Organization of Psychosocial Processes in Metropolitan and Non-Metropolitan Regions

Article Sidebar

View PDF

Information Fusion

Article Type: Research Article
Issue: Vol. 1 No. 1 (2025)
Published: 30 October 2025
Pages: 37-49

How to Cite

Assari, S., & Pallera, J. A. (2025). Organization of Psychosocial Processes in Metropolitan and Non-Metropolitan Regions. Urban-Regional Ecology, 1(1), 37-49. https://doi.org/10.65773/ure.1.1.68

Main Article Content

Authors

Shervin Assari 1 * , 
John Ashley Pallera 2
1 Department of Psychiatry, Charles R. Drew University of Medicine and Science, Los Angeles, CA, USA
2 College of Medicine, Charles R. Drew University of Medicine and Science, Los Angeles, CA, USA

Abstract

Background: Adolescents’ social, emotional, and behavioral characteristics do not operate in isolation but form interconnected systems that shape well-being. These processes may differ across geographic settings, particularly between metropolitan (MSA) and non-metropolitan (non-MSA) environments, which vary in social norms, community resources, and daily experiences. However, little research has examined how these psychosocial factors are organized as part of a broader system in different environments. Objectives: This study compared the structure of psychosocial networks among adolescents living in MSA and non-MSA settings. We aimed to identify whether social, emotional, and behavioral constructs cluster differently across environments and whether specific constructs show stronger influence or bridging roles within each network. Methods: Data were drawn from the 2023 Monitoring the Future survey of U.S. adolescents. Twelve psychosocial and behavioral constructs were examined, including emotional distress, self-esteem, positive well-being, social connectedness, sensation seeking, boredom, problem behaviors, and perceived parental and peer disapproval of substance use, and substance use. Separate correlation-based networks were generated for MSA and non-MSA youth. System-level measures (average degree, betweenness, eigenvector centrality) were used to assess overall structure, and node-level metrics identified constructs serving as central or bridging elements within each network. Results: Emotional distress, sensation seeking, and problem behaviors played stronger bridging roles in non-MSA than MSA environments. In contrast, MSA networks were more evenly distributed, with positive well-being, social connectedness, and parental or peer disapproval showing stronger central influence. Conclusions: Different organization of psychosocial processes across environments can inform context-sensitive strategies to support adolescent well-being.

Keywords:
adolescence, psychosocial factors, emotional well-being, social connectedness

Article Details

References

[1]Aoki, C., Romeo, R. D., & Smith, S. S. (2017). Adolescence as a critical period for developmental plasticity. Brain Research, 1654(Pt B), 85–86. https://doi.org/10.1016/j.brainres.2016.11.026

[2]Bernheim, A., Halfon, O., & Boutrel, B. (2013). Controversies about the enhanced vulnerability of the adolescent brain to develop addiction. Frontiers in Pharmacology, 4, 118. https://doi.org/10.3389/fphar.2013.00118

[3]Chen, G., Zhou, Z., Shek, D. T. L., & Zhu, X. (2025). The network structure of positive youth development attributes among Chinese rural adolescents. Applied Research in Quality of Life. https://doi.org/10.1007/s11482-025-10465-7

[4]Demetriou, A., Kazi, S., Makris, N., & Spanoudis, G. (2020). Cognitive ability, cognitive self-awareness, and school performance: From childhood to adolescence. Intelligence, 79, 101432. https://doi.org/10.1016/j.intell.2020.101432

[5]Fergus, S., & Zimmerman, M. A. (2005). Adolescent resilience: A framework for understanding healthy development in the face of risk. Annual Review of Public Health, 26, 399–419. https://doi.org/10.1146/annurev.publhealth.26.021304.144357

[6]Fuhrmann, D., Knoll, L. J., & Blakemore, S.-J. (2015). Adolescence as a sensitive period of brain development. Trends in Cognitive Sciences, 19(10), 558–566. https://doi.org/10.1016/j.tics.2015.07.008

[7]Williams, W. M., & Ceci, S. J. (1997). A person–process–context–time approach to understanding intellectual development. Review of General Psychology, 1(3), 288–310. https://doi.org/10.1037/1089-2680.1.3.288

[8]Willen, S. S., Knipper, M., Abadía-Barrero, C. E., & Davidovitch, N. (2017). Syndemic vulnerability and the right to health. The Lancet, 389(10072), 964–977. https://doi.org/10.1016/S0140-6736(17)30261-1

[9]Adinkrah, E., Najand, B., Young-Brinn, A., & Salimi, S. (2023). Association between school achievement and tobacco susceptibility among US adolescents: Ethnic differences. Children, 10(2), 327. https://doi.org/10.3390/children10020327

[10]Krishnan, V. (2010). Early child development: A conceptual model. In Proceedings of the Early Childhood Council Annual Conference 2010: Valuing Care (pp. 1–17).

