What is in a text and what does it do: Qualitative Evaluations of an NLG system–the BT-Nurse–using content analysis and discourse analysis. (original) (raw)
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2017
BACKGROUND Qualitative research methods are increasingly being used across disciplines because of their ability to help investigators understand the perspectives of participants in their own words. However, qualitative analysis is a laborious and resource-intensive process. To achieve depth, researchers are limited to smaller sample sizes when analyzing text data. One potential method to address this concern is natural language processing (NLP). Qualitative text analysis involves researchers reading data, assigning code labels, and iteratively developing findings; NLP has the potential to automate part of this process. Unfortunately, little methodological research has been done to compare automatic coding using NLP techniques and qualitative coding, which is critical to establish the viability of NLP as a useful, rigorous analysis procedure. OBJECTIVE The purpose of this study was to compare the utility of a traditional qualitative text analysis, an NLP analysis, and an augmented ap...
Natural Language Processing (NLP) in Qualitative Public Health Research: A Proof of Concept Study
International Journal of Qualitative Methods
Qualitative data-analysis methods provide thick, rich descriptions of subjects’ thoughts, feelings, and lived experiences but may be time-consuming, labor-intensive, or prone to bias. Natural language processing (NLP) is a machine learning technique from computer science that uses algorithms to analyze textual data. NLP allows processing of large amounts of data almost instantaneously. As researchers become conversant with NLP, it is becoming more frequently employed outside of computer science and shows promise as a tool to analyze qualitative data in public health. This is a proof of concept paper to evaluate the potential of NLP to analyze qualitative data. Specifically, we ask if NLP can support conventional qualitative analysis, and if so, what its role is. We compared a qualitative method of open coding with two forms of NLP, Topic Modeling, and Word2Vec to analyze transcripts from interviews conducted in rural Belize querying men about their health needs. All three methods re...
Using Corpora to Aid Qualitative Text Analysis
2018
Aim. The aim of this paper is to present and exemplify a number of basic uses of corpus-based text analysis tools that can supplement and provide additional insight for an otherwise qualitative analysis of a text. I attempt to show that nowadays certain corpus tools are easily accessible to any researcher and can be used to enrich the results of studies concerned with texts. Methods. This paper comprises the basics of corpus building, the main types of data that can be drawn from a simple corpus and a detailed description of four methods that can aid text analysis: wordlists, concordances, dispersion plots and keywords. Each of those four methods is thoroughly described, including a number of examples of its applications and indicates its possible limitations. Results. The examples provided suggest that even performing a very simple corpus analysis of a text might unveil certain trends and phenomena not noticeable through the classic qualitative text analysis methods (e.g. close rea...
How to Analyse Texts
It's been over three decades since Malcolm Coulthard first published 'An Introduction to Discourse Analysis' (1977), 'Advances in Spoken Discourse Analysis' (1992) and 'Advances in Written Text Analysis' (1994). Taken together, the three books, which were preceded by Sinclair and Coulthard's 'Towards an Analysis of Discourse: English Used by Teachers and Pupils' (1974), provide beginners and advanced learners, native and non-native speakers of English alike, with an in-depth knowledge across all areas of applied linguistics, and guidelines on how to analyse the different instances of written and spoken text. 'How to Analyse Texts: A Toolkit for Students of English' recalls these books for several reasons: not only is the book aimed at students of English across the world, but also, as a textbook, it encourages the readers to think about language use in everyday texts. As it focuses on language patterns both intrinsically and extrinsically, it is a step-by-step resource for understanding and interpreting different texts.
