Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-24T16:32:36.676Z Has data issue: false hasContentIssue false

29 - Psychiatric Classification: An A-reductionist Perspective

from Section 10

Published online by Cambridge University Press:  02 April 2020

Kenneth S. Kendler
Affiliation:
Virginia Commonwealth University
Josef Parnas
Affiliation:
University of Copenhagen
Peter Zachar
Affiliation:
Auburn University, Montgomery
Get access

Summary

This paper develops the idea that nosological reform is ultimately a matter of finding homogeneous groups of patients that are maximally distinct from each other. The focus lies on the statistical properties of patients, so that the problem of classification coincides with the problem of the reference class from the philosophy of science. It is argued that specific statistical methods – model selection and causal modeling – can assist in finding good classifications. An important advantage of these statistical methods is that they do not favor any particular explanatory level or vocabulary. Whether or not we should include some patient characteristic in our classification scheme is an empirical issue, to be settled entirely by its contribution to the performance of the scheme in predictions and intervention decisions. For this reason the paper adopts a so-called a-reductionist perspective: we do not need a principled discussion on reductionism.

Type
Chapter
Information
Levels of Analysis in Psychopathology
Cross-Disciplinary Perspectives
, pp. 349 - 370
Publisher: Cambridge University Press
Print publication year: 2020

