228 research outputs found

    Employers skill survey : case study - telecommunications sector

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    New technology industries

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    Is Quality of Life a Healthy Concept? Measuring and Understanding Life Experiences of Older People.

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    The concept of quality of life has received considerable attention as an inclusive notion of health and as a basis for health interventions. The authors' argument in this article is that notwithstanding this attention, little consensus exists as to definition of the term. In addition, a focus on measurement has led to the neglect of wider aspects of quality of life. Such difficulties are particularly relevant to the study of quality of life of older people. Analysis of interview data suggests that older people's understandings of quality of life are not readily measurable and should be viewed in terms of phenomenological experience. The authors discuss the implications for studying quality of life of this group and difficulties for the concept itself.div_PaSAddington-Hall, J., & Kalra, L. (2001). Who should measure quality of life? British Medical Journal, 322, 1417-1420. Albrecht, G. L.,&Devlieger, P. J. (1999).The disability paradox: High quality of life against all odds. Social Science & Medicine, 48, 977-988. Allison, P. J., Locker, D.,&Feine, J. S. (1997). Quality of life:Adynamic construct. Social Science&Medicine, 45, 221-230. Avis, N. E.,&Smith, K.W. (1998). Quality of life in older adults with HIV disease. Research on Aging, 20(6), 822-845. Bowling, A. (1995). What things are important in people's lives? Asurvey of the public's judgements to inform scales of health related quality of life. Social Science & Medicine, 10, 1447-1462. Bowling, A. (2001). Measuring disease. Buckingham, UK: Open University Press. Browne, J. P., McGee, H. M., & O'Boyle, C. I. (1997). Conceptual approaches to the assessment of quality of life. Psychology & Health, 12, 737-751. Calman, K. C. (1984) Quality of life in cancer patients-Ahypothesis. Journal of Medical Ethics, 10, 124-127. Carr, A. J., Gibson, B.,& Robinson, P. G. (2001). Measuring quality of life: Is quality of life determined by expectations or experience? British Medical Journal, 322, 1240-1243. Chamberlain, K., Stephens, C.,&Young, A. C. (1997). Encompassing experience: Meanings and methods in health psychology. Psychology & Health, 12, 691-709. Coen, R. F.,O'Boyle, C.A., Swanwick, G. R. J.,&Coakley, D. (1999). Measuring the impact on relatives of caring for people with Alzheimer's disease: Quality of life, burden and well-being. Psychology & Health, 14, 253-261. Coen, R.,O'Mahoney, D.,O'Boyle, C., Joyce, C. R. B., Hiltbrunner, B.,Walsh, J. B., et al. (1993). Measuring the quality of life of dementia patients using the schedule for the evaluation of individual quality of life. Irish Journal of Psychology, 14(1), 154-163. Davies, S., Ellis, L., & Laker, S. (2000). Promoting autonomy and independence for older people within nursing practice: An observational study. Journal of Clinical Nursing, 9, 127-136. Duncan-Myers, A. M., & Huebner, R. A. (2000). Relationship between choice and quality of life among residents in long-term-care facilities. American Journal of Occupational Therapy, 54, 504-508. Dworkin, S. F., &Wilson, L. (1993). Measurement of illness behavior: Review of concepts and common measures. In P. M. Conn (Ed.), Paradigms for the study of behavior (pp. 329-344).New York: Academic Press. Evans, R. W. (1991). Quality of life. Lancet, 338, 363. Farquhar, M. (1995a). Definitions of quality-of-life: Ataxonomy. Journal of Advanced Nursing, 22(3), 502- 508. Farquhar, M. (1995b). Elderly people's definitions of quality of life. Social Science&Medicine, 41(10), 1439- 1446. Garratt, A. M., & Ruta, D. A. (1999). The patient generated index. In C. R. B. Joyce, H. M. McGee, & C. A. O'Boyle (Eds.), Individual quality of life: Approaches to conceptualisation and assessment (pp. 118-134). Amsterdam: Harwood Academic. Garratt, A., Schmidt, L., Mackintosh, A., & Fitzpatrick, R. (2002). Quality