Language use and patterns in nursing records. A discourse analytical approach
Sykepleien Nett, 2021
A care discourse, aimed at the patient's needs, was prominent in the evaluation and assessment notes. The treatment plans reflected a problem-focused discourse, where only problems were recorded. Nabila Sabab Intensivsykepleier Thoraxkirurgisk intensiv, Hjerte-, lunge-og karklinikken, Oslo universitetssykehus, Rikshospitalet og Avdeling for tverrfaglig helsevitenskap, Institutt for helse og samfunn, Universitetet i Oslo
Augmenting Qualitative Text Analysis with Natural Language Processing: Methodological Study
Journal of Medical Internet Research
Background: Qualitative research methods are increasingly being used across disciplines because of their ability to help investigators understand the perspectives of participants in their own words. However, qualitative analysis is a laborious and resource-intensive process. To achieve depth, researchers are limited to smaller sample sizes when analyzing text data. One potential method to address this concern is natural language processing (NLP). Qualitative text analysis involves researchers reading data, assigning code labels, and iteratively developing findings; NLP has the potential to automate part of this process. Unfortunately, little methodological research has been done to compare automatic coding using NLP techniques and qualitative coding, which is critical to establish the viability of NLP as a useful, rigorous analysis procedure. Objective: The purpose of this study was to compare the utility of a traditional qualitative text analysis, an NLP analysis, and an augmented approach that combines qualitative and NLP methods. Methods: We conducted a 2-arm cross-over experiment to compare qualitative and NLP approaches to analyze data generated through 2 text (short message service) message survey questions, one about prescription drugs and the other about police interactions, sent to youth aged 14-24 years. We randomly assigned a question to each of the 2 experienced qualitative analysis teams for independent coding and analysis before receiving NLP results. A third team separately conducted NLP analysis of the same 2 questions. We examined the results of our analyses to compare (1) the similarity of findings derived, (2) the quality of inferences generated, and (3) the time spent in analysis. Results: The qualitative-only analysis for the drug question (n=58) yielded 4 major findings, whereas the NLP analysis yielded 3 findings that missed contextual elements. The qualitative and NLP-augmented analysis was the most comprehensive. For the police question (n=68), the qualitative-only analysis yielded 4 primary findings and the NLP-only analysis yielded 4 slightly different findings. Again, the augmented qualitative and NLP analysis was the most comprehensive and produced the highest quality inferences, increasing our depth of understanding (ie, details and frequencies). In terms of time, the NLP-only approach was quicker than the qualitative-only approach for the drug (120 vs 270 minutes) and police (40 vs 270 minutes) questions. An approach beginning with qualitative analysis followed by qualitative-or NLP-augmented analysis took longer time than that beginning with NLP for both drug (450 vs 240 minutes) and police (390 vs 220 minutes) questions.
elsevier, 2019
This paper discusses the development of corpus-based curriculum for ESP, with a focus on two underresearched areas: health care communication and the use of corpus materials for pronunciation. Three aspects of corpus-based curriculum development are explored: corpus-based needs analysis; corpus-based materials development; and corpus-based assessment and evaluation (Flowerdew, 2012; Tono, 2011). First, this paper briefly reports on a quantitative corpus-based analysis of 104 nurse-patient interactions that was conducted to identify needs of nurses in clinical interactions, with a focus on the findings related to pronunciation (pitch range, tone choice, and prominence/sentence stress). Key differences were found between international and U.S. nurse discourse in the use of these features. Next, the paper describes the curriculum for a Pronunciation for Nurses course, with an emphasis on corpus-based materials development from the corpus described above. Finally, the paper discusses the corpus-based assessment of participants' progress and an evaluation of the Pronunciation for Nurses curriculum, including pre and post-tests, interviews with nurse participants, interviews with ESL teachers, and course evaluations. The methods discussed in the paper have implications for other ESP contexts and other aspects of language use.
Applying language technology to nursing documents: Pros and cons with a focus on ethics
International Journal of Medical Informatics, 2007
Nursing a b s t r a c t Objectives: The present study discusses ethics in building and using applications based on natural language processing in electronic nursing documentation. Specifically, we first focus on the question of how patient confidentiality can be ensured in developing language technology for the nursing documentation domain. Then, we identify and theoretically analyze the ethical outcomes which arise when using natural language processing to support clinical judgement and decision-making. In total, we put forward and justify 10 claims related to ethics in applying language technology to nursing documents.