M Ruggeri1, R Gater, G Bisoffi, C Barbui, M Tansella. 1. Department of Medicine and Public Health, Section of Psychiatry, University of Verona, Italia. mirella.ruggeri@univr.it
Abstract
OBJECTIVE: Investigate the relationship of various domains of quality of life (QoL) with socio-demographics, clinical and social characteristics, service use and satisfaction in a representative sample of patients in contact with the South-Verona community mental health service. METHOD: Measures included: Lancashire Quality of Life Profile (LQOLP), demographics, diagnosis and service utilization data from the Case Register, Brief Psychiatric Rating Scale (BPRS), Disability Assessment Schedule (DAS), Global Assessment of Functioning (GAF) and Verona Service Satisfaction Scale (VSSS). Analyses were conducted using a block-stratified multiple regression model. RESULTS: Demographics, diagnosis, psychopathology, disability, functioning and service use together explained different amounts of variance in each LQOLP domain, but always less than 14%. VSSS explained more variance than any other indicator in health (13.1%), social relations (12.1%), leisure/participation (9.1%), and general wellbeing (9.0%). CONCLUSION: Different domains of QoL are predicted by different indicators. In some important domains, self-perceived satisfactory and effective care might have an impact on the QoL of patients.
OBJECTIVE: Investigate the relationship of various domains of quality of life (QoL) with socio-demographics, clinical and social characteristics, service use and satisfaction in a representative sample of patients in contact with the South-Verona community mental health service. METHOD: Measures included: Lancashire Quality of Life Profile (LQOLP), demographics, diagnosis and service utilization data from the Case Register, Brief Psychiatric Rating Scale (BPRS), Disability Assessment Schedule (DAS), Global Assessment of Functioning (GAF) and Verona Service Satisfaction Scale (VSSS). Analyses were conducted using a block-stratified multiple regression model. RESULTS: Demographics, diagnosis, psychopathology, disability, functioning and service use together explained different amounts of variance in each LQOLP domain, but always less than 14%. VSSS explained more variance than any other indicator in health (13.1%), social relations (12.1%), leisure/participation (9.1%), and general wellbeing (9.0%). CONCLUSION: Different domains of QoL are predicted by different indicators. In some important domains, self-perceived satisfactory and effective care might have an impact on the QoL of patients.
Authors: Lorenzo Burti; Francesco Amaddeo; Marta Ambrosi; Chiara Bonetto; Doriana Cristofalo; Mirella Ruggeri; Michele Tansella Journal: Community Ment Health J Date: 2005-12
Authors: Carlos Zubaran; Jonathan Emerson; Rishi Sud; Elham Zolfaghari; Katia Foresti Journal: Health Qual Life Outcomes Date: 2012-03-18 Impact factor: 3.186