Factor Structure and Sensitivity to Change of the Recovery Assessment Scale

  • Salene M. W. JonesEmail author
  • Evette J. Ludman


The focus on recovery, not just symptom reduction, in mental health care brings a need for psychometrically sound measures of recovery. This study examined the factor structure and sensitivity to change of a common measure of mental health recovery, the Recovery Assessment Scale (RAS). We conducted a secondary data analysis from a randomized clinical trial of self-management for depression (n = 302). We tested both bifactor and the previously found five-factor model. Sensitivity to change was examined three ways: (1) between the intervention and control group; (2) across time in the intervention group; and (3) in those whose depression remitted. The previous five-factor model was supported. One subscale, no domination by symptoms, was particularly sensitive to change and showed sensitivity to change whereas the subscale reliance on others did not show change in any of the comparisons. Results suggest that the subscales of the RAS should be examined separately in future studies of recovery.



This study was supported by the National Institute of Mental Health (grant number MH065530). Registration number at is NCT01139060.

Compliance with Ethical Standards

All participants provided informed consent, and the institutional review boards of the study centers approved the procedures before the study was conducted.

Conflict of Interest

The authors declare that they have no conflicts of interest.


  1. 1.
    President's New Freedom Commission on Mental Health. Achieving the Promise: Transforming Mental Health Care in America. In: Services HaH, ed2003.Google Scholar
  2. 2.
    Schrank B, Slade M. Recovery in psychiatry. Psychiatric Bulletin. 2007;31:321–325.CrossRefGoogle Scholar
  3. 3.
    Giffort D, Schmook A, Woody C, et al. Construction of a scale to measure consumer recovery. 1995, Springfield, IL.Google Scholar
  4. 4.
    Corrigan PW, Salzer M, Ralph RO, et al. Examining the factor structure of the recovery assessment scale. Schizophrenia Bulletin. 2004;30(4):1035–1041.CrossRefGoogle Scholar
  5. 5.
    Holzinger KJ, Swineford F. The bifactor method. Psychometrika. 1937;2:41–54.CrossRefGoogle Scholar
  6. 6.
    Corrigan PW, Giffort D, Rashid F, et al. Recovery as a psychological construct. Community Mental Health Journal. 1999;35(3):231–239.CrossRefGoogle Scholar
  7. 7.
    McNaught M, Caputi P, Oades LG, et al. Testing the validity of the Recovery Assessment Scale using an Australian sample. Australian and New Zealand Journal Psychiatry. 2007;41(5):450–457.CrossRefGoogle Scholar
  8. 8.
    Streiner DL, Norman GR. Health Measurement Scales: A practical guide to their development and use. Oxford University Press; 2008.Google Scholar
  9. 9.
    Ludman EJ, Simon GE, Grothaus LC, et al. Organized Self-Management Support Services for Chronic Depressive Symptoms: A Randomized Controlled Trial. Psychiatric Services. 2015:appips201400295.Google Scholar
  10. 10.
    First MB, Spitzer RL, Gibbon M, et al. Structured clinical interview for DSM-IV Axis I disorders, research version, non-patient edition (SCID-I/NP). New York: Biometrics Research, New York State Psychiatric Institute; 2002.Google Scholar
  11. 11.
    American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-IV-TR. 4th ed., text revision ed. Washington, DC: American Psychiatric Association; 2000.Google Scholar
  12. 12.
    Browne M, Cudeck R. Alternative ways of assessing model fit. London, England: Sage; 1993.Google Scholar
  13. 13.
    Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal. 1999;6(1):1–55.CrossRefGoogle Scholar
  14. 14.
    Cohen J. Statistical power analysis for the behavioral sciences. 2 ed. Hillsdale, NJ: Lawrence Earlbaum Associates; 1988.Google Scholar
  15. 15.
    Kessler RC, Chiu WT, Demler O, et al. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry. 2005;62(6):617–627.CrossRefGoogle Scholar
  16. 16.
    Reise SP, Morizot J, Hays RD. The role of the bifactor model in resolving dimensionality issues in health outcomes measures. Quality of Life Research. 2007;16 Suppl 1:19–31.CrossRefGoogle Scholar
  17. 17.
    Drapalski AL, Medoff D, Unick GJ, et al. Assessing recovery of people with serious mental illness: development of a new scale. Psychiatric Services. 2012;63(1):48–53.CrossRefGoogle Scholar

Copyright information

© National Council for Behavioral Health 2017

Authors and Affiliations

  1. 1.Group Health Research InstituteSeattleUSA

Personalised recommendations