[11]Bronfenbrenner, U. (2019). The context of development and the development of context. In Developmental psychology (pp. 147–184). Routledge. https://doi.org/10.4324/9780367816247-6

[12]Black, M., Barnes, A., Strong, M., Brook, A., Ray, A., Holden, B., Foster, C., & Taylor-Robinson, D. (2021). Relationships between child development at school entry and adolescent health—A participatory systematic review. International Journal of Environmental Research and Public Health, 18(21), 11613. https://doi.org/10.3390/ijerph182111613

[13]Cole, D. A., Maxwell, S. E., Martin, J. M., Peeke, L. G., Seroczynski, A. D., Tram, J. M., Hoffman, K. B., Ruiz, M. D., Jacquez, F., & Maschman, T. (2001). The development of multiple domains of child and adolescent self-concept: A cohort sequential longitudinal design. Child Development, 72(6), 1723–1746. https://doi.org/10.1111/1467-8624.00375

[14]Masten, A. S., Coatsworth, J. D., Neemann, J., Gest, S. D., Tellegen, A., & Garmezy, N. (1995). The structure and coherence of competence from childhood through adolescence. Child Development, 66(6), 1635–1659. https://doi.org/10.1111/j.1467-8624.1995.tb00956.x

[15]Smetana, J. G., Campione-Barr, N., & Metzger, A. (2006). Adolescent development in interpersonal and societal contexts. Annual Review of Psychology, 57, 255–284. https://doi.org/10.1146/annurev.psych.57.102904.190124

[16]Bray, R. M. (1998). Drug use in metropolitan America. SAGE Publications. https://doi.org/10.4135/9781452204833

[17]Cooper, H., Friedman, S. R., Tempalski, B., Friedman, R., & Keem, M. (2005). Racial/ethnic disparities in injection drug use in large US metropolitan areas. Annals of Epidemiology, 15(5), 326–334. https://doi.org/10.1016/j.annepidem.2004.10.008

[18]Roberts, E. T., Friedman, S. R., Brady, J. E., Pouget, E. R., Tempalski, B., & Galea, S. (2010). Environmental conditions, political economy, and rates of injection drug use in large US metropolitan areas 1992–2002. Drug and Alcohol Dependence, 106(2–3), 142–153. https://doi.org/10.1016/j.drugalcdep.2009.08.007

[19]Assari, S. (2021). Parental education and children's sleep disturbance: Minorities' diminished returns. International Journal of Epidemiology Research, 8(1), 31–39. https://doi.org/10.34172/ijer.2021.06

[20]Assari, S., Mardani, A., Maleki, M., Boyce, S., & Bazargan, M. (2021). Black-White achievement gap: Role of race, school urbanity, and parental education. Pediatric Health, Medicine and Therapeutics, 12, 1–11. https://doi.org/10.2147/PHMT.S238877

[21]Boyce, S., Bazargan, M., Caldwell, C. H., Zimmerman, M. A., & Assari, S. (2020). Parental educational attainment and social environmental of urban public schools in the U.S.: Blacks' diminished returns. Children, 7(5), 44. https://doi.org/10.3390/children7050044

[22]Fishbein, D. H., Herman-Stahl, M., Eldreth, D., Paschall, M. J., Hyde, C., Hubal, R., Hubbard, S., Williams, J., & Ialongo, N. (2006). Mediators of the stress–substance-use relationship in urban male adolescents. Prevention Science, 7(2), 113–126. https://doi.org/10.1007/s11121-006-0027-4

[23]Friel, S., Akerman, M., Hancock, T., Kumaresan, J., Marmot, M., Melin, T., & Vlahov, D. (2011). Addressing the social and environmental determinants of urban health equity: Evidence for action and a research agenda. Journal of Urban Health, 88(5), 860–874. https://doi.org/10.1007/s11524-011-9606-1

