from the article: Abstract Based on a review of recent literature, this paper addresses the question of how urban planners can steer urban environmental quality, given the fact that it is multidimensional in character, is assessed largely in subjective terms and varies across time. The paper explores three questions that are at the core of planning and designing cities: ‘quality of what?’, ‘quality for whom?’ and ‘quality at what time?’ and illustrates the dilemmas that urban planners face in answering these questions. The three questions provide a novel framework that offers urban planners perspectives for action in finding their way out of the dilemmas identified. Rather than further detailing the exact nature of urban quality, these perspectives call for an approach to urban planning that is integrated, participative and adaptive. ; ; sustainable urban development; trade-offs; quality dimensions
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There are lots of definitions of quality, and also of quality in education. Garvin (1984)discerns five approaches: the transcendental approach, the product-oriented approach, the customeroriented approach, the manufacturing-oriented approach and the value-for-money approach. Harvey and Green (1993) give five interrelated concepts of quality as: exceptional, perfection (or consistency), fitness for purpose, value for money and transformative. A new definition of quality is needed to explain recent quality issues in higher education. This article describes a quality concept with four constituents: object, standard, subject and values. The article elaborates on the values. Four value systems derived from Beck and Cowan (1996) are transformed into four value systems on quality and quality management: control, continuous improvement, commitment and breakthrough. These value systems make it possible to explain some recent developments in quality management in higher education.
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Background. Quality of life is an important health outcome for older persons. It predicts the adverse outcomes of institutionalization and premature death. The aim of this cross-sectional study was to determine the influence of both disability in activities of daily living (ADL) and instrumental activities of daily living (IADL) on physical and mental dimensions of quality of life. Methods. A total of 377 Dutch people aged 75 years and older completed a web-based questionnaire. This questionnaire contained the Groningen Activity Restriction Scale (GARS) for measuring ADL and IADL and the Short-Form Health Survey (SF-12) for measuring quality of life. The SF-12 distinguishes two dimensions of quality of life, a physical and mental dimension.
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Objective: The effects of sociodemographic factors on quality of life in older people differ strongly, possibly due to the fact that different measurement instruments have been used. The main aim of this cross-sectional study is to compare the associations of sex, age, marital status, education, and income with quality of life assessed with the Short-Form Health Survey (SF-12), the World Health Organization Quality of Life Questionnaire-BREF (WHOQOL-BREF), and the World Health Organization Quality of Life Questionnaire-Older Adults Module (WHOQOL-OLD). Methods: The associations between sociodemographic factors and eleven quality of life domains were examined using a sample of 1,492 Dutch people aged $50 years. Participants completed the “Senioren Barometer”, a web-based questionnaire including sociodemographic factors, the SF-12, the WHOQOL-BREF, and the WHOQOL-OLD. Results: All the sociodemographic factors together explained a significant part of the variance of all the quality of life domains’ scores, ranging from 5% to 17% for the WHOQOL-BREF, 5.8% to 6.7% for the SF-12, and 1.4% to 26% for the WHOQOL-OLD. Being a woman and being older were negatively associated with two and four quality of life domains, respectively. Being a woman, being married or cohabiting, and having higher education and a higher income were positively associated with six, six, one, and eleven quality of life domains, respectively. Conclusion: Our study showed that the associations of sociodemographic factors and quality of life in middle-aged and older people depend on the instruments used to assess quality of life. We recommend that health care and welfare professionals focus particularly on people with a low income and carry out interventions aimed at improving their quality of life.
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Abstract Purpose To determine the predictive value of quality of life for mortality at the domain and item levels. Methods This longitudinal study was carried out in a sample of 479 Dutch people aged 75 years or older living independently, using a follow-up of 7 years. Participants completed a self-report questionnaire. Quality of life was assessed with the WHOQOL-BREF, including four domains: physical health, psychological, social relationships, and environment. The municipality of Roosendaal (a town in the Netherlands) indicated the dates of death of the individuals. Results Based on mean, all quality of life domains predicted mortality adjusted for gender, age, marital status, education, and income. The hazard ratios ranged from 0.811 (psychological) to 0.933 (social relationships). The areas under the curve (AUCs) of the four domains were 0.730 (physical health), 0.723 (psychological), 0.693 (social relationships), and 0.700 (environment). In all quality of life domains, at least one item predicted mortality (adjusted). Conclusion Our study showed that all four quality of life domains belonging to the WHOQOL-BREF predict mortality in a sample of Dutch community-dwelling older people using a follow-up period of 7 years. Two AUCs were above threshold (psychological, physical health). The findings offer health care and welfare professionals evidence for conducting interventions to reduce the risk of premature death.
