197 resultados para quality of welding
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PURPOSE/OBJECTIVES: To identify latent classes of individuals with distinct quality-of-life (QOL) trajectories, to evaluate for differences in demographic characteristics between the latent classes, and to evaluate for variations in pro- and anti-inflammatory cytokine genes between the latent classes. DESIGN: Descriptive, longitudinal study. SETTING: Two radiation therapy departments located in a comprehensive cancer center and a community-based oncology program in northern California. SAMPLE: 168 outpatients with prostate, breast, brain, or lung cancer and 85 of their family caregivers (FCs). METHODS: Growth mixture modeling (GMM) was employed to identify latent classes of individuals based on QOL scores measured prior to, during, and for four months following completion of radiation therapy. Single nucleotide polymorphisms (SNPs) and haplotypes in 16 candidate cytokine genes were tested between the latent classes. Logistic regression was used to evaluate the relationships among genotypic and phenotypic characteristics and QOL GMM group membership. MAIN RESEARCH VARIABLES: QOL latent class membership and variations in cytokine genes. FINDINGS: Two latent QOL classes were found: higher and lower. Patients and FCs who were younger, identified with an ethnic minority group, had poorer functional status, or had children living at home were more likely to belong to the lower QOL class. After controlling for significant covariates, between-group differences were found in SNPs in interleukin 1 receptor 2 (IL1R2) and nuclear factor kappa beta 2 (NFKB2). For IL1R2, carrying one or two doses of the rare C allele was associated with decreased odds of belonging to the lower QOL class. For NFKB2, carriers with two doses of the rare G allele were more likely to belong to the lower QOL class. CONCLUSIONS: Unique genetic markers in cytokine genes may partially explain interindividual variability in QOL. IMPLICATIONS FOR NURSING: Determination of high-risk characteristics and unique genetic markers would allow for earlier identification of patients with cancer and FCs at higher risk for poorer QOL. Knowledge of these risk factors could assist in the development of more targeted clinical or supportive care interventions for those identified.
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Background To determine the impact of cataract surgery on vision-related quality of life (VRQOL) and examine the association between objective visual measures and change in VRQOL after surgery among bilateral cataract patients in Ho Chi Minh City, Vietnam. Methods A cohort of older patients with bilateral cataract was assessed one week before and one to three months after first eye or both eye cataract surgery. Visual measures including visual acuity, contrast sensitivity and stereopsis were obtained. Vision-related quality of life was assessed using the NEI VFQ-25. Descriptive analyses and a generalized linear estimating equation (GEE) analysis were undertaken to measure change in VRQOL after surgery. Results Four hundred and thirteen patients were assessed before cataract surgery and 247 completed the follow-up assessment one to three months after first or both eye cataract surgery. Overall, VRQOL significantly improved after cataract surgery (p < 0.001) particularly after both eye surgeries. Binocular contrast sensitivity (p < 0.001) and stereopsis (p < 0.001) were also associated with change in VRQOL after cataract surgery. Visual acuity was not associated with VRQOL. Conclusions Cataract surgery significantly improved VRQOL among bilateral cataract patients in Vietnam. Contrast sensitivity as well as stereopsis, rather than visual acuity significantly affected VRQOL after cataract surgery.
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Health Information Exchange (HIE) is an interesting phenomenon. It is a patient centric health and/or medical information management scenario enhanced by integration of Information and Communication Technologies (ICT). While health information systems are repositioning complex system directives, in the wake of the ‘big data’ paradigm, extracting quality information is challenging. It is anticipated that in this talk, ICT enabled healthcare scenarios with big data analytics will be shared. In addition, research and development regarding big data analytics, such as current trends of using these technologies for health care services and critical research challenges when extracting quality of information to improve quality of life will be discussed.
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Background Few studies have examined the long-term changes experienced by women treated for endometrial cancer. Objective The objectives of this study were to describe what women perceived important to their lifestyle and quality of life in the years following their diagnosis and to provide new insights that might inform healthcare practice. Methods This was a thematic analysis of 237 open-ended comments from Australian women diagnosed with endometrial cancer 3 to 5 years previously. Results We identified 3 main themes: (1) personal change, in which women spoke about cancer as permanently altering their lives in mostly negative but sometimes positive ways; (2) continuity of former life, which described both the minimal impact of cancer on women's lives and identities and the difficulties negotiating this within the dominant "cancer survivorship" culture; (3) social support, where women wrote about how the quality of their relationships shaped their cancer trajectory. Conclusions While typical "survivorship" issues exist for many women with endometrial cancer (eg, physical, emotional, sexual health changes), a proportion of women will not be focused on their cancer and can be encouraged to form lives and identities that are not situated within the "cancer survivorship" culture. Implications for Practice A network of support, sensitive to women's responses to having cancer, may benefit women's long-term adjustment. Regular standardized assessment of women's needs may facilitate appropriate support for those with concerns, whereas those without concerns could be reassured by health professionals that their experience is normal and shared by other people with cancer. This may encourage women to form lives that are personally meaningful.
