Study of Personality and Mental Disorders by Roman Kotov, PhD, and Colleagues in Psychological Bulletin

Study by Stony Brook researcher and colleagues identifies strong links between personality traits and mental disorders with implications for future research, prevention and treatment

A meta-analysis of the relationships between personality traits and mental disorders performed by Roman Kotov, PhD, and colleagues provides conclusive evidence that common psychiatric diseases in adults are strongly linked to traits of personality. The study, titled “Personality and Mental Disorders,” is scheduled to be published in the September issue of Psychological Bulletin.  Dr. Kotov is Research Assistant Professor in the Department of Psychiatry and Behavioral Science at Stony Brook University.

The review is based on 175 research studies published between 1980 and 2007. It measures the strength of the associations between six personality traits and eleven psychiatric disorders, resulting in sixty-six discrete analyses. While the original empirical studies provide the foundation for knowledge about the links between personality traits and psychiatric disorders, the meta-analysis provides more definitive answers to research questions because it aggregates the data to produce larger sample sizes and reveals patterns hidden among the disparate studies. Greater attention to the these patterns, Dr. Kotov and his colleagues suggest, can significantly benefit both psychiatric research and clinical practice.

Although the link between personality and mental disorders has been recognized since the days of Hippocrates, it was not until thirty years ago that researchers developed a common language for studying these phenomena. The development of the modern classification of mental illnesses, coupled with the emergence of a consensus among psychologists regarding personality traits, enabled researchers to study their relationships using a common set of definitions and methods. 

The six dimensions of personality studied are derived from models widely accepted by personality theorists. They are neuroticism, extraversion, conscientiousness, agreeableness, openness, and disinhibition. There is a growing consensus among psychologists that these are the higher order domains of human personality that explain stable patterns of thought and behavior.

The eleven psychiatric disorders studied include common diagnoses associated with depression, anxiety and substance use. They include major depressive disorder, generalized anxiety disorder, PTSD, obsessive-compulsive disorder, and substance use disorders, among others.

The researchers were able to integrate the results of all 175 studies by converting them to a standard unit of measure - Cohen’s d - a statistical construct that represents effect size. In this analysis, effect size is the difference between the average score of people diagnosed with a mental disorder and the average score of the general population on an instrument that measures personality.

The core findings are presented in a single table showing the effect sizes of each personality trait plotted against each mental disorder, along with credibility intervals for each. The most striking result is the strength of the associations between neuroticism and all the disorders included in the study. While this is not surprising - neuroticism is defined as a tendency to experience negative emotional states like anxiety, guilt and depression - the magnitude of the effect sizes is much larger that previous theories appreciated.

Equally apparent is the inverse link between conscientiousness and mental disease. Conscientiousness, which reflects traits like reliability and self-discipline, is negatively correlated with each of the disorders, although the effect sizes are not as large.

Although the scientific literature does not provide sufficient data for Dr. Kotov and his associates to infer causal relationships between personality and mental illness, the meta-analysis opens up new avenues of investigation by identifying which traits are most likely to be associated with any particular disorder or cluster of disorders.

Dr. Kotov sees a possible use for this information in the prevention of mental disease. Because personality traits are easily assessed in just a few minutes, it might be possible to identify at-risk individuals in large populations and introduce procedures for early detection and intervention. It might also be possible to screen rescue workers for risk of PTSD, for example, or to identify high school students at risk for depression.