Perception of prescription medicine sample packs among Australian professional, government, industry, and consumer organizations, based on automated textual analysis of one-on-one interviews

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.

Using textual analysis with Concept Inventories to identify root causes of misconceptions

Engineers must have deep and accurate conceptual understanding of their field and Concept inventories (CIs) are one method of assessing conceptual understanding and providing formative feedback. Current CI tests use Multiple Choice Questions (MCQ) to identify misconceptions and have undergone reliability and validity testing to assess conceptual understanding. However, they do not readily provide the diagnostic information about students’ reasoning and therefore do not effectively point to specific actions that can be taken to improve student learning. We piloted the textual component of our diagnostic CI on electrical engineering students using items from the signals and systems CI. We then analysed the textual responses using automated lexical analysis software to test the effectiveness of these types of software and interviewed the students regarding their experience using the textual component. Results from the automated text analysis revealed that students held both incorrect and correct ideas for certain conceptual areas and provided indications of student misconceptions. User feedback also revealed that the inclusion of the textual component is helpful to students in assessing and reflecting on their own understanding.

Insights into students' conceptual understanding using textual analysis: A case study in signal processing

Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering concepts exist due to a lack of mental frameworks, or schemas, for these types of concepts or conceptual areas. This study incorporated an open textual response component in a multiple-choice concept inventory test to capture written explanations of students' selections. The study's goal was to identify, through text analysis of student responses, the types and categorizations of concepts in these explanations that had not been uncovered by the distractor selections. The analysis of the textual explanations of a subset of the discrete-time signals and systems concept inventory questions revealed that students have difficulty conceptually explaining several dimensions of signal processing. This contributed to their inability to provide a clear explanation of the underlying concepts, such as mathematical concepts. The methods used in this study evaluate students' understanding of signals and systems concepts through their ability to express understanding in written text. This may present a bias for students with strong written communication skills. This study presents a framework for extracting and identifying the types of concepts students use to express their reasoning when answering conceptual questions.

Integrating textual analysis and evidential reasoning for decision making in Engineering design

Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach. © 2013 Elsevier B.V. All rights reserved.

Studying administrative reforms through textual analysis: the case of Italian central government accounting

This paper contributes to the literature on public-sector reforms by proposing textual analysis as a useful research strategy to explore how reform archetypes and related ideas are deployed in the parliamentary debate and regulations advancing reforms. Public Administration (PA) (Wilson 1887; Weber 1922), New Public Management (NPM) (Hood 1991, 1995; Dunleavy and Hood 1994; Ferlie et al. 1996) and Public Governance (GOV) (Osborne 2010; Rhodes 1997) can be depicted as three different archetypes providing characteristic administrative ideas and concepts (i.e. interpretive schemes) and related tools and practices (i.e. structures and systems) which lead reforms. We use textual analysis to look into more than twenty years of Italian central government accounting reforms and investigate how the three administrative archetypes have evolved, intertwined and replaced each other. Textual analysis proves a useful tool to investigate reform processes and allows highlighting that in neo-Weberian countries, such as Italy, NPM and GOV, far from being revolutionary paradigms, may represent fashionable trends that did not leave significant traces in the practice and rhetoric of reforms. These results also suggest interesting implications for practitioners and policy makers.

Ontario's curriculum for individuals with disabilities : a textual analysis

The purpose of this study was to examine the disability discourses present in Ontario elementary schools curriculum. The study used a critical social analysis perspective to employ a textual discourse analysis on the Planning [title of subject] Programs for Students with Special Education Needs (PPSSEN) section of the curriculum. The present study utilized Parker's (1992) seven criteria for distinguishing discourses and discovered five main discourses; Independent, dependent, legal, scientific and agency discourses. The second step to this research was the placement and discussion of these five discourses on three diverse texts, Paulo Freire's (2008) Pedagogy o/ the Oppressed, Psychiatry Inside Out, Selected writings of Franco Basaglia, written by Scheper-Huges and Lovell (1987) and Aronowitz and Giroux's (1985) Education Under Siege: The Conservative, Liberal and Radical Debate over Schooling. These unique perspectives were used as methods of analysis tools to further analyze the dominate disability discourses. The texts provided textual support in three major areas; dialectics, critical education and structural conditions of power and language of traditional roles and responsibilities. The findings and discussions presented in this project contain significant implications for anyone involved with students with disabilities in any education system.

Examination and Critique of Codebook for Textual Analysis

The researcher presents the details, findings, and critique of a pre-pilot study conducted on a codebook created for a textbook comparison. She used Cohen’s alpha and percent agreement to determine inter-rater reliabilities for coding categories. These values revealed changes needed in the coding scheme and in the coder training process for the future comparison study.