of life measurement: Bibliographic study of patient assessed health outcome measures. British Medical Journal, 324, 1417-1419. Higgs, P., Hyde, M., Wiggins, R., & Blane, D. (2003). Researching quality of life in early old age: The importance of the sociological dimension. Social Policy & Administration, 37(3), 239-252. Jirojanakul, P., & Skevington, S. (2000). Developing a quality of life measure for children aged 5-8 years. British Journal of Health Psychology, 5, 299-321. Jones, P.W.,&Kaplan, R. M. (2003). Methodological issues in evaluatingmeasures of health as outcomes for COPD. European Respiratory Journal, 21(Suppl. 41), 13S-18S. Joyce, C. R. B, McGee, H. M., & O'Boyle, C. A. (Eds.). (1999). Individual quality of life: Approaches to conceptualisation and assessment. Amsterdam: Harwood Academic. King, N., Carroll, C., Newton, P., & Dornan, T. (2002). You can't cure it so you have to endure it-: The experience of adaptation to diabetic renal disease. Qualitative Health Research, 12, 329-346. Koch, T. (2000). The illusion of paradox. Social Science & Medicine, 50, 757-759. Langer, E. J.,&Rodin, J. (1976). The effects of choice and enhanced personal responsibility for the aged:A field experiment in an institutional setting. Journal of Personality&Social Psychology, 34(2), 191-198. Lawton, M. P. (1999). Quality of life in chronic illness. Gerontology, 45, 181-183. 974 QUALITATIVE HEALTH RESEARCH / September 2004 Downloaded from qhr.sagepub.com at Queen Margaret Univ College on April 16, 2012 Lundh, U., & Nolan, M. (1996). Ageing and quality of life 2: Understanding successful ageing. British Journal of Nursing, 5(21), 1291-1295. Mallinson, S. (1998). The Short-Form 36 and older people: Some problems encountered when using postal administration. Journal of Epidemiology & Community Health, 52(5), 324-328. McKee, K. J., Houston, D. M., & Barnes, S. (2002). Methods for assessing quality of life and well-being in frail older people. Psychology & Health, 17(6), 737-751. McMillan, S. C., &Weitzner, M. (1999). Quality of life in cancer patients: Use of a revised hospice index. Cancer Practice, 6, 282-288. Michalos, A. C. (2004). Social indicators research and health-related quality of life research. Social Indicators Research, 65(1), 27-72. Nystrom, A.,&Segesten, K. (1994).Onsources of powerlessness in nursing home life. Journal of Advanced Nursing, 19, 124-133. Power, M., Bullinger, M., Harper, A.,&TheWHOQOLGroup. (1999). TheWorld Health Organization of WHOQOL-100:Tests of the universality of quality of life in 15 different cultural groups world-wide. Health Psychology, 18(5), 495-505. Rogerson, R. J. (1995). Environmental and health-related quality of life: Conceptual and methodological similarities. Social Science & Medicine, 41, 1373-1382. Skevington, S. M. (2002). Advancing cross-cultural research on quality of life: Observations drawn from the WHOQOL development. Quality of Life Research, 11, 135-144. Skevington, S. M.,&Wright, A. (2001). Changes in the quality of life of patients receiving antidepressant medication in primary care: Validation of the WHOQOL-100. British Journal of Psychiatry, 178, 261- 267. Smith, J. A. (1996). Beyond the divide between cognition and discourse: Using interpretative phenomenological analysis in health psychology. Psychology & Health, 11, 261-271. Smith, J. A., Jarman,M.,&Osborn,M. (1999).Doing interpretative phenomenological analysis. InM.Murray & K. Chamberlain (Eds.), Qualitative Health Psychology (pp. 218-240). London: Sage. Sollano, J. A., Rose, E. A., Williams, D. L., Thornton, B., Quint, E., Apfelbaum, M., et al. (1998). Costeffectiveness of coronary artery bypass surgery in octogenarians. Annals of Surgery, 228(3), 297-304. Spink, M. P. (1999). Making sense of illness experiences. In M. Murray & K. Chamberlain (Eds.), Qualitative health psychology: Theories and methods (pp. 83-97). London: Sage. Taillefer, M. C., Dupuis, G., Roberge, M. A.,&LeMay, S. (2003). 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    Irritable Bowel Syndrome patients exhibit depressive and anxiety scores in the subsyndromal range

