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.
The aim of the paper is to identify the mechanisms shaping the quality of life of the residents of poor neighborhoods based on the example of a deprived area of Łódź city center. To analyze this multidimensional phenomenon, the capability approach is used with a special focus on conversion factors that limit the pursuit of preferred lifestyles. Based on 80 in–depth interviews with residents and register data from public authorities (at the building level, which enables presenting the detailed spatial distribution of the analyzed issues), individual trajectories in the form of individual mechanisms have been established and then aggregated. The aggregation is presented as a web of social exclusion. The collected information has allowed the author to create a categorization of conversion factors in degraded areas that take into account their interrelationships and complex cause–effect mechanisms. The classification is constructed using the following categories: housing conditions, economic wealth, knowledge and skills, norms, attitudes and social capital, work environment, and life conditions (defined mainly as access to public services and space). Combining quantitative data (at the building level) with qualitative data provided the author with crucial input for the identification of specific public policy actions that can affect conversion factors.
Although financed from both private and public resources-the current edition from the Human Capital Operational Programme (from ESF funds), a research grant from the Ministry of Science and Higher Education and funds from the National Bank of Poland-the Social Diagnosis study is an entirely public undertaking. The complete set of tables with response distribution* and a database of cumulated data from six waves
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