Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-22T16:49:59.245Z Has data issue: false hasContentIssue false
  • English
  • Français

Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder

Published online by Cambridge University Press:  01 December 2015

A. K. Wittenborn ,
H. Rahmandad ,
J. Rick  and
N. Hosseinichimeh
A. K. Wittenborn*
Affiliation:
Department of Human Development and Family Studies, Michigan State University, East Lansing, MI, USA
H. Rahmandad
Affiliation:
Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA
J. Rick
Affiliation:
Department of Human Development and Family Studies, Michigan State University, East Lansing, MI, USA
N. Hosseinichimeh
Affiliation:
Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA
*
*Address for correspondence: A. K. Wittenborn, Ph.D., Department of Human Development and Family Studies, Michigan State University, 552 W. Circle Drive, East Lansing, MI 48824, USA. (Email: andreaw@msu.edu)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Depression is a complex public health problem with considerable variation in treatment response. The systemic complexity of depression, or the feedback processes among diverse drivers of the disorder, contribute to the persistence of depression. This paper extends prior attempts to understand the complex causal feedback mechanisms that underlie depression by presenting the first broad boundary causal loop diagram of depression dynamics.

Method

We applied qualitative system dynamics methods to map the broad feedback mechanisms of depression. We used a structured approach to identify candidate causal mechanisms of depression in the literature. We assessed the strength of empirical support for each mechanism and prioritized those with support from validation studies. Through an iterative process, we synthesized the empirical literature and created a conceptual model of major depressive disorder.

Results

The literature review and synthesis resulted in the development of the first causal loop diagram of reinforcing feedback processes of depression. It proposes candidate drivers of illness, or inertial factors, and their temporal functioning, as well as the interactions among drivers of depression. The final causal loop diagram defines 13 key reinforcing feedback loops that involve nine candidate drivers of depression.

Conclusions

Future research is needed to expand upon this initial model of depression dynamics. Quantitative extensions may result in a better understanding of the systemic syndrome of depression and contribute to personalized methods of evaluation, prevention and intervention.

