183 resultados para Qualitative data analysis software


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There is currently little information available about reasons for contraceptive use or non-use among young Australian women and the reasons for choosing specific types of contraceptive methods. A comprehensive life course perspective of women's experiences in using and obtaining contraceptives is lacking, particularly relating to women's perceived or physical barriers to access. This paper presents an analysis of qualitative data gathered from free-text comments provided by women born between 1973 and 1978 as part of their participation in the Australian Longitudinal Study on Women's Health. The Australian Longitudinal Study on Women's Health is a large cohort study involving over 40,000 women from three age groups (aged 18-23, aged 40-45 and aged 70-75) who were selected from the database of Medicare the Australian universal health insurance system in 1995. The women have been surveyed every 3 years about their health by mailed self-report surveys, and more recently online. Written comments from 690 women across five surveys from 1996 (when they were aged 18-23 years) to 2009 (aged 31-36 years) were examined. Factors relating to contraceptive use and barriers to access were identified and explored using thematic analysis. Side-effects, method satisfaction, family timing, and hormonal balance were relevant to young women using contraception. Most women who commented about a specific contraceptive method wrote about the oral contraceptive pill. While many women were positive or neutral about their method, noting its convenience or non-contraceptive benefits, many others were concerned about adverse effects, affordability, method failure, and lack of choice. Negative experiences with health services, lack of information, and cost were identified as barriers to access. As the cohort aged over time, method choice, changing patterns of use, side-effects, and negative experiences with health services remained important themes. Side-effects, convenience, and family timing play important roles in young Australian women's experiences of contraception and barriers to access. Contrary to assumptions, barriers to contraceptive access continue to be experienced by young women as they move into adulthood. Further research is needed about how to decrease barriers to contraceptive use and minimise negative experiences in order to ensure optimal contraceptive access for Australian women.

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Background Prescription medicine samples provided by pharmaceutical companies are predominantly newer and more expensive products. The range of samples provided to practices may not represent the drugs that the doctors desire to have available. Few studies have used a qualitative design to explore the reasons behind sample use. Objective The aim of this study was to explore the opinions of a variety of Australian key informants about prescription medicine samples, using a qualitative methodology. Methods Twenty-three organizations involved in quality use of medicines in Australia were identified, based on the authors' previous knowledge. Each organization was invited to nominate 1 or 2 representatives to participate in semistructured interviews utilizing seeding questions. Each interview was recorded and transcribed verbatim. Leximancer v2.25 text analysis software (Leximancer Pty Ltd., Jindalee, Queensland, Australia) was used for textual analysis. The top 10 concepts from each analysis group were interrogated back to the original transcript text to determine the main emergent opinions. Results A total of 18 key interviewees representing 16 organizations participated. Samples, patient, doctor, and medicines were the major concepts among general opinions about samples. The concept drug became more frequent and the concept companies appeared when marketing issues were discussed. The Australian Pharmaceutical Benefits Scheme and cost were more prevalent in discussions about alternative sample distribution models, indicating interviewees were cognizant of budgetary implications. Key interviewee opinions added richness to the single-word concepts extracted by Leximancer. Conclusions Participants recognized that prescription medicine samples have an influence on quality use of medicines and play a role in the marketing of medicines. They also believed that alternative distribution systems for samples could provide benefits. The cost of a noncommercial system for distributing samples or starter packs was a concern. These data will be used to design further research investigating alternative models for distribution of samples.

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A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

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Many educational researchers conducting studies in non-English speaking settings attempt to report on their project in English to boost their scholarly impact. It requires preparing and presenting translations of data collected from interviews and observations. This paper discusses the process and ethical considerations involved in this invisible methodological phase. The process includes activities prior to data analysis and to its presentation to be undertaken by the bilingual researcher as translator in order to convey participants’ original meanings as well as to establish and fulfil translation ethics. This paper offers strategies to address such issues; the most appropriate translation method for qualitative study; and approaches to address political issues when presenting such data.

