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Validation of hierarchical taxonomy in a clinical sample

Published online by Cambridge University Press:  29 November 2022

Holly Frances Levin-Aspenson Open the ORCID record for Holly Frances Levin-Aspenson [Opens in a new window]  and
Mark Zimmerman
Holly Frances Levin-Aspenson*
Affiliation:
Department of Psychology, University of North Texas, Denton, TX, USA Department of Psychiatry and Human Behavior, Brown University School of Medicine, Providence, RI, USA Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA
Mark Zimmerman
Affiliation:
Department of Psychiatry and Human Behavior, Brown University School of Medicine, Providence, RI, USA Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA
*
Author for correspondence: Holly Frances Levin-Aspenson, E-mail: holly.levin-aspenson@unt.edu
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Abstract

Background

Quantitatively derived dimensional models of psychopathology enjoy overwhelming empirical support, and a large and active community of psychopathology researchers has been establishing an empirically based dimensional hierarchical taxonomy of psychopathology (or HiTOP) as a strong candidate replacement for the current categorical classification system. The hierarchical nature of this taxonomy implies that different levels of resolution are likely to be optimal for different purposes. Our aim was to identify which level of detail is likely to provide optimal validity and explanatory power with regard to relevant clinical variables.

Methods

In the present report from the Rhode Island Methods to Improve Diagnostic Assessment and Services project, we used data from a sample of 2900 psychiatric outpatients to compare different levels from a bass-ackwards model of psychopathology in relation to psychosocial impairment across different domains (global functioning, inability to work, social functioning, suicidal ideation, history of suicide attempts, history of psychiatric hospitalization).

Results

All functioning indices were significantly associated with general psychopathology, but more complex levels provided significant incremental validity. The optimal level of complexity varied across functioning indices, suggesting that there is no single ‘best’ level for understanding relations between psychopathology and functioning.

Conclusions

Results support the hierarchical organization of psychopathology dimensions with regard to validity considerations and downstream implications for applied assessment. It would be fruitful to develop and implement measurement of these dimensions at the appropriate level for the purpose at hand. These findings can be used to guide HiTOP-consistent assessment in other research and clinical settings.