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    Irritable bowel syndrome (IBS) patients frequently experience affective disorders and psychiatric outpatients frequently meet criteria for IBS. The exact nature of this co-morbidity is not clear. 34 patients with Rome-II diagnosed IBS were recruited from a Gastroenterology clinic. Patients with social anxiety disorder (10 SSRI-remitted and 7 untreated subjects) were used as a psychiatric comparison, 28 normal subjects from our register were included as a fourth group (Volunteers). Depressive and anxiety symptoms were measured by the Beck Depression Inventory (BDI) and Spielberger Trait Anxiety Inventory (STAI), respectively. Personality traits were measured with the Swedish universities Scales of Personality (SSP). IBS subjects had BDI and STAI scores intermediate between those of volunteers and patients, despite their lack of a co-morbid psychiatric diagnosis. A principle component factor analysis of the SSP dataset corresponded closely to the solution published with other samples. ANOVA revealed significant between-group differences for 7 of the 13 SSP variables

    Binary Neutron Star Mergers and Third Generation Detectors: Localization and Early Warning

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    For third generation gravitational wave detectors, such as the Einstein Telescope, gravitational wave signals from binary neutron stars can last up to a few days before the neutron stars merge. To estimate the measurement uncertainties of key signal parameters, we develop a Fisher matrix approach which accounts for effects on such long duration signals of the time-dependent detector response and the earths rotation. We use this approach to characterize the sky localization uncertainty for gravitational waves from binary neutron stars at 40, 200, 400, 800 and 1600Mpc, for the Einstein Telescope and Cosmic Explorer individually and operating as a network. We find that the Einstein Telescope alone can localize the majority of detectable binary neutron stars at a distance of ≤200\leq200Mpc to within 100deg2100\text{deg}^2 with 90% confidence. A network consisting of the Einstein Telescope and Cosmic Explorer can enhance the sky localization performance significantly - with the 90% credible region of O(1)deg2\mathcal{O}(1) \text{deg}^2 for most sources at ≤200\leq200Mpc and ≤100deg2\leq100\text{deg}^2 for most sources at ≤1600\leq1600Mpc. We also investigate the prospects for third generation detectors identifying the presence of a signal prior to merger. To do this, we require a signal to have a network signal-to-noise ratio of ≥12\geq12 and ≥5.5\geq5.5 for at least two interferometers, and to have a 90% credible region for the sky localization that is no larger than 100deg2100 \text{deg}^2. We find that the Einstein Telescope can send out such "early-warning" detection alerts 1 - 20 hours before merger for 100% of detectable binary neutron stars at 40Mpc and for ∼58%\sim58\% of sources at 200Mpc. For sources at a distance of 400Mpc, a network of the Einstein telescope and Cosmic Explorer can produce detection alerts up to ∼3\sim 3 hours prior to merger for 98% of detectable binary neutron stars

    Influence of nanotube length and density on the plasmonic terahertz response of single-walled carbon nanotubes

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    We measure the conductivity spectra of thin films comprising bundled single-walled carbon nanotubes (CNTs) of different average lengths in the frequency range 0.3-1000 THz and temperature interval 10-530 K. The observed temperature-induced changes in the terahertz conductivity spectra are shown to depend strongly on the average CNT length, with a conductivity around 1 THz that increases/decreases as the temperature increases for short/long tubes. This behaviour originates from the temperature dependence of the electron scattering rate, which we obtain from Drude fits of the measured conductivity in the range 0.3-2 THz for 10 μ\mum length CNTs. This increasing scattering rate with temperature results in a subsequent broadening of the observed THz conductivity peak at higher temperatures and a shift to lower frequencies for increasing CNT length. Finally, we show that the change in conductivity with temperature depends not only on tube length, but also varies with tube density. We record the effective conductivities of composite films comprising mixtures of WS2_2 nanotubes and CNTs vs CNT density for frequencies in the range 0.3-1 THz, finding that the conductivity increases/decreases for low/high density films as the temperature increases. This effect arises due to the density dependence of the effective length of conducting pathways in the composite films, which again leads to a shift and temperature dependent broadening of the THz conductivity peak.Comment: Submitted to Journal of Physics D. Main manuscript: 9 pages, 8 figures. Supplementary material: 5 pages, 6 figure

    Strategies for the Follow-up of Gravitational Wave Transients with the Cherenkov Telescope Array

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    The observation of the electromagnetic counterpart of gravitational-wave (GW) transient GW170817 demonstrated the potential in extracting astrophysical information from multimessenger discoveries. The forthcoming deployment of the first telescopes of the Cherenkov Telescope Array (CTA) observatory will coincide with Advanced LIGO/Virgo's next observing run, O3, enabling the monitoring of gamma-ray emission at E > 20 GeV, and thus particle acceleration, from GW sources. CTA will not be greatly limited by the precision of GW localization as it will be be capable of rapidly covering the GW error region with sufficient sensitivity. We examine the current status of GW searches and their follow-up effort, as well as the status of CTA, in order to identify some of the general strategies that will enhance CTA's contribution to multimessenger discoveries.Comment: 10 page

    Inference on inspiral signals using LISA MLDC data

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    In this paper we describe a Bayesian inference framework for analysis of data obtained by LISA. We set up a model for binary inspiral signals as defined for the Mock LISA Data Challenge 1.2 (MLDC), and implemented a Markov chain Monte Carlo (MCMC) algorithm to facilitate exploration and integration of the posterior distribution over the 9-dimensional parameter space. Here we present intermediate results showing how, using this method, information about the 9 parameters can be extracted from the data.Comment: Accepted for publication in Classical and Quantum Gravity, GWDAW-11 special issu
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