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Substance user MMPI-2 profiles: predicting failure in completing treatment

L L Marshall1, R J Roiger

  • 1Chemical Dependency Studies, Mankato State University, Minnesota 56002, USA.

Substance Use & Misuse
|January 1, 1996
PubMed
Summary
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This study used the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) to predict treatment completion in chemically dependent patients. Neurotic patients and those with elevated scores on Scales 7 and 8 were more likely to not complete treatment.

Area of Science:

  • Psychology
  • Addiction Medicine
  • Clinical Psychology

Background:

  • Identifying patients likely to discontinue substance abuse treatment is crucial for optimizing resource allocation and patient outcomes.
  • The Minnesota Multiphasic Personality Inventory-2 (MMPI-2) is a widely used psychometric tool for assessing personality characteristics.

Purpose of the Study:

  • To develop a predictive model using MMPI-2 data to identify chemically dependent patients at high risk of treatment noncompletion.
  • To investigate the relationship between specific MMPI-2 profile types and treatment outcome in a chemically dependent population.

Main Methods:

  • Analysis of MMPI-2 profiles from 173 chemically dependent patients (142 male).
  • Utilized profile code types and multiple analysis of variance (MANOVA) for data analysis.

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  • Chi-square tests were employed to assess categorical relationships.
  • Main Results:

    • Patients classified as neurotic demonstrated a higher likelihood of treatment failure (chi-square analysis).
    • Elevated T-scores on MMPI-2 Scales 7 (Psychasthenia) and 8 (Schizophrenia) were significantly associated with treatment noncompletion (MANOVA, p < .05).

    Conclusions:

    • Specific MMPI-2 characteristics, particularly neuroticism and elevated scores on Scales 7 and 8, can indicate a higher risk of treatment noncompletion.
    • The findings suggest that while MMPI-2 provides valuable insights, relying on a single objective measure may be insufficient for comprehensive outcome prediction in addiction treatment.