742 research outputs found

    A Knowledge-Driven Approach to Predicting Technology Adoption among Persons with Dementia

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    As the demographics of many countries shift towards an ageing population it is predicted that the prevalence of diseases affecting cognitive capabilities will continually increase. One approach to enabling individuals with cognitive decline to remain in their own homes is through the use of cognitive pros-thetics such as reminding technology. However, the benefit of such technologies is intuitively predicated upon their successful adoption and subsequent use. Within this paper we present a knowledge-based feature set which may be utilized to predict technology adoption amongst Persons with Dementia (PwD). The chosen feature set is readily obtainable during a clinical visit, is based upon real data and grounded in established research. We present results demonstrating 86% accuracy in successfully predicting adopters/non-adopters amongst PwD

    Development of a technology adoption and usage prediction tool for assistive technology for people with dementia

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    This article is available open access through the publisherā€™s website at the link below. Copyright @ The Authors 2013.In the current work, data gleaned from an assistive technology (reminding technology), which has been evaluated with people with Dementia over a period of several years was retrospectively studied to extract the factors that contributed to successful adoption. The aim was to develop a prediction model with the capability of prospectively assessing whether the assistive technology would be suitable for persons with Dementia (and their carer), based on user characteristics, needs and perceptions. Such a prediction tool has the ability to empower a formal carer to assess, through a very limited amount of questions, whether the technology will be adopted and used.EPSR

    Urinary naphthalene and phenanthrene as biomarkers of occupational exposure to polycyclic aromatic hydrocarbons.

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    OBJECTIVES: The study investigated the utility of unmetabolised naphthalene (Nap) and phenanthrene (Phe) in urine as surrogates for exposures to mixtures of polycyclic aromatic hydrocarbons (PAHs). METHODS: The report included workers exposed to diesel exhausts (low PAH exposure level, n = 39) as well as those exposed to emissions from asphalt (medium PAH exposure level, n = 26) and coke ovens (high PAH exposure level, n = 28). Levels of Nap and Phe were measured in urine from each subject using head space-solid phase microextraction and gas chromatography-mass spectrometry. Published levels of airborne Nap, Phe and other PAHs in the coke-producing and aluminium industries were also investigated. RESULTS: In post-shift urine, the highest estimated geometric mean concentrations of Nap and Phe were observed in coke-oven workers (Nap: 2490 ng/l; Phe: 975 ng/l), followed by asphalt workers (Nap: 71.5 ng/l; Phe: 54.3 ng/l), and by diesel-exposed workers (Nap: 17.7 ng/l; Phe: 3.60 ng/l). After subtracting logged background levels of Nap and Phe from the logged post-shift levels of these PAHs in urine, the resulting values (referred to as ln(adjNap) and ln(adjPhe), respectively) were significantly correlated in each group of workers (0.71 < or = Pearson r < or = 0.89), suggesting a common exposure source in each case. Surprisingly, multiple linear regression analysis of ln(adjNap) on ln(adjPhe) showed no significant effect of the source of exposure (coke ovens, asphalt and diesel exhaust) and further suggested that the ratio of urinary Nap/Phe (in natural scale) decreased with increasing exposure levels. These results were corroborated with published data for airborne Nap and Phe in the coke-producing and aluminium industries. The published air measurements also indicated that Nap and Phe levels were proportional to the levels of all combined PAHs in those industries. CONCLUSION: Levels of Nap and Phe in urine reflect airborne exposures to these compounds and are promising surrogates for occupational exposures to PAH mixtures

    The Empowering Role of Mobile Apps in Behavior Change Interventions: The Gray Matters Randomized Controlled Trial

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    BACKGROUND: Health education and behavior change programs targeting specific risk factors have demonstrated their effectiveness in reducing the development of future diseases. Alzheimer disease (AD) shares many of the same risk factors, most of which can be addressed via behavior change. It is therefore theorized that a behavior change intervention targeting these risk factors would likely result in favorable rates of AD prevention. OBJECTIVE: The objective of this study was to reduce the future risk of developing AD, while in the short term promoting vascular health, through behavior change. METHODS: The study was an interventional randomized controlled trial consisting of subjects who were randomly assigned into either treatment (n=102) or control group (n=42). Outcome measures included various blood-based biomarkers, anthropometric measures, and behaviors related to AD risk. The treatment group was provided with a bespoke ā€œGray Mattersā€ mobile phone app designed to encourage and facilitate behavior change. The app presented evidence-based educational material relating to AD risk and prevention strategies, facilitated self-reporting of behaviors across 6 behavioral domains, and presented feedback on the userā€™s performance, calculated from reported behaviors against recommended guidelines. RESULTS: This paper explores the rationale for a mobile phoneā€“led intervention and details the appā€™s effect on behavior change and subsequent clinical outcomes. Via the app, the average participant submitted 7.3 (SD 3.2) behavioral logs/day (n=122,719). Analysis of these logs against primary outcome measures revealed that participants who improved their high-density lipoprotein cholesterol levels during the study duration answered a statistically significant higher number of questions per day (mean 8.30, SD 2.29) than those with no improvement (mean 6.52, SD 3.612), t(97.74)=āˆ’3.051, P=.003. Participants who decreased their body mass index (BMI) performed significantly better in attaining their recommended daily goals (mean 56.21 SD 30.4%) than those who increased their BMI (mean 40.12 SD 29.1%), t(80) = āˆ’2.449, P=.017. In total, 69.2% (n=18) of those who achieved a mean performance percentage of 60% or higher, across all domains, reduced their BMI during the study, whereas 60.7% (n=34) who did not, increased their BMI. One-way analysis of variance of systolic blood pressure category changes showed a significant correlation between reported efforts to reduce stress and category change as a whole, P=.035. An exit survey highlighted that respondents (n=83) reported that the app motivated them to perform physical activity (85.4%) and make healthier food choices (87.5%). CONCLUSIONS: In this study, the ubiquitous nature of the mobile phone excelled as a delivery platform for the intervention, enabling the dissemination of educational intervention material while simultaneously monitoring and encouraging positive behavior change, resulting in desirable clinical effects. Sustained effort to maintain the achieved behaviors is expected to mitigate future AD risk. TRIAL REGISTRATION: ClinicalTrails.gov NCT02290912; https://clinicaltrials.gov/ct2/show/NCT02290912 (Archived by WebCite at http://www.webcitation.org/6ictUEwnm

