A comparative analysis of graphical interaction and logistic regression modelling: self-care and coping with a chronic illness in later life

Quantitative research especially in the social, but also in the biological sciences has been limited by the availability and applicability of analytic techniques that elaborate interactions among behaviours, treatment effects, and mediating variables. This gap has been filled by a newly developed statistical technique, known as graphical interaction modelling. The merit of graphical models for analyzing highly structured data is explored in this paper by an empirical study on coping with a chronic condition as a function of interrelationships between three sets of factors. These include background factors, illness context factors and four self--care practices. Based on a graphical chain model, the direct and indirect dependencies are revealed and discussed in comparison to the results obtained from a simple logistic regression model ignoring possible interaction effects. Both techniques are introduced from a more tutorial point of view instead of going far into technical details

Machine Learning Algorithms for Classification Patients with Parkinson`s Disease and Hereditary Ataxias

Neurodegenerative diseases are a group of neurological conditions characterized by the loss or destruction of neurons in the central nervous system, resulting in severe impairments and death. Researchers commonly used a two-group classification (Patients with a Neurodegenerative disease vs. healthy subjects of control). Thus, the principal purpose of this article is to distinguish between Parkinson\u27s patients and subjects with Hereditary Ataxias using machine learning techniques. We conducted experiments using a real dataset comprising Gait characteristics derived from the inertial motion sensors of a smartphone (iPhone 5S). This investigation had 67 participants, 53 of who had Parkinson\u27s disease and 14 of whom had Hereditary Ataxias. Methods of feature selection were applied to reduce dimensionality. In addition, five classification algorithms were constructed and assessed based on their accuracy, precision, sensitivity, and specificity. The Support Vector Machine algorithm achieved an accuracy of 92.7%, a precision of 91.1%, a sensitivity of 96.2%, and a specificity of 89.1%. These results show that the suggested technique might inspire new research issues and have a direct therapeutic impact

Functional disability and social participation restriction associated with chronic conditions in middle-aged and older adults

Abstract : Background. We examine the population impact on functional disability and social participation of physical and mental chronic conditions individually and in combination. Methods. Cross-sectional, population-based data from community-dwelling people aged 45 years and over living in the 10 Canadian provinces in 2008–2009 were used to estimate the population attributable risk (PAR) for functional disability in basic (ADL) and instrumental (IADL) activities of daily living and social participation restrictions for individual and combinations of chronic conditions, stratified by age and gender, after adjusting for confounding variables. Results. Five chronic conditions (arthritis, depression, diabetes, heart disease and eye disease) made the largest contributions to ADL-related and IADL-related functional disability and social participation restrictions, with variation in magnitude and ranking by age and gender. While arthritis was consistently associated with higher PARs across gender and most age groups, depression, alone and in combination with the physical chronic conditions, was associated with ADL and IADL disability as well as social participation restrictions in the younger age groups, especially among women. Compared to women, the combinations of conditions associated with higher PARs in men more often included heart disease and diabetes. Conclusions. Our findings suggest that in community dwelling middle-aged and older adults, the impact of combinations of mental and physical chronic conditions on functional disability and social participation restriction is substantial and differed by gender and age. Recognising the differences in the drivers of PAR by gender and age group will ultimately increase the efficiency of clinical and public health interventions

Co-designing Urban Living Solutions to Improve Older People’s Mobility and Well-Being

Mobility is a key aspect of active ageing enabling participation and autonomy into later life. Remaining active brings multiple physical but also social benefits leading to higher levels of well-being. With globally increasing levels of urbanisation alongside demographic shifts meaning in many parts of the world this urban population will be older people, the challenge is how cities should evolve to enable so-called active ageing. This paper reports on a co-design study with 117 participants investigating the interaction of existing urban spaces and infrastructure on mobility and well-being for older residents (aged 55 + years) in three cities. A mixed method approach was trialled to identify locations beneficial to subjective well-being and participant-led solutions to urban mobility challenges. Spatial analysis was used to identify key underlying factors in locations and infrastructure that promoted or compromised mobility and well-being for participants. Co-designed solutions were assessed for acceptability or co-benefits amongst a wider cross-section of urban residents (n = 233) using online and face-to-face surveys in each conurbation. Our analysis identified three critical intersecting and interacting thematic problems for urban mobility amongst older people: The quality of physical infrastructure; issues around the delivery, governance and quality of urban systems and services; and the attitudes and behaviors of individuals that older people encounter. This identified complexity reinforces the need for policy responses that may not necessarily involve design or retrofit measures, but instead might challenge perceptions and behaviors of use and access to urban space. Our co-design results further highlight that solutions need to move beyond the generic and placeless, instead embedding specific locally relevant solutions in inherently geographical spaces, populations and processes to ensure they relate to the intricacies of place

Cardiovascular risk assessment - From individual risk prediction to estimation of global risk and change in risk in the population

Cardiovascular disease is the most common cause of death and risk prediction formulae such as the Framingham Risk Score have been developed to easily identify patients at high risk that may require therapeutic interventions. Using cardiovascular risk formulae at a population level to estimate and compare average cardiovascular risk among groups has been recently proposed as a way to facilitate surveillance of net cardiovascular risk and target public health interventions. Risk prediction formulas may help to compare interventions that cause effects of different magnitudes and directions in several cardiovascular risk factors, because these formulas assess the net change in risk using easily obtainable clinical variables. Because of conflicting data estimates of the incidence and prevalence of cardiovascular disease, risk prediction formulae may be a useful tool to estimate such risk at a population level

Design principles in housing for people with complex physical and cognitive disability: towards an integrated framework for practice

To develop a research-based environmental framework to guide the design and construction of suitable residential dwellings for individuals with complex disability. An environmental approach to housing design and development recognises that there are physical, psychological and social components relating to housing design, dwelling location and the neighbourhood context, and that these elements interact to affect the physical, psychological, and social wellness of individuals. Following theoretical review and synthesis, a comprehensive set of design features that are conducive to residents’ wellness and quality of life are described. It is clear that housing design and development for people with complex disability ought to consider the physical, social, natural, symbolic, and care environment in relation to housing design, dwelling location, and the neighbourhood context for improved housing outcomes. An integrated housing design and development framework is presented. It is hoped this practical matrix/evaluative tool will inform future inclusive housing design and development decisions in Australia and internationally. The application of this framework is especially relevant to political climates striving to achieve design innovation to increase housing choice for people with complex disability