Keywords

Feedback loopsfeedback mechanismsmajor depressive disorderpersonalized medicinesystem dynamics
Type
Original Articles
Information
Psychological Medicine , Volume 46 , Issue 3 , February 2016 , pp. 551 - 562
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aggen, SH, Neale, MC, Kendler, KS (2005). DSM criteria for major depression: evaluating symptom patterns using latent-trait item response models. Psychological Medicine 35, 475–487.CrossRefGoogle ScholarPubMed
Barber, JP, Barrett, MS, Gallop, R, Rynn, MA, Rickels, K (2012). Short-term dynamic psychotherapy versus pharmacotherapy for major depressive disorder: a randomized, placebo-controlled trial. Journal of Clinical Psychiatry 73, 66–73.Google Scholar
Beck, AT (2008). The evolution of the cognitive model of depression and its neurobiological correlates. American Journal of Psychiatry 165, 969–977.CrossRefGoogle ScholarPubMed
Belmaker, RH, Agam, G (2008). Major depressive disorder. New England Journal of Medicine 358, 47–60.Google Scholar
Bohm, D (1980). Wholeness and the Implicate Order. Routledge: New York.Google Scholar
Borsboom, D, Cramer, AOJ (2013). Network analysis: an integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology 9, 91–121.CrossRefGoogle Scholar
Carter, JD, McIntosh, VV, Jordan, J, Porter, RJ, Frampton, CM, Joyce, PR (2013). Psychotherapy for depression: a randomized clinical trial comparing schema therapy and cognitive behavior therapy. Journal of Affective Disorders 151, 500–505.CrossRefGoogle ScholarPubMed
Choi, JHK, Abel, T (2013). Sleep and long-term memory storage. In The Genetic Basis of Sleep and Sleep Disorders (ed. Shaw, P., Tafti, M. and Thorpy, M.), pp. 208–218. Cambridge University Press: New York.Google Scholar
Clow, A, Patel, S, Najafi, M, Evans, PD, Hucklebridge, F (1997). The cortisol response to psychological challenge is preceded by a transient rise in endogenous inhibitor of monoamine oxidase. Life Sciences 61, 567–575.Google Scholar
Cole, DA, Dukewich, TL, Roeder, K, Sinclair, KR, McMillan, J, Will, E, Bilsky, SA, Martin, NC, Felton, JW (2014). Linking peer victimization to the development of depressive self-schemas in children and adolescents. Journal of Abnormal Child Psychology 42, 149–160.CrossRefGoogle Scholar
De Kloet, ER, Vreugdenhil, E, Oitzl, MS, Joëls, M (1998). Brain corticosteroid receptor balance in health and disease. Endocrine Reviews 19, 269–301.Google ScholarPubMed
De Lissnyder, E, Koster, EHW, Everaert, J, Schacht, R, Van Den Abeele, D, De Raedt, R (2012). Internal cognitive control in clinical depression: general but no emotion-specific impairments. Psychiatry Research 199, 124–130.CrossRefGoogle ScholarPubMed
De Raedt, R, Koster, EHW (2010). Understanding vulnerability for depression from a cognitive neuroscience perspective: a reappraisal of attentional factors and a new conceptual framework. Cognitive, Affective and Behavioral Neuroscience 10, 50–70.CrossRefGoogle Scholar
Dimatteo, MR, Lepper, HS, Croghan, TW (2000). Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. Archives of Internal Medicine 160, 2101–2107.CrossRefGoogle ScholarPubMed
Eshel, N, Roiser, JP (2010). Reward and punishment processing in depression. Biological Psychiatry 68, 118–124.Google Scholar
Ferrari, AJ, Charlson, FJ, Norman, RE, Patten, SB, Freedman, G, Murray, CJ, Vos, T, Whiteford, HA (2013). Burden of depressive disorders by country, sex, age, and year: findings from the Global Burden of Disease Study 2010. PLoS Medicine 10, e1001547.Google Scholar
Forrester, JW (1994). System dynamics, systems thinking, and soft OR. System Dynamics Review 10, 245–256.CrossRefGoogle Scholar
Gotlib, IH, Hammen, CL (editors) (2014). Handbook of Depression, 3rd edn. Guilford Press: New York.Google Scholar
Greenberg, PE, Fournier, AA, Sisitsky, T, Pike, CT, Kessler, RC (2015). The economic burden of adults with major depressive disorder in the United States (2005 and 2010). Journal of Clinical Psychiatry 76, 155–162.Google Scholar
