Results 281 to 290 of about 26,240,118 (323)
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Reflecting on reflexive thematic analysis

Qualitative Research in Sport, Exercise and Health, 2019
Since initially writing on thematic analysis in 2006, the popularity of the method we outlined has exploded, the variety of TA approaches have expanded, and, not least, our thinking has developed and shifted. In this reflexive commentary, we look back at
Virginia Braun, Victoria Clarke
semanticscholar   +1 more source

A THEMATIC ANALYSIS OF THE AIDS LITERATURE [PDF]

open access: possibleBiocomputing 2002, 2001
Faced with the need for human comprehension of any large collection of objects, a time honored approach has been to cluster the objects into groups of closely related objects. Individual groups are then summarized in some convenient manner to provide a more manageable view of the data.
openaire   +2 more sources

Thematic Analysis

Abstract This chapter presents the theory and practice of thematic analysis as an accessible and flexible method for analyzing qualitative data in emerging adulthood research. As a family of approaches ranging on a continuum from systematically scientific to creatively artful, thematic analysis’ defining feature is a focus on the ...
Mauricio Toval-Gajardo   +1 more
  +6 more sources

Thematizer

2023
Thematic theory, comprised of the concepts of theme, rheme, and thematic progression, concerns itself with the interplay between word order, information status, propositional content and discourse function. In contemporary research on thematic theory, researchers have begun to leverage computational means for text analysis with respect to thematic ...
openaire   +2 more sources

To saturate or not to saturate? Questioning data saturation as a useful concept for thematic analysis and sample-size rationales

, 2019
The concept of data saturation, defined as ‘information redundancy’ or the point at which no new themes or codes ‘emerge’ from data, is widely referenced in thematic analysis (TA) research in sport and exercise, and beyond.
Virginia Braun, Victoria Clarke
semanticscholar   +1 more source

Is thematic analysis used well in health psychology? A critical review of published research, with recommendations for quality practice and reporting

Health Psychology Review, 2023
Despite the persistent dominance of a ‘scientific psychology’ paradigm in health psychology, the use of qualitative research continues to grow. Qualitative approaches are often based on fundamentally different values from (post)positivistempiricism ...
Virginia Braun, Victoria Clarke
semanticscholar   +1 more source

LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis

Conference on Empirical Methods in Natural Language Processing, 2023
Thematic analysis (TA) has been widely used for analyzing qualitative data in many disciplines and fields. To ensure reliable analysis, the same piece of data is typically assigned to at least two human coders.
Shih-Chieh Dai, Aiping Xiong, Lun-Wei Ku
semanticscholar   +1 more source

Advancing AI-driven thematic analysis in qualitative research: a comparative study of nine generative models on Cutaneous Leishmaniasis data

BMC Medical Informatics and Decision Making
As part of qualitative research, the thematic analysis is time-consuming and technical. The rise of generative artificial intelligence (A.I.), especially large language models, has brought hope in enhancing and partly automating thematic analysis.
Issam Bennis, Safwane Mouwafaq
semanticscholar   +1 more source

Thematic-LM: A LLM-based Multi-agent System for Large-scale Thematic Analysis

The Web Conference
Thematic analysis (TA) is a widely used qualitative method for identifying underlying meanings within unstructured text. However, TA requires manual processes, which become increasingly labour-intensive and time-consuming as datasets grow.
Tingrui Qiao   +3 more
semanticscholar   +1 more source

Inductive thematic analysis of healthcare qualitative interviews using open-source large language models: How does it compare to traditional methods?

Comput. Methods Programs Biomed.
BACKGROUND Large language models (LLMs) are generative artificial intelligence that have ignited much interest and discussion about their utility in clinical and research settings.
W. S. Mathis   +4 more
semanticscholar   +1 more source

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