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Background Multi attribute utility instruments (MAUIs) are preference-based measures that comprise a health state classification system (HSCS) and a scoring algorithm that assigns a utility value to each health state in the HSCS. When developing a MAUI from a health-related quality of life (HRQOL) questionnaire, first a HSCS must be derived. This typically involves selecting a subset of domains and items because HRQOL questionnaires typically have too many items to be amendable to the valuation task required to develop the scoring algorithm for a MAUI. Currently, exploratory factor analysis (EFA) followed by Rasch analysis is recommended for deriving a MAUI from a HRQOL measure. Aim To determine whether confirmatory factor analysis (CFA) is more appropriate and efficient than EFA to derive a HSCS from the European Organisation for the Research and Treatment of Cancer’s core HRQOL questionnaire, Quality of Life Questionnaire (QLQ-C30), given its well-established domain structure. Methods QLQ-C30 (Version 3) data were collected from 356 patients receiving palliative radiotherapy for recurrent/metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter informed by the established QLQ-C30 structure and views of both patients and clinicians on which are the most relevant items. Dimensions determined by EFA or CFA were then subjected to Rasch analysis. Results CFA results generally supported the proposed QLQ-C30 structure (comparative fit index =0.99, Tucker–Lewis index =0.99, root mean square error of approximation =0.04). EFA revealed fewer factors and some items cross-loaded on multiple factors. Further assessment of dimensionality with Rasch analysis allowed better alignment of the EFA dimensions with those detected by CFA. Conclusion CFA was more appropriate and efficient than EFA in producing clinically interpretable results for the HSCS for a proposed new cancer-specific MAUI. Our findings suggest that CFA should be recommended generally when deriving a preference-based measure from a HRQOL measure that has an established domain structure.
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Background: Quality of life is poorer in Parkinson’s disease than in other conditions and in the general population without Parkinson’s disease. Malnutrition also results in poorer quality of life. This study aimed at determining the relationship between quality of life and nutritional status. Methods: Community-dwelling people with Parkinson’s disease >18 years old were recruited. The Patient-Generated Subjective Global Assessment (PG-SGA) assessed nutritional status. The Parkinson’s Disease Questionnaire 39 (PDQ-39) measured quality of life. Phase I was cross-sectional. The malnourished in Phase I were eligible for a nutrition intervention phase, randomised into 2 groups: standard care (SC) with provision of nutrition education materials only and intervention (INT) with individualised dietetic advice and regular weekly follow-up. Data were collected at baseline, 6 weeks, and 12 weeks. Results: Phase I consisted of 120 people who completed the PDQ-39. Phase II consisted of 9 in the SC group and 10 in the INT group. In Phase I, quality of life was poorer in the malnourished, particularly for mobility and activities of daily living domains. There was a significant correlation between PG-SGA and PDQ-39 scores (Phase I, rs = 0.445, p = .000; Phase II, rs = .426, p = .002). In Phase II, no significant difference in the PDQ-39 total or sub-scores was observed between the INT and SC groups; however, there was significant improvement in the emotional well-being domain for the entire group, X2(2) = 8.84, p = .012. Conclusions: Malnourished people with Parkinson’s disease had poorer quality of life than the well-nourished, and improvements in nutritional status resulted in quality of life improvements. Attention to nutritional status is an important component of quality of life and therefore the total care of people with Parkinson’s disease.
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Emotion and cognition are known to interact during human decision processes. In this study we focus on a specific kind of cognition, namely metacognition. Our experiment induces a negative emotion, worry, during a perceptual task. In a numerosity task subjects have to make a two alternative forced choice and then reveal their confidence in this decision. We measure metacognition in terms of discrimination and calibration abilities. Our results show that metacognition, but not choice, is affected by the level of worry anticipatedbefore the decision. Under worry individuals tend to have better metacognition in terms of the two measures. Furthermore understanding the formation of confidence is better explained with taking into account the level of worry in the model. This study shows the importance of an emotional component in the formation and the quality of the subjective probabilities.
