How to measure multidimensional quality of life of persons with disabilities in public policies - a case of Poland

• Main Authors: Izabela Grabowska (Author), Radosław Antczak (Author), Jan Zwierzchowski (Author), Tomasz Panek (Author)
• Format: Book
• Published: BMC, 2022-11-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s13690-022-00981-5; 2049-3258
• Keywords: Quality of life; Disability; Life quality domains; MIMIC; Public aspects of medicine; RA1-1270
• Source: Archives of Public Health, Vol 80, Iss 1, Pp 1-16 (2022)

Abstract Background The aim of this paper is to construct a tool that can be used to measure multidimensional quality of life of persons with disabilities in comparison with population without disabilities for the purpose of monitoring of the UN Convention on the Rights of Persons with Disabilities (UNCRPD) in Poland. Methods The Sen's capability approach was applied to conceptualize the quality of life in various life domains. We followed guidelines of The Quality of Life Framework developed within the European Statistical System on choosing the life domains in which the QoL should be measured. The QoL scores in each domain (covered by the UNCRPD) were constructed using multiply indicators and multiple causes model (MIMIC). All analysis were based on 2018 EU-SILC data for Poland. We constructed quality of life indicators for population with and without disabilities and compared the differences. Results Persons without disability experienced higher QoL as compared to population with disabilities, overall and in various domains. Lower average QoL of persons with disabilities is a result of a lower share of those who experience high QoL. The biggest difference is observed for health and for productive and main activity domains. For material conditions and economic security and physical safety there was a moderate difference recorded. For the leisure and social relations domain there is almost no difference observed. Additionally, we identified diversified associations between such factors as age, gender, household situation, education, partner status, urbanization, health on the QoL across domains and analysed populations. Conclusions A tool developed in this paper can be calibrated to enable cross-country and in time comparisons between different populations and support evidenced-based social policy.