Gruenewald, TL, Kemeny, ME, Aziz, N, Fahey, JL (2004). Acute threat to the social self: shame, social self-esteem, and cortisol activity. Psychosomatic Medicine 66, 915–924.Google Scholar
Hamilton, JL, Stange, JP, Shapero, BG, Connolly, SL, Abramson, LY, Alloy, LB (2013). Cognitive vulnerabilities as predictors of stress generation in early adolescence: pathway to depressive symptoms. Journal of Abnormal Child Psychology 41, 1027–1039.Google Scholar
Hammen, CL (2006). Stress generation in depression: reflections on origins, research, and future directions. Journal of Clinical Psychology 62, 1065–1082.Google Scholar
Hankin, BL, Fraley, RC, Lahey, BB, Waldman, ID (2005). Is depression best viewed as a continuum or discrete category? A taxometric analysis of childhood and adolescent depression in a population-based sample. Journal of Abnormal Psychology 114, 96–110.CrossRefGoogle ScholarPubMed
Herbert, J, Goodyer, IM, Grossman, AB, Hastings, MH, De Kloet, ER, Lightman, SL, Lupien, SJ, Roozendaal, B, Seckl, JR (2006). Do corticosteroids damage the brain? Journal of Neuroendocrinology 18, 393–411.CrossRefGoogle ScholarPubMed
Hobfoll, SE, Johnson, RJ, Ennis, N, Jackson, AP (2003). Resource loss, resource gain, and emotional outcomes among inner city women. Journal of Personality and Social Psychology 84, 632–643.Google Scholar
Hosseinichimeh, N, Rahmandad, H, Wittenborn, AK (2015). Modeling the hypothalamus–pituitary–adrenal axis: a review and extension. Mathematical Biosciences 268, 52–65.Google Scholar
Hu, K, Rahmandad, H, Smith-Jackson, T, Winchester, W (2011). Factors influencing the risk of falls in the construction industry: a review of the evidence. Construction Management and Economics 29, 397–416.Google Scholar
Insel, TR (2014). The NIMH Research Domain Criteria (RDoC) Project: precision medicine for psychiatry. American Journal of Psychiatry 171, 395–397.Google Scholar
Joiner, TE, Wingate, LR, Otamendi, A (2005). An interpersonal addendum to the hopelessness theory of depression: hopelessness as a stress and depression generator. Journal of Social and Clinical Psychology 24, 649–664.CrossRefGoogle Scholar
Kendler, KS, Gardner, CO, Prescott, CA (2002). Toward a comprehensive developmental model for major depression in women. American Journal of Psychiatry 159, 1133–1145.Google Scholar
Kendler, KS, Gardner, CO, Prescott, CA (2006). Toward a comprehensive developmental model for major depression in men. American Journal of Psychiatry 163, 115–124.Google Scholar
Kendler, KS, Zachar, P, Craver, C (2011). What kinds of things are psychiatric disorders? Psychological Medicine 41, 1143–1150.CrossRefGoogle ScholarPubMed
Kirsch, I, Deacon, BJ, Huedo-Medina, TB, Scoboria, A, Moore, TJ, Johnson, BT (2008). Initial severity and antidepressant benefits: a meta-analysis of data submitted to the Food and Drug Administration. PLoS Medicine 5, e45.Google Scholar
Lacro, RV, Dietz, HC, Sleeper, LA, Yetman, AT, Bradley, TJ, Colan, SD, Pearson, GD, Selamet Tierney, ES, Levine, JC, Atz, AM, Benson, DW, Braverman, AC, Chen, S, De Backer, J, Gelb, BD, Grossfeld, PD, Klein, GL, Lai, WW, Liou, A, Loeys, BL, Markham, LW, Olson, AK, Paridon, SM, Pemberton, VL, Pierpont, ME, Pyeritz, RE, Radojewski, E, Roman, MJ, Sharkey, AM, Stylianou, MP, Wechsler, SB, Young, LT, Mahony, L (2014). Atenolol versus Losartan in children and young adults with Marfan's syndrome. New England Journal of Medicine 371, 2061–2071.CrossRefGoogle Scholar
Lovejoy, MC, Graczyk, PA, O'hare, E, Neuman, G (2000). Maternal depression and parenting behavior: a meta-analytic review. Clinical Psychology Review 20, 561–592.Google Scholar
Maier, SF, Amat, J, Baratta, MV, Paul, E, Watkins, LR (2006). Behavioral control, the medial prefrontal cortex, and resilience. Dialogues in Clinical Neuroscience 8, 397–406.Google Scholar
