Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-23T06:19:16.637Z Has data issue: false hasContentIssue false
  • English
  • Français

Examining the shared and unique relationships among substance use and mental disorders

Published online by Cambridge University Press:  17 September 2014

M. Sunderland ,
T. Slade  and
R. F. Krueger
M. Sunderland*
Affiliation:
NHMRC Centre for Research Excellence in Mental Health and Substance Use, National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia
T. Slade
Affiliation:
NHMRC Centre for Research Excellence in Mental Health and Substance Use, National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia
R. F. Krueger
Affiliation:
Department of Psychology, University of Minnesota, Minneapolis, MN, USA
*
*Address for correspondence: Dr M. Sunderland, Centre for Research Excellence in Mental Health and Substance Use, National Drug and Alcohol Research Centre, Randwick Campus, University of New South Wales, Sydney, NSW 2052, Australia. (Email: matthews@unsw.edu.au)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background.

Co-morbidity among use of different substances can be explained by a shared underlying dimensional factor. What remains unknown is whether the relationship between substance use and various co-morbid mental disorders can be explained solely by the general factor or whether there remain unique contributions of specific substances.

Method.

Data were from the 2007 Australian National Survey of Mental Health and Wellbeing (NSMHWB). A unidimensional latent factor was constructed that represented general substance use. The shared and specific relationships between lifetime substance use indicators and internalizing disorders, suicidality and psychotic-like experiences (PLEs) were examined using Multiple Indicators Multiple Causes (MIMIC) models in the total sample. Additional analyses then examined the shared and specific relationships associated with substance dependence diagnoses as indicators of the latent trait focusing on a subsample of substance users.

Results.

General levels of latent substance use were significantly and positively related to internalizing disorders, suicidality and psychotic-like experiences. Similar results were found when examining general levels of latent substance dependence in a sample of substance users. There were several direct effects between specific substance use/dependence indicators and the mental health correlates that significantly improved the overall model fit but they were small in magnitude and had relatively little impact on the general relationship.

Conclusions.

The majority of pairwise co-morbid relationships between substance use/dependence and mental health correlates can be explained through a general latent factor. Researchers should focus on investigating the commonalities across all substance use and dependence indicators when studying mental health co-morbidity.

Keywords

Co-morbiditydimensionsmental disordersMIMIC modelssubstance use disorders
Type
Original Articles
Information
Psychological Medicine , Volume 45 , Issue 5 , April 2015 , pp. 1103 - 1113
Copyright
Copyright © Cambridge University Press 2014 