[24]Gibbons, F. X., Reimer, R. A., Gerrard, M., Yeh, H.-C., Houlihan, A. E., Cutrona, C., Simons, R., & Brody, G. (2007). Rural-urban differences in substance use among African-American adolescents. The Journal of Rural Health, 23(Suppl. 1), 22–28. https://doi.org/10.1111/j.1748-0361.2007.00120.x

[25]Gordon, W. R., & Caltabiano, M. L. (1996). Urban-rural differences in adolescent self-esteem, leisure boredom, and sensation-seeking as predictors of leisure-time usage and satisfaction. Adolescence, 31(124), 883–901.

[26]Monnat, S. M., & Rigg, K. K. (2016). Examining rural/urban differences in prescription opioid misuse among US adolescents. The Journal of Rural Health, 32(2), 204–218. https://doi.org/10.1111/jrh.12141

[27]Warren, J. C., Smalley, K. B., & Barefoot, K. N. (2015). Perceived ease of access to alcohol, tobacco and other substances in rural and urban US students. Rural and Remote Health, 15(4), 3397. https://doi.org/10.22605/RRH3397

[28]Wight, R. G., Aneshensel, C. S., Miller-Martinez, D., Botticello, A. L., Cummings, J. R., Karlamangla, A. S., & Seeman, T. E. (2006). Urban neighborhood context, educational attainment, and cognitive function among older adults. American Journal of Epidemiology, 163(12), 1071–1078. https://doi.org/10.1093/aje/kwj176

[29]Huang, S., Hou, J., Sun, L., Dou, D., Liu, X., & Zhang, H. (2017). The effects of objective and subjective socioeconomic status on subjective well-being among rural-to-urban migrants in China: The moderating role of subjective social mobility. Frontiers in Psychology, 8, 819. https://doi.org/10.3389/fpsyg.2017.00819

[30]Noland, M., Rayens, M. K., Wiggins, A. T., Huntington-Moskos, L., Rayens, E. A., Howard, T., & Hahn, E. J. (2018). Current use of e-cigarettes and conventional cigarettes among US high school students in urban and rural locations: 2014 National Youth Tobacco Survey. American Journal of Health Promotion, 32(5), 1239–1247. https://doi.org/10.1177/0890117117719621

[31]Rhew, I. C., Hawkins, J. D., & Oesterle, S. (2011). Drug use and risk among youth in different rural contexts. Health & Place, 17(3), 775–783. https://doi.org/10.1016/j.healthplace.2011.02.003

[32]Roscigno, V. J., & Crowle, M. L. (2001). Rurality, institutional disadvantage, and achievement/attainment. Rural Sociology, 66(2), 268–292. https://doi.org/10.1111/j.1549-0831.2001.tb00067.x

[33]Wagner, F., Diaz, D. B., López, A. L., Collado, M. E., & Aldaz, E. (2002). Social cohesion, cultural identity, and drug use in Mexican rural communities. Substance Use & Misuse, 37(5–7), 715–747. https://doi.org/10.1081/JA-120004280

[34]Probst, J. C., Barker, J. C., Enders, A., & Gardiner, P. (2018). Current state of child health in rural America: How context shapes children's health. The Journal of Rural Health, 34(Suppl. 1), s3–s12. https://doi.org/10.1111/jrh.12222

[35]Hermida, M. J., Shalom, D. E., Segretin, M. S., Goldin, A. P., Abril, M. C., Lipina, S. J., & Sigman, M. (2019). Risks for child cognitive development in rural contexts. Frontiers in Psychology, 9, 2735. https://doi.org/10.3389/fpsyg.2018.02735

[36]Tutzauer, F. (2007). Entropy as a measure of centrality in networks characterized by path-transfer flow. Social Networks, 29(2), 249–265. https://doi.org/10.1016/j.socnet.2006.10.001

[37]Wasil, A. R., Venturo-Conerly, K. E., Shinde, S., Patel, V., & Jones, P. J. (2020). Applying network analysis to understand depression and substance use in Indian adolescents. Journal of Affective Disorders, 265, 278–286. https://doi.org/10.1016/j.jad.2020.01.025