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Objective: To predict mortality by disability in a sample of 479 Dutch community-dwelling people aged 75 years or older. Methods: A longitudinal study was carried out using a follow-up of seven years. The Groningen Activity Restriction Scale (GARS), a self-reported questionnaire with good psychometric properties, was used for data collection about total disability, disability in activities in daily living (ADL) and disability in instrumental activities in daily living (IADL). The mortality dates were provided by the municipality of Roosendaal (a city in the Netherlands). For analyses of survival, we used Kaplan–Meier analyses and Cox regression analyses to calculate hazard ratios (HR) with 95% confidence intervals (CI). Results: All three disability variables (total, ADL and IADL) predicted mortality, unadjusted and adjusted for age and gender. The unadjusted HRs for total, ADL and IADL disability were 1.054 (95%-CI: [1.039;1.069]), 1.091 (95%-CI: [1.062;1.121]) and 1.106 (95%-CI: [1.077;1.135]) with p-values <0.001, respectively. The AUCs were <0.7, ranging from 0.630 (ADL) to 0.668 (IADL). Multivariate analyses including all 18 disability items revealed that only “Do the shopping” predicted mortality. In addition, multivariate analyses focusing on 11 ADL items and 7 IADL items separately showed that only the ADL item “Get around in the house” and the IADL item “Do the shopping” significantly predicted mortality. Conclusion: Disability predicted mortality in a seven years follow-up among Dutch community-dwelling older people. It is important that healthcare professionals are aware of disability at early stages, so they can intervene swiftly, efficiently and effectively, to maintain or enhance the quality of life of older people.
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Quality of life serves a reference against which you can measure the various domains of your own life or that of other individuals, and that can change over time. This definition of the World Health Organization encompasses many elements of daily living, including features of the individual and the environment around us, which can either be the social environment, the built environment, or other environmental aspects. This is one of the rationales for the special issue on “Quality of Life: The Interplay between Human Behaviour, Technology and the Environment”. This special issue is a joint project by the Centre of Expertise Health Innovation of the Hague University of Applied Sciences in The Netherlands. The main focus of this Special Issue is how optimising the interplay between people, the environment, and technology can enhance people’s quality of life. The focus of the contributions in this special issue is on the person or end‐user and his or her environment, both the physical, social, and digital environment, and on the interaction between (1) people, (2) health, care, and systems, and (3) technology. Recent advances in technology offer a wide range of solutions that support a healthy lifestyle, good quality of life, and effective and efficient healthcare processes, for a large number of end‐users, both patients/clients from minus 9 months until 100+ years of age, as well as practitioners/physicians. The design of new services and products is at the roots of serving the quality of life of people. Original article at MDPI; DOI: https://doi.org/10.3390/ijerph16245106 (Editorial of Special Issue with the same title: "Quality of Life: The Interplay between Human Behaviour, Technology and the Environment")
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From the article : "Based on a review of recent literature, this paper addresses the question of how urban planners can steer urban environmental quality, given the fact that it ismultidimensional in character, is assessed largely in subjective terms and varies across time. A novel perspective of urban environmental quality is proposed, simultaneously exploring three questions that are at the core of planning and designing cities: ‘quality of what?’, ‘quality for whom?’ and ‘quality at what time?’. The dilemmas that urban planners face in answering these questions are illustrated using secondary material. This approach provides perspectives for action. Rather than further detailing the exact nature of urban quality, it calls for sustainable urban environmental quality planning that is integrated, participative and adaptive" ( wileyonlinelibrary.com ) DOI: 10.1002/eet.1759 - Preprint available for free download.
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BACKGROUND: Recent evidence suggests that an increase in baccalaureate-educated registered nurses (BRNs) leads to better quality of care in hospitals. For geriatric long-term care facilities such as nursing homes, this relationship is less clear. Most studies assessing the relationship between nurse staffing and quality of care in long-term care facilities are US-based, and only a few have focused on the unique contribution of registered nurses. In this study, we focus on BRNs, as they are expected to serve as role models and change agents, while little is known about their unique contribution to quality of care in long-term care facilities. METHODS: We conducted a cross-sectional study among 282 wards and 6,145 residents from 95 Dutch long-term care facilities. The relationship between the presence of BRNs in wards and quality of care was assessed, controlling for background characteristics, i.e. ward size, and residents' age, gender, length of stay, comorbidities, and care dependency status. Multilevel logistic regression analyses, using a generalized estimating equation approach, were performed. RESULTS: 57% of the wards employed BRNs. In these wards, the BRNs delivered on average 4.8 min of care per resident per day. Among residents living in somatic wards that employed BRNs, the probability of experiencing a fall (odds ratio 1.44; 95% CI 1.06-1.96) and receiving antipsychotic drugs (odds ratio 2.15; 95% CI 1.66-2.78) was higher, whereas the probability of having an indwelling urinary catheter was lower (odds ratio 0.70; 95% CI 0.53-0.91). Among residents living in psychogeriatric wards that employed BRNs, the probability of experiencing a medication incident was lower (odds ratio 0.68; 95% CI 0.49-0.95). For residents from both ward types, the probability of suffering from nosocomial pressure ulcers did not significantly differ for residents in wards employing BRNs. CONCLUSIONS: In wards that employed BRNs, their mean amount of time spent per resident was low, while quality of care on most wards was acceptable. No consistent evidence was found for a relationship between the presence of BRNs in wards and quality of care outcomes, controlling for background characteristics. Future studies should consider the mediating and moderating role of staffing-related work processes and ward environment characteristics on quality of care.
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