Keywords

hierarchical taxonomy of psychopathology (HiTOP)transdiagnosticquantitative psychopathologydimensional modelshierarchical modelsbass-ackwards analysisvalidityclinical utility
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 13 , October 2023 , pp. 6142 - 6149
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Authors.Google Scholar
Andrews, G., Goldberg, D. P., Krueger, R. F., Carpenter, W. T., Hyman, S. E., Sachdev, P., & Pine, D. S. (2009). Exploring the feasibility of a meta-structure for DSM-V and ICD-11: Could it improve utility and validity? Psychological Medicine, 39(12), 1993–2000. https://doi.org/10.1017/S0033291709990250.CrossRefGoogle ScholarPubMed
Andrews, G., Slade, T., & Issakidis, C. (2002). Deconstructing current comorbidity: Data from the Australian national survey of mental health and well-being. British Journal of Psychiatry, 181, 306–314. https://doi.org/10.1192/bjp.181.4.306.CrossRefGoogle ScholarPubMed
Bijl, R. V., van Zessen, G., Ravelli, A., de Rijk, C., & Langendoen, Y. (1998). The Netherlands mental health survey and incidence study (NEMESIS): Objectives and design. Social Psychiatry and Psychiatric Epidemiology, 33, 581–586. https://doi.org/10.1007/s001270050097.CrossRefGoogle ScholarPubMed
Carragher, N., Krueger, R. F., Eaton, N. R., & Slade, T. (2015). Disorders without borders: Current and future directions in the meta-structure of mental disorders. Social Psychiatry and Psychiatric Epidemiology, 50(3), 339–350. https://doi.org/10.1007/s00127-014-1004-z.CrossRefGoogle ScholarPubMed
Cicero, D. C., & Ruggero, C. J. (2021). Commentary– opening a can of worms: The importance of testing the measurement invariance of hierarchical models of psychopathology – a commentary on He and Li (2020). The Journal of Child Psychology and Psychiatry, 62(3), 299–302. https://doi.org/10.1111/jcpp.13353.CrossRefGoogle Scholar
Eaton, N. R., Rodriguez-Seijas, C., Carragher, N., & Krueger, R. F. (2015). Transdiagnostic factors of psychopathology and substance use disorders: A review. Social Psychiatry and Psychiatric Epidemiology, 50, 171–182. https://doi.org/10.1007/s00127-014-1001-2.CrossRefGoogle ScholarPubMed
Endicott, J., & Spitzer, R. L. (1978). A diagnostic interview: The schedule for affective disorders and schizophrenia. Archive of General Psychiatry, 35(7), 837–844. https://doi.org/10.1001/archpsyc.1978.01770310043002.CrossRefGoogle ScholarPubMed
First, M. B., Spitzer, R. L., Gibbon, M., & Williams, J. B. W. (1995). Structured clinical interview for DSM-IV axis I disorders – patient edition (SCID-I/P, version 2.0). New York: Biometrics Research Department, New York State Psychiatric Institute.Google Scholar
Forbes, M. K., Greene, A. L., Levin-Aspenson, H. F., Watts, A. L., Hallquist, M. N., Lahey, B. B., … Krueger, R. F. (2021a). Three recommendations based on a comparison of the reliability and validity of the predominant models used in research on the empirical structure of psychopathology. Journal of Abnormal Psychology, 130(3), 297–317. https://doi.org/10.1037/abn0000533.CrossRefGoogle ScholarPubMed
Forbes, M. K., Kotov, R., Ruggero, C. J., Watson, D., Zimmerman, M., & Krueger, R. F. (2017). Delineating the joint hierarchical structure of clinical and personality disorders in an outpatient psychiatric sample. Comprehensive Psychiatry, 79, 19–30. https://doi.org/10.1016/j.comppsych.2017.04.006.CrossRefGoogle Scholar
Forbes, M. K., Sunderland, M., Rapee, R. M., Batterham, P. J., Calear, A. L., Carragher, N., … Krueger, R. F. (2021b). A detailed hierarchical model of psychopathology: From individual symptoms up to the general factor of psychopathology. Clinical Psychological Science, 9(2), 139–168. https://doi.org/10.1177/2167702620954799.CrossRefGoogle ScholarPubMed
Forbush, K. T., Hagan, K. E., Kite, B. A., Chapa, D. A. N., Bohrer, B. K., & Gould, S. R. (2017). Understanding eating disorders within internalizing psychopathology: A novel transdiagnostic, hierarchical-dimensional model. Comprehensive Psychiatry, 79, 40–52. https://doi.org/10.1016/j.comppsych.2017.06.009.CrossRefGoogle ScholarPubMed
Goldberg, L. R. (2006). Doing it all bass-ackwards: The development of hierarchical factor structures from the top down. Journal of Research in Personality, 40(4), 347–358. https://doi.org/10.1016/j.jrp.2006.01.001.CrossRefGoogle Scholar
Grant, B. F., Stinson, F. S., Dawson, D. A., Chou, S. P., Dufour, M. C., Compton, W., … Kaplan, K. (2004). Prevalence and co-occurrence of substance use disorders and independent mood and anxiety disorders. Archives of General Psychiatry, 61(2), 807–816. https://doi.org/10.1001/archpsyc.61.8.807.CrossRefGoogle ScholarPubMed
Haslam, N., Holland, E., & Kuppens, P. (2012). Categories versus dimensions in personality and psychopathology: A quantitative review of taxometric research. Psychological Medicine, 42(5), 903–920. https://doi.org/10.1017/S0033291711001966.CrossRefGoogle ScholarPubMed
Kessler, R. C., Chiu, W. T., Demler, O., & Walters, E. E. (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62(6), 617–627. https://doi.org/10.1001/archpsyc.62.6.617.CrossRefGoogle ScholarPubMed
Kim, H., & Eaton, N. R. (2015). The hierarchical structure of common mental disorders: Connecting multiple levels of comorbidity, bifactor models, and predictive validity. Journal of Abnormal Psychology, 124(4), 1064–1078. https://doi.org/10.1037/abn0000113.CrossRefGoogle ScholarPubMed
Kotov, R., Foti, D., Li, K., Bromet, E. J., Hajcak, G., & Ruggero, C. J. (2016). Validating dimensions of psychosis symptomatology: Neural correlates and 20-year outcomes. Journal of Abnormal Psychology, 125(8), 1103–1119. https://doi.org/10.1037/abn0000188.CrossRefGoogle ScholarPubMed
