Mental health service utilization in the United States. The role of personality factors.
BACKGROUND
The aim of this study was to determine the relationship between personality factors and the use of mental health services (past 12 months) among adults in the community.


METHODS
Data were drawn from the Midlife Development in the United States Survey (MIDUS), a representative sample of 3,032 adults aged 25-74 in the United States population. Analyses of variance and logistic regression analyses were used to determine the relationship between personality factors and mental health service utilization, in the presence and absence of mental disorders, during the past 12 months.


RESULTS
Neuroticism [OR = 1.5 (1.2, 1.9)] was associated with significantly increased likelihood of mental health service utilization among adults in the community. Conscientiousness [OR = 0.7 (0.5, 0.9)] and extraversion [OR = 0.7 (0.5, 0.98)], in contrast, were associated with decreased likelihood of use of mental health services. Among adults with mental disorders, conscientiousness [OR = 0.5 (0.3, 0.8)] was associated with decreased odds of mental health service utilization. Neuroticism [OR = 1.8 (1.3, 2.4)] was associated with increased likelihood of service use among those who did not meet criteria for common mental disorders.


CONCLUSIONS
These findings are the first to document a significant association between personality factors and the use of mental health services among adults in the general population. Our results highlight new ways in which personality may influence mental health in the community. This information may be useful in identifying those with unmet need for mental health treatment and developing more effective interventions for those at risk for common mental disorders. Replication of these findings is needed.
Goodwin
Renee D
RD
Department of Epidemiology, Columbia University and the New York State Psychiatric Institute, USA. rdg66@columbia.edu
Hoven
Christina W
CW
Lyons
John S
JS
Stein
Murray B
MB
D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D001523:Mental Disorders; D008605:Mental Health Services / Q000706:statistics & numerical data*; D008875:Middle Aged; D010342:Patient Acceptance of Health Care / Q000523:psychology*; D010551:Personality; D012959:Socioeconomic Factors; D014481:United States