Personality traits as predictors of recovery among patients with substance use disorder

Journal of Substance Use and Addiction Treatment(2024)

Cited 0|Views14
No score
Abstract
Introduction Substance use disorder (SUD) is often considered a chronic illness in which prolonged recovery, in terms of abstinence, is uncommon. Personality has been found to predict recovery, but not much is known about its long-term predictive ability as the majority of previous studies have had short follow-up periods (≥ one year). The current longitudinal cohort study therefore investigated whether personality traits predict short- (STR) as well as long-term recovery (LTR) in SUD patients. Methods Treatment-seeking patients with SUD (n = 123) completed the NEO Personality Inventory – Revised. STR and LTR categories were defined as scoring <8 on the Alcohol Use Disorders Identification Test – C and <2 on the Drug Use Disorder Identification Test – C at the one-year and 6–8-year follow-up, respectively. Whether personality traits predicted outcome was investigated by two-tailed independent samples t-tests, α < 0.05. Additional analysis was conducted with latent growth curve model. Results Neuroticism (inversely, p = .004, d = 0.55) and Extraversion (p = .04, d = 0.38) predicted STR (n = 114). Although not significant the effect size for Conscientiousness was above the cut-off for a practical significant effect (d = 0.31). No traits predicted LTR category. Still, the effect sizes for LTR regarding Neuroticism (d = 0.36), Extraversion (d = 0.21) and Conscientiousness (d = 0.27) indicated that these traits have relevance for LTR. The latent growth curve model indicated that these traits predicted the short-term use of drugs and long-term use of alcohol in this cohort dominated by patients suffering from severe poly-SUD. Conclusion Personality traits predict recovery. The effect sizes indicate that more studies with larger samples on personality traits and LTR are required to understand their possible influences on the recovery process.
More
Translated text
Key words
SUD,Outcome,Five-factor model,NEO-PI-R,Addiction
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined