833 resultados para Richards, Lyn: Handling qualitative data
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Purpose: To investigate the relationship between research data management (RDM) and data sharing in the formulation of RDM policies and development of practices in higher education institutions (HEIs). Design/methodology/approach: Two strands of work were undertaken sequentially: firstly, content analysis of 37 RDM policies from UK HEIs; secondly, two detailed case studies of institutions with different approaches to RDM based on semi-structured interviews with staff involved in the development of RDM policy and services. The data are interpreted using insights from Actor Network Theory. Findings: RDM policy formation and service development has created a complex set of networks within and beyond institutions involving different professional groups with widely varying priorities shaping activities. Data sharing is considered an important activity in the policies and services of HEIs studied, but its prominence can in most cases be attributed to the positions adopted by large research funders. Research limitations/implications: The case studies, as research based on qualitative data, cannot be assumed to be universally applicable but do illustrate a variety of issues and challenges experienced more generally, particularly in the UK. Practical implications: The research may help to inform development of policy and practice in RDM in HEIs and funder organisations. Originality/value: This paper makes an early contribution to the RDM literature on the specific topic of the relationship between RDM policy and services, and openness – a topic which to date has received limited attention.
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Background Despite the promising benefits of adaptive designs (ADs), their routine use, especially in confirmatory trials, is lagging behind the prominence given to them in the statistical literature. Much of the previous research to understand barriers and potential facilitators to the use of ADs has been driven from a pharmaceutical drug development perspective, with little focus on trials in the public sector. In this paper, we explore key stakeholders’ experiences, perceptions and views on barriers and facilitators to the use of ADs in publicly funded confirmatory trials. Methods Semi-structured, in-depth interviews of key stakeholders in clinical trials research (CTU directors, funding board and panel members, statisticians, regulators, chief investigators, data monitoring committee members and health economists) were conducted through telephone or face-to-face sessions, predominantly in the UK. We purposively selected participants sequentially to optimise maximum variation in views and experiences. We employed the framework approach to analyse the qualitative data. Results We interviewed 27 participants. We found some of the perceived barriers to be: lack of knowledge and experience coupled with paucity of case studies, lack of applied training, degree of reluctance to use ADs, lack of bridge funding and time to support design work, lack of statistical expertise, some anxiety about the impact of early trial stopping on researchers’ employment contracts, lack of understanding of acceptable scope of ADs and when ADs are appropriate, and statistical and practical complexities. Reluctance to use ADs seemed to be influenced by: therapeutic area, unfamiliarity, concerns about their robustness in decision-making and acceptability of findings to change practice, perceived complexities and proposed type of AD, among others. Conclusions There are still considerable multifaceted, individual and organisational obstacles to be addressed to improve uptake, and successful implementation of ADs when appropriate. Nevertheless, inferred positive change in attitudes and receptiveness towards the appropriate use of ADs by public funders are supportive and are a stepping stone for the future utilisation of ADs by researchers.
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The size and complexity of data sets generated within ecosystem-level programmes merits their capture, curation, storage and analysis, synthesis and visualisation using Big Data approaches. This review looks at previous attempts to organise and analyse such data through the International Biological Programme and draws on the mistakes made and the lessons learned for effective Big Data approaches to current Research Councils United Kingdom (RCUK) ecosystem-level programmes, using Biodiversity and Ecosystem Service Sustainability (BESS) and Environmental Virtual Observatory Pilot (EVOp) as exemplars. The challenges raised by such data are identified, explored and suggestions are made for the two major issues of extending analyses across different spatio-temporal scales and for the effective integration of quantitative and qualitative data.
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In this paper we introduce a parametric model for handling lifetime data where an early lifetime can be related to the infant-mortality failure or to the wear processes but we do not know which risk is responsible for the failure. The maximum likelihood approach and the sampling-based approach are used to get the inferences of interest. Some special cases of the proposed model are studied via Monte Carlo methods for size and power of hypothesis tests. To illustrate the proposed methodology, we introduce an example consisting of a real data set.
