Hostname: page-component-8448b6f56d-c47g7 Total loading time: 0 Render date: 2024-04-19T12:45:34.460Z Has data issue: false hasContentIssue false

Where are the breaks in translation from theory to clinical practice (and back) in addressing depression? An empirical graph-theoretic approach

Published online by Cambridge University Press:  18 December 2018

Greg J. Siegle*
Affiliation:
University of Pittsburgh, School of Medicine, Pittsburgh, PA, USA
Angélique O.J. Cramer
Affiliation:
Tilburg University, Tilburg, Netherlands
Nees Jan van Eck
Affiliation:
Leiden University, Leiden, Netherlands
Philip Spinhoven
Affiliation:
Leiden University, Leiden, Netherlands
Steven D. Hollon
Affiliation:
Vanderbilt University, Nashville, TN, USA
Johan Ormel
Affiliation:
University of Groningen, Groningen, Netherlands
Marlene Strege
Affiliation:
Virginia Tech, Nashvile, CA, USA
Claudi L. H. Bockting
Affiliation:
Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
*
Author for correspondence: Greg J. Siegle, E-mail: gsiegle@pitt.edu

Abstract

Background

Research in depression has progressed rapidly over the past four decades. Yet depression rates are not subsiding and treatment success is not improving. We examine the extent to which the gap between science and practice is associated with the level of integration in how depression is considered in research and stakeholder-relevant documents.

Methods

We used a network-science perspective to analyze similar uses of depression relevant terms in the Google News corpus (approximately 1 billion words) and the Web of Science database (120 000 documents).

Results

These analyses yielded consistent pictures of insular modules associated with: (1) patient/providers, (2) academics, and (3) industry. Within academia insular modules associated with psychology, general medical, and psychiatry/neuroscience/biology were also detected.

Conclusions

These analyses suggest that the domain of depression is fragmented, and that advancements of relevance to one stakeholder group (academics, industry, or patients) may not translate to the others. We consider potential causes and associated responses to this fragmentation that could help to unify and advance translation from research on depression to the clinic, largely involving harmonizing employed language, bridging conceptual domains, and increasing communication across stakeholder groups.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