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Over the past several years, there has been resurgent interest in regional planning in North America, Europe and Australasia. Spurred by issues such as metropolitan growth, transportation infrastructure, environmental management and economic development, many states and metropolitan regions are undertaking new planning initiatives. These regional efforts have also raised significant question about governance structures, accountability and measures of effectiveness.n this paper, the authors conducted an international review of ten case studies from the United States, Canada, England, Belgium, New Zealand and Australia to explore several critical questions. Using qualitative data template, the research team reviewed plans, documents, web sites and published literature to address three questions. First, what are the governance arrangements for delivering regional planning? Second, what are the mechanisms linking regional plans with state plans (when relevant) and local plans? Third, what means and mechanisms do these regional plans use to evaluate and measure effectiveness? The case study analysis revealed several common themes. First, there is an increasing focus on goverance at the regional level, which is being driven by a range of trends, including regional spatial development initiatives in Europe, regional transportation issues in the US, and the growth of metropolitan regions generally. However, there is considerable variation in how regional governance arrangements are being played out. Similarly, there is a range of processes being used at the regional level to guide planning that range from broad ranging (thick) processes to narrow and limited (thin) approaches. Finally, evaluation and monitoring of regional planning efforts are compiling data on inputs, processes, outputs and outcomes. Although there is increased attention being paid to indicators and monitoring, most of it falls into outcome evaluations such as Agenda 21 or sustainability reporting. Based on our review we suggest there is a need for increased attention on input, process and output indicators and clearer linkages of these indicators in monitoring and evaluation frameworks. The focus on outcome indicators, such as sustainability indicators, creates feedback systems that are too long-term and remote for effective monitoring and feedback. Although we found some examples of where these kinds of monitoring frameworks are linked into a system of governance, there is a need for clearer conceptual development for both theory and practice.

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This publication is the culmination of a 2 year Australian Learning and Teaching Council's Project Priority Programs Research Grant which investigates key issues and challenges in developing flexible guidelines lines for best practice in Australian Doctoral and Masters by Research Examination, encompassing the two modes of investigation, written and multi-modal (practice-led/based) theses, their distinctiveness and their potential interplay. The aims of the project were to address issues of assessment legitimacy raised by the entry of practice-orientated dance studies into Australian higher degrees; examine literal embodiment and presence, as opposed to cultural studies about states of embodiment; foreground the validity of questions around subjectivity and corporeal intelligence/s and the reliability of artistic/aesthetic communications, and finally to celebrate ‘performance mastery’(Melrose 2003) as a rigorous and legitimate mode of higher research. The project began with questions which centred around: the functions of higher degree dance research; concepts of 'master-ness’ and ‘doctorateness’; the kinds of languages, structures and processes which may guide candidates, supervisors, examiners and research personnel; the purpose of evaluation/examination; addressing positive and negative attributes of examination. Finally the study examined ways in which academic/professional, writing/dancing, tradition/creation and diversity/consistency relationships might be fostered to embrace change. Over two years, the authors undertook a qualitative national study encompassing a triangulation of semi-structured face to face interviews and industry forums to gather views from the profession, together with an analysis of existing guidelines, and recent literature in the field. The most significant primary data emerged from 74 qualitative interviews with supervisors, examiners, research deans and administrators, and candidates in dance and more broadly across the creative arts. Qualitative data gathered from the two primary sources, was coded and analysed using the NVivo software program. Further perspectives were drawn from international consultant and dance researcher Susan Melrose, as well as publications in the field, and initial feedback from a draft document circulated at the World Dance Alliance Global Summit in July 2008 in Brisbane. Refinement of data occurred in a continual sifting process until the final publication was produced. This process resulted in a set of guidelines in the form of a complex dynamic system for both product and process oriented outcomes of multi-modal theses, along with short position papers on issues which arose from the research such as contested definitions, embodiment and ephemerality, ‘liveness’ in performance research higher degrees, dissolving theory/practice binaries, the relationship between academe and industry, documenting practices and a re-consideration of the viva voce.

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Value creation is an area with long-standing importance in the marketing field, yet little is known about the value construct itself. In social marketing, value can be regarded as an incentive for consumers to perform desirable behaviours that lead to bother greater social good and individual benefit. An understanding of customer value in the consumption of social products is an important aspect of designing social marketing interventions that can effectively change social behaviours. This paper uses qualitative data, gathered during depth interviews, to explore the value dimensions women experience from using government-provided breast screening services every two years. Thematic analysis was used in discovering that emotional functional, social and altruistic dimensions of value were present in womens’ experiences with these services as well as in the outcomes from using them.

