Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-27T16:16:17.589Z Has data issue: false hasContentIssue false
  • English
  • Français

Evidence for the continuous latent structure of mania and depression in out-patients with bipolar disorder: results from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD)

Published online by Cambridge University Press:  17 April 2015

J. J. Prisciandaro  and
B. K. Tolliver
J. J. Prisciandaro*
Affiliation:
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
B. K. Tolliver
Affiliation:
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
*
* Address for correspondence: J. J. Prisciandaro, Psychiatry and Behavioral Sciences, Medical University of South Carolina, 67 President Street, PO Box 250861, Charleston, SC 29425, USA. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Evidence supporting the continuous latent structure of mood phenomena has not been incorporated into psychiatric diagnostic systems, in part because the evidence has been incomplete. For example, no studies have investigated the boundary between ‘sick’ and ‘well’ periods in individuals with bipolar disorder, despite agreement that characterization of mood disorders as having a discrete episodic course is inaccurate. The present study examined the validity of mood episode symptom thresholds in out-patients with bipolar disorder using multiple methodologies: taxometrics and information-theoretic latent distribution modeling (ITLDM), to evaluate the continuity/discontinuity of mood symptoms; and structural equation mixture modeling (SEMM), to evaluate the continuity/discontinuity of associations between mood symptoms and general functioning.

Method

A total of 3721 out-patients with bipolar disorder from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) were available for analysis. Data were collected at participants’ baseline STEP-BD visit. Taxometric [maximum covariance/means above minus below a cut (MAXCOV/MAMBAC) with simulated comparison data], ITLDM and SEMM methods were applied twice, once to the Montgomery–Åsberg Depression Rating Scale and again to the Young Mania Rating Scale.

Results

Taxometric results unequivocally supported a continuous interpretation of the data. ITLDM results favored many valued ‘discrete metrical’ models, suggesting that mood symptoms have continuous, but potentially non-normally distributed, latent structures in out-patients with bipolar disorder. Finally, SEMM results demonstrated that latent associations between mood symptoms and general functioning were linear.

Conclusions

Results from the present study argue against the validity of DSM mood episode thresholds and argue for a graded continuum of care of bipolar symptom management.

Keywords

Bipolar disordercategorical assessmentdepressiondimensional assessmentmaniataxometrics
Type
Original Articles
Information
Psychological Medicine , Volume 45 , Issue 12 , September 2015 , pp. 2595 - 2603
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

