36 research outputs found

    Family involvement in timely detection of changes in health of nursing homes residents: a qualitative exploratory study

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    YesThis article aims to explore family perspectives on their involvement in the timely detection of changes in their relatives' health in UK nursing homes. Increasingly, policy attention is being paid to the need to reduce hospitalisations for conditions that, if detected and treated in time, could be managed in the community. We know that family continue to be involved in the care of their family members once they have moved into a nursing home. Little is known, however, about family involvement in the timely detection of changes in health in nursing home residents. This was a qualitative exploratory study with thematic analysis. A purposive sampling strategy was applied. 14 semi-structured one-to-one telephone interviews with family members of people living in 13 different UK nursing homes. Data were collected from November 2015 to March 2016. Families were involved in the timely detection of changes in health in three key ways: noticing signs of changes in health, informing care staff about what they noticed, and educating care staff about their family members' changes in health. Families suggested they could be supported to detect timely changes in health by developing effective working practices with care staff. Families can provide a special contribution to the process of timely detection in nursing homes. Their involvement needs to be negotiated, better supported, as well as given more legitimacy and structure within the nursing home. Families could provide much needed support to nursing home nurses, care assistants, and managers in timely detection of changes in health. This may be achieved through communication about their preferred involvement on a case-by-case basis as well as providing appropriate support or services.NIH Research Programme Grant for Applied Research (RP-PG-0612-20010

    Family involvement in timely detection of changes in health of nursing homes residents:a qualitative exploratory study

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    Aims and objectives To explore family perspectives on their involvement in the timely detection of changes in their relatives’ health in UK nursing homes. Background Increasingly, policy attention is being paid to the need to reduce hospitalisations for conditions that, if detected and treated in time, could be managed in the community. We know that family continue to be involved in the care of their family members once they have moved into a nursing home. Little is known, however, about family involvement in the timely detection of changes in health in nursing home residents. Design Qualitative exploratory study with thematic analysis. Methods A purposive sampling strategy was applied. 14 semi-structured one-to-one telephone interviews with family members of people living in 13 different UK nursing homes. Data were collected from November 2015 to March 2016. Results Families were involved in the timely detection of changes in health in three key ways: noticing signs of changes in health, informing care staff about what they noticed, and educating care staff about their family members’ changes in health. Families suggested they could be supported to detect timely changes in health by developing effective working practices with care staff. Conclusion Families can provide a special contribution to the process of timely detection in nursing homes. Their involvement needs to be negotiated, better supported, as well as given more legitimacy and structure within the nursing home. Relevance to clinical practice Families could provide much needed support to nursing home nurses, care assistants, and managers in timely detection of changes in health. This may be achieved through communication about their preferred involvement on a case-by-case basis as well as providing appropriate support or services

    Towards defining the Mechanisms of Alzheimer’s disease based on a contextual analysis of molecular pathways

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    Alzheimer’s disease (AD) is posing an increasingly profound problem to society. Our genuine understanding of the pathogenesis of AD is inadequate and as a consequence, diagnostic and therapeutic strategies are currently insufficient. The understandable focus of many studies is the identification of molecules with high diagnostic utility however the opportunity to obtain a further understanding of the mechanistic origins of the disease from such putative biomarkers is often overlooked. This study examines the involvement of biomarkers in AD to shed light on potential mechanisms and pathways through which they are implicated in the pathology of this devastating neurodegenerative disorder. The computational tools required to analyse ever-growing datasets in the context of AD are also discussed

    Facial analysis technology for the detection of Down syndrome in the Democratic Republic of the Congo.

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    Down syndrome is one of the most common chromosomal anomalies affecting the worlds population, with an estimated frequency of 1 in 700 live births. Despite its relatively high prevalence, diagnostic rates based on clinical features have remained under 70% for most of the developed world and even lower in countries with limited resources. While genetic and cytogenetic confirmation greatly increases the diagnostic rate, such resources are often non-existent in many low- and middle-income countries, particularly in Sub-Saharan Africa. To address the needs of countries with limited resources, the implementation of mobile, user-friendly and affordable technologies that aid in diagnosis would greatly increase the odds of success for a child born with a genetic condition. Given that the Democratic Republic of the Congo is estimated to have one of the highest rates of birth defects in the world, our team sought to determine if smartphone-based facial analysis technology could accurately detect Down syndrome in individuals of Congolese descent. Prior to technology training, we confirmed the presence of trisomy 21 using low-cost genomic applications that do not need advanced expertise to utilize and are available in many low-resourced countries. Our software technology trained on 132 Congolese subjects had a significantly improved performance (91.67% accuracy, 95.45% sensitivity, 87.88% specificity) when compared to previous technology trained on individuals who are not of Congolese origin (p < 5%). In addition, we provide the list of most discriminative facial features of Down syndrome and their ranges in the Congolese population. Collectively, our technology provides low-cost and accurate diagnosis of Down syndrome in the local population
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