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Aims: To describe a local data linkage project to match hospital data with the Australian Institute of Health and Welfare (AIHW) National Death Index (NDI) to assess longterm outcomes of intensive care unit patients. Methods: Data were obtained from hospital intensive care and cardiac surgery databases on all patients aged 18 years and over admitted to either of two intensive care units at a tertiary-referral hospital between 1 January 1994 and 31 December 2005. Date of death was obtained from the AIHW NDI by probabilistic software matching, in addition to manual checking through hospital databases and other sources. Survival was calculated from time of ICU admission, with a censoring date of 14 February 2007. Data for patients with multiple hospital admissions requiring intensive care were analysed only from the first admission. Summary and descriptive statistics were used for preliminary data analysis. Kaplan-Meier survival analysis was used to analyse factors determining long-term survival. Results: During the study period, 21 415 unique patients had 22 552 hospital admissions that included an ICU admission; 19 058 surgical procedures were performed with a total of 20 092 ICU admissions. There were 4936 deaths. Median follow-up was 6.2 years, totalling 134 203 patient years. The casemix was predominantly cardiac surgery (80%), followed by cardiac medical (6%), and other medical (4%). The unadjusted survival at 1, 5 and 10 years was 97%, 84% and 70%, respectively. The 1-year survival ranged from 97% for cardiac surgery to 36% for cardiac arrest. An APACHE II score was available for 16 877 patients. In those discharged alive from hospital, the 1, 5 and 10-year survival varied with discharge location. Conclusions: ICU-based linkage projects are feasible to determine long-term outcomes of ICU patients

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Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. It is one of the several diagnostic techniques currently used for structural health monitoring (SHM) of civil infrastructure such as bridges. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. But several challenges still exist. Due to high sampling rate required for data capture, large amount of data is generated during AE testing. This is further complicated by the presence of a number of spurious sources that can produce AE signals which can then mask desired signals. Hence, an effective data analysis strategy is needed to achieve source discrimination. This also becomes important for long term monitoring applications in order to avoid massive date overload. Analysis of frequency contents of recorded AE signals together with the use of pattern recognition algorithms are some of the advanced and promising data analysis approaches for source discrimination. This paper explores the use of various signal processing tools for analysis of experimental data, with an overall aim of finding an improved method for source identification and discrimination, with particular focus on monitoring of steel bridges.

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Compared with viewing videos on PCs or TVs, mobile users have different experiences in viewing videos on a mobile phone due to different device features such as screen size and distinct usage contexts. To understand how mobile user’s viewing experience is impacted, we conducted a field user study with 42 participants in two typical usage contexts using a custom-designed iPhone application. With user’s acceptance of mobile video quality as the index, the study addresses four influence aspects of user experiences, including context, content type, encoding parameters and user profiles. Accompanying the quantitative method (acceptance assessment), we used a qualitative interview method to obtain a deeper understanding of a user’s assessment criteria and to support the quantitative results from a user’s perspective. Based on the results from data analysis, we advocate two user-driven strategies to adaptively provide an acceptable quality and to predict a good user experience, respectively. There are two main contributions from this paper. Firstly, the field user study allows a consideration of more influencing factors into the research on user experience of mobile video. And these influences are further demonstrated by user’s opinions. Secondly, the proposed strategies — user-driven acceptance threshold adaptation and user experience prediction — will be valuable in mobile video delivery for optimizing user experience.

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Unstructured text data, such as emails, blogs, contracts, academic publications, organizational documents, transcribed interviews, and even tweets, are important sources of data in Information Systems research. Various forms of qualitative analysis of the content of these data exist and have revealed important insights. Yet, to date, these analyses have been hampered by limitations of human coding of large data sets, and by bias due to human interpretation. In this paper, we compare and combine two quantitative analysis techniques to demonstrate the capabilities of computational analysis for content analysis of unstructured text. Specifically, we seek to demonstrate how two quantitative analytic methods, viz., Latent Semantic Analysis and data mining, can aid researchers in revealing core content topic areas in large (or small) data sets, and in visualizing how these concepts evolve, migrate, converge or diverge over time. We exemplify the complementary application of these techniques through an examination of a 25-year sample of abstracts from selected journals in Information Systems, Management, and Accounting disciplines. Through this work, we explore the capabilities of two computational techniques, and show how these techniques can be used to gather insights from a large corpus of unstructured text.