Ahmed, AO, Green, BA, Clark, CB, Stahl, KC, Mcfarland, ME (2011). Latent structure of unipolar and bipolar mood symptoms. Bipolar Disorders 13, 522–536.CrossRefGoogle ScholarPubMed
Altshuler, LL, Gitlin, MJ, Mintz, J, Leight, KL, Frye, MA (2002). Subsyndromal depression is associated with functional impairment in patients with bipolar disorder. Journal of Clinical Psychiatry 63, 807–811.CrossRefGoogle ScholarPubMed
American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders, 4th ed., text rev. American Psychiatric Association: Washington, DC.Google Scholar
American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). American Psychiatric Association: Washington, DC.Google Scholar
Angst, J, Gamma, A, Bowden, CL, Azorin, JM, Perugi, G, Vieta, E, Young, AH (2012). Diagnostic criteria for bipolarity based on an international sample of 5635 patients with DSM-IV major depressive episodes. European Archives of Psychiatry and Clinical Neuroscience 262, 3–11.CrossRefGoogle Scholar
Basco, MR, Rush, AJ (2005). Cognitive–Behavioral Therapy for Bipolar Disorder. Guilford Press: New York.Google Scholar
Bauer, DJ (2005). A semiparametric approach to modeling nonlinear relations among latent variables. Structural Equation Modeling 12, 513–535.CrossRefGoogle Scholar
Bonnin, CM, Sanchez-Moreno, J, Martinez-Aran, A, Sole, B, Reinares, M, Rosa, AR, Goikolea, JM, Benabarre, A, Ayuso-Mateos, JL, Ferrer, M, Vieta, E, Torrent, C (2012). Subthreshold symptoms in bipolar disorder: impact on neurocognition, quality of life and disability. Journal of Affective Disorders 136, 650–659.CrossRefGoogle ScholarPubMed
Cassidy, F, Forest, K, Murry, E, Carroll, BJ (1998). A factor analysis of the signs and symptoms of mania. Archives of General Psychiatry 55, 27–32.Google Scholar
Cohen, J (1983). The cost of dichotomization. Applied Psychological Measurement 7, 249–253.CrossRefGoogle Scholar
Cuthbert, BN (2014). The RDoC framework: facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry 13, 28–35.Google Scholar
Endicott, J, Nee, J, Harrison, W, Blumenthal, R (1993). Quality of Life Enjoyment and Satisfaction Questionnaire: a new measure. Psychopharmacology Bulletin 29, 321–326.Google Scholar
First, MB (1998). Structured Clinical Interview for DSM-IV Axis I Disorders: Patient Edition (February 1996 Final), SCID-I/P. Biometrics Research Department, New York State Psychiatric Institute: New York, NY.Google Scholar
Flett, GL, Vredenburg, K, Krames, L (1997). The continuity of depression in clinical and nonclinical samples. Psychological Bulletin 121, 395–416.Google Scholar
Hu, L, Bentler, PM (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling 6, 1–55.CrossRefGoogle Scholar
Judd, LL, Akiskal, HS (2003). The prevalence and disability of bipolar spectrum disorders in the US population: re-analysis of the ECA database taking into account subthreshold cases. Journal of Affective Disorders 73, 123–131.CrossRefGoogle ScholarPubMed
Kessler, RC (2002). The categorical versus dimensional assessment controversy in the sociology of mental illness. Journal of Health and Social Behavior 43, 171–188.Google Scholar
Langeheine, R, Van de Pol, F (2002). Latent Markov chains. In Applied Latent Class Analysis (ed. Hagenaars, J. A. and McCutcheon, A. L.), pp. 304–344. Cambridge University Press: Cambridge, UK.Google Scholar
Leon, AC, Solomon, DA, Mueller, TI, Turvey, CL, Endicott, J, Keller, MB (1999). The Range of Impaired Functioning Tool (LIFE-RIFT): a brief measure of functional impairment. Psychological Medicine 29, 869–878.Google Scholar
Markon, KE (2010). How things fall apart: understanding the nature of internalizing through its relationship with impairment. Journal of Abnormal Psychology 119, 447–458.Google Scholar
Markon, KE, Krueger, RF (2006). Information-theoretic latent distribution modeling: distinguishing discrete and continuous latent variable models. Psychological Methods 11, 228–243.CrossRefGoogle ScholarPubMed
Meehl, PE (1995). Bootstraps taxometrics. Solving the classification problem in psychopathology. American Psychologist 50, 266–275.Google Scholar
