9 research outputs found
Give me your lips, Give me your arms, Fit around me just like a glove [first line of chorus]
No full textstrophic with choruspiano and voice; ukeleleads on inside front and on back covers, and on bottom inside margins for Robbins Music stockSH 592-3Johns Hopkins University, Levy Sheet Music Collection, Box
044, Item 070aBy Fred Fisher and Martin Broones.from the Metro-Goldwyn-Mayer Picture "So This Is College."John Ree
The globalization of U.S. business investment
No full textThis paper documents some key facts about foreign direct investment flows by U.S. businesses overseas and foreign businesses in the United States. We show how the pattern of flows has evolved, examine the sources and destination of these flows, document associated employment and productivity gains, and show how investment-related sales compare with traditional exports. While the United States is a net debtor to the rest of the world, direct investment overseas by U.S. businesses exceeds direct investment in the U.S. by foreign businesses. Furthermore, U.S. businesses seem to earn more on their foreign investments than foreign firms earn on their U.S. investments. The globalization of business investment is a long-standing phenomenon, but it has accelerated in recent years and become a source of concern for some, as it is intimately related to the debate on offshore outsourcing. Yet contrary to what some think, the bulk of U.S. investment overseas is in other high-income countries. And foreign investment in the U.S. has been an important source of employment growth in recent years.Investments, Foreign - United States
Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L
No full textPurpose: It has been argued that generic health-related quality of life measures are not sensitive to certain disease-specific improvements; condition-specific preference-based measures may offer a better alternative. This paper assesses the validity, responsiveness and sensitivity of a cancer-specific preference-based measure, the EORTC-8D, relative to the EQ-5D-3L. Methods: A longitudinal prospective population-based cancer genomic cohort, Cancer 2015, was utilised in the analysis. EQ-5D-3L and the EORTC QLQ-C30 (which gives EORTC-8D values) were asked at baseline (diagnosis) and at various follow-up points (3 months, 6 months, 12 months). Baseline values were assessed for convergent validity, ceiling effects, agreement and sensitivity. Quality-adjusted life-years (QALYs) were estimated and similarly assessed. Multivariate regression analyses were employed to understand the determinants of the difference in QALYs. Results: Complete case analysis of 1678 patients found that the EQ-5D-3L values at baseline were significantly lower than the EORTC-8D values (0.748 vs 0.829, p < 0.001). While the correlation between the instruments was high, agreement between the instruments was poor. The baseline health state values using both instruments were found to be sensitive to a number of patient and disease characteristics, and discrimination between disease states was found to be similar. Mean generic QALYs (estimated using the EQ-5D-3L) were significantly lower than condition-specific QALYs (estimated using the EORTC-8D) (0.860 vs 0.909, p < 0.001). The discriminatory power of both QALYs was similar. Conclusions: When comparing a generic and condition-specific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated QALYs over time for cancer patients. The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably
Producing a preference-based quality of LIFE measure to quantify the impact of HYPOGLYCAEMIA on people living with diabetes: A mixed-methods research protocol
No full textBackground: Assessment of patient-reported outcome measures (PROMs), including quality of life (QoL), is essential in diabetes research and care. However, a recent review concluded that current hypoglycaemia-specific PROMs have limited evidence of validity, reliability and responsiveness for assessing the impact of hypoglycaemia on QoL in people living with diabetes. None of the PROMs identified could be used directly to inform the cost-effectiveness of treatments and interventions. There is a need for a new hypoglycaemia-specific QoL PROM, which can be used directly to inform economic evaluations. Aims: This project has three aims: (a) To develop draft PROM content for measuring the impact of hypoglycaemia on QoL in adults with diabetes. (b) To refine the draft content using cognitive debriefing interviews and psychometrics. This will result in a condition-specific PROM that can be used to quantify the impact of hypoglycaemia upon QoL. (c) To generate a preference-based measure (PBM) that will enable utility values to be calculated for economic evaluation. Methods: A mixed-methods, three-stage design is used: (a) Qualitative interviews will inform the draft PROM content. (b) Cognitive debriefing interview data will be used to refine the draft PROM content. The PROM will be administered in a large-scale survey to enable psychometric validation. Final item selection for the PROM will be informed by psychometric performance, translatability assessment and input from stakeholder groups. (c) A classification system will be generated, comprising a reduced number of items from the PROM. A valuation survey will be conducted to derive a value set for the PBM
Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L
