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The structure of depression, anxiety and somatic symptoms in primary care

Published online by Cambridge University Press:  20 June 2011

L. J. Simms ,
J. J. Prisciandaro ,
R. F. Krueger  and
D. P. Goldberg
L. J. Simms*
Affiliation:
University at Buffalo, The State University of New York, Buffalo, New York, USA
J. J. Prisciandaro
Affiliation:
Medical University of South Carolina, Charleston, SC, USA
R. F. Krueger
Affiliation:
University of Minnesota – Twin Cities, Minneapolis, MN, USA
D. P. Goldberg
Affiliation:
Institute of Psychiatry, King's College London, UK
*
*Address for correspondence: Dr L. J. Simms, Department of Psychology, Park Hall 218, University at Buffalo, The State University of New York, Buffalo, NY 14221, USA. (Email: [email protected])
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Abstract

Background

Observed co-morbidity among the mood and anxiety disorders has led to the development of increasingly sophisticated dimensional models to represent the common and unique features of these disorders. Patients often present to primary care settings with a complex mixture of anxiety, depression and somatic symptoms. However, relatively little is known about how somatic symptoms fit into existing dimensional models.

Method

We examined the structure of 91 anxiety, depression and somatic symptoms in a sample of 5433 primary care patients drawn from 14 countries. One-, two- and three-factor lower-order models were considered; higher-order and hierarchical variants were studied for the best-fitting lower-order model.

Results

A hierarchical, bifactor model with all symptoms loading simultaneously on a general factor, along with one of three specific anxiety, depression and somatic factors, was the best-fitting model. The general factor accounted for the bulk of symptom variance and was associated with psychosocial dysfunction. Specific depression and somatic symptom factors accounted for meaningful incremental variance in diagnosis and dysfunction, whereas anxiety variance was associated primarily with the general factor.

Conclusions

The results (a) are consistent with previous studies showing the presence and importance of a broad internalizing or distress factor linking diverse emotional disorders, and (b) extend the bounds of internalizing to include somatic complaints with non-physical etiologies.

Keywords

Anxietybifactor modeldepressiondiagnosissomatization
Type
Original Articles
Information
Psychological Medicine , Volume 42 , Issue 1 , January 2012 , pp. 15 - 28
Copyright
Copyright © Cambridge University Press 2011