McCall, WV, Dunn, AG (2003). Cognitive deficits are associated with functional impairment in severely depressed patients. Psychiatry Research 121, 179–184.Google Scholar
McGinn, LK, Cukor, D, Sanderson, WC (2005). The relationship between parenting style, cognitive style, and anxiety and depression: does increased early adversity influence symptom severity through the mediating role of cognitive style? Cognitive Therapy and Research 29, 219–242.Google Scholar
McIntyre, RS, Cha, DS, Soczynska, JK, Woldeyohannes, HO, Gallaugher, LA, Kudlow, P, Alsuwaidan, M, Baskaran, A (2013). Cognitive deficits and functional outcomes in major depressive disorder: determinants, substrates, and treatment interventions. Depression and Anxiety 30, 515–527.Google Scholar
Miller, AH, Maletic, V, Raison, CL (2009). Inflammation and its discontents: the role of cytokines in the pathophysiology of major depression. Biological Psychiatry 65, 732–741.Google Scholar
Mössner, R, Mikova, O, Koutsilieri, E, Saoud, M, Ehlis, A-C, Müller, N, Fallgatter, AJ, Riederer, P (2007). Consensus paper of the WFSBP Task Force on Biological Markers: biological markers in depression. World Journal of Biological Psychiatry 8, 141–174.CrossRefGoogle ScholarPubMed
National Center for Health Statistics (2014). Health, United States, 2013: With Special Feature on Prescription Drugs. National Center for Health Statistics: Hyattsville, MD.Google Scholar
Nolen-Hoeksema, S, Morrow, J (1991). A prospective study of depression and posttraumatic stress symptoms after a natural disaster: the 1989 Loma Prieta earthquake. Journal of Personality and Social Psychology 61, 115–121.Google Scholar
Paddon-Jones, D (2006). Interplay of stress and physical inactivity on muscle loss: nutritional countermeasures. Journal of Nutrition 136, 2123–2126.Google Scholar
Padesky, CA (1994). Schema change processes in cognitive therapy. Clinical Psychology and Psychotherapy 1, 267–278.Google Scholar
Palagini, L, Baglioni, C, Ciapparelli, A, Gemignani, A, Riemann, D (2013). REM sleep dysregulation in depression: state of the art. Sleep Medicine Reviews 17, 377–390.Google Scholar
Pariante, CM, Lightman, SL (2008). The HPA axis in major depression: classical theories and new developments. Trends in Neurosciences 31, 464–468.Google Scholar
Peng, G-P, Feng, Z, He, F-P, Chen, Z-Q, Liu, X-Y, Liu, P, Luo, B-Y (2015). Correlation of hippocampal volume and cognitive performances in patients with either mild cognitive impairment or Alzheimer's disease. CNS Neuroscience and Therapeutics 21, 15–22.Google Scholar
Pettit, JW, Joiner, TE (2006). Chronic Depression: Interpersonal Sources, Therapeutic Solutions. American Psychological Association: Washington, DC.Google Scholar
Pizzagalli, DA (2014). Depression, stress, and anhedonia: toward a synthesis and integrated model. Annual Review of Clinical Psychology 10, 393–423.Google Scholar
Rahmandad, H, Sterman, JD (2012). Reporting guidelines for simulation-based research in social sciences. System Dynamics Review 28, 396–411.Google Scholar
Richardson, GP (1999). Feedback Thought in Social Science and Systems Theory. Pegasus Communications: Waltham, MA.Google Scholar
Sapolsky, RM (2000). Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Archives of General Psychiatry 57, 925–935.Google Scholar
Seok, J, Warren, HS, Cuenca, AG, Mindrinos, MN, Baker, HV, Xu, W, Richards, DR, McDonald-Smith, GP, Gao, H, Hennessy, L, Finnerty, CC, López, CM, Honari, S, Moore, EE, Minei, JP, Cuschieri, J, Bankey, PE, Johnson, JL, Sperry, J, Nathens, AB, Billiar, TR, West, MA, Jeschke, MG, Klein, MB, Gamelli, RL, Gibran, NS, Brownstein, BH, Miller-Graziano, C, Calvano, SE, Mason, PH, Cobb, JP, Rahme, LG, Lowry, SF, Maier, RV, Moldawer, LL, Herndon, DN, Davis, RW, Xiao, W, Tompkins, RG, Abouhamze, A, Balis, UGJ, Camp, DG, De, AK, Harbrecht, BG, Hayden, DL, Kaushal, A, O'Keefe, GE, Kotz, KT, Qian, W, Schoenfeld, DA, Shapiro, MB, Silver, GM, Smith, RD, Storey, JD, Tibshirani, R, Toner, M, Wilhelmy, J, Wispelwey, B, Wong, WH, The Inflammation Host Response to Injury Large Scale Collaborative Research Program (2013). Genomic responses in mouse models poorly mimic human inflammatory diseases. Proceedings of the National Academy of Sciences USA 110, 3507–3512.Google Scholar