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

Ai, AL, Nicdao, EG, Appel, HB and Lee, DHJ (2015) Ethnic identity and major depression in Asian American subgroups nationwide: differential findings in relation to subcultural contexts. Journal of Clinical Psychology 71, 12251244.10.1002/jclp.22214Google Scholar
Alving, B, Dai, K and Chan, SHH (2012) Translational Medicine – What, Why and How: An International Perspective. Basel, Switzerland: Karger Medical and Scientific Publishers.10.1159/isbn.978-3-318-02285-8Google Scholar
Andrews, PW and Thomson, JA Jr (2009) The bright side of being blue: depression as an adaptation for analyzing complex problems. Psychological Review 116, 620654.10.1037/a0016242Google Scholar
Angst, J and Merikangas, K (1997) The depressive spectrum: diagnostic classification and course. Journal of Affective Disorders 45, 3140.10.1016/S0165-0327(97)00057-8Google Scholar
Baksa, D, Gonda, X and Juhasz, G (2017) Why are migraineurs more depressed? A review of the factors contributing to the comorbidity of migraine and depression. Neuropsychopharmacologia Hungarica 19, 3744.Google Scholar
Breslau, N, Lipton, RB, Stewart, WF, Schultz, LR and Welch, KMA (2003) Comorbidity of migraine and depression: investigating potential etiology and prognosis. Neurology 60, 13081312.10.1212/01.WNL.0000058907.41080.54Google Scholar
Cai, JJ, Borenstein, E and Petrov, DA (2010) Broker genes in human disease. Genome Biology and Evolution 2, 815825.10.1093/gbe/evq064Google Scholar
Casadevall, A and Fang, FC (2014) Specialized science. Infection and Immunity 82, 13551360.10.1128/IAI.01530-13Google Scholar
Caspi, A, Sugden, K, Moffitt, TE, Taylor, A, Craig, IW, Harrington, H, McClay, J, Mill, J, Martin, J, Braithwaite, A and Poulton, R (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301, 386389.10.1126/science.1083968Google Scholar
Cramer, AOJ, Waldorp, LJ, van der Maas, HLJ and Borsboom, D (2010) Comorbidity: a network perspective. The Behavioral and Brain Sciences 33, 137150, discussion 150–93.10.1017/S0140525X09991567Google Scholar
Daughtry, D and Kunkel, MA (1993) Experience of depression in college students: a concept map. Journal of Counseling Psychology 40, 316323.10.1037/0022-0167.40.3.316Google Scholar
Domingos, P and Richardson, M (2001) Mining the network value of customers. In Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining (KDD ’01), August, San Francisco, CA.10.1145/502512.502525Google Scholar
Duan, Z-G, Wu, Y and Long, C (2015) Analysis on international scientific collaboration and research focus on depression field. Chinese Medical Journal 128, 687.Google Scholar
Eisenberg, D and Druss, BG (2015) Time preferences, mental health and treatment utilization. The Journal of Mental Health Policy and Economics 18, 125136.Google Scholar
Frodl, T (2016) Systems Neuroscience in Depression. Cambridge, MA: Academic Press.Google Scholar
Gotlib, IH and Hammen, CL (2015) Handbook of Depression. New York, NY: Guilford Publications.Google Scholar
Hagmayer, Y and Engelmann, N (2014) Causal beliefs about depression in different cultural groups – what do cognitive psychological theories of causal learning and reasoning predict? Frontiers in Psychology 5, 1303.Google Scholar
Hausdorff, F (2001) Dimension und äußeres Maß. In Felix Hausdorff Gesammelte Werke. pp. 1954.10.1007/978-3-642-59483-0_2Google Scholar
Holmes, EA, Craske, MG and Graybiel, AM (2014) Psychological treatments: a call for mental-health science. Nature 511, 287289.10.1038/511287aGoogle Scholar
Humphries, MD and Gurney, K (2008) Network ‘small-world-ness’: a quantitative method for determining canonical network equivalence. PLoS ONE 3, e0002051.10.1371/journal.pone.0002051Google Scholar
Insel, TR (2012) Next-generation treatments for mental disorders. Science Translational Medicine 4, 155ps19155ps19.10.1126/scitranslmed.3004873Google Scholar
Institute of Medicine, Board on the Health of Select Populations (2013) Cognitive Rehabilitation Therapy for Traumatic Brain Injury: Model Study Protocols and Frameworks to Advance the State of the Science: Workshop Summary. Washington, DC: National Academies Press.Google Scholar
Jancin, B (2013) Depression fuels path from episodic to chronic migraine. Clinical Psychiatry News 41, 20.10.1016/S0270-6644(13)70020-1Google Scholar
Karlin, BE and Cross, G (2014) Enhancing access, fidelity, and outcomes in the national dissemination of evidence-based psychotherapies. The American Psychologist 69, 709711.10.1037/a0037384Google Scholar
Kempe, D, Kleinberg, J and Tardos, É (2003) Maximizing the spread of influence through a social network. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining (KDD ’03), August, Washington, DC.10.1145/956750.956769Google Scholar
