Distinguishing the Trees from the Forest: Applying Cluster Analysis to Thematic Qualitative Data

Guest, Greg; McLellan, Eleanor

doi:10.1177/1525822x03015002005

Cited by 120 publications

(109 citation statements)

References 13 publications

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“…Eight steps were used to identify individual differences in food schema structures represented by these food categories (Figure 1). Similar procedures have been used in prior studies (Guest & McLellan, 2003;Miller, Warland & Achterberg, 1997;Miller et. al., 2003).…”

Section: Methodsmentioning

confidence: 94%

“…They were then asked to split these piles into smaller groups if possible. These split piles represent the second stage (Guest & McLellan, 2003;Miller et. al., 1997;Miller et.…”

Section: Discussionmentioning

confidence: 99%

“…Intraclass correlations averaged 0.88 and ranged from 0.68-0.96 for the twelve food-category types. The researchers reviewed and discussed scoring discrepancies and scores were revised accordingly (Guest & McLellan, 2003;MacQueen et. al., 2001;Miller et.…”

Section: Discussionmentioning

confidence: 99%

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Individual differences in the conceptualization of food across eating contexts

Blake

2008

Food Quality and Preference

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Individual differences in food-related knowledge structures were explored by applying schema theory to examine the categories 42 adults used to classify foods across four eating contexts. Food card-sort labels were organized into 12 categories, category salience for each person was evaluated, and cluster analysis was used to identify clusters of participants according to the salience of their categories. Clusters were further evaluated for complexity and consistency of category use across contexts. Seven food schema clusters were identified. Meal/time and Routine categories were the most salient overall and were used by most clusters. Well-being, Person, Source, Convenience, Meal component, and Food group categories varied in salience across clusters. The complexity and consistency of the food categories participants used across the contexts varied among the clusters. This study provided insight about cognitions that may underlie food-choice behaviors. Understanding individuals' food schemas could help nutrition professionals tailor messages to maximize health impact.

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Section: Methodsmentioning

confidence: 94%

“…They were then asked to split these piles into smaller groups if possible. These split piles represent the second stage (Guest & McLellan, 2003;Miller et. al., 1997;Miller et.…”

Section: Discussionmentioning

confidence: 99%

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Individual differences in the conceptualization of food across eating contexts

Blake

2008

Food Quality and Preference

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“…In order to identify system interdependencies from the ROMS focus groups, we analysed co-occurrences of comments from our focus group participants using a pattern recognition technique recommended by Guest and McLennan (Guest and McLennan 2003). By cross referencing these multi-stakeholder accounts, we were able to construct a more accurate picture of what these dependencies and relationships were in practice.…”

Section: Methodsmentioning

confidence: 99%

Modelling the risks of extreme weather events for Australasian hospital infrastructure using rich picture diagrams

Loosemore

Chow

McGeorge

2012

Construction Management and Economics

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Citation: LOOSEMORE, M., CHOW, V. and MCGEORGE, D., 2012. Modelling the risks of extreme weather events for Australasian hospital infrastructure using rich picture diagrams. Construction Management and Economics, 30 (12) MODELLING THE RISKS OF EXTREME WEATHER EVENTS TO HOSPITAL INFRASTRUCTURE USING RICH PICTURE DIAGRAMS AbstractClimate change has been linked to an increase in the occurrence of extreme weather events. This will expose hospital infrastructure to new risks which are poorly understood. Traditional approaches to risk identification and analysis produce linear, narrow and static risk profiles which fail to consider complex sub-system interdependencies that may assist or hinder healthcare delivery during an extreme weather event. The ability to create resilient hospitals depends on new risk management methodologies which provide an understanding of these complex relationships. To this end focus groups with key stakeholders in three major tertiary hospitals in Australia, are used to construct Rich Picture Diagrams (RPDs) of hospital infrastructure interdependencies under different extreme weather event scenarios. They show that the risks posed to hospitals by extreme weather events cannot be considered in isolation from the surrounding infrastructure, emergency management systems, health systems and communities in which they are imbedded.The new insights provided have major governance and policy implications for those agencies who are responsible for ensuring hospital infrastructure can continue to support the delivery of effective health services during extreme weather events.

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“…Furthermore, it clarified what the researcher was looking for. Clustering was used to make the material more visual (Guest & McLellan, 2003) and to ensure the web-based course was feasible for the students. Clustering was helpful to determine the main picture of the transcribed material, but it did not provide information that would describe experiences with mediation in web-based learning.…”

Section: Tracing Mediators In Web-based Learningmentioning

confidence: 99%

Own Pace, Own Space, Own Face, Human, and Tool Support: Mediators in Web-Based Self-Regulation Learning

Latva-Karjanmaa

2015

J Cogn Educ Psych

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The focus of the study is to identify how mediation supports a web-based course on self-regulation. In the context of education, mediation can be defined as a supporter or promoter of learning. Mediation selects, interprets, and amplifies objects for human learners. The study creates an integrated view of mediators as learning promoters based on Vygotsky's (1978) and Feuerstein's theories (1990 for studying mediators in web-based learning. This study presents an integrated definition of mediators which focuses on the task, quality and types of mediators and suggests the following: (1) mediators are learning promoters who trigger, support, and amplify learning; (2) learning requires high-quality mediators, and the quality of mediation is ensured by mediated learning experiences; and (3) mediators can be social/human mediators or tool/symbolic mediators. This integrated view is then evaluated based on the empirical research results.The study analyzes an asynchronous web-based learning environment (IQ Form) from the perspective of mediation; this learning environment was designed for the Finnish Virtual University (FVU). The research setting involves students from the Karelia University of Applied Sciences. The IQ Form environment aims to help students take charge of their own learning process, i.e., develop their self-regulative strategies and skills. The IQ Learn section of IQ Form includes tests, a tutorial with assignments, and a diary to develop students' learning skills and strategies.The research focuses on mediators that support learning self-regulation by analyzing students' experiences of learning support on a web-based course for learning self-regulation. The methodological approach used, on a philosophical level, qualitatively relies on phenomenology, while at the methodological level, the approach relies on the qualitative research tradition. The study includes two pre-studies and one actual research phase. The main source of data was 14 interviews of first-year students in a Business Information Technology degree program. In addition, 12 students were included in the two pre-studies. The interview data were also supported by the students' 56 diary texts, which were comprised of written assignments sent to their online teacher and background information collected from the students. The data analysis developed into a triangulation between qualitative clustering, a structured empirical phenomenological analysis, and a narrative analysis. The phenomenological analysis was decisive for finding the mediators.The research results suggest five kinds of mediators in this web-based selfregulation setting. The phenomenological analysis made it possible to discover the mediators supporting or triggering students' learning processes. The mediators found were the following: own pace, own space, own face, human and tool.The mediators own pace, space and face were born situationally due to the special circumstances of web-based learning; they were not pre-designed or arranged as were the human and tool mediat...

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Distinguishing the Trees from the Forest: Applying Cluster Analysis to Thematic Qualitative Data

Cited by 120 publications

References 13 publications

Individual differences in the conceptualization of food across eating contexts

Individual differences in the conceptualization of food across eating contexts

Modelling the risks of extreme weather events for Australasian hospital infrastructure using rich picture diagrams

Own Pace, Own Space, Own Face, Human, and Tool Support: Mediators in Web-Based Self-Regulation Learning

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