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

American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders: DSM-5 (5th ed). American Psychiatric Publishing, Washington, DC.Google Scholar
Baumeister, H, Parker, G (2012) ‘Meta-review of depressive subtyping models.’ Journal of Affective Disorders 139, 126140.Google Scholar
Cartwright, N, Hardie, J (2012) Evidence-Based Policy. Oxford University Press, New York.CrossRefGoogle Scholar
Chalupka, K, Eberhardt, F, Perona, P (2017) ‘Causal feature learning: An overview.’ Behaviormetrika 44, 137164.CrossRefGoogle Scholar
Claeskens, G, Hjort, N (2008) Model Selection and Model Averaging. Cambridge University Press, Cambridge, UK.Google Scholar
Eaton, WW, Shao, H, Nestadt, G, Lee, BH, Bienvenu, OJ, Zandi, P (2008) ‘Population-based study of first onset and chronicity in major depressive disorder.’ Archives of General Psychiatry 65, 513520.CrossRefGoogle ScholarPubMed
Eronen, MI (2019) ‘The levels problem in psychopathology.’ Psychological Medicine, 1–7. https://doi.org/10.1017/S0033291719002514Google Scholar
First, MB, Kendler, KS, Leibenluft, E (2017) ‘The future of the DSM Implementing a continuous improvement model.’ JAMA Psychiatry 74, 115.CrossRefGoogle ScholarPubMed
Glymour, C, Spirtes, P, Scheines, R (2001) Causation, Prediction, and Search (2nd ed). MIT Press, Cambridge, MA.Google Scholar
Grove, WM, Meehl, PE (1996) ‘Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: The clinical–statistical controversy.’ Psychology, Public Policy, and Law 2, 293323.Google Scholar
Hájek, A (2007) ‘The reference class problem is your problem too.’ Synthese 156, 185215.CrossRefGoogle Scholar
Hathaway, SR, McKinley, JC (1940) ‘A multiphasic personality schedule (Minnesota): Construction of the schedule.’ Journal of Psychology 10, 249254.CrossRefGoogle Scholar
James, G, Witten, D, Hastie, T, Tibshirani, R (2013) An Introduction to Statistical Learning with Applications in R. Springer, New York.Google Scholar
Kendler, KS (2013) ‘A history of the DSM-5 scientific review committee.’ Psychological Medicine 43, 17931800.Google Scholar
Kendler, KS (2014) ‘The structure of psychiatric science.’ The American Journal of Psychiatry 171, 931938.Google Scholar
Kessler, RC, van Loo, HM, Wardenaar, KJ, Bossarte, RM, Brenner, LA, Cai, T, Ebert, DD, Hwang, I, Li, J, de Jonge, P, Nierenberg, AA, Petukhova, M V, Rosellini, AJ, Sampson, NA, Schoevers, RA, Wilcox, MA, Zaslavsky, AM (2016) ‘Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports.’ Molecular Psychiatry 21, 13661371.Google Scholar
Kessler, RC, Ustun, TB (eds) (2008) The WHO World Mental Health Surveys: Global Perspectives on the Epidemiology of Mental Disorders. Cambridge University Press, New York.Google Scholar
Kuhn, T. (1962) The Structure of Scientific Revolutions. Chicago University Press, Chicago, IL.Google Scholar
Kupfer, DJ, Regier, DA, Kuhl, EA (2008) ‘On the road to DSM-V and ICD-11.’ European Archives of Psychiatry and Clinical Neuroscience 258, 26.CrossRefGoogle ScholarPubMed
van Loo, HM, Cai, T, Gruber, MJ, Li, J, de Jonge, P, Petukhova, M, Rose, S, Sampson, NA, Schoevers, RA, Wardenaar, KJ, Wilcox, MA, Al-Hamzawi, AO, Andrade, LH, Bromet, EJ, Bunting, B, Fayyad, J, Florescu, SE, Gureje, O, Hu, C, Huang, Y, Levinson, D, Medina-Mora, ME, Nakane, Y, Posada-Villa, J, Scott, KM, Xavier, M, Zarkov, Z, Kessler, RC (2014) ‘Major depressive disorder subtypes to predict long-term course.’ Depression and Anxiety 31, 765777.CrossRefGoogle ScholarPubMed
Lubke, GH, Muthén, B (2005) ‘Investigating population heterogeneity with factor mixture models.’ Psychological Methods 10(1), 2139.CrossRefGoogle ScholarPubMed
Meehl, PE (1956). ‘Wanted—a good cook-book.’ American Psychologist, 11(6), 263272. http://dx.doi.org/10.1037/h0044164Google Scholar
Morgan, M, Morrison, M (1999) Models as Mediators. Cambridge University Press, Cambridge, UK.CrossRefGoogle Scholar
Nandi, A, Beard, JR, Galea, S (2009) ‘Epidemiologic heterogeneity of common mood and anxiety disorders over the lifecourse in the general population: A systematic review.’ BMC Psychiatry 9, 31.Google Scholar
Olbert, CM, Gala, GJ, Tupler, LA (2014) ‘Quantifying heterogeneity attributable to polythetic diagnostic criteria: Theoretical framework and empirical application.’ Journal of Abnormal Psychology 123(2), 452462.CrossRefGoogle ScholarPubMed
Pearl, J (2000) Causality. MIT Press, Cambridge, MA.,Google Scholar
Pearl, J (2018) The Book of Why. Basic Books, New York.Google Scholar
Reichenbach, H (1949) The Theory of Probability. University of Chicago Press, Chicago, IL.Google Scholar
Roy-Byrne, PP, Stang, P, Wittchen, H-U, Ustun, B, Walters, EE, Kessler, RC (2000) ‘Lifetime panic–depression comorbidity in the National Comorbidity Survey.’ British Journal of Psychiatry 176, 229235.CrossRefGoogle ScholarPubMed
Tabb, K. (2015) ‘Psychiatric progress and the assumption of diagnostic discrimination.’ Philosophy of Science 82, 10471058.Google Scholar
Tabb, K. (2017) ‘Philosophy of psychiatry after diagnostic kinds.’ Synthese 196(6), 21772195. doi:10.1007/s11229-017-1659-6.Google Scholar
Wardenaar, KJ, van Loo, HM, Cai, T, Fava, M, Gruber, MJ, Li, J, de Jonge, P, Nierenberg, AA, Pethukova, M V, Rose, S, Sampson, NA, Schoevers, RA, Wilcox, MA, Alonso, J, Bromet, EJ, Bunting, B, Florescu, SE, Fukao, A, Gureje, O, Hu, C, Huang, YQ, Karam, AN, Levinson, D, Medina-Mora, ME, Posada-Villa, J, Scott, KM, Taib, NI, Viana, MC, Xavier, M, Zarkov, Z, Kessler, RC (2014) ‘The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.’ Psychological Medicine 44, 32893302.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×