Meehl, PE, Yonce, LJ (1994). Taxometric analysis: I. Detecting taxonicity with two quantitative indicators using means above and below a sliding cut (MAMBAC procedure). Psychological Reports 74, 1059–1274.Google Scholar
Meehl, PE, Yonce, LJ (1996). Taxometric analysis: II. Detecting taxonicity using covariance of two quantitative indicators in successive intervals of a third indicator (MAXCOV procedure). Psychological Reports 78, 1091–1227.CrossRefGoogle Scholar
Montgomery, SA, Åsberg, M (1979). A new depression scale designed to be sensitive to change. British Journal of Psychiatry 134, 382–389.CrossRefGoogle ScholarPubMed
Muthén, B, Muthén, LK (2000). Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and Experimental Research 24, 882–891.CrossRefGoogle ScholarPubMed
Muthén, BO (1989). Dichtomous factor analysis of symptom data. Sociological Methods and Research 18, 19–65.CrossRefGoogle Scholar
Muthén, LK, Muthén, BO (2011). Mplus User's Guide, 6th edn. Muthén & Muthén: Los Angeles, CA.Google Scholar
Prisciandaro, JJ, Roberts, JE (2005). A taxometric investigation of unipolar depression in the National Comorbidity Survey. Journal of Abnormal Psychology 114, 718–728.Google Scholar
Prisciandaro, JJ, Roberts, JE (2011). Evidence for the continuous latent structure of mania in the Epidemiologic Catchment Area from multiple latent structure and construct validation methodologies. Psychological Medicine 41, 575–588.CrossRefGoogle ScholarPubMed
R Core Team (2011). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria.Google Scholar
Ruscio, J (2009). Assigning cases to groups using taxometric results: an empirical comparison of classification techniques. Assessment 16, 55–70.Google Scholar
Ruscio, J, Haslam, N, Ruscio, AM (2006). Introduction to the Taxometric Method: A Practical Guide. Erlbaum: Mahwah, NJ.Google Scholar
Ruscio, J, Kaczetow, W (2008). Simulating multivariate nonnormal data using an iterative technique. Multivariate Behavioral Research 43, 355–381.Google Scholar
Ruscio, J, Ruscio, AM (2000). Informing the continuity controversy: a taxometric analysis of depression. Journal of Abnormal Psychology 109, 473–487.Google Scholar
Ruscio, J, Ruscio, AM, Keane, TM (2004). Using taxometric analysis to distinguish a small latent taxon from a latent dimension with positively skewed indicators: the case of involuntary defeat syndrome. Journal of Abnormal Psychology 113, 145–154.CrossRefGoogle ScholarPubMed
Ruscio, J, Walters, GD, Marcus, DK, Kaczetow, W (2010). Comparing the relative fit of categorical and dimensional latent variable models using consistency tests. Psychological Assessment 22, 5–21.Google Scholar
Ruscio, J, Zimmerman, M, McGlinchey, JB, Chelminski, I, Young, D (2007). Diagnosing major depressive disorder XI: a taxometric investigation of the structure underlying DSM-IV symptoms. Journal of Nervous and Mental Disease 195, 10–19.Google Scholar
Sachs, GS, Thase, ME, Otto, MW, Bauer, M, Miklowitz, D, Wisniewski, SR, Lavori, P, Lebowitz, B, Rudorfer, M, Frank, E, Nierenberg, AA, Fava, M, Bowden, C, Ketter, T, Marangell, L, Calabrese, J, Kupfer, D, Rosenbaum, JF (2003). Rationale, design, and methods of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Biological Psychiatry 53, 1028–1042.Google Scholar
Schwarz, G (1978). Estimating the dimension of a model. Annals of Statistics 6, 461–464.Google Scholar
Sclove, SL (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika 52, 333–343.CrossRefGoogle Scholar
Sheehan, DV, Lecrubier, Y, Sheehan, KH, Amorim, P, Janavs, J, Weiller, E, Hergueta, T, Baker, R, Dunbar, GC (1998). The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry 59 (Suppl. 20), 22–33; quiz 34–57.Google Scholar
Solomon, A, Ruscio, J, Seeley, JR, Lewinsohn, PM (2006). A taxometric investigation of unipolar depression in a large community sample. Psychological Medicine 36, 973–985.CrossRefGoogle Scholar
Walters, GD, Ruscio, J (2010). Where do we draw the line? Assigning cases to subsamples for MAMBAC, MAXCOV, and MAXEIG taxometric analyses. Assessment 17, 321–333.Google Scholar
Young, RC, Biggs, JT, Ziegler, VE, Meyer, DA (1978). A rating scale for mania: reliability, validity and sensitivity. British Journal of Psychiatry 133, 429–435.CrossRefGoogle ScholarPubMed