Kotov, R., Krueger, R. F., Watson, D., Achenbach, T. M., Althoff, R. R., Bagby, R. M., … Zimmerman, M. (2017). The hierarchical taxonomy of psychopathology (HiTOP): A dimensional alternative to traditional nosologies. Journal of Abnormal Psychology, 126(4), 454–477. https://doi.org/10.1037/abn0000258.CrossRefGoogle ScholarPubMed
Kotov, R., Ruggero, C. J., Krueger, R. F., Watson, D., Yuan, Q., & Zimmerman, M. (2011). New dimensions in the quantitative classification of mental illness. Archives of General Psychiatry, 68(10), 1003–1011. https://doi.org/10.1001/archgenpsychiatry.2011.107.CrossRefGoogle ScholarPubMed
Krueger, R. F. (2005). Continuity of axes I and II: Toward a unified model of personality, personality disorders, and clinical disorders. Journal of Personality Disorders, 19(3), 233–261. https://doi.org/10.1521/pedi.2005.19.3.233.CrossRefGoogle Scholar
Krueger, R. F., Caspi, A., Moffitt, T. E., & Silva, P. A. (1998). The structure and stability of common mental disorders (DSM-III-R): A longitudinal-epidemiological study. Journal of Abnormal Psychology, 107(2), 216–227. https://doi.org/10.1037/0021-843X.107.2.216.CrossRefGoogle ScholarPubMed
Krueger, R. F., & Piasecki, T. M. (2002). Toward a dimensional and psychometrically-informed approach to conceptualizing psychopathology. Behaviour Research and Therapy, 40(5), 485–499. https://doi.org/10.1016/S0005-7967(02)00016-5.CrossRefGoogle Scholar
Langwerden, R. J., Thompson, M. G., & Wagner, E. F. (2021). Multidimensional conceptualization of identity and psychopathology: Assessing mental health disparities from an intersectional and dimensional framework. Personality and Mental Health, 15, 293–308. https://doi.org/10.1002/pmh.1519.CrossRefGoogle ScholarPubMed
Levin-Aspenson, H. F., Watson, D., Ellickson-Larew, S., Stanton, K., & Stasik-O'Brien, S. M. (2021). Beyond distress and fear: Differential psychopathology correlates of PTSD symptom clusters. Journal of Affective Disorders, 284(1), 9–17. https://doi.org/10.1016/j.jad.2021.01.090.CrossRefGoogle ScholarPubMed
Loehlin, J. C., & Goldberg, L. R. (2014). Do personality traits conform to lists or hierarchies? Personality and Individual Differences, 70, 51–56. https://doi.org/10.1016/j.paid.2014.06.018.CrossRefGoogle ScholarPubMed
Markon, K. E. (2015). Ontology, measurement, and other fundamental problems of scientific inference. Psychological Inquiry, 26(3), 259–262. https://doi.org/10.1080/1047840X.2015.1039921.CrossRefGoogle Scholar
Martin, E. A., Jonas, K. G., Lian, W., Foti, D., Donaldson, K. R., Bromet, E. J., & Kotov, R. (2021). Predicting long-term outcomes in first-admission psychosis: Does the hierarchical taxonomy of psychopathology aid DSM in prognostication? Schizophrenia Bulletin, 47(5), 1331–1341. https://doi.org/10.1093/schbul/sbab043.CrossRefGoogle ScholarPubMed
Michelini, G., Barch, D. M., Tian, Y., Watson, D., Klein, D. N., & Kotov, R. (2019). Delineating and validating higher-order dimensions of psychopathology in the adolescent brain cognitive development (ABCD) study. Translational Psychiatry, 9(1), 21–25. https://doi.org/10.1038/s41398-019-0593-4.CrossRefGoogle ScholarPubMed
Pfohl, B., Blum, N., & Zimmerman, M. (1997). Structured interview for DSM-IV personality. Washington, DC: American Psychiatric Press.Google Scholar
Revelle, W. (2022). Psych: Procedures for personality and psychological research. Evanston, IL, USA: Northwestern University. Retrieved from https://cran.r-project.org/package=psych.Google Scholar
Ringwald, W. R., Forbes, M. K., & Wright, A. G. C. (2021). Meta-analysis of structural evidence for the hierarchical taxonomy of psychopathology (HiTOP) model. Psychological Medicine, 1–14. https://doi.org/10.1017/S0033291721001902.CrossRefGoogle ScholarPubMed
Sanislow, C. A. (2016). Connecting psychopathology meta-structure and mechanisms. Journal of Abnormal Psychology, 125(8), 1158–1165. https://doi.org/10.1037/abn0000207.CrossRefGoogle ScholarPubMed
Widiger, T. A., & Samuel, D. B. (2005). Diagnostic categories or dimensions? A question for the diagnostic and statistical manual of mental disorders – fifth edition. Journal of Abnormal Psychology, 114(4), 494–504. https://doi.org/10.1037/0021-843X.114.4.494.CrossRefGoogle ScholarPubMed
Wright, A. G. C., Krueger, R. F., Hobbs, M. J., Markon, K. E., Eaton, N. R., & Slade, T. (2013). The structure of psychopathology: Toward an expanded quantitative empirical model. Journal of Abnormal Psychology, 122(1), 281–294. https://doi.org/10.1037/a0030133.CrossRefGoogle ScholarPubMed
Zald, D. H., & Lahey, B. B. (2017). Implications of the hierarchical structure of psychopathology for psychiatric neuroimaging. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2(4), 310–317. https://doi.org/10.1016/j.bpsc.2017.02.003.Google ScholarPubMed
Zimmerman, M. (2003). Integrating the assessment methods of researchers in routine clinical practice: The Rhode Island methods to improve diagnostic assessment and services (MIDAS) project. In First, M. B. (Ed.), Standardized evaluation in clinical practice (pp. 29–74). Arlington, VA: American Psychiatric Publishing.Google Scholar
Zimmerman, M. (2016). A review of 20 years of research on overdiagnosis and underdiagnosis in the Rhode Island methods to improve diagnostic assessment and services (MIDAS) project. Canadian Journal of Psychiatry, 61(2), 71–79. https://doi.org/10.1177/0706743715625935.CrossRefGoogle ScholarPubMed
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