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Currently, it is easy to find health professionals who not only attach importance to qualitative methods, but also recognize their help to better understand their patients' lives. However, its use in dentistry is still incipient, either due to ignorance or because of technical / operational difficulties in identifying possibilities for their use in research. Thus, the purpose of this study was to review the literature on the characteristics and peculiarities of the qualitative methodology, demonstrating their techniques of collecting, recording and analyzing data. For this, we performed a descriptive literature, from a survey in the "LILACS", "BBO" and "PUBMED" databases, by keywords related to the theme, selecting only the papers that mentioned the "importance" of qualitative research, the "characteristics and fundamentals," and the "techniques of collecting, recording and data analysis" involving this methodology. It was found that all studies have highlighted the importance of qualitative research to the construction of new knowledge that cannot be achieved by quantitative data. We found many different techniques to gather, record and analyze qualitative data applied to the dentistry field. It was concluded that qualitative research represents a new path to be followed by dentistry, so that we are able to plan actions in ethical and humane public health dentistry, bringing better results to the population, because of the depth of knowledge that your date can.
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[EN]Qualitative and quantitative research approaches are often considered as incompatible, and when they are brought together in a study, the analyses often stay within the realm of the same research field. The study at hand aims at combining the two methods from the perspectives of different disciplines and tries to determine to which degree a corpus-based analysis might support the traditional content-focused approach to qualitative data and render additional results.
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The WOCAT network has collected, documented, and assessed more than 350 case studies on promising and good practices of SLM. Information on on- and off-site benefits of different SLM types, as well as on investment and maintenance costs is available, sometimes in quantitative and often in qualitative form. The objective of the present paper is to analyse what kind of economic benefits accrue to local stakeholders, and to better understand how these benefits compare to investment and maintenance costs. The large majority of the technologies contained in the database are perceived by land users as having positive benefits that outweigh costs in the long term. About three quarters of them also have positive or at least neutral benefits in the short term. The analysis shows that many SLM measures exist which can generate important benefits to land users, but also to other stakeholders. However, methodological issues need to be tackled and further quantitative and qualitative data are needed to better understand and support the adoption of SLM measures. Keywords: Sustainable Land Management, Costs, Benefits, Technologies
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Most statistical analysis, theory and practice, is concerned with static models; models with a proposed set of parameters whose values are fixed across observational units. Static models implicitly assume that the quantified relationships remain the same across the design space of the data. While this is reasonable under many circumstances this can be a dangerous assumption when dealing with sequentially ordered data. The mere passage of time always brings fresh considerations and the interrelationships among parameters, or subsets of parameters, may need to be continually revised. ^ When data are gathered sequentially dynamic interim monitoring may be useful as new subject-specific parameters are introduced with each new observational unit. Sequential imputation via dynamic hierarchical models is an efficient strategy for handling missing data and analyzing longitudinal studies. Dynamic conditional independence models offers a flexible framework that exploits the Bayesian updating scheme for capturing the evolution of both the population and individual effects over time. While static models often describe aggregate information well they often do not reflect conflicts in the information at the individual level. Dynamic models prove advantageous over static models in capturing both individual and aggregate trends. Computations for such models can be carried out via the Gibbs sampler. An application using a small sample repeated measures normally distributed growth curve data is presented. ^
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Although there is dissimiliarity in theoretical research approaches to subjective well-being and to assessments of well-being, there is agreement regarding the value of well-being, especially among student populations. In the highly structured, achievement-oriented, non-optimal context of a classroom, individual well-being is a necessary pre-condition for learning. Among student populations well-being should not be construed as an achievement enhancer; but, rather, recognized and measured as an educational value of its own. However, it is necessary for the positive bias towards learning at least in highly structured, achievement-orientated, non-optional learning contexts like school [cf. Hascher, T. (2004). Wohlbefinden in der Schule. Münster: Waxmann]. How can it be measured? Since different research approaches lead to a variety of instruments, the following paper will focus on two ways of assessing well-being in school: a questionnaire on student well-being (N = 2014) 1 and a semi-structured daily diary about relevant emotional situations in school (N = 58, period 3 × 2 weeks). Both methods are introduced and their methodological quality is discussed in terms of reliability, validity and in terms of their usefulness for improving school practice. Furthermore, the research potential of combining quantitative and qualitative data on students’ well-being is addressed.
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The purpose of this study is to examine the stages of program realization of the interventions that the Bronx Health REACH program initiated at various levels to improve nutrition as a means for reducing racial and ethnic disparities in diabetes. This study was based on secondary analyses of qualitative data collected through the Bronx Health REACH Nutrition Project, a project conducted under the auspices of the Institute on Urban Family Health, with support from the Centers for Disease Control and Prevention (CDC). Local human subjects' review and approval through the Institute on Urban Family Health was required and obtained in order to conduct the Bronx Health REACH Nutrition Project. ^ The study drew from two theoretical models—Glanz and colleagues' nutrition environments model and Shediac-Rizkallah and Bone's sustainability model. The specific study objectives were two-fold: (1) to categorize each nutrition activity to a specific dimension (i.e. consumer, organizational or community nutrition environment); and (2) to evaluate the stage at which the program has been realized (i.e. development, implementation or sustainability). ^ A case study approach was applied and a constant comparative method was used to analyze the data. Triangulation of data based was also conducted. Qualitative data from this study revealed the following principal findings: (1) communities of color are disproportionately experiencing numerous individual and environmental factors contributing to the disparities in diabetes; (2) multi-level strategies that targeted the individual, organizational and community nutrition environments can appropriately address these contributing factors; (3) the nutrition strategies greatly varied in their ability to appropriately meet criteria for the three program stages; and (4) those nutrition strategies most likely to succeed (a) conveyed consistent and culturally relevant messages, (b) had continued involvement from program staff and partners, (c) were able to adapt over time or setting, (d) had a program champion and a training component, (e) were integrated into partnering organizations, and (f) were perceived to be successful by program staff and partners in their efforts to create individual, organizational and community/policy change. As a result of the criteria-based assessment and qualitative findings, an ecological framework elaborating on Glanz and colleagues model was developed. The qualitative findings and the resulting ecological framework developed from this study will help public health professionals and community leaders to develop and implement sustainable multi-level nutrition strategies for addressing racial and ethnic disparities in diabetes. ^
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Background. Over half of children in the United States under age five spend 32 hours a week in child care, facilities, where they consume approximately 33-50% of their food intake. ^ Objectives. The aim of this research was to identify the effects of state nutrition policies on provision of food in child care centers. ^ Subjects. Eleven directors or their designee from ten randomly selected licensed child care centers in Travis County, Texas were interviewed. Centers included both nonprofit and for-profit centers, with enrollments ranging from 19 to 82. ^ Methods. Centers were selected using a web-based list of licensed child care providers in the Austin area. One-on-one interviews were conducted in person with center directors using a standard set of questions developed from previous pilot work. Interview items included demographic data, questions about state policies regarding provision of foods in centers, effects of policies on child care center budgets and foods offered, and changes in the provision of food. All interviews were audiotaped and transcribed, and themes were identified using standard qualitative techniques. ^ Results. Four of the centers provided both meals and snacks, four provided snacks only, and two did not provide any food. Directors of centers that provided food were more likely to report adherence to the Minimum Standards than directors of centers that did not. In general, center directors reported that the regulations were loosely enforced. In contrast, center directors were more concerned about a local city-county regulation that required food permits and new standards for kitchens. Most of these local regulations were cost prohibitive and, as a result, centers had changed the types of foods provided, which included providing less fresh produce and more prepackaged items. Although implementation of local regulations had reduced provision of fruits and vegetables to children, no adjustments were reported for allocation of resources, tuition costs or care of the children. ^ Conclusions. Qualitative data from a small sample of child care directors indicate that the implementation and accountability of food- and nutrition-related guidelines for centers is sporadic, uncoordinated, and can have unforeseen effects on the provision of food. A quantitative survey and dietary assessment methods should be conducted to verify these findings in a larger and more representative sample.^
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The overarching goal of the Pathway Semantics Algorithm (PSA) is to improve the in silico identification of clinically useful hypotheses about molecular patterns in disease progression. By framing biomedical questions within a variety of matrix representations, PSA has the flexibility to analyze combined quantitative and qualitative data over a wide range of stratifications. The resulting hypothetical answers can then move to in vitro and in vivo verification, research assay optimization, clinical validation, and commercialization. Herein PSA is shown to generate novel hypotheses about the significant biological pathways in two disease domains: shock / trauma and hemophilia A, and validated experimentally in the latter. The PSA matrix algebra approach identified differential molecular patterns in biological networks over time and outcome that would not be easily found through direct assays, literature or database searches. In this dissertation, Chapter 1 provides a broad overview of the background and motivation for the study, followed by Chapter 2 with a literature review of relevant computational methods. Chapters 3 and 4 describe PSA for node and edge analysis respectively, and apply the method to disease progression in shock / trauma. Chapter 5 demonstrates the application of PSA to hemophilia A and the validation with experimental results. The work is summarized in Chapter 6, followed by extensive references and an Appendix with additional material.