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

Andrews, G, Goldberg, D, Krueger, R, Carpenter, W, Hyman, S, Sachdev, P, Pine, D (2009). Exploring the feasibility of a meta-structure for DSM-V and ICD-11: could it improve utility and validity? Psychological Medicine 39, 1993–2000.Google Scholar
Andrews, G, Issakidis, C, Slade, T (2003). How common is comorbidity? In Comorbid Mental Disorders and Substance Use Disorders: Epidemiology, Prevention, and Treatment (ed. Teesson, M. and Proudfoot, H.), pp. 26–41. Department of Health and Ageing: Canberra, ACT.Google Scholar
APA (2013). Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. American Psychiatric Association: Arlington, VA.Google Scholar
Bolton, J, Cox, B, Clara, I, Sareen, J (2006). Use of alcohol and drugs to self-medicate anxiety disorders in a nationally representative sample. Journal of Nervous and Mental Disease 194, 818–825.Google Scholar
Brown, TA, Barlow, DH (2005). Dimensional versus categorical classification of mental disorder in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders and beyond: comment on the special section. Journal of Abnormal Psychology 114, 551–556.Google Scholar
Brown, TA, Barlow, DH (2009). A proposal for a dimensional classification system based on the shared features of the DSM-IV anxiety and mood disorders: implications for assessment and treatment. Psychological Assessment 21, 256–271.Google Scholar
Burnham, KP, Anderson, DR (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd edn. Springer-Verlag: New York, NY.Google Scholar
Derringer, J, Krueger, RF, Dick, DM, Agrawal, A, Bucholz, KK, Foroud, T, Grucza, RA, Hesselbrock, MN, Hesselbrock, V, Kramer, J, Nurnberger, JI, Schuckit, M, Bierut, LJ, Iacono, WG, McGue, M (2013). Measurement invariance of DSM-IV alcohol, marijuana and cocaine dependence between community-sampled and clinically overselected studies. Addiction 108, 1767–1776.CrossRefGoogle ScholarPubMed
Dickey, B, Azeni, H (1996). Persons with dual diagnoses of substance abuse and major mental illness: their excess costs of psychiatric care. American Journal of Public Health 86, 973–977.Google Scholar
Dickey, B, Dembling, B, Azeni, H, Normand, S-L (2004). Externally caused deaths for adults with substance use and mental disorders. Journal of Behavioral Health Services and Research 31, 75–85.Google Scholar
Eaton, NR, Krueger, RF, Markon, KE, Keyes, KM, Skodol, AE, Wall, M, Hasin, DS, Grant, BF (2013). The structure and predictive validity of the internalizing disorders. Journal of Abnormal Psychology 122, 86–92.Google Scholar
Gallo, JJ, Anthony, JC, Muthén, BO (1994). Age differences in the symptoms of depression: a latent trait analysis. Journal of Gerontology 49, P251–P264.Google Scholar
Hall, W, Degenhardt, L, Teesson, M (2009). Understanding comorbidity between substance use, anxiety and affective disorders: broadening the research base. Addictive Behaviors 34, 526–530.Google Scholar
Hall, W, Teesson, M, Lynskey, M, Degenhardt, L (1999). The 12-month prevalence of substance use and ICD-10 substance use disorders in Australian adults: findings from the National Survey of Mental Health and Well-Being. Addiction 94, 1541–1550.CrossRefGoogle ScholarPubMed
Hesse, M (2009). Integrated psychological treatment for substance use and co-morbid anxiety or depression vs. treatment for substance use alone. A systematic review of the published literature. BMC Psychiatry 9, 6.Google Scholar
Hu, LT, Bentler, PM (1998). Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychological Methods 3, 424–453.Google Scholar
Kavanagh, DJ, Mueser, KT, Baker, A (2003). Management of comorbidity. In Comorbid Mental Disorders and Substance Use Disorders: Epidemiology, Prevention, and Treatment (ed. Teesson, M. and Proudfoot, H.), pp. 78–120. Department of Health and Ageing: Canberra, ACT.Google Scholar
Kelly, TM, Daley, DC, Douaihy, AB (2012). Treatment of substance abusing patients with comorbid psychiatric disorders. Addictive Behaviors 37, 11–24.Google Scholar
Kendler, KS, Prescott, CA, Myers, J, Neale, MC (2003). The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Archives of General Psychiatry 60, 929–937.Google Scholar
Kessler, RC, Abelson, J, Demler, O, Escobar, JI, Gibbon, M, Guyer, ME, Howes, MJ, Jin, R, Vega, WA, Walters, EE, Wang, P, Zaslavsky, A, Zheng, H (2004). Clinical calibration of DSM-IV diagnoses in the World Mental Health (WMH) version of the World Health Organization (WHO) Composite International Diagnostic Interview (WMH-CIDI). International Journal of Methods in Psychiatric Research 13, 122–139.Google Scholar
Kessler, RC, Cox, BJ, Green, JG, Ormel, J, McLaughlin, KA, Merikangas, KR, Petukhova, M, Pine, DS, Russo, LJ, Swendsen, J, Wittchen, HU, Zaslavsky, AM (2011 a). The effects of latent variables in the development of comorbidity among common mental disorders. Depression and Anxiety 28, 29–39.CrossRefGoogle ScholarPubMed
Kessler, RC, Ormel, J, Petukhova, M, McLaughlin, KA, Green, JG, Russo, LJ, Stein, DJ, Zaslavsky, AM, Anguilar-Gaxiola, S, Alonso, J, Andrade, L, Benjet, C, de Girolamo, G, de Graaf, R, Demyttenaere, K, Fayyad, J, Haro, JM, Hu, CY, Karam, A, Lee, S, Lepine, J-P, Matchsinger, H, Mihaescu-Pintia, C, Posada-Villa, J, Sagar, R, Ustün, TB (2011 b). Development of lifetime comorbidity in the World Health Organization world mental health surveys. Archives of General Psychiatry 68, 90–100.Google Scholar
Kessler, RC, Ustün, TB (2004). The World Mental Health (WMH) Survey Initiative Version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI). International Journal of Methods in Psychiatric Research 13, 93–121.Google Scholar
Krueger, RF (1999). The structure of common mental disorders. Archives of General Psychiatry 56, 921–926.Google Scholar