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This research is one of several ongoing studies conducted within the IT Professional Services (ITPS) research programme at Queensland University of Technology (QUT). In 2003, ITPS introduced the IS-Impact model, a measurement model for measuring information systems success from the viewpoint of multiple stakeholders. The model, along with its instrument, is robust, simple, yet generalisable, and yields results that are comparable across time, stakeholders, different systems and system contexts. The IS-Impact model is defined as “a measure at a point in time, of the stream of net benefits from the Information System (IS), to date and anticipated, as perceived by all key-user-groups”. The model represents four dimensions, which are ‘Individual Impact’, ‘Organizational Impact’, ‘Information Quality’ and ‘System Quality’. The two Impact dimensions measure the up-to-date impact of the evaluated system, while the remaining two Quality dimensions act as proxies for probable future impacts (Gable, Sedera & Chan, 2008). To fulfil the goal of ITPS, “to develop the most widely employed model” this research re-validates and extends the IS-Impact model in a new context. This method/context-extension research aims to test the generalisability of the model by addressing known limitations of the model. One of the limitations of the model relates to the extent of external validity of the model. In order to gain wide acceptance, a model should be consistent and work well in different contexts. The IS-Impact model, however, was only validated in the Australian context, and packaged software was chosen as the IS understudy. Thus, this study is concerned with whether the model can be applied in another different context. Aiming for a robust and standardised measurement model that can be used across different contexts, this research re-validates and extends the IS-Impact model and its instrument to public sector organisations in Malaysia. The overarching research question (managerial question) of this research is “How can public sector organisations in Malaysia measure the impact of information systems systematically and effectively?” With two main objectives, the managerial question is broken down into two specific research questions. The first research question addresses the applicability (relevance) of the dimensions and measures of the IS-Impact model in the Malaysian context. Moreover, this research question addresses the completeness of the model in the new context. Initially, this research assumes that the dimensions and measures of the IS-Impact model are sufficient for the new context. However, some IS researchers suggest that the selection of measures needs to be done purposely for different contextual settings (DeLone & McLean, 1992, Rai, Lang & Welker, 2002). Thus, the first research question is as follows, “Is the IS-Impact model complete for measuring the impact of IS in Malaysian public sector organisations?” [RQ1]. The IS-Impact model is a multidimensional model that consists of four dimensions or constructs. Each dimension is represented by formative measures or indicators. Formative measures are known as composite variables because these measures make up or form the construct, or, in this case, the dimension in the IS-Impact model. These formative measures define different aspects of the dimension, thus, a measurement model of this kind needs to be tested not just on the structural relationship between the constructs but also the validity of each measure. In a previous study, the IS-Impact model was validated using formative validation techniques, as proposed in the literature (i.e., Diamantopoulos and Winklhofer, 2001, Diamantopoulos and Siguaw, 2006, Petter, Straub and Rai, 2007). However, there is potential for improving the validation testing of the model by adding more criterion or dependent variables. This includes identifying a consequence of the IS-Impact construct for the purpose of validation. Moreover, a different approach is employed in this research, whereby the validity of the model is tested using the Partial Least Squares (PLS) method, a component-based structural equation modelling (SEM) technique. Thus, the second research question addresses the construct validation of the IS-Impact model; “Is the IS-Impact model valid as a multidimensional formative construct?” [RQ2]. This study employs two rounds of surveys, each having a different and specific aim. The first is qualitative and exploratory, aiming to investigate the applicability and sufficiency of the IS-Impact dimensions and measures in the new context. This survey was conducted in a state government in Malaysia. A total of 77 valid responses were received, yielding 278 impact statements. The results from the qualitative analysis demonstrate the applicability of most of the IS-Impact measures. The analysis also shows a significant new measure having emerged from the context. This new measure was added as one of the System Quality measures. The second survey is a quantitative survey that aims to operationalise the measures identified from the qualitative analysis and rigorously validate the model. This survey was conducted in four state governments (including the state government that was involved in the first survey). A total of 254 valid responses were used in the data analysis. Data was analysed using structural equation modelling techniques, following the guidelines for formative construct validation, to test the validity and reliability of the constructs in the model. This study is the first research that extends the complete IS-Impact model in a new context that is different in terms of nationality, language and the type of information system (IS). The main contribution of this research is to present a comprehensive, up-to-date IS-Impact model, which has been validated in the new context. The study has accomplished its purpose of testing the generalisability of the IS-Impact model and continuing the IS evaluation research by extending it in the Malaysian context. A further contribution is a validated Malaysian language IS-Impact measurement instrument. It is hoped that the validated Malaysian IS-Impact instrument will encourage related IS research in Malaysia, and that the demonstrated model validity and generalisability will encourage a cumulative tradition of research previously not possible. The study entailed several methodological improvements on prior work, including: (1) new criterion measures for the overall IS-Impact construct employed in ‘identification through measurement relations’; (2) a stronger, multi-item ‘Satisfaction’ construct, employed in ‘identification through structural relations’; (3) an alternative version of the main survey instrument in which items are randomized (rather than blocked) for comparison with the main survey data, in attention to possible common method variance (no significant differences between these two survey instruments were observed); (4) demonstrates a validation process of formative indexes of a multidimensional, second-order construct (existing examples mostly involved unidimensional constructs); (5) testing the presence of suppressor effects that influence the significance of some measures and dimensions in the model; and (6) demonstrates the effect of an imbalanced number of measures within a construct to the contribution power of each dimension in a multidimensional model.

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Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.