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References

APA (1987). Diagnostic and Statistical Manual of Mental Disorders (3rd edn, rev.). American Psychiatric Association: Washington, DC.Google Scholar
Brown, TA, Chorpita, BF, Barlow, DH (1998). Structural relationships among dimensions of the DSM-IV anxiety and mood disorders and dimensions of negative affect, positive affect, and autonomic arousal. Journal of Abnormal Psychology 107, 179–192.CrossRefGoogle ScholarPubMed
Clark, LA, Watson, D (1991). Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. Journal of Abnormal Psychology 100, 316–336.CrossRefGoogle ScholarPubMed
Dimsdale, JE, Xin, Y, Kleinman, A, Patel, V, Narrow, WE, Sirvatka, PJ, Regier, DA (2009). Somatic Presentations of Mental Disorders: Refining the Research Agenda for DSM-5. American Psychiatric Association: Arlington, VA.Google Scholar
Gibbons, RD, Bock, RD, Hedeker, D, Weiss, DJ, Segawa, E, Bhaumik, DK, Kupfer, DJ, Frank, E, Grochocinski, VJ, Stover, A (2007). Full-information item bifactor analysis of graded response data. Applied Psychological Measurement 31, 4–19.CrossRefGoogle Scholar
Goldberg, DP, Goodyer, I (2005). The Origins and Course of Common Mental Disorders. Routledge: London.Google Scholar
Goldberg, DP, Kendler, KS, Sirovatka, PJ, Regier, DA (2010). Diagnostic Issues in Depression and Generalized Anxiety Disorder: Refining the Research Agenda for DSM-5. American Psychiatric Association: Arlington, VA.Google Scholar
Goldberg, DP, Krueger, RF, Andrews, G, Hobbs, MJ (2009). Emotional disorders: Cluster 4 of the proposed meta-structure for DSM-5 and ICD-11. Psychological Medicine 39, 2043–2059.CrossRefGoogle ScholarPubMed
Goldberg, DP, Williams, P (1988). A User's Guide to the General Health Questionnaire. NFER-Nelson: Windsor, UK.Google Scholar
Griffith, JW, Zinbarg, RE, Craske, MG, Mineka, S, Rose, RD, Waters, AM, Sutton, JM (2010). Neuroticism as a common dimension in the internalizing disorders. Psychological Medicine 40, 1125–1136.Google Scholar
Helzer, JE, Kraemer, HC, Krueger, RF (2006). The feasibility and need for dimensional psychiatric diagnoses. Psychological Medicine 36, 1671–1680.Google Scholar
Hettema, JM, Neale, MC, Myers, JM, Prescott, CA, Kendler, KS (2006). A population-based twin study of the relationship between neuroticism and internalizing disorders. American Journal of Psychiatry 163, 857–864.Google Scholar
Kessler, RC, Chiu, WT, Demler, O, Walters, EE (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62, 617–627.CrossRefGoogle ScholarPubMed
Kroenke, K (2003). Patients presenting with somatic complaints: epidemiology, psychiatric comorbidity, and management. International Journal of Methods in Psychiatric Research 12, 34–43.CrossRefGoogle ScholarPubMed
Krueger, RF, Chentsova-Dutton, YE, Markon, KE, Goldberg, DP, Ormel, J (2003). A cross-cultural study of the structure of comorbidity among common psychopathological syndromes in the general health care setting. Journal of Abnormal Psychology 112, 437–447.Google Scholar
Krueger, RF, Finger, MS (2001). Using item response theory to understand comorbidity among anxiety and unipolar mood disorders. Psychological Assessment 13, 140–151.CrossRefGoogle ScholarPubMed
Kupfer, DJ (2005). Dimensional models for research and diagnosis: a current dilemma. Journal of Abnormal Psychology 114, 557–559.CrossRefGoogle ScholarPubMed
Lambert, SF, McCreary, BT, Joiner, TE, Schmidt, NB, Ialongo, NS (2004). Structure of anxiety and depression in urban youth: an examination of the tripartite model. Journal of Consulting and Clinical Psychology 72, 904–908.CrossRefGoogle ScholarPubMed
Longley, SL, Watson, D, Noyes, R (2005). Assessment of the hypochondriasis domain: the Multidimensional Inventory of Hypochondriacal Traits (MIHT). Psychological Assessment 17, 3–14.CrossRefGoogle ScholarPubMed
Löwe, B, Spitzer, RL, Williams, JBW, Mussell, M, Schellberg, D, Kroenke, K (2008). Depression, anxiety and somatization in primary care: syndrome overlap and functional impairment. General Hospital Psychiatry 30, 191–199.Google Scholar
Mayou, R, Kirmayer, LJ, Simon, G, Kroenke Sharpe, M (2005). Somatoform disorders: time for a new approach in DSM-5. American Journal of Psychiatry 162, 847–855.CrossRefGoogle Scholar
McGlinchey, JB, Zimmerman, M (2007). Examining a dimensional representation of depression and anxiety disorders' comorbidity in psychiatric outpatients with item response modeling. Journal of Abnormal Psychology 116, 464–474.CrossRefGoogle ScholarPubMed