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Background Patient-relevant outcome measures are essential for high-quality clinical research, and quality-of-life (QoL) tools are the current standard. Currently, there is no validated children's acute cough-specific QoL questionnaire. Objective The objective of this study was to develop and validate the Parent-proxy Children's Acute Cough-specific QoL Questionnaire (PAC-QoL). Methods Using focus groups, a 48-item PAC-QoL questionnaire was developed and later reduced to 16 items by using the clinical impact method. Parents of children with a current acute cough (<2 weeks) at enrollment completed 2 validated cough score measures, the preliminary 48-item PAC-QoL, and 3 other questionnaires (the State Trait Anxiety Inventory [STAI], the Short-Form 8-item 24-hour recall Health Survey [SF-8], and the Depression, Anxiety, and Stress 21-item Scale [DASS21]). All measures were repeated on days 3 and 14. Results The median age of the 155 children enrolled was 2.3 years (interquartile range, 1.3-4.6). Median cough duration at enrollment was 3 days (interquartile range, 2-5). The reduced 16-item scale had high internal consistency (Cronbach α = 0.95). Evidence for repeatability and criterion validity was shown by significant correlations between the domains and total PAC-QoL scores and the SF-8 (r = −0.36 and −0.51), STAI (r = −0.27 and −0.39), and DASS21 (r = −0.32 and −0.41) scales on days 0 and 3, respectively. The final PAC-QoL questionnaire was sensitive to change over time, with changes significantly relating to changes in cough score measures (P < .001). Conclusion The 16-item PAC-QoL is a reliable and valid outcome measure that assesses QoL related to childhood acute cough at a given time point and reflects changes in acute cough-specific QoL over time.
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This program of research linked police and health data collections to investigate the potential benefits for road safety in terms of enhancing the quality of data. This research has important implications for road safety because, although police collected data has historically underpinned efforts in the area, it is known that many road crashes are not reported to police and that these data lack specific injury severity information. This research shows that data linkage provides a more accurate quantification of the severity and prevalence of road crash injuries which is essential for: prioritising funding; targeting interventions; and estimating the burden and cost of road trauma.
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This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.
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This presentation investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.
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This study explores how explicit transit quality of services (TQoS) measures including service frequency, service span, and travel time ratio, along with implicit environmental predictors such as topographic grade factor influence bus ridership using a case study city of Brisbane, Australia. The primary hypothesis tested was that bus ridership is higher within suburbs with high transit quality of service than suburbs that have limited service quality. Using Multiple Linear Regression (MLR) this study identifies a strong positive relationship between route intensity (bus-km/h-km2) and bus ridership, indicating that increasing both service frequency and spatial route density correspond to higher bus ridership. Additionally, travel time ratio (in-vehicle transit travel time to in-vehicle auto travel time) is also found to have significant negative association with ridership within a suburb, reflecting a decline in transit use with increased travel time ratio. Conversely, topographic grade and service span are not found to exert any significant impact on bus ridership in a suburb. Our study findings enhance the fundamental understanding of traveller behaviour which is informative to urban transportation policy, planning and provision.
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This study investigates whether an Australian city’s suburbs having high transit Quality of Service (QoS) are associated with higher transit ridership than those having low transit QoS •We explore how QoS measures including service frequency, service span, service coverage, and travel time ratio, along with implicit environmental predictors such as topographic grade factor influence bus ridership •We applied Multiple Linear Regression (MLR) to examine the relationship between QoS and ridership •Its outcomes enhance our understanding of transit user behavior, which is informative to urban transportation policy, planning, and provision
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This paper investigates stochastic analysis of transit segment hourly passenger load factor variation for transit capacity and quality of service (QoS) analysis using Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia. It compares stochastic analysis to traditional peak hour factor (PHF) analysis to gain further insight into variability of transit route segments’ passenger loading during a study hour. It demonstrates that hourly design load factor is a useful method of modeling a route segment’s capacity and QoS time history across the study weekday. This analysis method is readily adaptable to different passenger load standards by adjusting design percentile, reflecting either a more relaxed or more stringent condition. This paper also considers hourly coefficient of variation of load factor as a capacity and QoS assessment measure, in particular through its relationships with hourly average and design load factors. Smaller value reflects uniform passenger loading, which is generally indicative of well dispersed passenger boarding demands and good schedule maintenance. Conversely, higher value may be indicative of pulsed or uneven passenger boarding demands, poor schedule maintenance, and/or bus bunching. An assessment table based on hourly coefficient of variation of load factor is developed and applied to this case study. Inferences are drawn for a selection of study hours across the weekday studied.