Beyond Neurotransmitters: Integrating Biological, Structural, and Digital Determinants in Contemporary Psychiatry
DOI:
https://doi.org/10.64784/145Keywords:
Mental health disorders, neurobiology, social determinants, digital psychiatry, neuroinflammation, stress physiology, digital phenotyping, socioeconomic inequality, smartphone interventions, global mental healthAbstract
Mental health disorders represent a leading cause of disability worldwide and require integrative frameworks that transcend traditional single-domain explanations. This review analyzes the neurobiological, social, and digital dimensions of psychiatric disorders through a structured synthesis of international literature. Neurobiological evidence highlights circuit-level dysfunction, stress-mediated neuroplasticity, inflammatory pathways, and gut–brain interactions as core vulnerability mechanisms. Social epidemiology research demonstrates that income gradients, structural inequality, and hierarchical stress responses shape population-level distribution of mental morbidity. Concurrently, digital environments function as both intervention platforms and behavioral risk modifiers, with smartphone-based tools showing therapeutic potential while excessive screen exposure and maladaptive social media engagement correlate with adverse outcomes. The findings support a multidimensional systems-based model in which biological substrates, structural determinants, and technological ecosystems interact dynamically. This framework holds particular relevance for middle-income contexts, including Mexico, Colombia, and Ecuador, where rapid digitalization coexists with socioeconomic disparities. Integrating these domains strengthens clinical reasoning, psychiatric education, and public health strategy design, promoting a comprehensive and ethically guided approach to contemporary mental health care.
References
[1] T. A. Insel, “Rethinking schizophrenia,” Nature, vol. 468, no. 7321, pp. 187–193, 2010, doi: 10.1038/nature09552.
[2] R. S. Kessler et al., “Twelve-month and lifetime prevalence of DSM-IV disorders,” Arch. Gen. Psychiatry, vol. 62, no. 6, pp. 617–627, 2005, doi: 10.1001/archpsyc.62.6.617.
[3] H. A. Whiteford et al., “Global burden of mental and substance use disorders,” Lancet, vol. 382, no. 9904, pp. 1575–1586, 2013, doi: 10.1016/S0140-6736(13)61611-6.
[4] E. J. Nestler et al., “Neurobiology of depression,” Neuron, vol. 34, no. 1, pp. 13–25, 2002, doi: 10.1016/S0896-6273(02)00653-0.
[5] A. Meyer-Lindenberg and D. R. Weinberger, “Intermediate phenotypes and genetic mechanisms of psychiatric disorders,” Nat. Rev. Neurosci., vol. 7, no. 10, pp. 818–827, 2006, doi: 10.1038/nrn1993.
[6] S. McEwen, “Neurobiological and systemic effects of chronic stress,” N. Engl. J. Med., vol. 338, no. 3, pp. 171–179, 1998, doi: 10.1056/NEJM199801153380307.
[7] R. M. Post, “Kindling and sensitization in mood disorders,” Psychol. Med., vol. 22, no. 3, pp. 467–471, 1992, doi: 10.1017/S0033291700038051.
[8] R. Sapolsky, “Social status and health in humans and other animals,” Annu. Rev. Anthropol., vol. 33, pp. 393–418, 2004, doi: 10.1146/annurev.anthro.33.070203.144000.
[9] M. Marmot, “The influence of income on health,” Lancet, vol. 365, no. 9464, pp. 1099–1104, 2005, doi: 10.1016/S0140-6736(05)71146-6.
[10] N. Krieger, “Theories for social epidemiology in the 21st century,” Int. J. Epidemiol., vol. 30, no. 4, pp. 668–677, 2001, doi: 10.1093/ije/30.4.668.
[11] World Health Organization, “World mental health report: Transforming mental health for all,” WHO, 2022, doi: 10.2471/BLT.22.288219.
[12] J. Torous and J. Firth, “The digital revolution in mental health,” Lancet Psychiatry, vol. 3, no. 6, pp. 489–491, 2016, doi: 10.1016/S2215-0366(16)30034-5.
[13] J. Firth et al., “The efficacy of smartphone-based mental health interventions,” World Psychiatry, vol. 16, no. 3, pp. 287–298, 2017, doi: 10.1002/wps.20472.
[14] J. Huckvale, J. Torous, and M. Larsen, “Assessment of the data sharing and privacy practices of smartphone apps for depression and smoking cessation,” JAMA Netw. Open, vol. 2, no. 4, e192542, 2019, doi: 10.1001/jamanetworkopen.2019.2542.
[15] T. Insel and S. Sahakian, “Digital phenotyping and psychiatry,” Lancet Psychiatry, vol. 5, no. 3, pp. 196–198, 2018, doi: 10.1016/S2215-0366(18)30047-2.
[16] J. F. Cryan and T. G. Dinan, “Mind-altering microorganisms: The impact of the gut microbiota on brain and behaviour,” Nat. Rev. Neurosci., vol. 13, no. 10, pp. 701–712, 2012, doi: 10.1038/nrn3346.
[17] E. D. M. Jones et al., “Neuroinflammation and psychiatric disorders,” Mol. Psychiatry, vol. 23, no. 3, pp. 401–410, 2018, doi: 10.1038/mp.2017.186.
[18] S. H. Kennedy et al., “Inflammatory biomarkers in major depressive disorder,” Biol. Psychiatry, vol. 85, no. 9, pp. 786–795, 2019, doi: 10.1016/j.biopsych.2018.12.010.
[19] J. Twenge et al., “Associations between screen time and depressive symptoms among adolescents,” Clin. Psychol. Sci., vol. 6, no. 1, pp. 3–17, 2018, doi: 10.1177/2167702617723376.
[20] R. Calati et al., “Social media use and suicide-related outcomes,” Curr. Opin. Psychiatry, vol. 32, no. 5, pp. 388–397, 2019, doi: 10.1097/YCO.0000000000000535.