No full textPurpose: It has been argued that generic health-related quality of life measures are not sensitive to certain disease-specific improvements; condition-specific preference-based measures may offer a better alternative. This paper assesses the validity, responsiveness and sensitivity of a cancer-specific preference-based measure, the EORTC-8D, relative to the EQ-5D-3L. Methods: A longitudinal prospective population-based cancer genomic cohort, Cancer 2015, was utilised in the analysis. EQ-5D-3L and the EORTC QLQ-C30 (which gives EORTC-8D values) were asked at baseline (diagnosis) and at various follow-up points (3 months, 6 months, 12 months). Baseline values were assessed for convergent validity, ceiling effects, agreement and sensitivity. Quality-adjusted life-years (QALYs) were estimated and similarly assessed. Multivariate regression analyses were employed to understand the determinants of the difference in QALYs. Results: Complete case analysis of 1678 patients found that the EQ-5D-3L values at baseline were significantly lower than the EORTC-8D values (0.748 vs 0.829, p < 0.001). While the correlation between the instruments was high, agreement between the instruments was poor. The baseline health state values using both instruments were found to be sensitive to a number of patient and disease characteristics, and discrimination between disease states was found to be similar. Mean generic QALYs (estimated using the EQ-5D-3L) were significantly lower than condition-specific QALYs (estimated using the EORTC-8D) (0.860 vs 0.909, p < 0.001). The discriminatory power of both QALYs was similar. Conclusions: When comparing a generic and condition-specific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated QALYs over time for cancer patients. The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably
Generation, Selection, and Face Validation of Items for a New Generic Measure of Quality of Life: The EQ-HWB
No full textObjectives: This article aims to describe the generation and selection of items (stage 2) and face validation (stage 3) of a large international (multilingual) project to develop a new generic measure, the EQ-HWB (EQ Health and Wellbeing), for use in economic evaluation across health, social care, and public health to estimate quality-adjusted life-years. Methods: Items from commonly used generic, carer, social care, and mental health quality of life measures were mapped onto domains or subdomains identified from a literature review. Potential terms and items were reviewed and refined to ensure coverage of the construct of the domains/subdomain (stage 2). Input on the potential item pool, response options, and recall period was sought from 3 key stakeholder groups. The pool of candidate items was tested in qualitative interviews with potential future users in an international face validation study (stage 3). Results: Stage 2 resulted in the generation of 687 items. Predetermined selection criteria were applied by the research team resulting in 598 items being dropped, leaving 89 items that were reviewed by key stakeholder groups. Face validation (stage 3) tested 97 draft items and 4 response scales. A total of 47 items were retained and 14 were modified, whereas 3 were added to the candidate pool of items. This resulted in a 64-item set. Conclusions: This international multiculture, multilingual study with a common methodology identified many items that performed well across all countries. These were taken to the psychometric testing along with modified and new items for the EQ-HWB
Developing a New Generic Health and Wellbeing Measure: Psychometric Survey Results for the EQ-HWB
No full textObjectives: The development of measures such as the EQ-HWB (EQ Health and Wellbeing) requires selection of items. This study explored the psychometric performance of candidate items, testing their validity in patients, social carer users, and carers. Methods: Article and online surveys that included candidate items (N = 64) were conducted in Argentina, Australia, China, Germany, United Kingdom, and the United States. Psychometric assessment on missing data, response distributions, and known group differences was undertaken. Dimensionality was explored using exploratory and confirmatory factor analysis. Poorly fitting items were identified using information functions, and the function of each response category was assessed using category characteristic curves from item response theory (IRT) models. Differential item functioning was tested across key subgroups. Results: There were 4879 respondents (Argentina = 508, Australia = 514, China = 497, Germany = 502, United Kingdom = 1955, United States = 903). Where missing data were allowed, it was low (UK article survey 2.3%; US survey 0.6%). Most items had responses distributed across all levels. Most items could discriminate between groups with known health conditions with moderate to large effect sizes. Items were less able to discriminate across carers. Factor analysis found positive and negative measurement factors alongside the constructs of interest. For most of the countries apart from China, the confirmatory factor analysis model had good fit with some minor modifications. IRT indicated that most items had well-functioning response categories but there was some evidence of differential item functioning in many items. Conclusions: Items performed well in classical psychometric testing and IRT. This large 6-country collaboration provided evidence to inform item selection for the EQ-HWB measure
Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L
No full textPurpose: It has been argued that generic health-related quality of life measures are not sensitive to certain disease-specific improvements; condition-specific preference-based measures may offer a better alternative. This paper assesses the validity, responsiveness and sensitivity of a cancer-specific preference-based measure, the EORTC-8D, relative to the EQ-5D-3L. Methods: A longitudinal prospective population-based cancer genomic cohort, Cancer 2015, was utilised in the analysis. EQ-5D-3L and the EORTC QLQ-C30 (which gives EORTC-8D values) were asked at baseline (diagnosis) and at various follow-up points (3 months, 6 months, 12 months). Baseline values were assessed for convergent validity, ceiling effects, agreement and sensitivity. Quality-adjusted life-years (QALYs) were estimated and similarly assessed. Multivariate regression analyses were employed to understand the determinants of the difference in QALYs. Results: Complete case analysis of 1678 patients found that the EQ-5D-3L values at baseline were significantly lower than the EORTC-8D values (0.748 vs 0.829, p < 0.001). While the correlation between the instruments was high, agreement between the instruments was poor. The baseline health state values using both instruments were found to be sensitive to a number of patient and disease characteristics, and discrimination between disease states was found to be similar. Mean generic QALYs (estimated using the EQ-5D-3L) were significantly lower than condition-specific QALYs (estimated using the EORTC-8D) (0.860 vs 0.909, p < 0.001). The discriminatory power of both QALYs was similar. Conclusions: When comparing a generic and condition-specific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated QALYs over time for cancer patients. The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably
Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation.
No full textBACKGROUND: Dementia is one of the most common and serious disorders in later life and the economic and personal cost of caring for people with dementia is immense. There is a need to be able to evaluate interventions in dementia using cost-effectiveness analyses, but the generic preference-based measures typically used to measure effectiveness do not work well in dementia. Existing dementia-specific measures can effectively measure health-related quality of life but in their current form cannot be used directly to inform cost-effectiveness analysis using quality-adjusted life-years as the measure of effectiveness. OBJECTIVES: The aim was to develop two brief health-state classifications, one from DEMQOL and one from DEMQOL-Proxy, to generate health states amenable to valuation. These classification systems consisted of items taken from DEMQOL and DEMQOL-Proxy so they can be derived from any study that has used these instruments. DATA SOURCES: In the first stage of the study we used a large, clinically representative sample aggregated from two sources: a sample of patients and carers attending a memory service in south London and a sample of patients and carers from other community services in south London. This included 644 people with a diagnosis of mild/moderate dementia and 689 carers of those with mild/moderate dementia. For the valuation study, the general population sample of 600 respondents was drawn to be representative of the UK general population. Households were sampled in urban and rural areas in northern England and balanced to the UK population according to geodemographic profiles. In the patient/carer valuation study we interviewed a sample of 71 people with mild dementia and 71 family carers drawn from a memory service in south London. Finally, the instruments derived were applied to data from the HTA-SADD (Study of Antidepressants for Depression in Dementia) trial. REVIEW METHODS: This was a complex multiphase study with four linked phases: phase 1 - derivation of the health-state classification system; phase 2 - general population valuation survey and modelling to produce values for every health state; phase 3 - patient/carer valuation survey; and phase 4 - application of measures to trial data. RESULTS: All four phases were successful and this report details this development process leading to the first condition-specific preference-based measures in dementia, an important new development in this field. LIMITATIONS: The first limitation relates to the lack of an external data set to validate the DEMQOL-U and DEMQOL-Proxy-U classification systems. Throughout the development process we have made decisions about which methodology to use. There are other valid techniques that could be used and it is possible to criticise the choices that we have made. It is also possible that the use of a mild to moderate dementia sample has resulted in classification systems that do not fully reflect the challenges of severe dementia. CONCLUSION: The results presented are sufficiently encouraging to recommend that the DEMQOL instruments be used alongside a generic measure such as the European Quality of Life-5 Dimensions (EQ-5D) in future studies of interventions in dementia as there was evidence that they can be more sensitive for patients at the milder end of disease and some limited evidence that the person with dementia measure may be able to reflect deterioration. FUNDING: The National Institute for Health Research Health Technology Assessment programme
