolescents: A Systematic Review. Int. J. Behav. Nutr. Phys. Act. 2016, 13, 108. [Google Scholar] [CrossRef]
- Roche, K.M.; Bingenheimer, J.B.; Ghazarian, S.R. The Dynamic Interdependence between Family Support and Depressive Symptoms among Adolescents in Ghana. Int. J. Public Health 2016, 61, 487–494. [Google Scholar] [CrossRef]
- Dray, J.; Bowman, J.; Campbell, E.; Freund, M.; Hodder, R.; Wolfenden, L.; Richards, J.; Leane, C.; Green, S.; Lecathelinais, C.; et al. Effectiveness of a Pragmatic School-Based Universal Intervention Targeting Student Resilience Protective Factors in Reducing Mental Health Problems in Adolescents. J. Adolesc. 2017, 57, 74–89. [Google Scholar] [CrossRef]
- Jenkins, E.K.; Bungay, V.; Patterson, A.; Saewyc, E.M.; Johnson, J.L. Assessing the Impacts and Outcomes of Youth Driven Mental Health Promotion: A Mixed-Methods Assessment of the Social Networking Action for Resilience Study. J. Adolesc. 2018, 67, 1–11. [Google Scholar] [CrossRef]
- Husky, M.M.; Kaplan, A.; McGuire, L.; Flynn, L.; Chrostowski, C.; Olfson, M. Identifying Adolescents at Risk through Voluntary School-Based Mental Health Screening. J. Adolesc. 2011, 34, 505–511. [Google Scholar] [CrossRef]
N (%) | Mean (±SD) | ||
---|---|---|---|
Age | 15.28 (1.70) | ||
Gender of students | Male | 997 (60.76%) | |
Female | 644 (39.24%) | ||
Educational attainment of father | Not known | 181 (11.62%) | |
Primary school or less | 60 (3.85%) | ||
Vocational school | 434 (27.87%) | ||
Secondary school/high school | 375 (24.08%) | ||
University/college | 507 (32.56%) | ||
Educational attainment of mother | Not known | 131 (8.47%) | |
Primary school or less | 60 (3.88%) | ||
Vocational school | 214 (13.84%) | ||
Secondary school/high school | 515 (33.31%) | ||
University/college | 626 (40.49%) | ||
Family affluence | Low | 645 (43.58%) | |
Medium | 656 (44.32%) | ||
High | 179 (12.09%) | ||
Subjective perception of family wealth | Not well-off | 63 (3.91%) | |
Average | 918 (56.95%) | ||
Well-off | 631 (39.14%) | ||
Residence | Debrecen | 1012 (61.82%) | |
Other surrounding settlements | 625 (38.18%) | ||
Type of school | Primary school | 358 (21.95%) | |
Vocational school | 62 (3.80%) | ||
Secondary school | 516 (31.64%) | ||
High school | 695 (42.61%) | ||
Life satisfaction | 7.42 (1.94) | ||
Depression scale | 2.12 (2.44) | ||
Psychosomatic symptoms | 21.17 (7.77) |
Life Satisfaction β (95% CI) | Depression β (95% CI) | Psychosomatic Symptoms β (95% CI) | ||
---|---|---|---|---|
Gender of students | Male (ref: female) | 0.42 (0.21; 0.62) * | −0.90 (−1.14; −0.67) * | −3.05 (−3.88; −2.21) * |
Educational attainment of father | Not known (ref: university/college) | 0.34 (−0.02; 0.70) | 0.31 (−0.11; 0.73) | 1.83 (0.33; 3.32) * |
Primary school (ref: university/college) | −0.39 (−0.85; 0.07) | 0.23 (−0.30; 0.77) | 0.79 (−1.13; 2.70) | |
Vocational school (ref: university/college) | −0.18 (−0.42; 0.07) | −0.02 (−0.30; 0.27) | 1.04 (0.03; 2.05) * | |
Secondary school/high school (ref: university/college) | −0.03 (−0.27; 0.22) | −0.06 (−0.34; 0.23) | −0.26 (−1.27; 0.75) | |