    Applying multi-phase DES approach for modelling the patient journey through accident and emergency departments

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    Accident and Emergency departments (A&ED) are in charge of providing access to patients requiring urgent acute care. A&ED are difficult to model due to the presence of interactions, different pathways and the multiple outcomes that patients may undertake depending on their health status. In addition, public concern has focused on the presence of overcrowding, long waiting times, patient dissatisfaction and cost overruns associated with A&ED. There is then a need for tackling these problems through developing integrated and explicit models supporting healthcare planning. However, the studies directly concentrating on modelling the A&EDs are largely limited. Therefore, this paper presents the use of a multi-phase DES framework for modelling the A&ED and facilitating the assessment of potential improvement strategies. Initially, the main components, critical variables and different states of the A&ED are identified to correctly model the entire patient journey. In this step, it is also necessary to characterize the demand in order to categorize the patients into pipelines. After this, a discrete-event simulation (DES) model is developed. Then, validation is conducted through the 2-sample t test to demonstrate whether the model is statistically comparable with the real-world A&ED department. This is followed by the use of Markov phase-type models for calculating the total costs of the whole system. Finally, various scenarios are explored to assess their potential impact on multiple outcomes of interest. A case study of a mixed-patient environment in a private A&E department is provided to validate the effectiveness of the multi-phase DES approach

    Occupational asphalt is not associated with head and neck cancer

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    Epidemiologic studies that evaluate the relationship between occupational asphalt exposure and head and neck cancer have had a limited ability to control for known risk factors such as smoking, alcohol and human papillomavirus (HPV)

    Drugs developed to treat diabetes, liraglutide and lixisenatide, cross the blood brain barrier and enhance neurogenesis

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    <p>Abstract</p> <p>Background</p> <p>Type 2 diabetes is a risk factor for Alzheimer's disease (AD), most likely linked to an impairment of insulin signalling in the brain. Therefore, drugs that enhance insulin signalling may have therapeutic potential for AD. Liraglutide (Victoza) and exenatide (Byetta) are novel long-lasting analogues of the GLP-1 incretin hormone and are currently available to treat diabetes. They facilitate insulin signalling via the GLP-1 receptor (GLP-1R). Numerous <it>in vitro </it>and <it>in vivo </it>studies have shown that GLP-1 analogues have a range of neuroprotective properties. GLP-1Rs are expressed in the hippocampal area of the brain an important site of adult neurogenesis and maintenance of cognition and memory formation. Therefore, if GLP-1 analogues can cross the blood brain barrier, diffuse through the brain to reach the receptors and most importantly activate them, their neuroprotective effects may be realized.</p> <p>Results</p> <p>In the present study we profiled the GLP-1 receptor agonists liraglutide (Victoza) and lixisenatide (Lyxumia). We measured the kinetics of crossing the blood brain barrier (BBB), activation of the GLP-1R by measuring cAMP levels, and physiological effects in the brain on neuronal stem cell proliferation and neurogenesis. Both drugs were able to cross the BBB. Lixisenatide crossed the BBB at all doses tested (2.5, 25, or 250 nmol/kg bw ip.) when measured 30 min post-injection and at 2.5-25 nmol/kg bw ip. 3 h post-injection. Lixisenatide also enhanced neurogenesis in the brain. Liraglutide crossed the BBB at 25 and 250 nmol/kg ip. but no increase was detectable at 2.5 nmol/kg ip. 30 min post-injection, and at 250 nmol/kg ip. at 3 h post-injection. Liraglutide and lixisenatide enhanced cAMP levels in the brain, with lixisenatide being more effective.</p> <p>Conclusions</p> <p>Our results suggest that these novel incretin analogues cross the BBB and show physiological activity and neurogenesis in the brain, which may be of use as a treatment of neurodegenerative diseases.</p
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