[38]Zhang, J., & Luo, Y. (2017). Degree centrality, betweenness centrality, and closeness centrality in social network. In Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017) (pp. 300–303). Atlantis Press. https://doi.org/10.2991/msam-17.2017.68

[39]Zhang, Q., Li, M., & Deng, Y. (2018). Measure the structure similarity of nodes in complex networks based on relative entropy. Physica A: Statistical Mechanics and its Applications, 491, 749–763. https://doi.org/10.1016/j.physa.2017.09.042

[40]Johnston, L. D., O’Malley, P. M., & Bachman, J. G. (2001). Monitoring the Future national survey results on drug use, 1975–2000. Volume I: Secondary school students (NIH Publication No. 01-4924). National Institute on Drug Abuse.

[41]Johnston, L. D., Miech, R. A., Patrick, M. E., O’Malley, P. M., Schulenberg, J. E., & Bachman, J. G. (2023). Monitoring the Future national survey results on drug use, 1975–2022: Overview, key findings on adolescent drug use. Institute for Social Research, University of Michigan.

[42]Miech, R. A., Johnston, L. D., O’Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2011). Monitoring the Future national survey results on drug use, 1975–2010. Volume I: Secondary school students. Institute for Social Research, University of Michigan.

[43]Johnston, L. D., O’Malley, P. M., Miech, R. A., Bachman, J. G., & Schulenberg, J. E. (2017). Monitoring the Future national survey results on drug use, 1975–2016: Overview, key findings on adolescent drug use. Institute for Social Research, University of Michigan.

[44]Johnston, L. D., O’Malley, P. M., & Bachman, J. G. (2003). Monitoring the future: National results on adolescent drug use: Overview of key findings. FOCUS, 1(2), 213–234. https://doi.org/10.1176/foc.1.2.213

[45]Miech, R. A., Johnston, L. D., O’Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2014). Monitoring the Future national survey results on drug use, 1975–2013: Volume I, Secondary school students. Institute for Social Research, University of Michigan.

[46]Miech, R. A., Johnston, L. D., & Patrick, M. E. (2024). Monitoring the Future: A continuing study of American youth (8th- and 10th-grade surveys), 2023 (ICPSR 39171, Version 1). Inter-university Consortium for Political and Social Research. https://doi.org/10.3886/ICPSR39171.v1

[47]Miech, R. A., Johnston, L. D., O’Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2015). Monitoring the Future national survey results on drug use, 1975–2014: Volume I, Secondary school students. Institute for Social Research, University of Michigan.

[48]Miech, R. A., Johnston, L. D., O’Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2016). Monitoring the Future national survey results on drug use, 1975–2015: Volume I, Secondary school students. Institute for Social Research, University of Michigan.

[49]Witherspoon, D. P., White, R. M. B., Bámaca, M. Y., Browning, C. R., Leech, T. G. J., Leventhal, T., Matthews, S. A., Pinchak, N., Roy, A. L., Sugie, N., & Winkler, E. N. (2023). Place-based developmental research: Conceptual and methodological advances in studying youth development in context. Monographs of the Society for Research in Child Development, 88(3), 7–130. https://doi.org/10.1111/mono.12472

[50]Boardman, J. D., & Saint Onge, J. M. (2005). Neighborhoods and adolescent development. Children, Youth and Environments, 15(1), 138–164. https://doi.org/10.1353/cye.2005.0083

[51]Pettigrew, J., Miller-Day, M., Krieger, J., & Hecht, M. L. (2012). The rural context of illicit substance offers: A study of Appalachian rural adolescents. Journal of Adolescent Research, 27(4), 523–550. https://doi.org/10.1177/0743558411432639

[52]Warren, J. C., Smalley, K. B., & Barefoot, K. N. (2017). Recent alcohol, tobacco, and substance use variations between rural and urban middle and high school students. Journal of Child & Adolescent Substance Abuse, 26(1), 60–65. https://doi.org/10.1080/1067828X.2016.1210550

[53]Assari, S., Assari, G., & Zare, H. (2025). Weaker effects of parental education on oral nicotine use of high school students in rural areas: Marginalization-related diminished returns. Open Journal of Educational Research, 5(2), 6042. https://doi.org/10.31586/ojer.2025.6042

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.