Educational attainment of mother | Not known (ref: university/college) | −0.72 (−1.12; −0.32) * | −0.37 (−0.84; 0.10) | −1.53 (−3.20; 0.14) |
Primary school (ref: university/college) | 0.26 (−0.20; 0.72) | −0.22 (−0.75; 0.31) | −2.15 (−4.05; −0.25) * | |
Vocational school (ref: university/college) | −0.05 (−0.33; 0.22) | 0.05 (−0.27; 0.37) | −1.20 (−2.35; −0.06) * | |
Secondary school/high school (ref: university/college) | 0.07 (−0.14; 0.28) | −0.18 (−0.43; 0.06) | −0.09 (−0.96; 0.79) | |
Subjective perception of family wealth | Not well-off (ref: well-off) | −1.25 (−1.70; −0.80) * | 0.80 (0.27; 1.32) * | 1.54 (−0.33; 3.41) |
Average (ref: well-off) | −0.48 (−0.66; −0.29) * | −0.04 (−0.25; 0.17) | 0.09 (−0.66; 0.84) | |
Family affluence | Low (ref: high) | −0.22 (−0.51; 0.08) | −0.02 (−0.37; 0.32) | −0.20 (−1.43; 1.03) |
Medium (ref: high) | −0.10 (−0.37; 0.17) | 0.05 (−0.26; 0.37) | −0.19 (−1.31; 0.94) | |
Type of school | Primary school (ref: high school) | 0.29 (−0.02; 0.60) | 0.02 (−0.34; 0.38) | −1.49 (−2.77; −0.21) * |
Vocational school (ref: high school) | −0.34 (−0.79; 0.12) | −0.06 (−0.59; 0.46) | −0.24 (−2.11; 1.64) | |
Secondary school (ref: high school) | −0.18 (−0.39; 0.03) | −0.02 (−0.27; 0.22) | −0.37 (−1.25; 0.51) | |
Residence | Debrecen (ref: other surrounding settlements) | −0.18 (−0.36; 0.00) | 0.03 (−0.18; 0.25) | 0.64 (−0.11; 1.39) |
Factors | Social support | 0.42 (0.34; 0.50) * | −0.75 (−0.84; −0.65) * | −1.13 (−1.47; −0.79) * |
Breakfast consumption and family meals | 0.19 (0.11; 0.28) * | −0.46 (−0.56; −0.36) * | −1.52 (−1.88; −1.17) * | |
Healthy food consumption | 0.20 (0.11; 0.28) * | −0.08 (−0.18; 0.01) | 0.16 (−0.18; 0.50) | |
Unhealthy food consumption | 0.04 (−0.05; 0.12) | 0.15 (0.05; 0.24) * | 0.84 (0.50; 1.19) * | |
Physical activity | 0.19 (0.10; 0.27) * | −0.20 (−0.30; −0.10) * | −0.18 (−0.53; 0.17) | |
Entertainment screen time | −0.15 (−0.24; −0.06) * | 0.17 (0.07; 0.27) * | 0.10 (−0.26; 0.46) | |
Using the computer not for playing | 0.02 (−0.07; 0.10) | 0.19 (0.10; 0.29) * | 0.86 (0.51; 1.21) * | |
Age | 0.03 (−0.04; 0.11) | −0.01 (−0.09; 0.08) | 0.07 (−0.24; 0.39) |
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Nagy-Pénzes, G.; Vincze, F.; Bíró, É. Contributing Factors in Adolescents’ Mental Well-Being—The Role of Socioeconomic Status, Social Support, and Health Behavior. Sustainability 2020, 12, 9597. https://doi.org/10.3390/su12229597
Nagy-Pénzes G, Vincze F, Bíró É. Contributing Factors in Adolescents’ Mental Well-Being—The Role of Socioeconomic Status, Social Support, and Health Behavior. Sustainability. 2020; 12(22):9597. https://doi.org/10.3390/su12229597
Chicago/Turabian StyleNagy-Pénzes, Gabriella, Ferenc Vincze, and Éva Bíró. 2020. "Contributing Factors in Adolescents’ Mental Well-Being—The Role of Socioeconomic Status, Social Support, and Health Behavior" Sustainability 12, no. 22: 9597. https://doi.org/10.3390/su12229597
APA StyleNagy-Pénzes, G., Vincze, F., & Bíró, É. (2020). Contributing Factors in Adolescents’ Mental Well-Being—The Role of Socioeconomic Status, Social Support, and Health Behavior. Sustainability, 12(22), 9597. https://doi.org/10.3390/su12229597