Content-aware compression for big textual data analysis

A substantial amount of information on the Internet is present in the form of text. The value of this semi-structured and unstructured data has been widely acknowledged, with consequent scientific and commercial exploitation. The ever-increasing data production, however, pushes data analytic platforms to their limit. This thesis proposes techniques for more efficient textual big data analysis suitable for the Hadoop analytic platform. This research explores the direct processing of compressed textual data. The focus is on developing novel compression methods with a number of desirable properties to support text-based big data analysis in distributed environments. The novel contributions of this work include the following. Firstly, a Content-aware Partial Compression (CaPC) scheme is developed. CaPC makes a distinction between informational and functional content in which only the informational content is compressed. Thus, the compressed data is made transparent to existing software libraries which often rely on functional content to work. Secondly, a context-free bit-oriented compression scheme (Approximated Huffman Compression) based on the Huffman algorithm is developed. This uses a hybrid data structure that allows pattern searching in compressed data in linear time. Thirdly, several modern compression schemes have been extended so that the compressed data can be safely split with respect to logical data records in distributed file systems. Furthermore, an innovative two layer compression architecture is used, in which each compression layer is appropriate for the corresponding stage of data processing. Peripheral libraries are developed that seamlessly link the proposed compression schemes to existing analytic platforms and computational frameworks, and also make the use of the compressed data transparent to developers. The compression schemes have been evaluated for a number of standard MapReduce analysis tasks using a collection of real-world datasets. In comparison with existing solutions, they have shown substantial improvement in performance and significant reduction in system resource requirements.

An analysis of completeness and historical accuracy in the most commonly used college jazz history texts

Historical accuracy is only one of the components of a scholarly college textbook used to teach the history of jazz music. Textbooks in this field should include accurate ethnic representation of the most important musical figures as jazz is considered the only original American art form. As college and universities celebrate diversity, it is important that jazz history be accurate and complete. ^ The purpose of this study was to examine the content of the most commonly used jazz history textbooks currently used at American colleges and universities. This qualitative study utilized grounded and textual analysis to explore the existence of ethnic representation in these texts. The methods used were modeled after the work of Kane and Selden each of whom conducted a content analysis focused on a limited field of study. This study is focused on key jazz artists and composers whose work was created in the periods of early jazz (1915-1930), swing (1930-1945) and modern jazz (1945-1960). ^ This study considered jazz notables within the texts in terms of ethnic representation, authors' use of language, contributions to the jazz canon, and place in the standard jazz repertoire. Appropriate historical sections of the selected texts were reviewed and coded using predetermined rubrics. Data were then aggregated into categories and then analyzed according to the character assigned to the key jazz personalities noted in the text as well as the comparative standing afforded each personality. ^ The results of this study demonstrate that particular key African-American jazz artists and composers occupy a significant place in these texts while other significant individuals representing other ethnic groups are consistently overlooked. This finding suggests that while America and the world celebrates the quality of the product of American jazz as great musically and significant socially, many ethnic contributors are not mentioned with the result being a less than complete picture of the evolution of this American art form. ^

Teaching Empowerment Through Sport: An Analysis of Fast and Female

This project is about Fast and Female, a community-based girls’ sport organization, that focuses on empowering girls through sport. In this thesis I produce a discourse analysis from interviews with six expert sportswomen and a textual analysis of the organization’s online content – including its social media pages. I ground my analysis in poststructural theory as explained by Chris Weedon (1997) and in literature that helps contextualize and better define empowerment (Collins, 2000; Cruikshank, 1999; Hains, 2012; Sharma, 2008; Simon, 1994) and neoliberalism (Silk & Andrews, 2012). My analysis in this project suggests that Fast and Female develops a community through online and in-person interaction. This community is focused on girls’ sport and empowerment, but, as the organization is situated in a neoliberal context, organizers must take extra consideration in order for the organization to develop a girls’ sport culture that is truly representative of the desires and needs of the participants rather than implicit neoliberal values. It is important to note that Fast and Female does not identify as a feminist organization. Through this thesis I argue that Fast and Female teaches girls that sport is empowering – but, while the organization draws on “empowerment,” a term often used by feminists, it promotes a notion of empowerment that teaches female athletes how to exist within current mainstream and sporting cultures, rather than encouraging them to be empowered female citizens who learn to question and challenge social inequity. I conclude my thesis with suggestions for Fast and Female to encourage empowerment in spite of the current neoliberal situation. I also offer a goal-setting workbook that I developed to encourage girls to set goals while thinking about their communities rather than just themselves.