Kennedy, N, Foy, K, Sherazi, R, McDonough, M and McKeon, P (2007) Long-term social functioning after depression treated by psychiatrists: a review. Bipolar Disorders 9, 2537.10.1111/j.1399-5618.2007.00326.xGoogle Scholar
Kessler, RC and Bromet, EJ (2013) The epidemiology of depression across cultures. Annual Review of Public Health 34, 119138.10.1146/annurev-publhealth-031912-114409Google Scholar
Kilbourne, AM, Williams, M, Bauer, MS and Arean, P (2012) Implementation research: reducing the research-to-practice gap in depression treatment. Depression Research and Treatment 2012, 12.10.1155/2012/476027Google Scholar
Kleinman, A and Good, B (1985) Culture and Depression: Studies in the Anthropology and Cross-Cultural Psychiatry of Affect and Disorder. Berkeley, CA: Univ. of California Press.Google Scholar
Konganti, K, Wang, G, Yang, E and Cai, JJ (2013) SBEToolbox: a Matlab toolbox for biological network analysis. Evolutionary Bioinformatics Online 9, 355362.Google Scholar
Krieger, S (2011) Multiple sclerosis therapeutic pipeline: opportunities and challenges. Mount Sinai Journal of Medicine: A Journal of Translational and Personalized Medicine 78, 192206.10.1002/msj.20241Google Scholar
Lantéri-Minet, M, Radat, F, Chautard, M-H and Lucas, C (2005) Anxiety and depression associated with migraine: influence on migraine subjects' disability and quality of life, and acute migraine management. Pain 118, 319326.10.1016/j.pain.2005.09.010Google Scholar
Lemieux-Charles, L and McGuire, WL (2006) What do we know about health care team effectiveness? A review of the literature. Medical Care Research and Review: MCRR 63, 263300.10.1177/1077558706287003Google Scholar
Llesuy, JR (2012) Depression and migraine. In Kanner, AM (ed.), Depression in Neurologic Disorders: Diagnosis and Management. Hoboken, NJ: Blackwell Publishing Ltd, pp. 103115.10.1002/9781118348093.ch9Google Scholar
Lyall, C, Bruce, A, Marsden, W and Meagher, L (2013) The role of funding agencies in creating interdisciplinary knowledge. Science & Public Policy 40, 6271.10.1093/scipol/scs121Google Scholar
Mikolov, T, Chen, K, Corrado, G and Dean, J (2013) Efficient estimation of word representations in vector space. In Proceedings of the International Conference on Learning Representations (ICLR), May, Scottsdale, Arizona. Available web: https://arxiv.org/pdf/1301.3781.pdfGoogle Scholar
Morris, ZS, Wooding, S and Grant, J (2011) The answer is 17 years, what is the question: understanding time lags in translational research. Journal of the Royal Society of Medicine 104, 510520.10.1258/jrsm.2011.110180Google Scholar
Nebes, RD, Pollock, BG, Houck, PR, Butters, MA, Mulsant, BH, Zmuda, MD and Reynolds, CF (2003) Persistence of cognitive impairment in geriatric patients following antidepressant treatment: a randomized, double-blind clinical trial with nortriptyline and paroxetine. Journal of Psychiatric Research 37, 99108.10.1016/S0022-3956(02)00085-7Google Scholar
Oborn, E (2012) Facilitating implementation of the translational research pipeline in neurological rehabilitation. Current Opinion in Neurology 25, 676681.10.1097/WCO.0b013e32835a35f2Google Scholar
Read, A (1992) The scientific dialogue: from basic research to clinical intervention. Behaviour Research and Therapy 30, 80.10.1016/0005-7967(92)90104-OGoogle Scholar
Torres, L (2010) Predicting levels of Latino depression: acculturation, acculturative stress, and coping. Cultural Diversity & Ethnic Minority Psychology 16, 256263.10.1037/a0017357Google Scholar
To thwart disease, apply now (2008). Nature 453, 823.Google Scholar
Tsuji, K and Tsutani, K (2008) Follow the leader. Nature 453, 851852.10.1038/453851aGoogle Scholar
van Eck, NJ and Waltman, L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84, 523538.Google Scholar
Van Eck, N and Waltman, JL (2011) Text mining and visualization using VOSviewer. ISSI Newsletter 7, 5054.Google Scholar
Weersing, VR, Rozenman, M and Gonzalez, A (2009) Core components of therapy in youth: do we know what to disseminate? Behavior Modification 33, 2447.Google Scholar
Wehling, M (2015) Principles of Translational Science in Medicine: From Bench to Bedside. Cambridge, MA: Academic Press.Google Scholar
Williams, MS (2015) Is the genomic translational pipeline being disrupted? Human Genomics 9, 9.Google Scholar
World Health Organization (2017) Depression and Other Common Mental Disorders: Global Health Estimates. Geneva, Switzerland: World Health Organization.Google Scholar
Zarcone, D and Corbetta, S (2017) Shared mechanisms of epilepsy, migraine and affective disorders. Neurological Sciences 38, 7376.Google Scholar
Zerhouni, E (2003) Medicine: the NIH roadmap. Science 302, 6372.Google Scholar
Supplementary material: PDF

Siegle et al. supplementary material

Siegle et al. supplementary material 1

Download Siegle et al. supplementary material(PDF)
PDF 1.5 MB