Author:
Kovess-Masfety Viviane,Boyd Anders
Abstract
Purpose
: To
develop and validate a prediction model for mental health needs (MHN) and
psychiatric needs (PN) using specific social indicators, obtainable from census
data, within low-density departments (LDD) and high- density departments (HDD).
Methods: In a population-based study of 20,404 participants from
22 departments in France, mental health needs were defined into three categories
(no needs, MHN, and PN) using the Composite International Diagnosis Interview
Short-Form, Sheehan disability scale, and presence of depressive and alcohol
disorders. Within HDD (n=9) and LDD (n=13) departments, two separate logistic
regression models, using MHN or PN as an endpoint, were fitted using available
sociodemographic data. Model validation was performed using 2007 census data.
Overall accuracy was evaluated using average residuals (AR) calculated within
density stratum.
Results
: In LDD
and HDD respectively, 26.6% and 28.7% of persons had MHN and 9.8% and 11.3% had
PN. In LDD, housing type, age, employment, living alone, housing support, and
household size predicted MHN and PN. In HDD, housing type, living alone,
household size, living in a marriage/partnership, and duration of dwelling
habitation predicted MHN and PN. Predictions were more accurate in HDD, in which
the AR was 30% lower for MHN and 40% lower for PN. Predictions were less
accurate when using census data, yet they were consistently better in HDD.
Conclusions
: Sociodemographic indicators
from either survey or census data may be useful in predicting MHN and PN in
high-density settings. The ideal territorial size still needs to be evaluated
when planning psychiatric and mental health resources.
Publisher
Bentham Science Publishers Ltd.
Subject
Psychiatry and Mental health,Epidemiology
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