Mineka, S, Watson, D, Clark, LA (1998). Comorbidity of anxiety and unipolar mood disorders. Annual Review of Psychology 49, 377–412.CrossRefGoogle ScholarPubMed
Muthén, BO, Muthén, LK (2006). IRT in Mplus. (www.statmodel.com/download/MplusIRT1.pdf). Accessed 16 August 2010.Google Scholar
Muthén, LK, Muthén, BO (2009). Mplus User's Guide. Fifth Edition. Muthén & Muthén: Los Angeles, CA.Google Scholar
Noyes, R, Watson, DB, Letuchy, EM, Longley, SL, Black, DW, Carney, CP, Doebbeling, BN (2005). Relationship between hypochondriacal concerns and personality dimensions and traits in a military population. Journal of Nervous and Mental Disease 193, 110–118.Google Scholar
Ormel, J, VonKorff, M, Üstün, B, Pini, S, Korten, A, Oldehinkel, T (1994). Common mental disorders and disability across cultures: results from the WHO Collaborative Study on Psychological Problems in General Health Care. Journal of the American Medical Association 272, 1741–1748.CrossRefGoogle Scholar
Phillips, BM, Lonigan, CJ, Driscoll, K, Hooe, ES (2002). Positive and negative affectivity in children: a multitrait-multimethod investigation. Journal of Clinical Child and Adolescent Psychology 31, 465–479.CrossRefGoogle ScholarPubMed
Piccinelli, M, Rucci, P, Üstün, B, Simon, G (1999). Typologies of anxiety, depression and somatization symptoms among primary care attenders with no formal mental disorder. Psychological Medicine 29, 677–688.CrossRefGoogle ScholarPubMed
Raftery, AE (1995). Bayesian model selection in social research. Sociological Methodology 25, 111–196.Google Scholar
Regier, DA, Goldberg, ID, Taube, CA (1978). The de facto US mental health services system: a public health perspective. Archives of General Psychiatry 35, 685–693.CrossRefGoogle Scholar
Regier, DA, Narrow, WE, Rae, DS, Manderscheid, RW, Locke, BZ, Goodwin, FK (1993). The de facto US mental and addictive disorders service system. Epidemiologic catchment area prospective 1-year prevalence rates of disorders and services. Archives of General Psychiatry 50, 85–94.CrossRefGoogle Scholar
Reise, SP, Morizot, J, Hays, RD (2007). The role of the bifactor model in resolving dimensionality issues in health outcomes measures. Quality of Life Research 16 (Suppl. 1), 19–31.CrossRefGoogle ScholarPubMed
Sartorius, N, Üstün, TB, Costa e Silva, JA, Goldberg, D, Lecrubier, Y, Ormel, J, Von Korff, M, Wittchen, HU (1993). An international study of psychological problems in primary care. Preliminary report from the World Health Organization Collaborative Project on ‘Psychological Problems in General Health Care’. Archives of General Psychiatry 50, 819–824.CrossRefGoogle Scholar
Simms, LJ, Grös, DF, Watson, D, O'Hara, MW (2008). Parsing the general and specific components of depression and anxiety with bifactor modeling. Depression and Anxiety 25, E34–E46.CrossRefGoogle ScholarPubMed
Üstün, B, Sartorius, N (1995). Mental Illness in General Health Care. An International Study. Wiley: London.Google Scholar
VonKorff, M, Üstün, TB, Ormel, J, Kaplan, I, Simon, GE (1996). Self report disability in an international primary care study of psychological illness. Journal of Clinical Epidemiology 49, 297–303.CrossRefGoogle Scholar
Watson, D (2005). Rethinking the mood and anxiety disorders: a quantitative hierarchical model for DSM-5. Journal of Abnormal Psychology 114, 522–536.CrossRefGoogle Scholar
Watson, D, Clark, LA, Weber, K, Assenheimer, JS, Strauss, ME, McCormick, RA (1995 a). Testing a tripartite model: II. Exploring the symptom structure of anxiety and depression in student, adult, and patient samples. Journal of Abnormal Psychology 104, 15–25.CrossRefGoogle ScholarPubMed
Watson, D, Weber, K, Assenheimer, JS, Clark, LA, Strauss, ME, McCormick, RA (1995 b). Testing a tripartite model: I. Evaluating the convergent and discriminant validity of anxiety and depression symptom scales. Journal of Abnormal Psychology 104, 3–14.CrossRefGoogle ScholarPubMed
Wiersma, D, DeJong, A, Ormel, J (1988). The Groningen Social Disability Schedule: development, relationship with ICIDH, and psychometric properties. International Journal of Rehabilitation Research 11, 213–224.CrossRefGoogle ScholarPubMed
Zinbarg, RE, Barlow, DH (1996). Structure of anxiety and the anxiety disorders: a hierarchical model. Journal of Abnormal Psychology 105, 181–193.Google Scholar