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Since the middle of the twentieth century criticism towards quantitative research tools in social sciences has gradually led to attempts to find a new methodology, called 'qualitative research'. At the same time, qualitative research has called for a reconsideration of the usefulness of many of the beneficial tools and methodologies that were discarded during the move to research based on the employment of quantitative research tools. The purpose of this paper is to discuss the essential elements of the qualitative research approach, and then argue for the possibility of introducing the old-established methodology of historical science into qualitative research, in order to raise the accuracy of the qualitative data.
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This article shows software that allows determining the statistical behavior of qualitative data originating surveys previously transformed with a Likert’s scale to quantitative data. The main intention is offer to users a useful tool to know statistics' characteristics and forecasts of financial risks in a fast and simple way. Additionally,this paper presents the definition of operational risk. On the other hand, the article explains different techniques to do surveys with a Likert’s scale (Avila, 2008) to know expert’s opinion with the transformation of qualitative data to quantitative data. In addition, this paper will show how is very easy to distinguish an expert’s opinion related to risk, but when users have a lot of surveys and matrices is very difficult to obtain results because is necessary to compare common data. On the other hand, statistical value representative must be extracted from common data to get weight of each risk. In the end, this article exposes the development of “Qualitative Operational Risk Software” or QORS by its acronym, which has been designed to determine the root of risks in organizations and its value at operational risk OpVaR (Jorion, 2008; Chernobai et al, 2008) when input data comes from expert’s opinion and their associated matrices.
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CD38 ligation on mouse B cells by CS/2, an anti-mouse CD38 mAb, induced proliferation, interleukin 5 (IL-5) receptor α chain expression, and tyrosine phosphorylation of Bruton tyrosine kinase (Btk) from wild-type, but not from X chromosome-linked, immunodeficient mice. B cells from fyn-deficient (Fyn−/−) and lyn-deficient (Lyn−/−) mice showed an impaired response to mAb CS/2 for proliferation and IL-5 receptor α chain expression, and B cells from fyn/lyn double-deficient (Fyn/Lyn−/−) mice did not respond at all to mAb CS/2. The Btk activation by CD38 ligation was observed in B cells from Fyn−/− mice, and it was severely impaired in B cells from Lyn−/− and Fyn/Lyn−/− mice. CD38 expression on B cells from three mutant strains was comparable to that on control B cells. We infer from these results that both Fyn and Lyn are required and that their signals are synergistic for B cell triggering after CD38 ligation. Lyn is upstream of Btk activation in the CD38 signaling. Stimulation of B cells with IL-5 together with CD38 ligation induces not only IgM but also IgG1 secretion. Analysis of the synergistic effects of IL-5 and CD38 ligation on IgG1 secretion revealed the impaired IgG1 secretion of B cells from Lyn−/− and Fyn/Lyn−/− mice. These data imply that Lyn is involved in B cell triggering by CD38 ligation plus IL-5 for isotype switching.