Slopen, N, Kubzansky, LD, Koenen, KC (2013). Internalizing and externalizing behaviors predict elevated inflammatory markers in childhood. Psychoneuroendocrinology 38, 2854–2862.CrossRefGoogle ScholarPubMed
Stapelberg, NJC, Neumann, DL, Shum, DHK, McConnell, H, Hamilton-Craig, I (2011). A topographical map of the causal network of mechanisms underlying the relationship between major depressive disorder and coronary heart disease. Australian and New Zealand Journal of Psychiatry 45, 351–369.Google Scholar
Sterman, JD (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin/McGraw-Hill: Boston, MA.Google Scholar
Sterman, JD (2006). Learning from evidence in a complex world. American Journal of Public Health 96, 505–514.Google Scholar
Stewart, WF, Ricci, JA, Chee, E, Hahn, SR, Morganstein, D (2003). Cost of lost productive work time among US workers with depression. Journal of the American Medical Association 289, 3135–3144.Google Scholar
Strüber, N, Strüber, D, Roth, G (2014). Impact of early adversity on glucocorticoid regulation and later mental disorders. Neuroscience and Biobehavioral Reviews 38, 17–37.Google Scholar
Van De Leemput, IA, Wichers, M, Cramer, AOJ, Borsboom, D, Tuerlinckx, F, Kuppens, P, Van Nes, EH, Viechtbauer, W, Giltay, EJ, Aggen, SH, Derom, C, Jacobs, N, Kendler, KS, Van Der Maas, HLJ, Neale, MC, Peeters, F, Thiery, E, Zachar, P, Scheffer, M (2014). Critical slowing down as early warning for the onset and termination of depression. Proceedings of the National Academy of Sciences USA 111, 87–92.Google Scholar
Van Dongen, HPA, Maislin, G, Mullington, JM, Dinges, DF (2003). The cumulative cost of additional wakefullness: dose–response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep 26, 117–126.Google Scholar
Wainwright, SR, Galea, LM (2013). The neural plasticity theory of depression: assessing the roles of adult neurogenesis and PSA-NCAM within the hippocampus. Neural Plasticity 2013, 805497.Google Scholar
Wichers, M (2014). The dynamic nature of depression: a new micro-level perspective of mental disorder that meets current challenges. Psychological Medicine 44, 1349–1360.Google Scholar
World Health Organization (2008). The global burden of disease: 2004 update (http://www.who.int/healthinfo/global_burden_disease/GBD_report_2004update_full.pdf). Accessed May 2012.Google Scholar
World Health Organization (2014). Global health estimates 2014 summary tables (http://www.who.int/healthinfo/global_burden_disease/estimates/en/index2.html). Accessed August 2015.Google Scholar
Xiang, L, Del Ben, KS, Rehm, KE, Marshall, GD Jr (2011). Effects of acute stress-induced immunomodulation on Th1/Th2 cytokine and catecholamine receptor expression in human peripheral blood cells. Neuropsychobiology 65, 12–19.CrossRefGoogle ScholarPubMed
Ye, S, Muntner, P, Shimbo, D, Judd, SE, Richman, J, Davidson, KW, Safford, MM (2013). Behavioral mechanisms, elevated depressive symptoms, and the risk for myocardial infarction or death in individuals with coronary heart disease: the REGARDS (Reason for Geographic and Racial Differences in Stroke) study. Journal of the American College of Cardiology 61, 622–630.Google Scholar
Zunszain, PA, Anacker, C, Cattaneo, A, Carvalho, LA, Pariante, CM (2011). Glucocorticoids, cytokines and brain abnormalities in depression. Progress in Neuropsychopharmacology and Biological Psychiatry 35, 722–729.Google Scholar
Supplementary material: File

Wittenborn supplementary material

Appendix

Download Wittenborn supplementary material(File)
File 151.6 KB