Krueger, RF, Finger, MS (2001). Using item response theory to understand comorbidity among anxiety and unipolar mood disorder. Psychological Assessment 13, 140–151.Google Scholar
Krueger, RF, Markon, KE (2006). Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annual Reviews in Clinical Psychology 2, 111–133.CrossRefGoogle ScholarPubMed
Krueger, RF, Markon, KE, Patrick, CJ, Benning, SD, Kramer, MD (2007). Linking antisocial behaviour, substance use, and personality: an integrative quantitative model of the adult externalizing spectrum. Journal of Abnormal Psychology 116, 645–666.Google Scholar
Krueger, RF, Markon, KE, Patrick, CJ, Iacono, WG (2005). Externalizing psychopathology in adulthood: a dimensional-spectrum conceptualization and its implication for DSM-V. Journal of Abnormal Psychology 114, 537–550.Google Scholar
Krueger, RF, McGue, M, Iacono, WG (2001). The higher-order structure of common DSM mental disorders: internalization, externalization, and their connections to personality. Personality and Individual Differences 30, 1245–1259.Google Scholar
Krueger, RF, South, S (2009). Externalizing disorders: cluster 5 of the proposed meta-structure for DSM-V and ICD-11. Psychological Medicine 39, 2061–2070.CrossRefGoogle ScholarPubMed
Kushner, MG, Wall, MM, Krueger, RF, Sher, KJ, Maurer, E, Thuras, P, Lee, S (2012). Alcohol dependence is related to overall internalizing psychopathology load rather than to particular internalizing disorders: evidence from a national sample. Alcoholism, Clinical and Experimental Research 36, 325–331.CrossRefGoogle ScholarPubMed
Markon, KE, Chmielewski, M, Miller, CJ (2011). The reliability and validity of discrete and continuous measures of psychopathology: a quantitative review. Psychological Bulletin 137, 856–879.Google Scholar
Muthén, LK, Muthén, BO (2010). Mplus User's Guide. Muthén & Muthén: Los Angeles, CA.Google Scholar
Myrick, H, Brady, K (2003). Current review of the comorbidity of affective, anxiety, and substance use disorders. Current Opinion in Psychiatry 16, 261–270.CrossRefGoogle Scholar
Patrick, CJ, Kramer, MD, Krueger, RF, Markon, KE (2013). Optimizing efficiency of psychopathology assessment through quantitative modelling: development of a brief form of the Externalizing Spectrum Inventory. Psychological Assessment 25, 1332–1348.Google Scholar
Proudfoot, H, Teesson, M, Brewin, E, Gournay, K (2003). Comorbidity and delivery of services. In Comorbid Mental Disorders and Substance Use Disorders: Epidemiology, Prevention, and Treatment (ed. Teesson, M. and Proudfood, H.), pp. 121–142. Department of Health and Ageing: Canberra, ACT.Google Scholar
Robinson, J, Sareen, J, Cox, BJ, Bolton, J (2009). Self-medication of anxiety disorders with alcohol and drugs: results from a nationally representative sample. Journal of Anxiety Disorders 23, 38–45.Google Scholar
Saha, S, Scott, J, Varghese, D, McGrath, J (2011). The association between general psychological distress and delusional-like experiences: a large population-based study. Schizophrenia Research 127, 246–251.Google Scholar
Schäfer, I, Eiroa-Orosa, FJ, Verthein, U, Dilg, C, Haasen, C, Reimer, J (2010). Effects of psychiatric comorbidity on treatment outcome in patients undergoing diamorphine or methadone maintenance treatment. Psychopathology 43, 88–95.Google Scholar
Scott, J, Chant, D, Andrews, G, Martin, G, McGrath, J (2007). Association between trauma exposure and delusional experiences in a large community-based sample. British Journal of Psychiatry 190, 339–343.Google Scholar
Slade, T, Johnston, A, Oakley Browne, MA, Andrews, G, Whiteford, H (2009). 2007 National Survey of Mental Health and Wellbeing: methods and key findings. Australian and New Zealand Journal of Psychiatry 43, 594–605.CrossRefGoogle ScholarPubMed
Slade, T, Watson, D (2006). The structure of common DSM-IV and ICD-10 mental disorders in the Australian general population. Psychological Medicine 36, 1593–1600.Google Scholar
Stinson, FS, Grant, BF, Dawson, DA, Ruan, WJ, Huang, B, Saha, T (2005). Comorbidity between DSM-IV alcohol and specific drug use disorders in the United States: results from the National Epidemiological Survey on Alcohol and Related Conditions. Drug and Alcohol Dependence 80, 105–116.Google Scholar
Swendsen, J, Conway, KP, Degenhardt, L, Glantz, M, Jin, R, Merikangas, KR, Sampson, N, Kessler, RC (2010). Mental disorders as risk factors for substance use, abuse and dependence: results from the 10-year follow-up of the National Comorbidity Survey. Addiction 105, 1117–1128.Google Scholar
Teesson, M, Proudfoot, H (2003). Responding to comorbid mental disorders and substance use disorders. In Comorbid Mental Disorders and Substance Use Disorders: Epidemiology, Prevention, and Treatment (ed. Teesson, M. and Proudfoot, H.), pp. 1–8. Department of Health and Ageing: Canberra, ACT.Google Scholar
Teesson, M, Slade, T, Mills, K (2009). Comorbidity in Australia: findings of the 2007 National Survey of Mental Health and Wellbeing. Australian and New Zealand Journal of Psychiatry 43, 606–614.Google Scholar
Woods, CM (2009). Evaluation of MIMIC-model methods for DIF testing with comparison to two-group analysis. Multivariate Behavioral Research 44, 1–27.Google Scholar
Woods, CM, Oltmanns, TF, Turkheimer, E (2009). Illustration of MIMIC-model DIF testing with the Schedule for Nonadaptive and Adaptive Personality. Journal of Psychopathology and Behavioural Assessment 31, 320–330.Google Scholar
Wright, AG, Krueger, RF, Hobbs, MJ, Markon, KE, Eaton, NR, Slade, T (2013). The structure of psychopathology: toward an expanded quantitative empirical model. Journal of Abnormal Psychology 122, 281–294.Google Scholar
Yu, C-Y (2002). Evaluating Cutoff Criteria of Model Fit Indices for Latent Variable Models with Binary and Continuous Outcomes. University of California: Los Angeles, CA.Google Scholar